COVID-19 Gateway Resources

Total COVID-19 Datasets: 19
Publisher Dataset Title Abstract
ALLIANCE > NHSX The National COVID-19 Chest Imaging Database The National COVID-19 Chest Imaging Database is a joint collaboration between NHSX, BSTI and Royal Surrey NHS Foundation Trust to create a centralised UK database of X-Ray, CT and MRI images from hospital patients to inform the COVID-19 response.
ALLIANCE > SAIL COVID-19 Symptom Tracker Dataset The COVID Symptom Tracker was designed by doctors and scientists at King's College London (KCL), Guys and St Thomas’ Hospital working in partnership with ZOE Global. Led by Dr Tim Spector, professor of genetic epidemiology at KCL and director of TwinsUK.
HUBS > BREATHE COVID-19 Detection from Chest X-Rays using Deep Learning We aim to establish a reliable diagnostic tool based on a deep-learning framework for the screening of patients who present with COVID-19 related abnormalities on chest x-rays.
ALLIANCE > SAIL COVID-19 Consolidated Deaths COVID-19 Consolidated Deaths dataset.
HUBS > BREATHE Community perception on public health measures for COVID-19 prevention/control One of the key approaches to containing COVID-19 has been self-quarantine and social distancing, which poses multiple challenges especially in a Pakistani community which follows strong cultural and social beliefs.
HUBS > BREATHE Early Pandemic Evaluation and Enhanced Surveillance of COVID-19 (EAVE II) Population-level surveillance and rapid assessment of the effectiveness of therapeutic or preventive interventions are required to ensure that interventions are targeted to those at highest risk of serious illness or death from COVID-19.
HUBS > BREATHE Exploring psychological issues of primary care teams in Malaysia amidst COVID-19 We aim to explore the impact of the COVID-19 pandemic on psychological stress and well-being of primary healthcare workers (HCWs) in Malaysia.
ALLIANCE > SAIL COVID-19 Shielded People list List of people notified of vulnerable status and instructed to self-isolate during Covid pandemic.
OTHER > COG-UK COG-UK Viral Genome Sequences COG-UK Consortium has published a dataset which contains over 20K SARS-CoV-2 viral genome sequences available as open access.
HUBS > PIONEER PIONEER - COVID Limited OMOP dataset of patient care at the Queen Elizabeth Hospital, Birmingham from the year 2020
ALLIANCE > ISARIC 4C COVID-19 Clinical Information Network (CO-CIN) CO-CIN has collected data on 79,000 patients of all ages requiring admission to hospital with covid-19, and patients in hospital subsequently diagnosed with covid-19 in England, Scotland and Wales.
HDR UK HDR UK Papers & Preprints Publications that mention HDR-UK (or any variant thereof) in Acknowledgements or Author Affiliations
HUBS > DISCOVER NOW North West London COVID-19 Patient Level Situation Report (NWL COVID19 PLD SITREP) The NWL COVID19 PLD SITREP linked table is a direct daily feed from NWL providers. The table provides the patient level data related to COVID admissions in hospital since the outbreak of the pandemic, includes bed status/ventilation status etc.
ALLIANCE > SAIL Daily Situation Report Data Daily Situation Report dataset. Daily situation report for healthcare equipment, staff, activity, capacity and usage.
ALLIANCE > SAIL COVID-19 Test results Test results from Laboratory Information Management System for COVID19 tests (coronavirus SARS CoV2 PCR and coronavirus PCR tests).
HUBS > DISCOVER NOW North West London Pathology (NWL PATH) The NWL Pathology linked table is a direct feed from The Doctors Laboratory and North West London Pathology for patients registered within NWL. Some of the data items included are test dates and times, test codes and names and test results.
HUBS > BREATHE Children's Health in London and Luton (CHILL) CHILL cohort was established in 2018/19 and comprises 3,225 primary schoolchildren in central London and Luton. The cohort will assess the impact of London's Ultra Low Emission Zone on respiratory health.
ALLIANCE > SAIL Annual District Death Daily Daily version of Annual District Death Dataset.
HUBS > NHS DIGITRIALS National Diabetes Audit Audit collects Information about general diabetes care. Data submitted by health care services, relevant to service they provide i.e. Secondary Care Bodies = Type 1, GP practices = Type 2. Includes demographics and diabetes relevant biometric information.
Total COVID-19 Papers/Preprints: 199
Author Title Journal Title Year Published
RECOVERY Collaborative Group, Horby P, Lim WS, Emberson JR, Mafham M, Bell JL, Linsell L, Staplin N, Brightling C, Ustianowski A, Elmahi E, Prudon B, Green C, Felton T, Chadwick D, Rege K, Fegan C, Chappell LC, Faust SN, Jaki T, Jeffery K, Montgomery A, Rowan K, Juszczak E, Baillie JK, Haynes R, Landray MJ. Dexamethasone in Hospitalized Patients with Covid-19 - Preliminary Report. The New England journal of medicine 2020
Banerjee A, Katsoulis M, Lai AG, Pasea L, Treibel TA, Manisty C, Denaxas S, Quarta G, Hemingway H, Cavalcante JL, Noursadeghi M, Moon JC. Clinical academic research in the time of Corona: A simulation study in England and a call for action. PloS one 2020
Garyfallos Konstantinoudis; Tullia Padellini; James E Bennett; Bethan Davies; Majid Ezzati; Marta Blangiardo Long-term exposure to air-pollution and COVID-19 mortality in England: a hierarchical spatial analysis Background: Recent studies suggested a link between long-term exposure to air-pollution and COVID-19 mortality. However, due to their ecological design, based on large spatial units, they neglect the strong localised air-pollution patterns, and potentially lead to inadequate confounding adjustment. We investigated the effect of long-term exposure to NO2 and PM2.5 on COVID-19 deaths up to June 30, 2020 in England using high geographical resolution. Methods: We included 38 573 COVID-19 deaths up to June 30, 2020 at the Lower Layer Super Output Area level in England (n=32 844 small areas). We retrieved averaged NO2 and PM2.5 concentration during 2014-2018 from the Pollution Climate Mapping. We used Bayesian hierarchical models to quantify the effect of air-pollution while adjusting for a series of confounding and spatial autocorrelation. Findings: We find a 0.5% (95% credible interval: -0.2%-1.2%) and 1.4% (-2.1%-5.1%) increase in COVID-19 mortality rate for every 1g/m3 increase in NO2 and PM2.5 respectively, after adjusting for confounding and spatial autocorrelation. This corresponds to a posterior probability of a positive effect of 0.93 and 0.78 respectively. The spatial relative risk at LSOA level revealed strong patterns, similar for the different pollutants. This potentially captures the spread of the disease during the first wave of the epidemic. Interpretation: Our study provides some evidence of an effect of long-term NO2 exposure on COVID-19 mortality, while the effect of PM2.5 remains more uncertain. Funding: Medical Research Council, Wellcome Trust, Environmental Protection Agency and National Institutes of Health. 2020-08-11
Krishnan Bhaskaran; Christopher T Rentsch; Brian MacKenna; Anna Schultz; Amir Mehrkar; Chris Bates; Rosalind M Eggo; Caroline E Morton; Seb Bacon; Peter Inglesby; Ian J Douglas; Alex J Walker; Helen I McDonald; Jonathan Cockburn; Elizabeth J Williamson; David Evans; Harriet J Forbes; Helen J Curtis; William Hulme; John Parry; Frank Hester; Sam Harper; Stephen JW Evans; Liam Smeeth; Ben Goldacre HIV infection and COVID-19 death: population-based cohort analysis of UK primary care data and linked national death registrations within the OpenSAFELY platform Background: It is unclear whether HIV infection is associated with risk of COVID-19 death. We aimed to investigate this in a large-scale population-based study in England. Methods: Working on behalf of NHS England, we used the OpenSAFELY platform to analyse routinely collected electronic primary care data linked to national death registrations. People with a primary care record for HIV infection were compared to people without HIV. COVID-19 death was defined by ICD-10 codes U07.1 or U07.2 anywhere on the death certificate. Cox regression models were used to estimate the association between HIV infection and COVID-19 death, initially adjusted for age and sex, then adding adjustment for index of multiple deprivation and ethnicity, and finally for a broad range of comorbidities. Interaction terms were added to assess effect modification by age, sex, ethnicity, comorbidities and calendar time. Results: 17.3 million adults were included, of whom 27,480 (0.16%) had HIV recorded. People living with HIV were more likely to be male, of black ethnicity, and from a more deprived geographical area than the general population. There were 14,882 COVID-19 deaths during the study period, with 25 among people with HIV. People living with HIV had nearly three-fold higher risk of COVID-19 death than those without HIV after adjusting for age and sex (HR=2.90, 95% CI 1.96-4.30). The association was attenuated but risk remained substantially raised, after adjustment for deprivation and ethnicity (adjusted HR=2.52, 1.70-3.73) and further adjustment for comorbidities (HR=2.30, 1.55-3.41). There was some evidence that the association was larger among people of black ethnicity (HR = 3.80, 2.15-6.74, compared to 1.64, 0.92-2.90 in non-black individuals, p-interaction=0.045) Interpretation: HIV infection was associated with a markedly raised risk of COVID-19 death in a country with high levels of antiretroviral therapy coverage and viral suppression; the association was larger in people of black ethnicity. 2020-08-07
Steven Riley; Kylie E. C. Ainslie; Oliver Eales; Caroline E Walters; Haowei Wang; Christina J Atchison; Peter Diggle; Deborah Ashby; Christl A. Donnelly; Graham Cooke; Wendy Barclay; Helen Ward; Ara Darzi; Paul Elliott Transient dynamics of SARS-CoV-2 as England exited national lockdown Control of the COVID-19 pandemic requires a detailed understanding of prevalence of SARS-CoV-2 virus in the population. Case-based surveillance is necessarily biased towards symptomatic individuals and sensitive to varying patterns of reporting in space and time. The real-time assessment of community transmission antigen study (REACT-1) is designed to overcome these limitations by obtaining prevalence data based on a nose and throat swab RT-PCR test among a representative community-based sample in England, including asymptomatic individuals. Here, we describe results comparing rounds 1 and 2 carried out during May and mid June / early July 2020 respectively across 315 lower tier local authority areas. In round 1 we found 159 positive samples from 120,620 tested swabs while round 2 there were 123 positive samples from 159,199 tested swabs, indicating a downwards trend in prevalence from 0.13% (95% CI, 0.11%, 0.15%) to 0.077% (0.065%, 0.092%), a halving time of 38 (28, 58) days, and an R of 0.89 (0.86, 0.93). The proportion of swab-positive participants who were asymptomatic at the time of sampling increased from 69% (61%, 76%) in round 1 to 81% (73%, 87%) in round 2. Although health care and care home workers were infected far more frequently than other workers in round 1, the odds were markedly reduced in round 2. Age patterns of infection changed between rounds, with a reduction by a factor of five in prevalence in 18 to 24 year olds. Our data were suggestive of increased risk of infection in Black and Asian (mainly South Asian) ethnicities. Using regional and detailed case location data, we detected increased infection intensity in and near London. Under multiple sensitivity analyses, our results were robust to the possibility of false positives. At the end of the initial lockdown in England, we found continued decline in prevalence and a shift in the pattern of infection by age and occupation. Community-based sampling, including asymptomatic individuals, is necessary to fully understand the nature of ongoing transmission. 2020-08-06
Anoop SV Shah; Rachael Wood; Ciara Gribben; David Caldwell; Jennifer Bishop; Amanda Weir; Sharon Kennedy; Martin Reid; Alison Smith-Palmer; David Goldberg; Jim McMenamin; Colin Fischbacher; Chris Robertson; Sharon Hutchinson; Paul M McKeigue; Helen M Colhoun; David McAllister Risk of hospitalisation with coronavirus disease 2019 in healthcare workers and their households:a nationwide linkage cohort study Objective: Many healthcare staff work in high-risk settings for contracting and transmitting Severe Acute Respiratory Syndrome Coronavirus 2. Their risk of hospitalisation for coronavirus disease 2019 (COVID-19), and that of their households, is poorly understood. Design and settings and participants: During the peak period for COVID-19 infection in Scotland (1st March 2020 to 6th June 2020) we conducted a national record linkage study to compare the risk of COVID-19 hospitalisation among healthcare workers (age: 18-65 years), their households and other members of the general population. Main outcome: Hospitalisation with COVID-19 Results: The cohort comprised 158,445 healthcare workers, the majority being patient facing (90,733 / 158,445; 57.3%), and 229,905 household members. Of all COVID-19 hospitalisations in the working age population (18-65-year-old), 17.2% (360 / 2,097) were in healthcare workers or their households. Adjusting for age, sex, ethnicity, socio-economic deprivation and comorbidity, the risk of COVID-19 hospitalisation in non-patient facing healthcare workers and their households was similar to the risk in the general population (hazards ratio [HR] 0.81; 95%CI 0.52-1.26 and 0.86; 95%CI 0.49-1.51 respectively). In models adjusting for the same covariates however, patient facing healthcare workers, compared to non-patient facing healthcare workers, were at higher risk (HR 3.30; 95%CI 2.13-5.13); so too were household members of patient facing healthcare workers (HR 1.79; 95%CI 1.10-2.91). On sub-dividing patient-facing healthcare workers into those who worked in front-door, intensive care and non-intensive care aerosol generating settings and other, those in front door roles were at higher risk (HR 2.09; 95%CI 1.49-2.94). For most patient facing healthcare workers and their households, the estimated absolute risk of COVID-19 hospitalisation was less than 0.5% but was 1% and above in older men with comorbidity. Conclusions: Healthcare workers and their households contribute a sixth of hospitalised COVID-19 cases. Whilst the absolute risk of hospitalisation was low overall, patient facing healthcare workers and their households had 3- and 2-fold increased risks of COVID-19 hospitalisation. 2020-08-04
Matt J Keeling; Louise Dyson; Glen Guyver-Fletcher; Alex Holmes; Malcolm G Semple; - ISARIC4C Investigators; Michael J Tildesley; Edward M Hill Fitting models to the COVID-19 outbreak and estimating R The COVID-19 pandemic has brought to the fore the need for policy makers to receive timely and ongoing scientific guidance in response to this recently emerged human infectious disease. Fitting mathematical models of infectious disease transmission to the available epidemiological data provides a key statistical tool for understanding the many quantities of interest that are not explicit in the underlying epidemiological data streams. Of these, the basic reproductive ratio, $R$, has taken on special significance in terms of the general understanding of whether the epidemic is under control ($R<1$). Unfortunately, none of the epidemiological data streams are designed for modelling, hence assimilating information from multiple (often changing) sources of data is a major challenge that is particularly stark in novel disease outbreaks. Here, we present in some detail the inference scheme employed for calibrating the Warwick COVID-19 model to the available public health data streams, which span hospitalisations, critical care occupancy, mortality and serological testing. We then perform computational simulations, making use of the acquired parameter posterior distributions, to assess how the accuracy of short-term predictions varied over the timecourse of the outbreak. To conclude, we compare how refinements to data streams and model structure impact estimates of epidemiological measures, including the estimated growth rate and daily incidence. 2020-08-04
Xiaomeng Zhang; Xue Li; Ziwen Sun; Yazhou He; Wei Xu; Harry Campbell; Malcolm G Dunlop; Maria Timofeeva; Evropi Theodoratou Physical activity, BMI and COVID-19: an observational and Mendelian randomisation study Physical activity (PA) is known to be a protective lifestyle factor against several non-communicable diseases while its impact on infectious diseases, including Coronavirus Disease 2019 (COVID-19) is not as clear. We performed univariate and multivariate logistic regression to identify associations between body mass index (BMI) and both objectively and subjectively measured PA collected prospectively and COVID-19 related outcomes (Overall COVID-19, inpatient COVID-19, outpatient COVID-19, and COVID-19 death) in the UK Biobank (UKBB) cohort. Subsequently, we tested causality by using two-sample Mendelian randomisation (MR) analysis. In the multivariable model, the increased acceleration vector magnitude PA (AMPA) was associated with a decreased probability of overall and outpatient COVID-19. No association was found between self-reported moderate-to-vigorous PA (MVPA) or BMI and COVID-19 related outcomes. Although no causal association was found by MR analyses, this may be due to limited power and we conclude policies to encourage and facilitate exercise at a population level during the pandemic should be considered. 2020-08-04
Stephen R Knight; Antonia Ho; Riinu Pius; Iain Buchan; Gail Carson; Thomas M Drake; Jake Dunning; Cameron J Fairfield; Carrol Gamble; Christopher A Green; Rishi K Gupta; Sophie Halpin; Hayley Hardwick; Karl Holden; Peter W Horby; Clare Jackson; Kenneth A McLean; Laura Merson; Jonathan S Nguyen-Van-Tam; Lisa Norman; Mahdad Noursadeghi; Piero L Olliaro; Mark G Pritchard; Clark D Russell; Catherine A Shaw; Aziz Sheikh; Tom Solomon; Cathie Sudlow; Olivia V Swann; Lance Turtle; Peter JM Openshaw; J Kenneth Baillie; Malcolm Gracie Semple; Annemarie B Docherty; Ewen M Harrison Risk stratification of patients admitted to hospital with covid-19 using the ISARIC WHO Clinical Characterisation Protocol: development and validation of the 4C Mortality Score Objectives To develop and validate a pragmatic risk score to predict mortality for patients admitted to hospital with covid-19. Design Prospective observational cohort study: ISARIC WHO CCP-UK study (ISARIC Coronavirus Clinical Characterisation Consortium [4C]). Model training was performed on a cohort of patients recruited between 6 February and 20 May 2020, with validation conducted on a second cohort of patients recruited between 21 May and 29 June 2020. Setting 260 hospitals across England, Scotland, and Wales. Participants Adult patients ([&ge;]18 years) admitted to hospital with covid-19 admitted at least four weeks before final data extraction. Main outcome measures In-hospital mortality. Results There were 34 692 patients included in the derivation dataset (mortality rate 31.7%) and 22 454 in the validation dataset (mortality 31.5%). The final 4C Mortality Score included eight variables readily available at initial hospital assessment: age, sex, number of comorbidities, respiratory rate, peripheral oxygen saturation, level of consciousness, urea, and C-reactive protein (score range 0-21 points). The 4C risk stratification score demonstrated high discrimination for mortality (derivation cohort: AUROC 0.79; 95% CI 0.78 - 0.79; validation cohort 0.78, 0.77-0.79) with excellent calibration (slope = 1.0). Patients with a score [&ge;]15 (n = 2310, 17.4%) had a 67% mortality (i.e., positive predictive value 67%) compared with 1.0% mortality for those with a score [&le;]3 (n = 918, 7%; negative predictive value 99%). Discriminatory performance was higher than 15 pre-existing risk stratification scores (AUROC range 0.60-0.76), with scores developed in other covid-19 cohorts often performing poorly (range 0.63-0.73). Conclusions We have developed and validated an easy-to-use risk stratification score based on commonly available parameters at hospital presentation. This outperformed existing scores, demonstrated utility to directly inform clinical decision making, and can be used to stratify inpatients with covid-19 into different management groups. The 4C Mortality Score may help clinicians identify patients with covid-19 at high risk of dying during current and subsequent waves of the pandemic. Study registration ISRCTN66726260 2020-08-02
John Dennis; Andrew McGovern; Sebastian Vollmer; Bilal A Mateen Improving COVID-19 critical care mortality over time in England: A national cohort study, March to June 2020 Objectives: To determine the trend in mortality risk over time in people with severe COVID-19 requiring critical care (high intensive unit [HDU] or intensive care unit [ICU]) management. Methods: We accessed national English data on all adult COVID-19 specific critical care admissions from the COVID-19 Hospitalisation in England Surveillance System (CHESS), up to the 29th June 2020 (n=14,958). The study period was 1st March until 30th May, meaning every patient had 30 days of potential follow-up available. The primary outcome was in-hospital 30-day all-cause mortality. Hazard ratios for mortality were estimated for those admitted each week using a Cox proportional hazards models, adjusting for age (non-linear restricted cubic spline), sex, ethnicity, comorbidities, and geographical region. Results: 30-day mortality peaked for people admitted to critical care in early April (peak 29.1% for HDU, 41.5% for ICU). There was subsequently a sustained decrease in mortality risk until the end of the study period. As a linear trend from the first week of April, adjusted mortality risk decreased by 11.2% (adjusted HR 0.89 [95% CI 0.87 - 0.91]) per week in HDU, and 9.0% (adjusted HR 0.91 [95% CI 0.88 - 0.94]) in ICU. Conclusions: There has been a substantial mortality improvement in people admitted to critical care with COVID-19 in England, with markedly lower mortality in people admitted in mid-April and May compared to earlier in the pandemic. This trend remains after adjustment for patient demographics and comorbidities suggesting this improvement is not due to changing patient characteristics. Possible causes include the introduction of effective treatments as part of clinical trials and a falling critical care burden. 2020-08-01
Ricardo Costeira; Karla A Lee; Benjamin Murray; Colette Christiansen; Juan Castillo-Fernandez; Mary Ni Lochlainn; Joan Capdevila Pujol; Iain Buchan; Louise C Kenny; Jonathan Wolf; Sebastien Ourselin; Claire Steves; Timothy Spector; Louise Newson; Jordana Bell Estrogen and COVID-19 symptoms: associations in women from the COVID Symptom Study Background: Men and older women have been shown to be at higher risk of adverse COVID-19 outcomes. Animal model studies of SARS-CoV and MERS suggest that the age and sex difference in COVID-19 symptom severity may be due to a protective effect of the female sex hormone estrogen. Females have shown an ability to mount a stronger immune response to a variety of viral infections because of more robust humoral and cellular immune responses. Objectives: We sought to determine whether COVID-19 positivity increases in women entering menopause. We also aimed to identify whether premenopausal women taking exogenous hormones in the form of the combined oral contraceptive pill (COCP) and post-menopausal women taking hormone replacement therapy (HRT) have lower predicted rates of COVID-19, using our published symptom-based model. Design: The COVID Symptom Study developed by Kings College London and Zoe Global Limited was launched in the UK on 24th March 2020. It captured self-reported information related to COVID-19 symptoms. Data used for this study included records collected between 7th May - 15th June 2020. Main outcome measures: We investigated links between COVID-19 rates and 1) menopausal status, 2) COCP use and 3) HRT use, using symptom-based predicted COVID-19, tested COVID-19, and disease severity based on requirement for hospital attendance or respiratory support. Participants: Female users of the COVID Symptom Tracker Application in the UK, including 152,637 women for menopause status, 295,689 for COCP use, and 151,193 for HRT use. Analyses were adjusted for age, smoking and BMI. Results: Post-menopausal women aged 40-60 years had a higher rate of predicted COVID (P=0.003) and a corresponding range of symptoms, with consistent, but not significant trends observed for tested COVID-19 and disease severity. Women aged 18-45 years taking COCP had a significantly lower predicted COVID-19 (P=8.03E-05), with a reduction in hospital attendance (P=0.023). Post-menopausal women using HRT or hormonal therapies did not exhibit consistent associations, including increased rates of predicted COVID-19 (P=2.22E-05) for HRT users alone. Conclusions: Our findings support a protective effect of estrogen on COVID-19, based on positive association between predicted COVID-19 and menopausal status, and a negative association with COCP use. HRT use was positively associated with COVID-19 symptoms; however, the results should be considered with caution due to lack of data on HRT type, route of administration, duration of treatment, and potential comorbidities. Trial registration: The App Ethics has been approved by KCL ethics Committee REMAS ID 18210, review reference LRS-19/20-18210 2020-08-01
Zachary J. Madewell; Yang Yang; Ira M. Longini Jr.; M. Elizabeth Halloran; Natalie E. Dean Household transmission of SARS-CoV-2: a systematic review and meta-analysis of secondary attack rate Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is spread by direct, indirect, or close contact with infected people via infected respiratory droplets or saliva. Crowded indoor environments with sustained close contact and conversations are a particularly high-risk setting. Methods: We performed a meta-analysis through July 29, 2020 of SARS-CoV-2 household secondary attack rate (SAR), disaggregating by several covariates (contact type, symptom status, adult/child contacts, contact sex, relationship to index case, index case sex, number of contacts in household, coronavirus). Findings: We identified 40 relevant published studies that report household secondary transmission. The estimated overall household SAR was 18.8% (95% confidence interval [CI]: 15.4%-22.2%), which is higher than previously observed SARs for SARS-CoV and MERS-CoV. We observed that household SARs were significantly higher from symptomatic index cases than asymptomatic index cases, to adult contacts than children contacts, to spouses than other family contacts, and in households with one contact than households with three or more contacts. Interpretation: To prevent the spread of SARS-CoV-2, people are being asked to stay at home worldwide. With suspected or confirmed infections referred to isolate at home, household transmission will continue to be a significant source of transmission. 2020-08-01
Wei Shi; Ming Chen; Yang Yang; Wei Zhou; Shiyun Chen; Yangbo Hu; Bin Liu A dynamic regulatory interface on SARS-CoV-2 RNA polymerase The RNA-dependent RNA polymerase (RdRp) of SARS-CoV-2 is the core machinery responsible for the viral genome replication and transcription and also a major antiviral target. Here we report the cryo-electron microscopy structure of a post-translocated SARS-CoV-2 RdRp core complex, comprising one nsp12, one separate nsp8(I) monomer, one nsp7-nsp8(II) subcomplex and a replicating RNA substrate. Compared with the recently reported SARS-CoV-2 RdRp complexes, the nsp8(I)/nsp7 interface in this RdRp complex shifts away from the nsp12 polymerase. Further functional characterizations suggest that specific interactions between the nsp8(I) and nsp7, together with the rearrangement of nsp8(I)/nsp7 interface, ensure the efficient and processive RNA synthesis by the RdRp complex. Our findings provide a mechanistic insight into how nsp7 and nsp8 cofactors regulate the polymerase activity of nsp12 and suggest a potential new intervention interface, in addition to the canonical polymerase active center, in RdRp for antiviral design. Author summarySince it was first discovered and reported in late 2019, the coronavirus disease 2019 (COVID-19) pandemic caused by highly contagious SARS-CoV-2 virus is wreaking havoc around the world. Currently, no highly effective and specific antiviral drug is available for clinical treatment. Therefore, the threat of COVID-19 transmission necessitates the discovery of more effective antiviral strategies. Viral RNA-dependent RNA polymerase (RdRp) is an important antiviral drug target. Here, our cryo-EM structure of a SARS-CoV-2 RdRp/RNA replicating complex reveals a previously uncharacterized overall shift of the cofactor nsp8(I)/nsp7 interface, leading to its rearrangement. Through in vitro functional test, we found that the specific interactions on the interface are important to the efficient RNA polymerase activity of SARS-CoV-2 RdRp. These observations let us to suggest this interface as a potential new drug intervention site, outside of the canonical polymerase active center, in RdRp for antiviral design. Our findings would provide new insights into regulatory mechanism of this novel SARS-CoV-2 RdRp, contribute to the design of antiviral drugs against SARS-CoV-2, and benefit the global public health. 2020-07-30
RICARDO AGUAS; Adam Mahdi; RIMA SHRETTA; Peter Horby; Martin Landray; Lisa J White The potential health and economic impact of dexamethasone treatment for patients with COVID-19 Dexamethasone has been shown to reduce mortality in hospitalised COVID-19 patients needing oxygen and ventilation by 18% and 36%, respectively. Here, we estimate the potential number of lives saved and life years gained if this treatment would be rolled out in the UK and globally, as well as its cost-effectiveness of implementing this intervention. We estimate that, for the UK, approximately 12,000 [4,250 - 27,000] lives could be saved by January 2021. Assuming that dexamethasone has a similar effect size in settings where access to oxygen therapies is limited, this would translate into approximately 650,000 [240,000 - 1,400,000] lives saved globally. If dexamethasone acts differently in these settings, the impact could be less than half of this value. To estimate the full potential of dexamethasone in the global fight against COVID-19, it is essential to perform clinical research in settings with limited access to oxygen and/or ventilators, e.g. in low and middle-income countries. 2020-07-30
Xiangyu Chen; Zhiwei Pan; Shuai Yue; Fei Yu; Junsong Zhang; Yang Yang; Ren Li; Bingfeng Liu; Xiaofan Yang; Leiqiong Gao; Zhirong Li; Yao Lin; Qizhao Huang; Lifan Xu; Jianfang Tang; Li Hu; Jing Zhao; Pinghuang Liu; Guozhong Zhang; Yaokai Chen; Kai Deng; Lilin Ye Disease severity dictates SARS-CoV-2-specific neutralizing antibody responses in COVID-19 COVID-19 patients exhibit differential disease severity after SARS-CoV-2 infection. It is currently unknown as to the correlation between the magnitude of neutralizing antibody (NAb) responses and the disease severity in COVID-19 patients. In a cohort of 59 recovered patients with disease severity including severe, moderate, mild and asymptomatic, we observed the positive correlation between serum neutralizing capacity and disease severity, in particular, the highest NAb capacity in sera from the patients with severe disease, while a lack of ability of asymptomatic patients to mount competent NAbs. Furthermore, the compositions of NAb subtypes were also different between recovered patients with severe symptoms and with mild-to-moderate symptoms. These results reveal the tremendous heterogeneity of SARS-CoV-2-specific NAb responses and their correlations to disease severity, highlighting the needs of future vaccination in COVID-19 patients recovered from asymptomatic or mild illness. 2020-07-30
Philippa M Wells; Katie M Doores; Simon Couvreur; Rocio Martin Martinez; Jeffrey Seow; Carl Graham; Sam Acors; Neophytos Kouphou; Stuart Neil; Richard Tedder; Pedro Matos; Kate Poulton; Maria Jose Lista; Ruth Dickenson; Helin Sertkaya; Thomas Maguire; Edward Scourfield; Ruth Bowyer; Deborah Hart; Aoife O'Byrne; Kathryn Steele; Oliver Hemmings; Carolina Rosadas; Myra McClure; Joan Capedevila-Pujol; Jonathan wolf; Sebastien Ourseilin; Matthew Brown; Michael Malim; Timothy Spector; Claire Steves Estimates of the rate of infection and asymptomatic COVID-19 disease in a population sample from SE England Background: Understanding of the true asymptomatic rate of infection of SARS-CoV-2 is currently limited, as is understanding of the population-based seroprevalence after the first wave of COVID-19 within the UK. The majority of data thus far come from hospitalised patients, with little focus on general population cases, or their symptoms. Methods: We undertook enzyme linked immunosorbent assay characterisation of IgM and IgG responses against SARS-CoV-2 spike glycoprotein and nucleocapsid protein of 431 unselected general-population participants of the TwinsUK cohort from South-East England, aged 19-86 (median age 48; 85% female). 382 participants completed prospective logging of 14 COVID-19 related symptoms via the COVID Symptom Study App, allowing consideration of serology alongside individual symptoms, and a predictive algorithm for estimated COVID-19 previously modelled on PCR positive individuals from a dataset of over 2 million. Findings: We demonstrated a seroprevalence of 12% (51participants of 431). Of 48 seropositive individuals with full symptom data, nine (19%) were fully asymptomatic, and 16 (27%) were asymptomatic for core COVID-19 symptoms: fever, cough or anosmia. Specificity of anosmia for seropositivity was 95%, compared to 88% for fever cough and anosmia combined. 34 individuals in the cohort were predicted to be Covid-19 positive using the App algorithm, and of those, 18 (52%) were seropositive. Interpretation: Seroprevalence amongst adults from London and South-East England was 12%, and 19% of seropositive individuals with prospective symptom logging were fully asymptomatic throughout the study. Anosmia demonstrated the highest symptom specificity for SARS-CoV-2 antibody response. Funding: NIHR BRC, CDRF, ZOE global LTD, RST-UKRI/MRC 2020-07-30
Hilton J, Keeling MJ. Estimation of country-level basic reproductive ratios for novel Coronavirus (SARS-CoV-2/COVID-19) using synthetic contact matrices. PLoS computational biology 2020
Colin Pawlowski; Arjun Puranik; Hari Bandi; AJ Venkatakrishnan; Vineet Agarwal; Richard Kennedy; John C O'Horo; Gregory J Gores; Amy W Williams; John Halamka; Andrew D Badley; Venky Soundararajan Exploratory analysis of immunization records highlights decreased SARS-CoV-2 rates in individuals with recent non-COVID-19 vaccinations Multiple clinical studies are ongoing to assess whether existing vaccines may afford protection against SARS-CoV-2 infection through trained immunity. In this exploratory study, we analyze immunization records from 137,037 individuals who received SARS-CoV-2 PCR tests. We find that polio, Hemophilus influenzae type-B (HIB), measles-mumps-rubella (MMR), varicella, pneumococcal conjugate (PCV13), geriatric flu, and hepatitis A / hepatitis B (HepA-HepB) vaccines administered in the past 1, 2, and 5 years are associated with decreased SARS-CoV-2 infection rates, even after adjusting for geographic SARS-CoV-2 incidence and testing rates, demographics, comorbidities, and number of other vaccinations. Furthermore, age, race/ethnicity, and blood group stratified analyses reveal significantly lower SARS-CoV-2 rate among black individuals who have taken the PCV13 vaccine, with relative risk of 0.45 at the 5 year time horizon (n: 653, 95% CI: (0.32, 0.64), p-value: 6.9e-05). These findings suggest that additional pre-clinical and clinical studies are warranted to assess the protective effects of existing non-COVID-19 vaccines and explore underlying immunologic mechanisms. We note that the findings in this study are preliminary and are subject to change as more data becomes available and as further analysis is conducted. 2020-07-28
Vasilis Kontis; James E Bennett; Theo Rashid; Robbie M Parks; Jonathan Pearson-Stuttard; Michel Guillot; Perviz Asaria; Bin Zhou; Marco Battaglini; Gianni Corsetti; Martin McKee; Mariachiara Di Cesare; Colin D Mathers; Majid Ezzati Magnitude, demographics and dynamics of the impact of the first phase of the Covid-19 pandemic on all-cause mortality in 17 industrialised countries The Covid-19 pandemic affects mortality directly through infection as well as through changes in the social, environmental and healthcare determinants of health. The impacts on mortality are likely to vary across countries in magnitude, timing, and age and sex composition. Here, we applied an ensemble of 16 Bayesian probabilistic models to vital statistics data, by age group and sex, to consistently and comparably estimate the impacts of the first phase of the pandemic on all-cause mortality for 17 industrialised countries. The models accounted for factors that affect death rates including seasonality, temperature, and public holidays, as well as for medium-long-term secular trends and the dependency of death rates in each week on those in preceding week(s). From mid-February through the end of May 2020, an estimated 202,900 (95% credible interval 179,400-224,900) more people died in these 17 countries than would have had the pandemic not taken place. Nearly three quarters of these excess deaths occurred in England and Wales, Italy and Spain, where less than half of the total population of these countries live. When all-cause mortality is considered, the total number of deaths, deaths per 100,000 people, and relative increase in deaths were similar between men and women in most countries. Further, in many countries, the balance of excess deaths changed from male-dominated early in the pandemic to being equal or female-dominated later on. Taken over the entire first phase of the pandemic, there was no detectable rise in all-cause mortality in New Zealand, Bulgaria, Hungary, Norway, Denmark and Finland and for women in Austria and Switzerland (posterior probability of an increase in deaths <90%). Women in Portugal and men in Austria experienced relatively small increases in all-cause mortality, with posterior probabilities of 90-99%. For men in Switzerland and Portugal, and both sexes in the Netherlands, France, Sweden, Belgium, Italy, Scotland, Spain and England and Wales, all-cause mortality increased as a result of the pandemic with a posterior probability >99%. After accounting for population size, England and Wales and Spain experienced the highest death toll, nearly 100 deaths per 100,000 people; they also had the largest relative (percent) increase in deaths (37% (95% credible interval 30-44) in England and Wales; 38% (31-44) in Spain). New Zealand, Bulgaria, Hungary, Norway, Denmark and Finland experienced changes in deaths that ranged from possible slight declines to increases of no more than 5%. The large impact in England and Wales stems partly from having experienced (together with Spain) the highest weekly increases in deaths, more than doubling in some weeks, and having had (together with Sweden) the longest duration when deaths exceeded levels that would be expected in the absence of the pandemic. The heterogeneous magnitude and character of the excess deaths due to the Covid-19 pandemic reflect differences in how well countries have managed the pandemic (e.g., timing, extent and adherence to lockdowns and other social distancing measures; effectiveness of test, trace and isolate mechanisms), and the resilience and preparedness of the health and social care system (e.g., effective facility and community care pathways; minimising spread of infection within hospitals and care homes, and between them and the community). 2020-07-28
Paul M McKeigue; Sharon Kennedy; Amanda Weir; Jen Bishop; Stuart J McGurnaghan; David McAllister; Chris Robertson; Rachael Wood; Nazir Lone; Janet Murray; Thomas M Caparrotta; Alison Smith-Palmer; David Goldberg; Jim McMenamin; Colin Ramsay; Bruce Guthrie; Sharon Hutchinson; Helen M Colhoun Associations of severe COVID-19 with polypharmacy in the REACT-SCOT case-control study Objectives -- To investigate the relation of severe COVID-19 to prior drug prescribing. Design -- Matched case-control study (REACT-SCOT) based on record linkage to hospital discharges since June 2015 and dispensed prescriptions issued in primary care during the last 240 days. Setting -- Scottish population. Main outcome measure -- Severe COVID-19, defined by entry to critical care or fatal outcome. Participants -- All 4272 cases of severe COVID-19 in Scotland since the start of the epidemic, with 36948 controls matched for age, sex and primary care practice. Results -- Severe COVID-19 was strongly associated with the number of non-cardiovascular drug classes dispensed. This association was strongest in those not resident in care homes, in whom the rate ratio (95% CI) associated with dispensing of 12 or more drug classes versus none was 10.8 (8.7, 13.2), and was not accounted for by treatment of conditions designated as conferring increased risk. Of 17 drug classes postulated at the start of the epidemic to be "medications compromising COVID", all were associated with increased risk of severe COVID-19. The largest effect was for antipsychotic agents: rate ratio 4.14 (3.39, 5.07). Other drug classes with large effects included proton pump inhibitors (rate rato 2.19 (1.70, 2.80) for >= 2 defined daily doses/day), opioids (3.62 (2.65, 4.94) for >= 50 mg morphine equivalent/day) and gabapentinoids. These associations persisted after adjusting for covariates, and were stronger with recent than with non-recent exposure. Conclusions -- Severe COVID-19 is associated with polypharmacy and with drugs that cause sedation, respiratory depression or dyskinesia, have anticholinergic effects or affect the gastrointestinal system. These associations are not easily explained by co-morbidity. Although the evidence for causality is not conclusive, these results support existing guidance on reducing overprescribing of these drug classes and limiting inappropriate polypharmacy as a potential means of reducing COVID-19 risk. Registration -- ENCEPP number EUPAS35558 2020-07-27
Ellen Brooks-Pollock; Jonathan M Read; Angela R McLean; Matt J Keeling; Leon Danon Using social contact data to predict and compare the impact of social distancing policies with implications for school re-opening Background Social distancing measures, including school closures, are being used to control SARS-CoV-2 transmission in many countries. Once "lockdown" has driven incidence to low levels, selected activities are being permitted. Re-opening schools is a priority because of the welfare and educational impact of closures on children. However, the impact of school re-opening needs to be considered within the context of other measures. Methods We use social contact data from the UK to predict the impact of social distancing policies on the reproduction number. We calibrate our tool to the COVID-19 epidemic in the UK using publicly available death data and Google Community Mobility Reports. We focus on the impact of re-opening schools against a back-drop of wider social distancing easing. Results We demonstrate that pre-collected social contact data, combined with incidence data and Google Community Mobility Reports, is able to provide a time-varying estimate of the reproduction number (R). From an pre-control setting when R=2.7 (95%CI 2.5, 2.9), we estimate that the minimum reproduction number that can be achieved in the UK without limiting household contacts is 0.45 (95%CI:0.41-0.50); in the absence of other changes, preventing leisure contacts has a smaller impact (R=2.0,95%CI:1.8-2.4) than preventing work contacts (R=1.5,95%CI:1.4-1.7). We find that following lockdown (when R=0.7 (95% CI 0.6, 0.8)), opening primary schools in isolation has a modest impact on transmission R=0.83 (95%CI:0.77-0.90) but that high adherence to other measures is needed. Opening secondary schools as well as primary school is predicted to have a larger overall impact (R=0.95,95%CI:0.85-1.07), however transmission could still be controlled with effective contact tracing. Conclusions Our findings suggest that primary school children can return to school without compromising transmission, however other measures, such as social distancing and contract tracing, are required to control transmission if all age groups are to return to school. Our tool provides a mapping from policies to the reproduction number and can be used by policymakers to compare the impact of social-easing measures, dissect mitigation strategies and support careful localized control strategies. 2020-07-27
Lucy MacDonald; Thomas Dan Otto; Aziza Elmesmari; Barbara Tolusso; Domenico Somma; Charles McSharry; Elisa Gremese; Iain B McInnes; Stefano Alivernini; Mariola Kurowska-Stolarska COVID-19 and Rheumatoid Arthritis share myeloid pathogenic and resolving pathways BackgroundWe recently delineated the functional biology of pathogenic and inflammation resolving synovial tissue macrophage clusters in rheumatoid arthritis (RA). Whilst RA is not a viral respiratory syndrome, it represents a pro-inflammatory cytokine-driven chronic articular condition often accompanied by cardiovascular and lung pathologies. We hypothesised that functionally equivalent macrophage clusters in the lung might govern inflammation and resolution of COVID-19 pneumonitis. MethodsTo provide insight into the targetable functions of COVID-19 bronchoalveolar lavage (BALF) macrophage clusters, a comparative analysis of BALF macrophage single cell transcriptomics (scRNA-seq) with synovial tissue (ST) macrophage scRNA-seq and functional biology was performed. The function of shared BALF and ST MerTK inflammation-resolving pathway was confirmed with inhibitor in primary macrophage-synovial fibroblast co-cultures. Results. Distinct BALF FCNpos and FCNposSPP1pos macrophage clusters emerging in severe COVID-19 patients were closely related to ST CD48highS100A12pos and CD48posSPP1pos clusters driving synovitis in active RA. They shared transcriptomic profile and pathogenic mechanisms. Healthy lung resident alveolar FABP4pos macrophages shared a regulatory transcriptomic profile, including TAM (Tyro, Axl, MerTK) receptors pathway with synovial tissue TREM2pos macrophages that govern RA remission. This pathway was substantially altered in BALF macrophages of severe COVID-19. In vitro dexamethasone inhibited tissue inflammation via macrophages MerTK function. ConclusionPathogenesis and resolution of COVID-19 pneumonitis and RA synovitis might be driven by similar macrophage clusters and pathways. The MerTK-dependent anti-inflammatory mechanisms of dexamethasone, and the homeostatic function of TAM pathways that maintain RA in remission advocate the therapeutic MerTK agonism to ameliorate the cytokine storm and pneumonitis of severe COVID-19. 2020-07-26
Rishi K Gupta; Michael Marks; Thomas H. A. Samuels; Akish Luintel; Tommy Rampling; Humayra Chowdhury; Matteo Quartagno; Arjun Nair; Marc Lipman; Ibrahim Abubakar; Maarten van Smeden; Wai Keong Wong; Bryan Williams; Mahdad Noursadeghi Systematic evaluation and external validation of 22 prognostic models among hospitalised adults with COVID-19: An observational cohort study Background The number of proposed prognostic models for COVID-19, which aim to predict disease outcomes, is growing rapidly. It is not known whether any are suitable for widespread clinical implementation. We addressed this question by independent and systematic evaluation of their performance among hospitalised COVID-19 cases. Methods We conducted an observational cohort study to assess candidate prognostic models, identified through a living systematic review. We included consecutive adults admitted to a secondary care hospital with PCR-confirmed or clinically diagnosed community-acquired COVID-19 (1st February to 30th April 2020). We reconstructed candidate models as per their original descriptions and evaluated performance for their original intended outcomes (clinical deterioration or mortality) and time horizons. We assessed discrimination using the area under the receiver operating characteristic curve (AUROC), and calibration using calibration plots, slopes and calibration-in-the-large. We calculated net benefit compared to the default strategies of treating all and no patients, and against the most discriminating predictor in univariable analyses, based on a limited subset of a priori candidates. Results We tested 22 candidate prognostic models among a cohort of 411 participants, of whom 180 (43.8%) and 115 (28.0%) met the endpoints of clinical deterioration and mortality, respectively. The highest AUROCs were achieved by the NEWS2 score for prediction of deterioration over 24 hours (0.78; 95% CI 0.73-0.83), and a novel model for prediction of deterioration <14 days from admission (0.78; 0.74-0.82). Calibration appeared generally poor for models that used probability outcomes. In univariable analyses, admission oxygen saturation on room air was the strongest predictor of in-hospital deterioration (AUROC 0.76; 0.71-0.81), while age was the strongest predictor of in-hospital mortality (AUROC 0.76; 0.71-0.81). No prognostic model demonstrated consistently higher net benefit than using the most discriminating univariable predictors to stratify treatment, across a range of threshold probabilities. Conclusions Oxygen saturation on room air and patient age are strong predictors of deterioration and mortality among hospitalised adults with COVID-19, respectively. None of the prognostic models evaluated offer incremental value for patient stratification to these univariable predictors. 2020-07-26
Kiesha Prem; Kevin van Zandvoort; Petra Klepac; Rosalind M Eggo; Nicholas G Davies; - Centre for the Mathematical Modelling of Infectious Diseases COVID-19 Working Group; Alex R Cook; Mark Jit Projecting contact matrices in 177 geographical regions: an update and comparison with empirical data for the COVID-19 era Mathematical models have played a key role in understanding the spread of directly-transmissible infectious diseases such as Coronavirus Disease 2019 (COVID-19), as well as the effectiveness of public health responses. As the risk of contracting directly-transmitted infections depends on who interacts with whom, mathematical models often use contact matrices to characterise the spread of infectious pathogens. These contact matrices are usually generated from diary-based contact surveys. However, the majority of places in the world do not have representative empirical contact studies, so synthetic contact matrices have been constructed using more widely available setting-specific survey data on household, school, classroom, and workplace composition combined with empirical data on contact patterns in Europe. In 2017, the largest set of synthetic contact matrices to date were published for 152 geographical locations. In this study, we update these matrices with the most recent data and extend our analysis to 177 geographical locations. Due to the observed geographic differences within countries, we also quantify contact patterns in rural and urban settings where data is available. Further, we compare both the 2017 and 2020 synthetic matrices to out-of-sample empirically-constructed contact matrices, and explore the effects of using both the empirical and synthetic contact matrices when modelling physical distancing interventions for the COVID-19 pandemic. We found that the synthetic contact matrices reproduce the main traits of the contact patterns in the empirically-constructed contact matrices. Models parameterised with the empirical and synthetic matrices generated similar findings with few differences observed in age groups where the empirical matrices have missing or aggregated age groups. This finding means that synthetic contact matrices may be used in modelling outbreaks in settings for which empirical studies have yet to be conducted. 2020-07-25
Islam Hamed; Nesreen Shaban; Marwan Nassar; Sam Love; Martin D Curran; Stephen Webb; Huina Yang; Anthony Rostron; Katherine Watson; Vilas Navapurkar; Razeenn Mahroof; Andrew Conway Morris Paired nasopharyngeal and deep lung testing for SARS-CoV2 reveals a viral gradient in critically ill patients: a multi-centre study Introduction Samples for diagnostic tests for SARS-CoV-2 can be obtained from the upper (nasopharyngeal/oropharyngeal swabs) or lower respiratory tract (sputum or tracheal aspirate or broncho-alveolar lavage - BAL). Data from different testing sites indicates different rates of positivity. Reverse-transcriptase polymerase chain reaction (RT-PCR) allows for semi-quantitative estimates of viral load as time to crossing threshold (Ct) is inversely related to viral load. Objectives The objective of our study was to evaluate SARS-CoV2 RNA loads between paired nasopharyngeal (NP) and deep lung (endotracheal aspirate or BAL) samples from critically ill patients. Methods SARS-CoV-2 RT-PCR results were retrospectively reviewed for 51 critically ill patients from 5 intensive care units in 3 hospitals ; Addenbrookes Hospital Cambridge (3 units), Royal Papworth Cambridge (1 unit), and Royal Sunderland Hospital (1 unit). At the times when paired NP and deep lung samples were obtained, one patient had been on oxygen only, 6 patients on non-invasive ventilation, 18 patients on ECMO, and 26 patients mechanically ventilated. Results Results collected showed significant gradient between NP and deep lung viral loads. Median Ct value was 29 for NP samples and 24 for deep lung samples. Of 51 paired samples, 16 were negative (below limit of detection) on NP swabs but positive (above limit of detection) on deep lung sample, whilst 2 were negative on deep sample but positive on NP (both patients were on ECMO). Conclusions It has been suggested that whilst SARS-CoV1 tends to replicate in the lower respiratory tract, SARS-CoV2 replicates more vigorously in the upper respiratory tract. These data challenge that assumption. These data suggest that viral migration to, and proliferation in, the lower respiratory tract may be a key factor in the progression to critical illness and the development of severe acute respiratory syndrome (SARS). Factors which promote this migration should be examined for association with severe COVID-19. From a practical point of view, patients with suspected severe COVID-19 should have virological samples obtained from the lower respiratory tract where-ever possible, as upper respiratory samples have a significant negative rate. 2020-07-25
Samuel Clifford; Billy J Quilty; Timothy W Russell; Yang Liu; Yung-Wai Desmond Chan; Carl A B Pearson; Rosalind M Eggo; Akira Endo; - CMMID COVID-19 Working Group; Stefan Flasche; W John Edmunds Strategies to reduce the risk of SARS-CoV-2 re-introduction from international travellers To mitigate SARS-CoV-2 transmission risks from international travellers, many countries currently use a combination of up to 14 days of self-quarantine on arrival and testing for active infection. We used a simulation model of air travellers arriving to the UK from the EU or the USA and the timing of their stages of infection to evaluate the ability of these strategies to reduce the risk of seeding community transmission. We find that a quarantine period of 8 days on arrival with a PCR test on day 7 (with a 1-day delay for test results) can reduce the number of infectious arrivals released into the community by a median 94% compared to a no quarantine, no test scenario. This reduction is similar to that achieved by a 14-day quarantine period (median 99% reduction). Shorter quarantine periods still can prevent a substantial amount of transmission; all strategies in which travellers spend at least 5 days (the mean incubation period) in quarantine and have at least one negative test before release are highly effective (e.g. a test on day 5 with release on day 6 results in a median 88% reduction in transmission potential). Without intervention, the current high prevalence in the US (40 per 10,000) results in a higher expected number of infectious arrivals per week (up to 23) compared to the EU (up to 12), despite an estimated 8 times lower volume of travel in July 2020. Requiring a 14-day quarantine period likely results in less than 1 infectious traveller each entering the UK per week from the EU and the USA (97.5th percentile). We also find that on arrival the transmission risk is highest from pre-symptomatic travellers; quarantine policies will shift this risk increasingly towards asymptomatic infections if eventually-symptomatic individuals self-isolate after the onset of symptoms. As passenger numbers recover, strategies to reduce the risk of re-introduction should be evaluated in the context of domestic SARS-CoV-2 incidence, preparedness to manage new outbreaks, and the economic and psychological impacts of quarantine. 2020-07-24
Matteo Scortichini; Rochelle Schneider dos Santos; Francesca De' Donato; Manuela De Sario; Paola Michelozzi; Marina Davoli; Pierre Masselot; Francesco Sera; Antonio Gasparrini Excess mortality during the COVID-19 outbreak in Italy: a two-stage interrupted time series analysis Background: Italy was the first country outside China to experience the impact of the COVID-19 pandemic, which resulted in a significant health burden. This study presents an analysis of the excess mortality across the 107 Italian provinces, stratified by sex, age group, and period of the outbreak. Methods: The analysis was performed using a two-stage interrupted time series design using daily mortality data for the period January 2015 - May 2020. In the first stage, we performed province-level quasi-Poisson regression models, with smooth functions to define a baseline risk while accounting for trends and weather conditions and to flexibly estimate the variation in excess risk during the outbreak. Estimates were pooled in the second stage using a mixed-effects multivariate meta-analysis. Results: In the period 15 February - 15 May 2020, we estimated an excess of 47,490 (95% empirical confidence intervals: 43,984 to 50,362) deaths in Italy, corresponding to an increase of 29.5% (95%eCI: 26.8 to 31.9%) from the expected mortality. The analysis indicates a strong geographical pattern, with the majority of excess deaths occurring in northern regions, where few provinces experienced up to 800% increase during the peak in late March. There were differences by sex, age, and area both in the overall impact and in its temporal distribution. Conclusions: This study offers a detailed picture of excess mortality during the first months of the COVID-19 pandemic in Italy. The strong geographical and temporal patterns can be related to implementation of lockdown policies and multiple direct and indirect pathways in mortality risk. 2020-07-24
Endo A, Centre for the Mathematical Modelling of Infectious Diseases COVID-19 Working Group, Abbott S, Kucharski AJ, Funk S. Estimating the overdispersion in COVID-19 transmission using outbreak sizes outside China. Wellcome open research 2020
Liu Y, Centre for Mathematical Modelling of Infectious Diseases nCoV Working Group, Funk S, Flasche S. The contribution of pre-symptomatic infection to the transmission dynamics of COVID-2019. Wellcome open research 2020
Leclerc QJ, Fuller NM, Knight LE, CMMID COVID-19 Working Group, Funk S, Knight GM. What settings have been linked to SARS-CoV-2 transmission clusters? Wellcome open research 2020
Gisli Jenkins; Tom Drake; Annemarie B Docherty; Ewan Harrison; Jennifer Quint; Huzaifa Adamali; Sarah Agnew; Suresh Babu; Christopher Barber; Shaney Barratt; Elisabeth Bendstrup; Stephen Bianchi; Diego Castillo; Nazia Chaudhuri; Felix Chua; Robina Coker; William Chang; Anjali Cranshaw; Louise Crowley; Davinder Dosanjh; Christine Fiddler; Ian A Forrest; Peter George; Michael Gibbons; Katherine Groom; Sarah Haney; Simon Hart; Emily Heiden; Michael Henry; Ling-Pei Ho; Rachel Hoyles; John Hutchinson; Killian Hurley; Mark Jones; Steve Jones; Maria Kokosi; Michael Kreuter; Laura Mackay; Siva Mahendran; Georgios Margaritopoulos; Maria Molina-Molina; Philip Molyneaux; Aidan D O'Brien; Katherine O'Reilly; Alice Packham; Helen Parfrey; Venerino Poletti; Joanna Porter; Elisabetta Renzoni; Pilar Rivera-Ortega; Anne-Marie Russell; Gauri Saini; Lisa G Spencer; Giulia Stella; Helen Stone; Sharon Sturney; David Thickett; Muhunthan Thillai; Timothy Wallis; Katie Ward; Athol U Wells; Alex West; Melissa Wickremasinghe; Felix Woodhead; Glenn Herson; Lucy Howard; Peter JM Openshaw; J Kenneth Baillie; Malcolm Gracie Semple; Iain Stewart Outcome of hospitalisation for COVID-19 in patients with Interstitial Lung Disease: An international multicentre study. Rationale: The impact of COVID-19 on patients with Interstitial Lung Disease (ILD) has not been established. Objectives: To assess outcomes following COVID-19 in patients with ILD versus those without in a contemporaneous age, sex and comorbidity matched population. Methods: An international multicentre audit of patients with a prior diagnosis of ILD admitted to hospital with COVID-19 between 1 March and 1 May 2020 was undertaken and compared with patients, without ILD obtained from the ISARIC 4C cohort, admitted with COVID-19 over the same period. The primary outcome was survival. Secondary analysis distinguished IPF from non-IPF ILD and used lung function to determine the greatest risks of death. Measurements and Main Results: Data from 349 patients with ILD across Europe were included, of whom 161 were admitted to hospital with laboratory or clinical evidence of COVID-19 and eligible for propensity-score matching. Overall mortality was 49% (79/161) in patients with ILD with COVID-19. After matching ILD patients with COVID-19 had higher mortality (HR 1.60, Confidence Intervals 1.17-2.18 p=0.003) compared with age, sex and co-morbidity matched controls without ILD. Patients with a Forced Vital Capacity (FVC) of <80% had an increased risk of death versus patients with FVC [&ge;]80% (HR 1.72, 1.05-2.83). Furthermore, obese patients with ILD had an elevated risk of death (HR 1.98, 1.13-3.46). Conclusions: Patients with ILD are at increased risk of death from COVID-19, particularly those with poor lung function and obesity. Stringent precautions should be taken to avoid COVID-19 in patients with ILD. 2020-07-17
Peter Horby; Marion Mafham; Louise Linsell; Jennifer L Bell; Natalie Staplin; Jonathan R Emberson; Martin Wiselka; Andrew Ustianowski; Einas Elmahi; Benjamin Prudon; Anthony Whitehouse; Timothy Felton; John Williams; Jakki Faccenda; Jonathan Underwood; J Kenneth Baillie; Lucy Chappell; Saul N Faust; Thomas Jaki; Katie Jeffery; Wei Shen Lim; Alan Montgomery; Kathryn Rowan; Joel Tarning; James A Watson; Nicholas J White; Edmund Juszczak; Richard Haynes; Martin J Landray Effect of Hydroxychloroquine in Hospitalized Patients with COVID-19: Preliminary results from a multi-centre, randomized, controlled trial. Background: Hydroxychloroquine and chloroquine have been proposed as treatments for coronavirus disease 2019 (COVID-19) on the basis of in vitro activity, uncontrolled data, and small randomized studies. Methods: The Randomised Evaluation of COVID-19 therapy (RECOVERY) trial is a randomized, controlled, open-label, platform trial comparing a range of possible treatments with usual care in patients hospitalized with COVID-19. We report the preliminary results for the comparison of hydroxychloroquine vs. usual care alone. The primary outcome was 28-day mortality. Results: 1561 patients randomly allocated to receive hydroxychloroquine were compared with 3155 patients concurrently allocated to usual care. Overall, 418 (26.8%) patients allocated hydroxychloroquine and 788 (25.0%) patients allocated usual care died within 28 days (rate ratio 1.09; 95% confidence interval [CI] 0.96 to 1.23; P=0.18). Consistent results were seen in all pre-specified subgroups of patients. Patients allocated to hydroxychloroquine were less likely to be discharged from hospital alive within 28 days (60.3% vs. 62.8%; rate ratio 0.92; 95% CI 0.85-0.99) and those not on invasive mechanical ventilation at baseline were more likely to reach the composite endpoint of invasive mechanical ventilation or death (29.8% vs. 26.5%; risk ratio 1.12; 95% CI 1.01-1.25). There was no excess of new major cardiac arrhythmia. Conclusions: In patients hospitalized with COVID-19, hydroxychloroquine was not associated with reductions in 28-day mortality but was associated with an increased length of hospital stay and increased risk of progressing to invasive mechanical ventilation or death. 2020-07-15
Peter F Dutey-Magni; Haydn Williams; Arnoupe Jhass; Greta Rait; Harry Hemingway; Andrew C Hayward; Laura Shallcross Covid-19 infection and attributable mortality in UK Long Term Care Facilities: Cohort study using active surveillance and electronic records (March-June 2020) Background: Rates of Covid-19 infection have declined in many countries, but outbreaks persist in residents of long-term care facilities (LTCFs) who are at high risk of severe outcomes. Epidemiological data from LTCFs are scarce. We used population-level active surveillance to estimate incidence of, and risk factors for Covid-19, and attributable mortality in elderly residents of LTCFs. Methods: Cohort study using individual-level electronic health records from 8,713 residents and daily counts of infection for 9,339 residents and 11,604 staff across 179 UK LTCFs. We modelled risk factors for infection and mortality using Cox proportional hazards and estimated attributable fractions. Findings: 2,075/9,339 residents developed Covid-19 symptoms (22.2% [95% confidence interval: 21.4%; 23.1%]), while 951 residents (10.2% [9.6%; 10.8%]) and 585 staff (5.0% [4.7%; 5.5%]) had laboratory confirmed infections. Confirmed infection incidence in residents and staff respectively was 152.6 [143.1; 162.6] and 62.3 [57.3; 67.5] per 100,000 person-days. 121/179 (67.6%) LTCFs had at least one Covid-19 infection or death. Lower staffing ratios and higher occupancy rates were independent risk factors for infection. 1,694 all-cause deaths occurred in 8,713 (19.4% [18.6%; 20.3%]) residents. 217 deaths occurred in 607 residents with confirmed infection (case-fatality rate: 35.7% [31.9%; 39.7%]). 567/1694 (33.5%) of all-cause deaths were attributable to Covid-19, 28.0% of which occurred in residents with laboratory-confirmed infection. The remainder of excess deaths occurred in asymptomatic or symptomatic residents in the context of limited testing for infection, suggesting substantial under-ascertainment. Interpretation: 1 in 5 residents had symptoms of infection during the pandemic, but many cases were not tested. Higher occupancy and lower staffing levels increase infection risk. Disease control measures should integrate active surveillance and testing with fundamental changes in staffing and care home occupancy to protect staff and residents from infection. Funding: Economic and Social Research Council [ES/V003887/1]. 2020-07-15
Drake T, Docherty A, Weiser T, Yule S, Sheikh A, Harrison E. The effects of physical distancing on population mobility during the COVID-19 pandemic in the UK The Lancet. Digital health 2020
Michelle Kendall; Luke Milsom; Lucie Abeler-Dorner; Chris Wymant; Luca Ferretti; Mark Briers; Chris Holmes; David Bonsall; Johannes Abeler; Christophe Fraser COVID-19 incidence and R decreased on the Isle of Wight after the launch of the Test, Trace, Isolate programme In May 2020 the UK introduced a Test, Trace, Isolate programme in response to the COVID-19 pandemic. The programme was first rolled out on the Isle of Wight and included Version 1 of the NHS contact tracing app. We used COVID-19 daily case data to infer incidence of new infections and estimate the reproduction number R for each of 150 Upper Tier Local Authorities in England, and at the National level, before and after the launch of the programme on the Isle of Wight. We used Bayesian and Maximum-Likelihood methods to estimate R, and compared the Isle of Wight to other areas using a synthetic control method. We observed significant decreases in incidence and R on the Isle of Wight immediately after the launch. These results are robust across each of our approaches. Our results show that the sub-epidemic on the Isle of Wight was controlled significantly more effectively than the sub-epidemics of most other Upper Tier Local Authorities, changing from having the third highest reproduction number R (of 150) before the intervention to the tenth lowest afterwards. The data is not yet available to establish a causal link. However, the findings highlight the need for further research to determine the causes of this reduction, as these might translate into local and national non-pharmaceutical intervention strategies in the period before a treatment or vaccination becomes available. 2020-07-14
Sue Mallett; Joy Allen; Sara Graziadio; Stuart A Taylor; Naomi S Sakai; Kile Green; Jana Suklan; Chris Hyde; Bethany Shinkins; Zhivko Zhelev; Jaime Peters; Philip Turner; Nia W Roberts; Lavinia Ferrante di Ruffano; Robert Wolff; Penny Whiting; Amanda Winter; Gauraang Bhatnagar; Brian D Nicholson; Steve Halligan At what times during infection is SARS-CoV-2 detectable and no longer detectable using RT-PCR based tests?: A systematic review of individual participant data Background Tests for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral ribonucleic acid (RNA), using reverse transcription polymerase chain reaction (RT-PCR) are pivotal to detecting current coronavirus disease (COVID-19) and duration of detectable virus indicating potential for infectivity. Methods We conducted an individual participant data (IPD) systematic review of longitudinal studies of RT-PCR test results in symptomatic SARS-CoV-2. We searched PubMed, LitCOVID, medRxiv and COVID-19 Living Evidence databases. We assessed risk of bias using a QUADAS-2 adaptation. Outcomes were the percentage of positive test results by time and the duration of detectable virus, by anatomical sampling sites. Findings Of 5078 studies screened, we included 32 studies with 1023 SARS-CoV-2 infected participants and 1619 test results, from -6 to 66 days post-symptom onset and hospitalisation. The highest percentage virus detection was from nasopharyngeal sampling between 0 to 4 days post-symptom onset at 89% (95% confidence interval (CI) 83 to 93) dropping to 54% (95% CI 47 to 61) after 10 to 14 days. On average, duration of detectable virus was longer with lower respiratory tract (LRT) sampling than upper respiratory tract (URT). Duration of faecal and respiratory tract virus detection varied greatly within individual participants. In some participants, virus was still detectable at 46 days post-symptom onset. Interpretation RT-PCR misses detection of people with SARS-CoV-2 infection; early sampling minimises false negative diagnoses. Beyond ten days post-symptom onset, lower RT or faecal testing may be preferred sampling sites. The included studies are open to substantial risk of bias so the positivity rates are probably overestimated. 2020-07-14
Robert Stewart; Matthew Broadbent; Jayati Das-Munshi Excess mortality in mental health service users during the COVID-19 pandemic described by ethnic group: South London and Maudsley data The COVID-19 pandemic in the UK was accompanied by excess all-cause mortality at a national level, only part of which was accounted for by known infections. Excess mortality has previously been described in people who had received care from the South London and Maudsley NHS Foundation Trust (SLaM), a large mental health service provider for 1.2m residents in south London. The SLaM Clinical Record Interactive Search (CRIS) data resource receives 24-hourly updates from its full electronic health record, including regularly sourced national mortality on all past and present SLaM service users. The SLaM urban catchment has high levels of deprivation and is ethnically diverse, so the objective of the descriptive analyses reported in this manuscript was to compare mortality in SLaM service users from 16th March to 15th May 2020 to that for the same period in 2019 within specific ethnic groups: i) White British, ii) Other White, iii) Black African/Caribbean, iv) South Asian, v) Other, and vi) missing/not stated. For Black African/Caribbean patients (the largest minority ethnic group) this ratio was 3.33, compared to 2.47 for White British patients. Considering premature mortality (restricting to deaths below age 70), these ratios were 2.74 and 1.96 respectively. Ratios were also high for those from Other ethnic groups (2.63 for all mortality, 3.07 for premature mortality). 2020-07-14
Domagoj Kifer; Dario Bugada; Judit Villar-Garcia; Ivan Gudelj; Cristina Menni; Carole Helene Sudre; Frano Vuckovic; Ivo Ugrina; Luca F Lorini; Silvia Bettinelli; Nicola Ughi; Alessandro Maloberti; Oscar Epis; Cristina Giannattasio; Claudio Rossetti; Livije Kalogjera; Jasminka Persec; Luke Ollivere; Benjamin Ollivere; Huadong Yan; Ting Cai; Guruprasad Aithal; Claire Steves; Anu Kantele; Mikael Kajova; Olli Vapalahti; Antti Sajantila; Rafal Wojtowicz; Waldemar Wierzba; Zbigniew Krol; Artur Zaczynski; Katarzyna Zycinska; Marek Postula; Ivica Luksic; Rok Civljak; Alemka Markotic; Christian Mahnkopf; Andreas Markl; Johannes Brachmann; Benjamin Murray; Sebastien Ourselin; Julio Pascual; Ana M Valdes; Margarita Posso; Juan Horcajada; Xavier Castells; Massimo Allegri; Dragan Primorac; Timothy Spector; Clara Barrios; Gordan Lauc Effects of environmental factors on severity and mortality of COVID-19 Background Most respiratory viruses show pronounced seasonality, but for SARS-CoV-2 this still needs to be documented. Methods We examined the disease progression of COVID-19 in 6,911 patients admitted to hospitals in Europe and China. In addition, we evaluated progress of disease symptoms in 37,187 individuals reporting symptoms into the COVID Symptom Study application. Findings Meta-analysis of the mortality risk in eight European hospitals estimated odds ratios per one day increase in the admission date to be 0.981 (0.973-0.988, p<0.001) and per increase in ambient temperature of one degree Celsius to be 0.854 (0.773-0.944, p=0.007). Statistically significant decreases of comparable magnitude in median hospital stay, probability of transfer to Intensive Care Unit and need for mechanical ventilation were also observed in most, but not all hospitals. The analysis of individually reported symptoms of 37,187 individuals in the UK also showed the decrease in symptom duration and disease severity with time. Interpretation Severity of COVID-19 in Europe decreased significantly between March and May and the seasonality of COVID-19 is the most likely explanation. Mucosal barrier and mucociliary clearance can significantly decrease viral load and disease progression, and their inactivation by low relative humidity of indoor air might significantly contribute to severity of the disease. 2020-07-14
Simpson CR, Robertson C, Vasileiou E, McMenamin J, Gunson R, Ritchie LD, Woolhouse M, Morrice L, Kelly D, Stagg HR, Marques D, Murray J, Sheikh A. Early Pandemic Evaluation and Enhanced Surveillance of COVID-19 (EAVE II): protocol for an observational study using linked Scottish national data. BMJ open 2020
Harrison G, Newport D, Robbins T, Arvanitis TN, Stein A. Mortality statistics in England and Wales: the SARS-CoV-2 paradox. The Journal of international medical research 2020
Bean DM, Kraljevic Z, Searle T, Bendayan R, Kevin O, Pickles A, Folarin A, Roguski L, Noor K, Shek A, Zakeri R, Shah AM, Teo JTH, Dobson RJB. Angiotensin-converting enzyme inhibitors and angiotensin II receptor blockers are not associated with severe COVID-19 infection in a multi-site UK acute hospital trust. European journal of heart failure 2020
Messner CB, Demichev V, Wendisch D, Michalick L, White M, Freiwald A, Textoris-Taube K, Vernardis SI, Egger AS, Kreidl M, Ludwig D, Kilian C, Agostini F, Zelezniak A, Thibeault C, Pfeiffer M, Hippenstiel S, Hocke A, von Kalle C, Campbell A, Hayward C, Porteous DJ, Marioni RE, Langenberg C, Lilley KS, Kuebler WM, Mülleder M, Drosten C, Suttorp N, Witzenrath M, Kurth F, Sander LE, Ralser M. Ultra-High-Throughput Clinical Proteomics Reveals Classifiers of COVID-19 Infection. Cell systems 2020
Sheikh A, Sheikh Z, Sheikh A. Novel approaches to estimate compliance with lockdown measures in the COVID-19 pandemic. Journal of global health 2020
Davies NG, Kucharski AJ, Eggo RM, Gimma A, Edmunds WJ, Centre for the Mathematical Modelling of Infectious Diseases COVID-19 working group. Effects of non-pharmaceutical interventions on COVID-19 cases, deaths, and demand for hospital services in the UK: a modelling study. The Lancet. Public health 2020
Drake TM, Docherty AB, Weiser TG, Yule S, Sheikh A, Harrison EM. The effects of physical distancing on population mobility during the COVID-19 pandemic in the UK. The Lancet. Digital Health
Aldridge RW, Lewer D, Katikireddi SV, Mathur R, Pathak N, Burns R, Fragaszy EB, Johnson AM, Devakumar D, Abubakar I, Hayward A. Black, Asian and Minority Ethnic groups in England are at increased risk of death from COVID-19: indirect standardisation of NHS mortality data. Wellcome open research 2020
Keeling MJ, Hollingsworth TD, Read JM. Efficacy of contact tracing for the containment of the 2019 novel coronavirus (COVID-19). Journal of epidemiology and community health 2020
Jombart T, van Zandvoort K, Russell TW, Jarvis CI, Gimma A, Abbott S, Clifford S, Funk S, Gibbs H, Liu Y, Pearson CAB, Bosse NI, Centre for the Mathematical Modelling of Infectious Diseases COVID-19 Working Group, Eggo RM, Kucharski AJ, Edmunds WJ. Inferring the number of COVID-19 cases from recently reported deaths. Wellcome open research 2020
Chandan JS, Taylor J, Bradbury-Jones C, Nirantharakumar K, Kane E, Bandyopadhyay S. COVID-19: a public health approach to manage domestic violence is needed. The Lancet. Public health 2020
Clark A, Jit M, Warren-Gash C, Guthrie B, Wang HHX, Mercer SW, Sanderson C, McKee M, Troeger C, Ong KL, Checchi F, Perel P, Joseph S, Gibbs HP, Banerjee A, Eggo RM, Centre for the Mathematical Modelling of Infectious Diseases COVID-19 working group. Global, regional, and national estimates of the population at increased risk of severe COVID-19 due to underlying health conditions in 2020: a modelling study. The Lancet. Global health 2020
Jacob J, Alexander D, Baillie JK, Berka R, Bertolli O, Blackwood J, Buchan I, Bloomfield C, Cushnan D, Docherty A, Edey A, Favaro A, Gleeson F, Halling-Brown M, Hare S, Jefferson E, Johnstone A, Kirby M, Mcstay R, Nair A, Openshaw PJM, Parker G, Reilly G, Robinson G, Roditi G, Rodrigues JCL, Sebire N, Semple MG, Sudlow C, Woznitza N, Joshi I. Using imaging to combat a pandemic: rationale for developing the UK National COVID-19 Chest Imaging Database. The European respiratory journal 2020
Steven Riley; Kylie E. C. Ainslie; Oliver Eales; Benjamin Jeffrey; Caroline E. Walters; Christina J Atchison; Peter J. Diggle; Deborah Ashby; Christl A. Donnelly; Graham Cooke; Wendy Barclay; Helen Ward; Graham Taylor; Ara Darzi; Paul Elliott Community prevalence of SARS-CoV-2 virus in England during May 2020: REACT study Background England has experienced one of the highest rates of confirmed COVID-19 mortality in the world. SARS-CoV-2 virus has circulated in hospitals, care homes and the community since January 2020. Our current epidemiological knowledge is largely informed by clinical cases with far less understanding of community transmission. Methods The REal-time Assessment of Community Transmission (REACT) study is a nationally representative prevalence survey of SARS-CoV-2 virus swab-positivity in the community in England. We recruited participants regardless of symptom status. Results We found 159 positives from 120,610 swabs giving an average prevalence of 0.13% (95% CI: 0.11%,0.15%) from 1st May to 1st June 2020. We showed decreasing prevalence with a halving time of 8.6 (6.2, 13.6) days, implying an overall reproduction number R of 0.57 (0.45, 0.72). Adults aged 18 to 24 yrs had the highest swab-positivity rates, while those >64 yrs had the lowest. Of the 126 participants who tested positive with known symptom status in the week prior to their swab, 39 reported symptoms while 87 did not, giving an estimate that 69% (61%,76%) of people were symptom-free for the 7 days prior testing positive in our community sample. Symptoms strongly associated with swab-positivity were: nausea and/or vomiting, diarrhoea, blocked nose, loss of smell, loss of taste, headache, chills and severe fatigue. Recent contact with a known COVID-19 case was associated with odds of 24 (16, 38) for swab-positivity. Compared with non-key workers, odds of swab-positivity were 7.7 (2.4, 25) among care home (long-term care facilities) workers and 5.2 (2.9, 9.3) among health care workers. However, some of the excess risk associated with key worker status was explained by recent contact with COVID-19 cases. We found no strong evidence for geographical variability in positive swab results. Conclusion Our results provide a reliable baseline against which the impact of subsequent relaxation of lockdown can be assessed to inform future public health efforts to control transmission. 2020-07-11
- TC CVD-COVID-UK Consortium; Simon Ball; Amitava Banerjee; Colin Berry; Jonathan Boyle; Benjamin Bray; William Bradlow; Afzal Chaudhry; Rikki Crawley; John Danesh; Alastair Denniston; Florian Falter; Jonine Figueroa; Christopher Hall; Harry Hemingway; Emily Jefferson; Tom Johnson; Graham King; Ken Lee; Paul McKean; Suzanne Mason; Nicholas Mills; Ewen Pearson; Munir Pirmohamed; Michael TC Poon; Rouven Priedon; Anoop Shah; Reecha Sofat; Jonathan Sterne; Fiona Strachan; Cathie LM Sudlow; Zsolt Szarka; William Whiteley; Mike Wyatt The 4C Initiative (Clinical Care for Cardiovascular disease in the COVID-19 pandemic): monitoring the indirect impact of the coronavirus pandemic on services for cardiovascular diseases in the UK Background: The coronavirus (COVID-19) pandemic affects cardiovascular diseases (CVDs) directly through infection and indirectly through health service reorganisation and public health policy. Real-time data are needed to quantify direct and indirect effects. We aimed to monitor hospital activity for presentation, diagnosis and treatment of CVDs during the pandemic to inform on indirect effects. Methods: We analysed aggregate data on presentations, diagnoses and treatments or procedures for selected CVDs (acute coronary syndromes, heart failure, stroke and transient ischaemic attack, venous thromboembolism, peripheral arterial disease and aortic aneurysm) in UK hospitals before and during the COVID-19 epidemic. We produced an online visualisation tool to enable near real-time monitoring of trends. Findings: Nine hospitals across England and Scotland contributed hospital activity data from 28 Oct 2019 (pre-COVID-19) to 10 May 2020 (pre-easing of lockdown), and for the same weeks during 2018-2019. Across all hospitals, total admissions and emergency department (ED) attendances decreased after lockdown (23 March 2020) by 57.9% (57.1-58.6%) and 52.9% (52.2-53.5%) respectively compared with the previous year. Activity for cardiac, cerebrovascular and other vascular conditions started to decline 1-2 weeks before lockdown, and fell by 31-88% after lockdown, with the greatest reductions observed for coronary artery bypass grafts, carotid endarterectomy, aortic aneurysm repair and peripheral arterial disease procedures. Compared with before the first UK COVID-19 (31 January 2020), activity declined across diseases and specialties between the first case and lockdown (total ED attendances RR 0.94, 0.93-0.95; total hospital admissions RR 0.96, 0.95-0.97) and after lockdown (attendances RR 0.63, 0.62-0.64; admissions RR 0.59, 0.57-0.60). There was limited recovery towards usual levels of some activities from mid-April 2020. Interpretation: Substantial reductions in total and cardiovascular activities are likely to contribute to a major burden of indirect effects of the pandemic, suggesting they should be monitored and mitigated urgently. 2020-07-11
Veronique Bataille; Alessia Visconti; Niccolo' Rossi; Benjamin Murray; Abigail Bournot; Jonathan Wolf; Sebastien Ourselin; Claire Steves; Timothy Spector; Mario Falchi Diagnostic value of skin manifestation of SARS-CoV-2 infection SARS-CoV-2 causes multiple immune-related reactions at various stages of the disease. The wide variety of skin presentations has delayed linking these to the virus. Previous studies had attempted to look at the prevalence and timing of SARS-COV-2 rashes but were based on mostly hospitalized severe cases and had little follow up. Using data collected on a subset of 336,847 eligible UK users of the COVID Symptom Study app, we observed that 8.8% of the swab positive cases (total: 2,021 subjects) reported either a body rash or an acral rash, compared to 5.4% of those with a negative swab test (total: 25,136). Together, these two skin presentations showed an odds ratio (OR) of 1.67 (95% confidence interval [CI]: 1.41-1.96) for being swab positive. Skin rashes were also predictive in the larger untested group of symptomatic app users (N=54,652), as 8.2% of those who had reported at least one classical COVID-19 symptom, i.e., fever, persistent cough, and/or anosmia, also reported a rash. Data from an independent online survey of 11,546 respondents with a rash showed that in 17% of swab positive cases, the rash was the initial presentation. Furthermore, in 21%, the rash was the only clinical sign. Skin rashes cluster with other COVID-19 symptoms, are predictive of a positive swab test and occur in a significant number of cases, either alone or before other classical symptoms. Recognising rashes is important in identifying new and earlier COVID-19 cases. 2020-07-11
Rosita Zakeri; Rebecca Bendayan; Mark Ashworth; Daniel M Bean; Hiten Dodhia; Stevo Durbaba; Kevin O Gallagher; Claire Palmer; Vasa Curcin; Elizabeth Aitken; William Bernal; Richard D Barker; Sam Norton; Martin C Gulliford; James T Teo; James Galloway; Richard J Dobson; Ajay M Shah A case-control and cohort study to determine the relationship between ethnic background and severe COVID-19 Background. People of minority ethnic background may be disproportionately affected by severe COVID-19 for reasons that are unclear. We sought to examine the relationship between ethnic background and (1) hospital admission for severe COVID-19; (2) in-hospital mortality. Methods. We conducted a case-control study of 872 inner city adult residents admitted to hospital with confirmed COVID-19 (cases) and 3,488 matched controls randomly sampled from a primary healthcare database comprising 344,083 people resident in the same region. To examine in-hospital mortality, we conducted a cohort study of 1827 adults consecutively admitted with COVID-19. Data collected included hospital admission for COVID-19, demographics, comorbidities, in-hospital mortality. The primary exposure variable was self-defined ethnicity. Results. The 872 cases comprised 48.1% Black, 33.7% White, 12.6% Mixed/Other and 5.6% Asian patients. In conditional logistic regression analyses, Black and Mixed/Other ethnicity were associated with higher admission risk than white (OR 3.12 [95% CI 2.63-3.71] and 2.97 [2.30- 3.85] respectively). Adjustment for comorbidities and deprivation modestly attenuated the association (OR 2.28 [1.87-2.79] for Black, 2.66 [2.01-3.52] for Mixed/Other). Asian ethnicity was not associated with higher admission risk (OR 1.20 [0.86-1.66]). In the cohort study of 1827 patients, 455 (28.9%) died over a median (IQR) of 8 (4-16) days. Age and male sex, but not Black (adjusted HR 0.84 [0.63-1.11]) or Mixed/Other ethnicity (adjusted HR 0.69 [0.43-1.10]), were associated with in-hospital mortality. Asian ethnicity was associated with higher in-hospital mortality (adjusted HR 1.54 [0.98-2.41]). Conclusions. Black and Mixed ethnicity are independently associated with greater admission risk with COVID-19 and may be risk factors for development of severe disease. Comorbidities and socioeconomic factors only partly account for this and additional ethnicity-related factors may play a large role. The impact of COVID-19 may be different in Asians. 2020-07-10
Nick Golding; Timothy W Russell; Sam Abbott; Joel Hellewell; Carl A B Pearson; Kevin van Zandvoort; Christopher I Jarvis; Hamish Gibbs; Yang Liu; Rosalind M Eggo; John W Edmunds; Adam J Kucharski Reconstructing the global dynamics of under-ascertained COVID-19 cases and infections Background: Asymptomatic or subclinical SARS-CoV-2 infections are often unreported, which means that confirmed case counts may not accurately reflect underlying epidemic dynamics. Understanding the level of ascertainment (the ratio of confirmed symptomatic cases to the true number of symptomatic individuals) and undetected epidemic progression is crucial to informing COVID-19 response planning, including the introduction and relaxation of control measures. Estimating case ascertainment over time allows for accurate estimates of specific outcomes such as seroprevalence, which is essential for planning control measures. Methods: Using reported data on COVID-19 cases and fatalities globally, we estimated the proportion of symptomatic cases (i.e. any person with any of fever >= to 37.5C, cough, shortness of breath, sudden onset of anosmia, ageusia or dysgeusia illness) that were reported in 210 countries and territories, given those countries had experienced more than ten deaths. We used published estimates of the case fatality ratio (CFR) as an assumed baseline. We then calculated the ratio of this baseline CFR to an estimated local delay-adjusted CFR to estimate the level of under-ascertainment in a particular location. We then fit a Bayesian Gaussian process model to estimate the temporal pattern of under-ascertainment. Results: We estimate that, during March 2020, the median percentage of symptomatic cases detected across the 84 countries which experienced more than ten deaths ranged from 2.38% (Bangladesh) to 99.6% (Chile). Across the ten countries with the highest number of total confirmed cases as of 6th July 2020, we estimated that the peak number of symptomatic cases ranged from 1.4 times (Chile) to 17.8 times (France) larger than reported. Comparing our model with national and regional seroprevalence data where available, we find that our estimates are consistent with observed values. Finally, we estimated seroprevalence for each country. Despite low case detection in some countries, our results that adjust for this still suggest that all countries have had only a small fraction of their populations infected as of July 2020. Conclusions: We found substantial under-ascertainment of symptomatic cases, particularly at the peak of the first wave of the SARS-CoV-2 pandemic, in many countries. Reported case counts will therefore likely underestimate the rate of outbreak growth initially and underestimate the decline in the later stages of an epidemic. Although there was considerable under-reporting in many locations, our estimates were consistent with emerging serological data, suggesting that the proportion of each country's population infected with SARS-CoV-2 worldwide is generally low. 2020-07-08
Mark Cherrie; Tom Clemens; Claudio Colandrea; Zhiqiang Feng; David Webb; Chris Dibben; Richard B Weller Ultraviolet A Radiation and COVID-19 Deaths: A Multi Country Study Objectives To determine whether UVA exposure might be associated with COVID-19 deaths Design Ecological regression, with replication in two other countries and pooled estimation Setting 2,474 counties of the contiguous USA, 6,755 municipalities in Italy, 6,274 small areas in England. Only small areas in their 'Vitamin D winter' (monthly mean UVvitd of under 165 KJ/m2) from Jan to April 2020. Participants The 'at-risk' population is the total small area population, with measures to incorporate spatial infection into the model. The model is adjusted for potential confounders including long-term winter temperature and humidity. Main outcome measures We derive UVA measures for each area from remote sensed data and estimate their relationship with COVID-19 mortality with a random effect for States, in a multilevel zero-inflated negative binomial model. In the USA and England death certificates had to record COVID-19. In Italy excess deaths in 2020 over expected from 2015-19. Data sources Satellite derived mean daily UVA dataset from Japan Aerospace Exploration Agency. Data on deaths compiled by Center for Disease Control (USA), Office for National Statistics (England) and Italian Institute of Statistics. Results Daily mean UVA (January-April 2020) varied between 450 to 1,000 KJ/m2 across the three countries. Our fully adjusted model showed an inverse correlation between UVA and COVID-19 mortality with a Mortality Risk Ratio (MRR) of 0.71 (0.60 to 0.85) per 100KJ/m2 increase UVA in the USA, 0.81 (0.71 to 0.93) in Italy and 0.49 (0.38 to 0.64) in England. Pooled MRR was 0.68 (0.52 to 0.88). Conclusions Our analysis, replicated in 3 independent national datasets, suggests ambient UVA exposure is associated with lower COVID-19 specific mortality. This effect is independent of vitamin D, as it occurred at irradiances below that likely to induce significant cutaneous vitamin D3 synthesis. Causal interpretations must be made cautiously in observational studies. Nonetheless this study suggests strategies for reduction of COVID-19 mortality. 2020-07-06
Joe Hollinghurst; Jane Lyons; Richard Fry; Ashley Akbari; Mike Gravenor; Alan Watkins; Fiona Verity; Ronan A Lyons The Impact of COVID-19 on Adjusted Mortality Risk in Care Homes for Older Adults in Wales, United Kingdom: A retrospective population-based cohort study for mortality in 2016-2020 Background: Mortality in care homes has had a prominent focus during the COVID-19 outbreak. Multiple and interconnected challenges face the care home sector in the prevention and management of outbreaks of COVID-19, including adequate supply of personal protective equipment, staff shortages, and insufficient or lack of timely COVID-19 testing. Care homes are particularly vulnerable to infectious diseases. Aim: To analyse the mortality of older care home residents in Wales during COVID-19 lockdown and compare this across the population of Wales and the previous 4-years. Study Design and Setting: We used anonymised Electronic Health Records (EHRs) and administrative data from the Secure Anonymised Information Linkage (SAIL) Databank to create a cross-sectional cohort study. We anonymously linked data for Welsh residents to mortality data up to the 14th June 2020. Methods: We calculated survival curves and adjusted Cox proportional hazards models to estimate hazard ratios (HRs) for the risk of mortality. We adjusted hazard ratios for age, gender, social economic status and prior health conditions. Results: Survival curves show an increased proportion of deaths between 23rd March and 14th June 2020 in care homes for older people, with an adjusted HR of 1.72 (1.55, 1.90) compared to 2016. Compared to the general population in 2016-2019, adjusted care home mortality HRs for older adults rose from 2.15 (2.11,2.20) in 2016-2019 to 2.94 (2.81,3.08) in 2020. Conclusions: The survival curves and increased HRs show a significantly increased risk of death in the 2020 study periods. 2020-07-04
Maik Pietzner; Eleanor Wheeler; Julia Carrasco-Zanini; Johannes Raffler; Nicola D. Kerrison; Erin Oerton; Victoria P.W. Auyeung; Chris Finan; Juan P. Casas; Rachel Ostroff; Steve A. Williams; Gabi Kastenmüller; Markus Ralser; Eric G. Gamazon; Nicholas J. Wareham; Aroon Dinesh Hingorani; Claudia Langenberg Genetic architecture of host proteins interacting with SARS-CoV-2 Strategies to develop therapeutics for SARS-CoV-2 infection may be informed by experimental identification of viral-host protein interactions in cellular assays and measurement of host response proteins in COVID-19 patients. Identification of genetic variants that influence the level or activity of these proteins in the host could enable rapid in silico assessment in human genetic studies of their causal relevance as molecular targets for new or repurposed drugs to treat COVID-19. We integrated large-scale genomic and aptamer-based plasma proteomic data from 10,708 individuals to characterize the genetic architecture of 179 host proteins reported to interact with SARS-CoV-2 proteins or to participate in the host response to COVID-19. We identified 220 host DNA sequence variants acting in cis (MAF 0.01-49.9%) and explaining 0.3-70.9% of the variance of 97 of these proteins, including 45 with no previously known protein quantitative trait loci (pQTL) and 38 encoding current drug targets. Systematic characterization of pQTLs across the phenome identified protein-drug-disease links, evidence that putative viral interaction partners such as MARK3 affect immune response, and establish the first link between a recently reported variant for respiratory failure of COVID-19 patients at the ABO locus and hypercoagulation, i.e. maladaptive host response. Our results accelerate the evaluation and prioritization of new drug development programmes and repurposing of trials to prevent, treat or reduce adverse outcomes. Rapid sharing and dynamic and detailed interrogation of results is facilitated through an interactive webserver (https://omicscience.org/apps/covidpgwas/). 2020-07-01
Robert Stewart; Matthew Broadbent Using past and current data to estimate potential crisis service use in mental healthcare after the COVID-19 lockdown: South London and Maudsley data The lockdown policy response to the COVID-19 pandemic in the UK has a potentially important impact on provision of mental healthcare with uncertain consequences over the 12 months ahead. Past activity may provide a means to predict future demand. Taking advantage of the Clinical Record Interactive Search (CRIS) data resource at the South London and Maudsley NHS Trust (SLaM; a large mental health service provider for 1.2m residents in south London), we carried out a range of descriptive analyses to inform the Trust on patient groups who might be most likely to require inpatient and home treatment team (HTT) crisis care. We considered the 12 months following UK COVID-19 lockdown policy on 16th March, drawing on comparable findings from previous years, and quantified levels of change in service delivery to those most likely to receive crisis care. For 12-month crisis days from 16th March in 2015-19, we found that most (over 80%) were accounted for by inpatient care (rather than HTT), most (around 75%) were used by patients who were current or recent Trust patients at the commencement of follow-up, and highest numbers were used by patients with a previously recorded schizophreniform disorder diagnosis. For current/recent patients on 16th March there had been substantial reductions in use of inpatient care in the following 31 days in 2020, more than previous years; changes in total non-inpatient contact numbers did not differ in 2020 compared to previous years, although there had been a marked switch from face-to-face to virtual contacts. 2020-06-30
Julia Hippisley-Cox; Ashley Kieran Clift; Carol AC Coupland; Ruth Keogh; Karla Diaz-Ordaz; Elizabeth Williamson; Ewen Harrison; Andrew Hayward; Harry Hemingway; Peter Horby; Nisha Mehta; Jonathan Kieran Benger; Kamlesh Khunti; David Spiegelhalter; Aziz Sheikh; Jonathan Valabhji; Ronan A Lyons; John Robson; Malcolm Gracie Semple; Frank Kee; Peter Johnson; Susan Jebb; Tony Williams; David Coggon Protocol for the development and evaluation of a tool for predicting risk of short-term adverse outcomes due to COVID-19 in the general UK population Introduction: Novel coronavirus 2019 (COVID-19) has propagated a global pandemic with significant health, economic and social costs. Emerging emergence has suggested that several factors may be associated with increased risk from severe outcomes or death from COVID-19. Clinical risk prediction tools have significant potential to generate individualised assessment of risk and may be useful for population stratification and other use cases. Methods and analysis: We will use a prospective open cohort study of routinely collected data from 1205 general practices in England in the QResearch database. The primary outcome is COVID-19 mortality (in or out-of-hospital) defined as confirmed or suspected COVID-19 mentioned on the death certificate, or death occurring in a person with SARS-CoV-2 infection between 24th January and 30th April 2020. Our primary outcome in adults is COVID-19 mortality (including out of hospital and in hospital deaths). We will also examine COVID-19 hospitalisation in children. Time-to-event models will be developed in the training data to derive separate risk equations in adults (19-100 years) for males and females for evaluation of risk of each outcome within the 3-month follow-up period (24th January to 30th April 2020), accounting for competing risks. Predictors considered will include age, sex, ethnicity, deprivation, smoking status, alcohol intake, body mass index, pre-existing medical co-morbidities, and concurrent medication. Measures of performance (prediction errors, calibration and discrimination) will be determined in the test data for men and women separately and by ten-year age group. For children, descriptive statistics will be undertaken if there are currently too few serious events to allow development of a risk model. The final model will be externally evaluated in (a) geographically separate practices and (b) other relevant datasets as they become available. Ethics and dissemination: The project has ethical approval and the results will be submitted for publication in a peer-reviewed journal. 2020-06-29
Claire E Hastie; Jill P Pell; Naveed Sattar Short Communication: Vitamin D and COVID-19 infection and mortality in UK Biobank Purpose Vitamin D has been proposed as a potential causal factor in COVID-19 risk. We aimed to establish whether blood 25-hydroxyvitamin D (25(OH)D) concentration was associated with COVID-19 mortality, and inpatient confirmed COVID-19 infection, in UK Biobank participants. Methods UK Biobank recruited 502,624 participants aged 37-73 years between 2006 and 2010. Baseline exposure data, including 25(OH)D concentration, were linked to COVID-19 mortality. Univariable and multivariable Cox proportional hazards regression analyses were performed for the association between 25(OH)D and COVID-19 death, and poisson regression analyses for the association between 25(OH)D and severe COVID-19 infection. Results Complete data were available for 341,484 UK Biobank participants, of which 656 had inpatient confirmed COVID-19 infection and 203 died of COVID-19 infection. Vitamin D was associated with severe COVID-19 infection and mortality univariably (mortality HR=0.99; 95% CI 0.98-0.998; p=0.016), but not after adjustment for confounders (mortality HR=0.998; 95% CI=0.99-1.01; p=0.696). Conclusions Our findings do not support a potential link between vitamin D concentrations and risk of severe COVID-19 infection and mortality. Recommendations for vitamin D supplementation to lessen COVID-19 risks may provide false reassurance. 2020-06-28
Mailis Maes; Ellen Higginson; Joana Pereira Dias; Martin D Curran; Surendra Parmar; Fahad Khokhar; Delphine Cuchet-Lourenço; Janine Lux; Sapna Sharma-Hajela; Benjamin Ravenhill; Razeen Mahroof; Amelia Solderholm; Sally Forrest; Sushmita Sridhar; Nicholas M Brown; Stephen Baker; Vilas Navapurkar; Gordon Dougan; Josefin Bartholdson Scott; Andrew Conway Morris Secondary pneumonia in critically ill ventilated patients with COVID-19 Background Pandemic COVID-19 caused by the coronavirus SARS-CoV-2 has a high incidence of patients with severe acute respiratory syndrome (SARS). Many of these patients require admission to an intensive care unit (ICU) for invasive artificial ventilation and are at significant risk of developing a secondary, ventilator-associated pneumonia (VAP). Objectives To study the incidence of VAP, as well as differences in secondary infections, and bacterial lung microbiome composition of ventilated COVID-19 and non-COVID-19 patients. Methods In this prospective observational study, we compared the incidence of VAP and secondary infections using a combination of a TaqMan multi-pathogen array and microbial culture. In addition, we determined the lung microbime composition using 16S RNA analyisis. The study involved eighteen COVID-19 and seven non-COVID-19 patients receiving invasive ventilation in three ICUs located in a single University teaching hospital between April 13th 2020 and May 7th 2020. Results We observed a higher percentage of confirmed VAP in COVID-19 patients. However, there was no statistical difference in the detected organisms or pulmonary microbiome when compared to non-COVID-19 patients. Conclusion COVID-19 makes people more susceptible to developing VAP, partly but not entirely due to the increased duration of ventilation. The pulmonary dysbiosis caused by COVID-19, and the array of secondary infections observed are similar to that seen in critically ill patients ventilated for other reasons. 2020-06-28
Bilal A Mateen; Harrison Wilde; John m Dennis; Andrew Duncan; Nicholas John Meyrick Thomas; Andrew P McGovern; Spiros Denaxas; Matt J Keeling; Sebastian J Vollmer A geotemporal survey of hospital bed saturation across England during the first wave of the COVID-19 Pandemic Background: Non-pharmacological interventions were introduced based on modelling studies which suggested that the English National Health Service (NHS) would be overwhelmed by the COVID-19 pandemic. In this study, we describe the pattern of bed occupancy across England during the first wave of the pandemic, January 31st to June 5th 2020. Methods: Bed availability and occupancy data was extracted from daily reports submitted by all English secondary care providers, between 27-Mar and 5-June. Two thresholds (85% as per Royal College of Emergency Medicine and 92% as per NHS Improvement) were applied as thresholds for safe occupancy. Findings: At peak availability, there were 2711 additional beds compatible with mechanical ventilation across England, reflecting a 53% increase in capacity, and occupancy never exceeded 62%. A consequence of the repurposing of beds meant that at the trough, there were 8.7% (8,508) fewer general and acute (G&A) beds across England, but occupancy never exceeded 72%. The closest to (surge) capacity that any trust in England reached was 99.8% for general and acute beds. For beds compatible with mechanical ventilation there were 326 trust-days (3.7%) spent above 85% of surge capacity, and 154 trust-days (1.8%) spent above 92%. 23 trusts spent a cumulative 81 days at 100% saturation of their surge ventilator bed capacity (median number of days per trust = 1 [range: 1 to 17]). However, only 3 STPs (aggregates of geographically co-located trusts) reached 100% saturation of their mechanical ventilation beds. Interpretation: Throughout the first wave of the pandemic, an adequate supply of all bed-types existed at a national level. Due to an unequal distribution of bed utilization, many trusts spent a significant period operating above safe occupancy thresholds, despite substantial capacity in geographically co-located trusts; a key operational issue to address in preparing for a potential second wave. Funding: This study received no funding. 2020-06-25
Michail Katsoulis; Laura Pasea; Alvina Lai; Richard JB Dobson; Spiros Denaxas; Harry Hemingway; Amitava Banerjee Obesity during the COVID-19 pandemic: cause of high risk or an effect of lockdown? A population-based electronic health record analysis in 1 958 184 individuals. Background: Obesity is a modifiable risk factor for coronavirus(COVID-19)-related mortality. We estimated excess mortality in obesity, both 'direct', through infection, and 'indirect', through changes in healthcare, and also due to potential increasing obesity during lockdown. Methods: In population-based electronic health records for 1 958 638 individuals in England, we estimated 1-year mortality risk('direct' and 'indirect' effects) for obese individuals, incorporating: (i)pre-COVID-19 risk by age, sex and comorbidities, (ii)population infection rate, and (iii)relative impact on mortality(relative risk, RR: 1.2, 1.5, 2.0 and 3.0). Using causal inference models, we estimated impact of change in body-mass index(BMI) and physical activity during 3-month lockdown on 1-year incidence for high-risk conditions(cardiovascular diseases, CVD; diabetes; chronic obstructive pulmonary disease, COPD and chronic kidney disease, CKD), accounting for confounders. Findings: For severely obese individuals (3.5% at baseline), at 10% population infection rate, we estimated direct impact of 240 and 479 excess deaths in England at RR 1.5 and 2.0 respectively, and indirect effect of 383 to 767 excess deaths, assuming 40% and 80% will be affected at RR=1.2. Due to BMI change during the lockdown, we estimated that 97 755 (5.4%: normal weight to overweight, 5.0%: overweight to obese and 1.3%: obese to severely obese) to 434 104 individuals (15%: normal weight to overweight, 15%: overweight to obese and 6%: obese to severely obese) individuals would be at higher risk for COVID-19 over one year. Interpretation: Prevention of obesity and physical activity are at least as important as physical isolation of severely obese individuals during the pandemic. 2020-06-23
Hamel Patel; Nicholas J Ashton; Richard J Dobson; Lars-magnus Anderson; Aylin Yilmaz; Kaj Blennow; Magnus Gisslen; Henrik Zetterberg Proteomic blood profiling in mild, severe and critical COVID-19 patients The recent SARS-CoV-2 pandemic manifests itself as a mild respiratory tract infection in the majority of individuals leading to COVID-19 disease. However, in some infected individuals, this can progress to severe pneumonia and acute respiratory distress syndrome (ARDS), leading to multi-organ failure and death. The purpose of this study is to explore the proteomic differences between mild, severe and critical COVID-19 positive patients. Blood protein profiling was performed on 59 COVID-19 mild (n=26), severe (n=9) or critical (n=24) cases and 28 controls using the OLINK inflammation, autoimmune, cardiovascular and neurology panels. Differential expression analysis was performed within and between disease groups to generate nine different analyses. From the 368 proteins measured per individual, more than 75% were observed to be significantly perturbed in COVID-19 cases. Six proteins (IL6, CKAP4, Gal-9, IL-1ra, LILRB4 and PD-L1) were identified to be associated with disease severity. The results have been made readily available through an interactive web-based application for instant data exploration and visualization, and can be accessed at https://phidatalab-shiny.rosalind.kcl.ac.uk/COVID19/. Our results demonstrate that dynamic changes in blood proteins that associate with disease severity can potentially be used as early biomarkers to monitor disease severity in COVID-19 and serve as potential therapeutic targets. 2020-06-23
Hisham Ziauddeen; Naresh Subramaniam; Deepti Gurdasani Modelling the impact of lockdown easing measures on cumulative COVID-19 cases and deaths in England Background: As countries begin to ease the lockdown measures instituted to control the COVID-19 pandemic, there is a risk of a resurgence of the pandemic, and early reports of this are already emerging from some countries. Unlike many other countries, the UK started easing lockdown in England when levels of community transmission were still high, and this could have a major impact on case numbers and deaths. However thus far, the likely impacts of easing restrictions at this point in the pandemic have not been quantified. Using a Bayesian model, we assessed the potential impacts of successive lockdown easing measures in England, focussing on scenarios where the reproductive number (R) remains <1 in line with the UK governments stated aim. Methods: We developed a Bayesian model to infer incident cases and R in England, from incident death data from the Office of National Statistics. We then used this to forecast excess cases and deaths in multiple plausible scenarios in which R increases at one or more time points, compared to a baseline scenario where R remains unchanged by the easing of lockdown. Findings: The model inferred an R of 0.752 on the 13th May when England first started easing lockdown. In the most conservative scenario where R increases to 0.80 as lockdown was eased further on 1st June and then remained constant, the model predicts an excess 257 (95% 108-492) deaths and 26,447 (95% CI 11,105-50,549) cumulative cases over 90 days. In the scenario with maximal increases in R (but staying <1) with successive easing of lockdown, the model predicts 3,174 (95% 1,334-6,060) excess cumulative deaths and 421,310 (95% 177,012-804,811) excess cases. Results: When levels of transmission are high, even small changes in R with easing of lockdown can have significant impacts on expected cases and deaths, even if R remains <1. This will have a major impact on population health, tracing systems and health care services in England. Following an elimination strategy rather than one of maintenance of R below 1 would substantially mitigate the impact of the COVID-19 epidemic within England. This study provides urgently needed information for developing public health policy for the next stages of the pandemic. 2020-06-23
Peter Horby; Wei Shen Lim; Jonathan Emberson; Marion Mafham; Jennifer Bell; Louise Linsell; Natalie Staplin; Christopher Brightling; Andrew Ustianowski; Einas Elmahi; Benjamin Prudon; Christopher Green; Timothy Felton; David Chadwick; Kanchan Rege; Christopher Fegan; Lucy C Chappell; Saul N Faust; Thomas Jaki; Katie Jeffery; Alan Montgomery; Kathryn Rowan; Edmund Juszczak; J Kenneth Baillie; Richard Haynes; Martin J Landray; - RECOVERY Collaborative Group Effect of Dexamethasone in Hospitalized Patients with COVID-19: Preliminary Report Background: Coronavirus disease 2019 (COVID-19) is associated with diffuse lung damage. Corticosteroids may modulate immune-mediated lung injury and reducing progression to respiratory failure and death. Methods: The Randomised Evaluation of COVID-19 therapy (RECOVERY) trial is a randomized, controlled, open-label, adaptive, platform trial comparing a range of possible treatments with usual care in patients hospitalized with COVID-19. We report the preliminary results for the comparison of dexamethasone 6 mg given once daily for up to ten days vs. usual care alone. The primary outcome was 28-day mortality. Results: 2104 patients randomly allocated to receive dexamethasone were compared with 4321 patients concurrently allocated to usual care. Overall, 454 (21.6%) patients allocated dexamethasone and 1065 (24.6%) patients allocated usual care died within 28 days (age-adjusted rate ratio [RR] 0.83; 95% confidence interval [CI] 0.74 to 0.92; P<0.001). The proportional and absolute mortality rate reductions varied significantly depending on level of respiratory support at randomization (test for trend p<0.001): Dexamethasone reduced deaths by one-third in patients receiving invasive mechanical ventilation (29.0% vs. 40.7%, RR 0.65 [95% CI 0.51 to 0.82]; p<0.001), by one-fifth in patients receiving oxygen without invasive mechanical ventilation (21.5% vs. 25.0%, RR 0.80 [95% CI 0.70 to 0.92]; p=0.002), but did not reduce mortality in patients not receiving respiratory support at randomization (17.0% vs. 13.2%, RR 1.22 [95% CI 0.93 to 1.61]; p=0.14). Conclusions: In patients hospitalized with COVID-19, dexamethasone reduced 28-day mortality among those receiving invasive mechanical ventilation or oxygen at randomization, but not among patients not receiving respiratory support. 2020-06-22
- The OpenSAFELY Collaborative; Anna Schultze; Alex J Walker; Brian MacKenna; Caroline E Morton; Krishnan Bhaskaran; Jeremy P Brown; Christopher T. Rentsch; Elizabeth J Williamson; Henry Drysdale; Richard Croker; Seb Bacon; William J Hulme; Chris Bates; Helen J Curtis; Amir Mehrkar; David Evans; Peter Inglesby; Jonathan Cockburn; Helen I McDonald; Laurie Tomlinson; Rohini Mathur; Kevin Wing; Angel YS Wong; Harriet Forbes; John Parry; Frank Hester; Sam Harper; Stephen JW Evans; Jennifer Quint; Liam Smeeth; Ian J Douglas; Ben Goldacre Inhaled corticosteroid use and risk COVID-19 related death among 966,461 patients with COPD or asthma: an OpenSAFELY analysis Background: Early descriptions of the coronavirus outbreak showed a lower prevalence of asthma and COPD than was expected for people diagnosed with COVID-19, leading to speculation that inhaled corticosteroids (ICS) may protect against infection with SARS-CoV-2, and development of serious sequelae. We evaluated the association between ICS and COVID-19 related death using linked electronic health records in the UK. Methods: We conducted cohort studies on two groups of people (COPD and asthma) using the OpenSAFELY platform to analyse data from primary care practices linked to national death registrations. People receiving an ICS were compared to those receiving alternative respiratory medications. Our primary outcome was COVID-19 related death. Findings: We identified 148,588 people with COPD and 817,973 people with asthma receiving relevant respiratory medications in the four months prior to 01 March 2020. People with COPD receiving ICS were at a greater risk of COVID-19 related death compared to those receiving a long-acting beta agonist (LABA) and a long-acting muscarinic antagonist (LAMA) (adjusted HR = 1.38, 95% CI = 1.08 - 1.75). People with asthma receiving high dose ICS were at an increased risk of death compared to those receiving a short-acting beta agonist (SABA) only (adjusted HR = 1.52, 95%CI = 1.08 - 2.14); the adjusted HR for those receiving low-medium dose ICS was 1.10 (95% CI = 0.82 - 1.49). Quantitative bias analyses indicated that an unmeasured confounder of only moderate strength of association with exposure and outcome could explain the observed associations in both populations. Interpretation: These results do not support a major role of ICS in protecting against COVID-19 related deaths. Observed increased risks of COVID-19 related death among people with COPD and asthma receiving ICS can be plausibly explained by unmeasured confounding due to disease severity. 2020-06-20
Andre Python; Andreas Bender; Marta Blangiardo; Janine B Illian; Ying Lin; Baoli Liu; Tim C D Lucas; Siwei Tan; Yingying Wen; Davit Svanidze; Jianwei Yin A downscaling approach to compare COVID-19 count data from databases aggregated at different spatial scales As the COVID-19 pandemic continues to threaten various regions around the world, obtaining accurate and reliable COVID-19 data is crucial for governments and local communities aiming at rigorously assessing the extent and magnitude of the virus spread and deploying efficient interventions. Using data reported between January and February 2020 in China, we compared counts of COVID-19 from near-real time spatially disaggregated data (city-level) with fine-spatial scale predictions from a Bayesian downscaling regression model applied to a reference province-level dataset. The results highlight discrepancies in the counts of coronavirus-infected cases at district level and identify districts that may require further investigation. 2020-06-20
Chun-Han Lo; Long H. Nguyen; David A. Drew; Mark S. Graham; Erica T. Warner; Amit D. Joshi; Christina M. Astley; Chuan-Guo Guo; Wenjie Ma; Raaj S. Mehta; Sohee Kwon; Mingyang Song; Richard Davies; Joan Capdevila; Karla A. Lee; Mary Ni Lochlainn; Thomas Varsavsky; Carole H. Sudre; Jonathan Wolf; Yvette C. Cozier; Lynn Rosenberg; Lynne R. Wilkens; Christopher A. Haiman; Loic Le Marchand; Julie R. Palmer; Tim D. Spector; Sebastien Ourselin; Claire J. Steves; Andrew T. Chan; - COPE Consortium Racial and ethnic determinants of Covid-19 risk Background Racial and ethnic minorities have disproportionately high hospitalization rates and mortality related to the novel coronavirus disease 2019 (Covid-19). There are comparatively scant data on race and ethnicity as determinants of infection risk. Methods We used a smartphone application (beginning March 24, 2020 in the United Kingdom [U.K.] and March 29, 2020 in the United States [U.S.]) to recruit 2,414,601 participants who reported their race/ethnicity through May 25, 2020 and employed logistic regression to determine the adjusted odds ratios (aORs) and 95% confidence intervals (CIs) for a positive Covid-19 test among racial and ethnic groups. Results We documented 8,858 self-reported cases of Covid-19 among 2,259,841 non-Hispanic white; 79 among 9,615 Hispanic; 186 among 18,176 Black; 598 among 63,316 Asian; and 347 among 63,653 other racial minority participants. Compared with non-Hispanic white participants, the risk for a positive Covid-19 test was increased across racial minorities (aORs ranging from 1.24 to 3.51). After adjustment for socioeconomic indices and Covid-19 exposure risk factors, the associations (aOR [95% CI]) were attenuated but remained significant for Hispanic (1.58 [1.24-2.02]) and Black participants (2.56 [1.93-3.39]) in the U.S. and South Asian (1.52 [1.38-1.67]) and Middle Eastern participants (1.56 [1.25-1.95]) in the U.K. A higher risk of Covid-19 and seeking or receiving treatment was also observed for several racial/ethnic minority subgroups. Conclusions Our results demonstrate an increase in Covid-19 risk among racial and ethnic minorities not completely explained by other risk factors for Covid-19, comorbidities, and sociodemographic characteristics. Further research investigating these disparities are needed to inform public health measures. 2020-06-20
Petra Mlcochova; Dami Collier; Allyson V Ritchie; Sonny M Assennato; Myra Hosmillo; Neha Goel; Bo Meng; Krishna Chatterji; Vivien Mendoza; Nigel Temperton; Leo Kiss; Katarzyna A Ciazyns; Xiaoli Xiong; John AG Briggs; James Nathan; Federica Mescia; Hongyi Zhang; Petros Barmpounakis; Nikos Demeris; Richard Skells; Paul Lyons; John Bradley; Stephen Baker; Jean Pierre Allain; Kenneth GC Smith; Ian Goodfellow; Ravindra K Gupta Combined point of care nucleic acid and antibody testing for SARS-CoV-2: a prospective cohort study in suspected moderate to severe COVID-19 disease. Background Rapid COVID-19 diagnosis in hospital is essential for patient management and identification of infectious patients to limit the potential for nosocomial transmission. The diagnosis of infection is complicated by 30-50% of COVID-19 hospital admissions with nose/throat swabs testing negative for SARS-CoV-2 nucleic acid, frequently after the first week of illness when SARS-CoV-2 antibody responses become detectable. We assessed the diagnostic accuracy of combined rapid antibody point of care (POC) and nucleic acid assays for suspected COVID-19 disease in the emergency department. Methods We developed (i) an in vitro neutralization assay using a lentivirus expressing a genome encoding luciferase and pseudotyped with spike (S) protein and (ii) an ELISA test to detect IgG antibodies to nucleocapsid (N) and S proteins from SARS-CoV-2. We tested two lateral flow rapid fingerprick tests with bands for IgG and IgM. We then prospectively recruited participants with suspected moderate to severe COVID-19 and tested for SARS-CoV-2 nucleic acid in a combined nasal/throat swab using the standard laboratory RT-PCR and a validated rapid POC nucleic acid amplification (NAAT) test. Additionally, serum collected at admission was retrospectively tested by in vitro neutralisation, ELISA and the candidate POC antibody tests. We evaluated the performance of the individual and combined rapid POC diagnostic tests against a composite reference standard of neutralisation and standard laboratory based RT-PCR. Results 45 participants had specimens tested for nucleic acid in nose/throat swabs as well as stored sera for antibodies. Using the composite reference standard, prevalence of COVID-19 disease was 53.3% (24/45). Median age was 73.5 (IQR 54.0-86.5) years in those with COVID-19 disease by our reference standard and 63.0 (IQR 41.0-72.0) years in those without disease. The overall detection rate by rapid NAAT was 79.2% (95CI 57.8-92.9%), decreasing from 100% (95% CI 65.3-98.6%) in days 1-4 to 50.0% (95% CI 11.8-88.2) for days 9-28 post symptom onset. Correct identification of COVID-19 with combined rapid POC diagnostic tests was 100% (95CI 85.8-100%) with a false positive rate of 5.3-14.3%, driven by POC LFA antibody tests. Conclusions Combined POC tests have the potential to transform our management of COVID-19, including inflammatory manifestations later in disease where nucleic acid test results are negative. A rapid combined approach will also aid recruitment into clinical trials and in prescribing therapeutics, particularly where potentially harmful immune modulators (including steroids) are used. 2020-06-18
Alex Siu Fung Kwong; Rebecca M Pearson; Mark J Adams; Kate Northstone; Kate Tilling; Daniel Smith; Chloe Fawns-Ritchie; Helen Bould; Naomi Warne; Stan Zammit; David J Gunnell; Paul Moran; Nadia Micali; Abraham Reichenberg; Matthew Hickman; Dheeraj Rai; Simon Haworth; Archie Campbell; Drew Altschul; Robin Flaig; Andrew M McIntosh; Deborah A Lawlor; David Porteous; Nicholas J Timpson Mental health during the COVID-19 pandemic in two longitudinal UK population cohorts Background: The impact of COVID-19 on mental health is unclear. Evidence from longitudinal studies with pre pandemic data are needed to address (1) how mental health has changed from pre-pandemic levels to during the COVID-19 pandemic and (2), whether there are groups at greater risk of poorer mental health during the pandemic? Methods: We used data from COVID-19 surveys (completed through April/May 2020), nested within two large longitudinal population cohorts with harmonised measures of mental health: two generations of the Avon Longitudinal Study of Parents and Children (ALPSAC): the index generation ALSPAC-G1 (n= 2850, mean age 28) and the parents generation ALSPAC-G0 (n= 3720, mean age = 59) and Generation Scotland: Scottish Family Health Study (GS, (n= 4233, mean age = 59), both with validated pre-pandemic measures of mental health and baseline factors. To answer question 1, we used ALSPAC-G1, which has identical mental health measures before and during the pandemic. Question 2 was addressed using both studies, using pre-pandemic and COVID-19 specific factors to explore associations with depression and anxiety in COVID-19. Findings: In ALSPAC-G1 there was evidence that anxiety and lower wellbeing, but not depression, had increased in COVID-19 from pre-pandemic assessments. The percentage of individuals with probable anxiety disorder was almost double during COVID-19: 24% (95% CI 23%, 26%) compared to pre-pandemic levels (13%, 95% CI 12%, 14%), with clinically relevant effect sizes. In both ALSPAC and GS, depression and anxiety were greater in younger populations, women, those with pre-existing mental and physical health conditions, those living alone and in socio-economic adversity. We did not detect evidence for elevated risk in key workers or health care workers. Interpretation: These results suggest increases in anxiety and lower wellbeing that may be related to the COVID-19 pandemic and/or its management, particularly in young people. This research highlights that specific groups may be disproportionally at risk of elevated levels of depression and anxiety during COVID-19 and supports recent calls for increasing funds for mental health services. Funding: The UK Medical Research Council (MRC), the Wellcome Trust and University of Bristol. 2020-06-18
Maria Beatrice Zazzara; Rose S. Penfold; Amy L. Roberts; Karla Lee; Hannah Dooley; Carole H. Sudre; Carly Welch; Ruth C. E. Bowyer; Alessia Visconti; Massimo Mangino; Maxim B. Freydin; Julia S. El-Sayed Moustafa; Kerrin Small; Benjamin Murray; Marc Modat; Jonathan Wolf; Sebastien Ourselin; Finbarr C. Martin; Claire J. Steves; Mary Ni Lochlainn Delirium is a presenting symptom of COVID-19 in frail, older adults: a cohort study of 322 hospitalised and 535 community-based older adults Background: Frailty, increased vulnerability to physiological stressors, is associated with adverse outcomes. COVID-19 exhibits a more severe disease course in older, co-morbid adults. Awareness of atypical presentations is critical to facilitate early identification. Objective: To assess how frailty affects presenting COVID-19 symptoms in older adults. Design: Observational cohort study of hospitalised older patients and self-report data for community-based older adults. Setting: Admissions to St Thomas' Hospital, London with laboratory-confirmed COVID-19. Community-based data for 535 older adults using the COVID Symptom Study mobile application. Subjects: Hospital cohort: patients aged 65 and over (n=322); unscheduled hospital admission between March 1st, 2020 - May 5th, 2020; COVID-19 confirmed by RT-PCR of nasopharyngeal swab. Community-based cohort: participants aged 65 and over enrolled in the COVID Symptom Study (n=535); reported test-positive for COVID-19 from March 24th (application launch)- May 8th, 2020. Methods: Multivariate logistic regression analysis performed on age-matched samples from hospital and community-based cohorts to ascertain association of frailty with symptoms of confirmed COVID-19. Results: Hospital cohort: significantly higher prevalence of delirium in the frail sample, with no difference in fever or cough. Community-based cohort: significantly higher prevalence of probable delirium in frailer, older adults, and fatigue and shortness of breath. Conclusions: This is the first study demonstrating higher prevalence of delirium as a COVID-19 symptom in older adults with frailty compared to other older adults. This emphasises need for systematic frailty assessment and screening for delirium in acutely ill older patients in hospital and community settings. Clinicians should suspect COVID-19 in frail adults with delirium. 2020-06-17
Livia Perfetto; Chiara Pastrello; Noemi Del-Toro; Margaret Duesbury; Marta Iannuccelli; Max Kotlyar; Luana Licata; Birgit Meldal; Kalpana Panneerselvam; Simona Panni; Negin Rahimzadeh; Sylvie Ricard-Blum; Lukasz Salwinski; Anjali Shrivastava; Gianni Cesareni; Matteo Pellegrini; Sandra Orchard; Igor Jurisica; Henning Hermjakob; Pablo Porras The IMEx Coronavirus interactome: an evolving map of Coronaviridae-Host molecular interactions The current Coronavirus Disease 2019 (COVID-19) pandemic, caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), has spurred a wave of research of nearly unprecedented scale. Among the different strategies that are being used to understand the disease and develop effective treatments, the study of physical molecular interactions enables studying fine-grained resolution of the mechanisms behind the virus biology and the human organism response. Here we present a curated dataset of physical molecular interactions, manually extracted by IMEx Consortium curators focused on proteins from SARS-CoV-2, SARS-CoV-1 and other members of the Coronaviridae family. Currently, the dataset comprises over 2,200 binarized interactions extracted from 86 publications. The dataset can be accessed in the standard formats recommended by the Proteomics Standards Initiative (HUPO-PSI) at the IntAct database website (www.ebi.ac.uk/intact), and will be continuously updated as research on COVID-19 progresses. 2020-06-16
Robert Stewart; Evangelia Martin; Matthew Broadbent Mental health service activity during COVID-19 lockdown: South London and Maudsley data on working age community and home treatment team services and mortality from February to mid-May 2020 The lockdown and social distancing policy response to the COVID-19 pandemic in the UK has a potentially important impact on provision of mental healthcare; however, there has been relatively little quantification of this. Taking advantage of the Clinical Record Interactive Search (CRIS) data resource with 24-hourly updates of electronic mental health records data, this paper describes daily caseloads and contact numbers (face-to-face and virtual) for home treatment teams (HTTs) and working age adult community mental health teams (CMHTs) from 1st February to 15th May 2020 at the South London and Maudsley NHS Trust (SLaM), a large mental health service provider for 1.2m residents in south London. In addition daily deaths are described for all current and previous SLaM service users over this period and the same dates in 2019. In summary, the CMHT sector showed relatively stable caseloads and total contact numbers, but a substantial shift from face-to-face to virtual contacts, while HTTs showed the same changeover but reductions in caseloads and total contacts (although potentially an activity rise again during May). Number of deaths for the two months between 16th March and 15th May were 2.4-fold higher in 2020 than 2019, with 958 excess deaths. 2020-06-16
Carole H Sudre; Karla Lee; Mary Ni Lochlainn; Thomas Varsavsky; Benjamin Murray; Mark S. Graham; Cristina Menni; Marc Modat; Ruth C.E. Bowyer; Long H Nguyen; David Alden Drew; Amit D Joshi; Wenjie Ma; Chuan Guo Guo; Chun Han Lo; Sajaysurya Ganesh; Abubakar Buwe; Joan Capdevila Pujol; Julien Lavigne du Cadet; Alessia Visconti; Maxim Freydin; Julia S. El Sayed Moustafa; Mario Falchi; Richard Davies; Maria F. Gomez; Tove Fall; M. Jorge Cardoso; Jonathan Wolf; Paul W Franks; Andrew T Chan; Timothy D Spector; Claire J Steves; Sebastien Ourselin Symptom clusters in Covid19: A potential clinical prediction tool from the COVID Symptom study app As no one symptom can predict disease severity or the need for dedicated medical support in COVID-19, we asked if documenting symptom time series over the first few days informs outcome. Unsupervised time series clustering over symptom presentation was performed on data collected from a training dataset of completed cases enlisted early from the COVID Symptom Study Smartphone application, yielding six distinct symptom presentations. Clustering was validated on an independent replication dataset between May 1- May 28th, 2020. Using the first 5 days of symptom logging, the ROC-AUC of need for respiratory support was 78.8%, substantially outperforming personal characteristics alone (ROC-AUC 69.5%). Such an approach could be used to monitor at-risk patients and predict medical resource requirements days before they are required. 2020-06-16
Sonia Johnson; Christian Dalton-Locke; Norha Vera San Juan; Una Foye; Sian Oram; Alexandra Papamichail; Sabine Landau; Rachel Rowan Olive; Tamar Jeynes; Prisha Shah; Luke Sheridan Rains; Brynmor Lloyd-Evans; Sarah Carr; Helen Killaspy; Steve Gillard; Alan Simpson; - The COVID-19 Mental Health Policy Research Unit Group Impact on mental health care and on mental health service users of the COVID-19 pandemic: a mixed methods survey of UK mental health care staff Purpose: The COVID-19 pandemic has potential to disrupt and burden the mental health care system, and to magnify inequalities experienced by mental health service users. Methods: We investigated staff reports regarding the impact of the COVID-19 pandemic in its early weeks on mental health care and mental health service users in the UK using a mixed methods online survey. Recruitment channels included professional associations and networks, charities and social media. Quantitative findings were reported with descriptive statistics, and content analysis conducted for qualitative data. Results: 2,180 staff from a range of sectors, professions and specialties participated. Immediate infection control concerns were highly salient for inpatient staff, new ways of working for community staff. Multiple rapid adaptations and innovations in response to the crisis were described, especially remote working. This was cautiously welcomed but found successful in only some clinical situations. Staff had specific concerns about many groups of service users, including people whose conditions are exacerbated by pandemic anxieties and social disruptions; people experiencing loneliness, domestic abuse and family conflict; those unable to understand and follow social distancing requirements; and those who cannot engage with remote care. Conclusion: This overview of staff concerns and experiences in the early COVID-19 pandemic suggests directions for further research and service development: we suggest that how to combine infection control and a therapeutic environment in hospital, and how to achieve effective and targeted tele-health implementation in the community, should be priorities. The limitations of our convenience sample must be noted. 2020-06-14
Ross McQueenie; Hamish Foster; Bhautesh D Jani; Srinivasa Vittal Katikireddi; Naveed Sattar; Jill P Pell; Frederick K Ho; Claire L Niedzwiedz; Claire E Hastie; Jana Anderson; Patrick B Mark; Michael Sullivan; Frances S Mair; Barbara I Nicholl Multimorbidity, Polypharmacy, and COVID-19 infection within the UK Biobank cohort. BACKGROUND: It is now well recognised that the risk of severe COVID-19 increases with some long-term conditions (LTCs). However, prior research primarily focuses on individual LTCs and there is a lack of data on the influence of multimorbidity ([&ge;]2 LTCs) on the risk of COVID-19. Given the high prevalence of multimorbidity, more detailed understanding of the associations with multimorbidity and COVID-19 would improve risk stratification and help protect those most vulnerable to severe COVID-19. Here we examine the relationships between multimorbidity, polypharmacy (a proxy of multimorbidity), and COVID-19; and how these differ by sociodemographic, lifestyle, and physiological prognostic factors. METHODS AND FINDINGS: We studied data from UK Biobank (428,199 participants; aged 37-73; recruited 2006-2010) on self-reported LTCs, medications, sociodemographic, lifestyle, and physiological measures which were linked to COVID-19 test data. Poisson regression models examined risk of COVID-19 by multimorbidity/polypharmacy and effect modification by COVID-19 prognostic factors (age/sex/ethnicity/socioeconomic status/smoking/physical activity/BMI/systolic blood pressure/renal function). 4,498 (1.05%) participants were tested; 1,324 (0.31%) tested positive for COVID-19. Compared with no LTCs, relative risk (RR) of COVID-19 in those with 1 LTC was no higher (RR 1.12 (CI 0.96-1.30)), whereas those with [&ge;]2 LTCs had 48% higher risk; RR 1.48 (1.28-1.71). Compared with no cardiometabolic LTCs, having 1 and [&ge;]2 cardiometabolic LTCs had a higher risk of COVID-19; RR 1.28 (1.12-1.46) and 1.77 (1.46-2.15), respectively. Polypharmacy was associated with a dose response increased risk of COVID-19. All prognostic factors were associated with a higher risk of COVID-19 infection in multimorbidity; being non-white, most socioeconomically deprived, BMI [&ge;]40 kg/m2, and reduced renal function were associated with the highest risk of COVID-19 infection: RR 2.81 (2.09-3.78); 2.79 (2.00-3.90); 2.66 (1.88-3.76); 2.13 (1.46-3.12), respectively. No multiplicative interaction between multimorbidity and prognostic factors was identified. Important limitations include the low proportion of UK Biobank participants with COVID-19 test data (1.05%) and UK Biobank participants being more affluent, healthier and less ethnically diverse than the general population. CONCLUSIONS: Increasing multimorbidity, especially cardiometabolic multimorbidity, and polypharmacy are associated with a higher risk of developing COVID-19. Those with multimorbidity and additional factors, such as non-white ethnicity, are at heightened risk of COVID-19. 2020-06-12
Trystan Leng; Connor White; Joe Hilton; Adam J Kucharski; Lorenzo Pellis; Helena Stage; Nicholas G Davies; Matt J Keeling; Stefan Flasche The effectiveness of social bubbles as part of a Covid-19 lockdown exit strategy, a modelling study Background: During the Covid-19 lockdown, contact clustering in social bubbles may allow extending contacts beyond the household at minimal additional risk and hence has been considered as part of modified lockdown policy or a gradual lockdown exit strategy. We estimated the impact of such strategies on epidemic and mortality risk using the UK as a case study. Methods: We used an individual based model for a synthetic population similar to the UK, that is stratified into transmission risks from the community, within the household and from other households in the same social bubble. The base case considers a situation where non-essential shops and schools are closed, the secondary household attack rate is 20% and the initial reproduction number is 0.8. We simulate a number of strategies including variations of social bubbles, i.e. the forming of exclusive pairs of households, for particular subsets of households (households including children and single occupancy households), as well as for all households. We test the sensitivity of the results to a range of alternative model assumptions and parameters. Results: Clustering contacts outside the household into exclusive social bubbles is an effective strategy of increasing contacts while limiting some of the associated increase in epidemic risk. In the base case scenario social bubbles reduced cases and fatalities by 17% compared to an unclustered increase of contacts. We find that if all households were to form social bubbles the reproduction number would likely increase to 1.1 and therefore beyond the epidemic threshold of one. However, strategies that allow households with young children or single occupancy households to form social bubbles only increased the reproduction number by less than 10%. The corresponding increase in morbidity andmortality is proportional to the increase in the epidemic risk but is largely focussed in older adults independently of whether these are included in the social bubbles. Conclusions: Social bubbles can be an effective way of extending contacts beyond the household limiting the increase in epidemic risk, if managed appropriately. 2020-06-12
Amitava Banerjee; Suliang Chen; Laura Pasea; Alvina Lai; Michail Katsoulis; Spiros Denaxas; Vahe Nafilyan; Bryan Williams; Wai Keong Wong; Ameet Bakhai; Kamlesh Khunti; Deenan Pillay; Mahdad Noursadeghi; Honghan Wu; Nilesh Pareek; Daniel Bromage; Theresa Mcdonagh; Jonathan Byrne; James T Teo; Ajay Shah; Ben Humberstone; Liang V Tang; Anoop SV Shah; Andrea Rubboli; Yutao Guo; Yu Hu; Cathie LM Sudlow; Gregory YH Lip; Harry Hemingway Excess deaths in people with cardiovascular diseases during the COVID-19 pandemic. Background: Cardiovascular diseases(CVD) increase mortality risk from coronavirus infection(COVID-19), but there are concerns that the pandemic has affected supply and demand of acute cardiovascular care. We estimated excess mortality in specific CVDs, both direct, through infection, and indirect, through changes in healthcare. Methods: We used population-based electronic health records from 3,862,012 individuals in England to estimate pre- and post-COVID-19 mortality risk(direct effect) for people with incident and prevalent CVD. We incorporated: (i)pre-COVID-19 risk by age, sex and comorbidities, (ii)estimated population COVID-19 prevalence, and (iii)estimated relative impact of COVID-19 on mortality(relative risk, RR: 1.5, 2.0 and 3.0). For indirect effects, we analysed weekly mortality and emergency department data for England/Wales and monthly hospital data from England(n=2), China(n=5) and Italy(n=1) for CVD referral, diagnosis and treatment until 1 May 2020. Findings: CVD service activity decreased by 60-100% compared with pre-pandemic levels in eight hospitals across China, Italy and England during the pandemic. In China, activity remained below pre-COVID-19 levels for 2-3 months even after easing lockdown, and is still reduced in Italy and England. Mortality data suggest indirect effects on CVD will be delayed rather than contemporaneous(peak RR 1.4). For total CVD(incident and prevalent), at 10% population COVID-19 rate, we estimated direct impact of 31,205 and 62,410 excess deaths in England at RR 1.5 and 2.0 respectively, and indirect effect of 49932 to 99865 excess deaths. Interpretation: Supply and demand for CVD services have dramatically reduced across countries with potential for substantial, but avoidable, excess mortality during and after the COVID-19 pandemic. 2020-06-11
Yang Yang; Yi Du; Igor A Kaltashov The utility of native MS for understanding the mechanism of action of repurposed therapeutics in COVID-19: heparin as a disruptor of the SARS-CoV-2 interaction with its host cell receptor. The emergence and rapid proliferation of the novel coronavirus (SARS-CoV-2) resulted in a global pandemic, with over six million cases and nearly four hundred thousand deaths reported world-wide by the end of May 2020. A rush to find the cures prompted re-evaluation of a range of existing therapeutics vis-a-vis their potential role in treating COVID-19, placing a premium on analytical tools capable of supporting such efforts. Native mass spectrometry (MS) has long been a tool of choice in supporting the mechanistic studies of drug/therapeutic target interactions, but its applications remain limited in the cases that involve systems with a high level of structural heterogeneity. Both SARS-CoV-2 spike protein (S-protein), a critical element of the viral entry to the host cell, and ACE2, its docking site on the host cell surface, are extensively glycosylated, making them challenging targets for native MS. However, supplementing native MS with a gas-phase ion manipulation technique (limited charge reduction) allows meaningful information to be obtained on the non-covalent complexes formed by ACE2 and the receptor-binding domain (RBD) of the S-protein. Using this technique in combination with molecular modeling also allows the role of heparin in destabilizing the ACE2/RBD association to be studied, providing critical information for understanding the molecular mechanism of its interference with the virus docking to the host cell receptor. Both short (pentasaccharide) and relatively long (eicosasaccharide) heparin oligomers form 1:1 complexes with RBD, indicating the presence of a single binding site. This association alters the protein conformation (to maximize the contiguous patch of the positive charge on the RBD surface), resulting in a notable decrease of its ability to associate with ACE2. The destabilizing effect of heparin is more pronounced in the case of the longer chains due to the electrostatic repulsion between the low-pI ACE2 and the heparin segments not accommodated on the RBD surface. In addition to providing important mechanistic information on attenuation of the ACE2/RBD association by heparin, the study demonstrates the yet untapped potential of native MS coupled to gas-phase ion chemistry as a means of facilitating rational repurposing of the existing medicines for treating COVID-19. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=108 SRC="FIGDIR/small/142794v1_ufig1.gif" ALT="Figure 1"> View larger version (46K): org.highwire.dtl.DTLVardef@ce764corg.highwire.dtl.DTLVardef@b8909corg.highwire.dtl.DTLVardef@11e13fcorg.highwire.dtl.DTLVardef@1b2383a_HPS_FORMAT_FIGEXP M_FIG C_FIG 2020-06-10
Marta Blangiardo; Michela Cameletti; Monica Pirani; Gianni Corsetti; Marco Battaglini; Gianluca Baio Estimating weekly excess mortality at subnational level in Italy during the COVID-19 pandemic Background Excess mortality from all-cause has been estimated at national level for different countries, to provide a picture of the total burden of the COVID-19 pandemic. Nevertheless, there have been no attempts at modelling it at high spatial resolution, needed to understand geographical differences in the mortality patterns, to evaluate temporal lags and to plan for future waves of the pandemic. Methods This is the first subnational study on excess mortality during the COVID-19 pandemic in Italy, the third most-hit country. We considered municipality level and estimated all-cause mortality weekly trends based on the first four months of 2016 -- 2019. We specified a Bayesian hierarchical model allowing for spatial heterogeneity as well as for non-linear smooth spatio-temporal terms. We predicted the weekly mortality rates at municipality level for 2020 based on the modelled spatio-temporal trends (i.e.~in the absence of the pandemic) and estimated the excess mortality and the uncertainty surrounding it. Results There was strong evidence of excess mortality for Northern Italy; Lombardia showed higher mortality rates than expected from the end of February, with 23,946 (23,013 to 24,786) total excess deaths. North-West and North-East regions showed higher mortality from the beginning of March, with 6,942 (6,142 to 7,667) and 8,033 (7,061 to 9,044) total excess deaths respectively. After discounting for the number of COVID-19-confirmed deaths, Lombardia still registered 10,197 (9,264 to 11,037) excess deaths, while regions in the North-West and North-East had 2,572 (1,772 to 3,297) and 2,047 (1,075 to 3,058) extra deaths, respectively. We observed marked geographical differences at municipality level. The city of Bergamo (Lombardia) showed the largest percent excess 88.9% (81.9% to 95.2%) at the peak of the pandemic. An excess of 84.2% (73.8% to 93.4%) was also estimated at the same time for the city of Pesaro (Central Italy), in stark contrast with the rest of the region, which does not show evidence of excess deaths. 2020-06-09
Michael TC Poon; Paul M Brennan; Kai Jin; Jonine Figueroa; Cathie LM Sudlow TRACKing Excess Deaths (TRACKED): an interactive online tool to monitor excess deaths associated with COVID-19 pandemic in the United Kingdom Aim: We aimed to describe trends of excess mortality in the United Kingdom (UK) stratified by nation and cause of death, and to develop an online tool for reporting the most up to date data on excess mortality. Methods: Population statistics agencies in the UK including the Office for National Statistics (ONS), National Records of Scotland (NRS), and Northern Ireland Statistics and Research Agency (NISRA) publish weekly data on deaths. We used mortality data up to 22nd May in the ONS and the NISRA and 24th May in the NRS. Crude mortality for non-COVID deaths (where there is no mention of COVID-19 on the death certificate) calculated. Excess mortality defined as difference between observed mortality and expected average of mortality from previous 5 years. Results: There were 56,961 excess deaths and 8,986 were non-COVID excess deaths. England had the highest number of excess deaths per 100,000 population (85) and Northern Ireland the lowest (34). Non-COVID mortality increased from 23rd March and returned to the 5-year average on 10th May. In Scotland, where underlying cause mortality data besides COVID-related deaths was available, the percentage excess over the 8-week period when COVID-related mortality peaked was: dementia 49%, other causes 21%, circulatory diseases 10%, and cancer 5%. We developed an online tool (TRACKing Excess Deaths - TRACKED) to allow dynamic exploration and visualisation of the latest mortality trends. Conclusions: Continuous monitoring of excess mortality trends and further integration of age- and gender-stratified and underlying cause of death data beyond COVID-19 will allow dynamic assessment of the impacts of indirect and direct mortality of the COVID-19 pandemic. 2020-06-07
Naveed Sattar; Frederick K Ho; Jason MR Gill; Nazim Ghouri; Stuart R Gray; Carlos A Celis-Morales; Srinivasa Vittal Katikireddi; Colin Berry; Jill P Pell; John JV McMurray; Paul Welsh Different adiposity measures across sex, age, ethnicity, and COVID-19 We examined the link between BMI and risk of a positive test for SARS-CoV-2 and risk of COVID-19-related death among UK Biobank participants. Among 4855 participants tested for SARS-CoV-2 in hospital, 839 were positive and of these 189 died from COVID-19. Poisson models with penalised thin plate splines were run relating exposures of interest to test positivity and case-fatality, adjusting for confounding factors. BMI was associated strongly with positive test, and risk of death related to COVID-19. The gradient of risk in relation to BMI was steeper in those under 70, compared with those aged 70 years or older for COVID-19 related death (Pinteraction=0.03). BMI was more strongly related to test positivity (Pinteraction=0.010) and death (Pinteraction=0.002) in non-whites, compared with whites. These data add support for adiposity being more strongly linked to COVID-19-related deaths in younger people and non-white ethnicities. If future studies confirm causality, lifestyle interventions to improve adiposity status may be important to reduce the risk of COVID-19 in all, but perhaps particularly, non-white communities. 2020-06-07
Vilas Navapurkar; Josefin Bartholdson-Scott; Mailis Maes; Ellen Higginson; Sally Forrest; Joana Pereira Dias; Surendra Parmar; Emma Heasman-Hunt; Petra Polgarova; Joanne Brown; Lissamma Titti; William PW Smith; Matthew Routledge; David Sapsford; Estee Torok; David Enoch; Vanessa Wong; Martin D Curran; Nicholas Brown; Jurgen Herre; Gordon Dougan; Andrew Conway Morris Development and implementation of a customised rapid syndromic diagnostic test for severe pneumonia Background The diagnosis of infectious diseases has been hampered by reliance on microbial culture. Cultures take several days to return a result and organisms frequently fail to grow. In critically ill patients this leads to the use of empiric, broad-spectrum antimicrobials and mitigates against stewardship. Methods Single ICU observational cohort study with contemporaneous comparator group. We developed and implemented a TaqMan array card (TAC) covering 52 respiratory pathogens in ventilated patients undergoing bronchoscopic investigation for suspected pneumonia. The time to result was compared against conventional culture, and sensitivity compared to conventional microbiology and metagenomic sequencing. We observed the clinician decisions in response to array results, comparing antibiotic free days (AFD) between the study cohort and comparator group. Findings 95 patients were enrolled with 71 forming the comparator group. TAC returned results 61 hours (IQR 42-90) faster than culture. The test had an overall sensitivity of 93% (95% CI 88-97%) compared to a combined standard of conventional culture and metagenomic sequencing, with 100% sensitivity for most individual organisms. In 54% of cases the TAC results altered clinical management, with 62% of changes leading to de-escalation, 30% to an increase in spectrum, and investigations for alternative diagnoses in 9%. There was a significant difference in the distribution of AFDs with more AFDs in the TAC group (p=0.02). Interpretation Implementation of a customised syndromic diagnostic for pneumonia led to faster results, with high sensitivity and measurable impact on clinical decision making. Funding Addenbrookes Charitable Trust, Wellcome Trust and Cambridge NIHR BRC 2020-06-05
Matt J Keeling; Michael J Tildesley; Benjamin D Atkins; Bridget Penman; Emma Southall; Glen Guyver-Fletcher; Alex Holmes; Hector McKimm; Erin E Gorsich; Edward M Hill; Louise Dyson The impact of school reopening on the spread of COVID-19 in England Background: In the UK, cases of COVID-19 have been declining since mid-April and there is good evidence to suggest that the effective reproduction number has dropped below 1, leading to a multi-phase relaxation plan for the country to emerge from lockdown. As part of this staggered process, primary schools are scheduled to partially reopen on 1st June. Evidence from a range of sources suggests that children are, in general, only mildly affected by the disease and have low mortality rates, though there is less certainty regarding children's role in transmission. Therefore, there is wide discussion on the impact of reopening schools. Methods: We compare eight strategies for reopening primary and secondary schools in England from 1st June, focusing on the return of particular year groups and the associated epidemic consequences. This is assessed through model simulation, modifying a previously developed dynamic transmission model for SARS-CoV-2. We quantify how the process of reopening schools affected contact patterns and anticipated secondary infections, the relative change in R according to the extent of school reopening, and determine the public health impact via estimated change in clinical cases and its sensitivity to decreases in adherence post strict lockdown. Findings: Whilst reopening schools, in any form, results in more mixing between children, an increase in R and hence transmission of the disease, the magnitude of that increase can be low dependent upon the age-groups that return to school and the behaviour of the remaining population. We predict that reopening schools in a way that allows half class sizes or that is focused on younger children is unlikely to push R above one, although there is noticeable variation between the regions of the country. Given that older children have a greater number of social contacts and hence a greater potential for transmission, our findings suggest reopening secondary schools results in larger increases in case burden than only reopening primary schools; reopening both generates the largest increase and could push R above one in some regions. The impact of less social-distancing in the rest of the population, generally has far larger effects than reopening schools and exacerbates the impacts of reopening. Discussion: Our work indicates that any reopening of schools will result in increased mixing and infection amongst children and the wider population, although the opening of schools alone is unlikely to push the value of R above one. However, impacts of other recent relaxations of lockdown measures are yet to be quantified, suggesting some regions may be closer to the critical threshold that would lead to a growth in cases. Given the uncertainties, in part due to limited data on COVID-19 in children, school reopening should be carefully monitored. Ultimately, the decision about reopening classrooms is a difficult trade-off between increased epidemiological consequences and the emotional, educational and developmental needs of children. 2020-06-05
Mohammed A Almeshari; Nowaf Y Alobaidi; Mansour Al Asmri; Eyas Alhuthail; Ziyad Alshehri; Farhan Alenezi; Elizabeth Sapey; Dhruv Parekh Mechanical ventilation utilization in COVID-19: A systematic review and meta-analysis Background: In December 2019, SARS-CoV-2 caused a global pandemic with a viral infection called COVID-19. The disease usually causes respiratory symptoms but in a small proportion of patients can lead to pneumonitis, Adult Respiratory Distress Syndrome and death. Invasive Mechanical Ventilation (IMV) is considered a life-saving treatment for COVID-19 patients and a huge demand for IMV devices was reported globally. This review aims to provide insight on the initial IMV practices for COVID-19 patients in the initial phase of the pandemic. Methods: Electronic databases (Embase and MEDLINE) were searched for applicable articles using relevant keywords. The references of included articles were hand searched. Articles that reported the use of IMV in adult COVID-19 patients were included in the review. The NIH quality assessment tool for cohort and cross-sectional studies was used to appraise studies. Results: 106 abstracts were identified from the databases search, of which 16 were included. 4 studies were included in the meta-analysis. In total, 9988 patients were included across all studies. The overall cases of COVID-19 requiring IMV ranged from 2-75%. Increased age and pre-existing comorbidities increased the likelihood of IMV requirement. The reported mortality rate in patients receiving IMV ranged between 50-100%. On average, IMV was required and initiated between 10-10.5 days from symptoms onset. When invasively ventilated, COVID-19 patients required IMV for a median of 10-17 days across studies. Little information was provided on ventilatory protocols or management strategies and was inconclusive. Conclusion: In these initial reporting studies for the first month of the pandemic, patients receiving IMV were older and had more pre-existing co-morbidities than those who did not require IMV. The mortality rate was high in COVID-19 patients who received IMV. Studies are needed to evaluate protocols and modalities of IMV to improve outcomes and identify the populations most likely to benefit from IMV. 2020-06-05
Zahra Raisi-Estabragh; Celeste McCracken; Mae S Bethell; Jackie Cooper; Cyrus Cooper; Mark J Caulfield; Patricia B Munroe; Nicholas C Harvey; Steffen E Petersen Greater risk of severe COVID-19 in non-White ethnicities is not explained by cardiometabolic, socioeconomic, or behavioural factors, or by 25(OH)-vitamin D status: study of 1,326 cases from the UK Biobank Background We examined whether the greater severity of coronavirus disease 2019 (COVID-19) amongst men and non-White ethnicities is explained by cardiometabolic, socio-economic, or behavioural factors. Methods We studied 4,510 UK Biobank participants tested for COVID-19 (positive, n=1,326). Multivariate logistic regression models including age, sex, and ethnicity were used to test whether addition of: 1)cardiometabolic factors (diabetes, hypertension, high cholesterol, prior myocardial infarction, smoking, BMI); 2)25(OH)-vitamin D; 3)poor diet; 4)Townsend deprivation score; 5)housing (home type, overcrowding); or 6)behavioural factors (sociability, risk taking) attenuated sex/ethnicity associations with COVID-19 status. Results There was over-representation of men and non-White ethnicities in the COVID-19 positive group. Non-Whites had, on average, poorer cardiometabolic profile, lower 25(OH)-vitamin D, greater material deprivation, and were more likely to live in larger households and flats/apartments. Male sex, non-White ethnicity, higher BMI, Townsend deprivation score, and household overcrowding were independently associated with significantly greater odds of COVID-19. The pattern of association was consistent for men and women; cardiometabolic, socio-demographic and behavioural factors did not attenuate sex/ethnicity associations. Conclusions Sex and ethnicity differential pattern of COVID-19 is not adequately explained by variations in cardiometabolic factors, 25(OH)-vitamin D levels, or socio-economic factors. Investigation of alternative biological pathways and different genetic susceptibilities is warranted. 2020-06-02
Rajeev Gupta; Vanya A Gant; Bryan Williams; Tariq Enver Respiratory Failure in Covid19 is associated with increased monocyte expression of complement receptor 3 A key question in COVID-19 infection is why some previously healthy patients develop severe pulmonary failure and some ultimately die. Initial pulmonary failure does not exhibit classical features of ARDS; hypercoagulability is a common laboratory feature, and pulmonary thrombotic microangiopathy has been reported post mortem1,2,3. Biomarkers cannot robustly identify such patients pre-emptively and no specific interventions exist to mitigate clinical deterioration. Mononuclear phagocytic cells are key immune cells and bind fibrinogen through the CD11b/CD18 dimer CR3, whose activated form can initiate microthrombus formation. Accordingly, we profiled circulating monocyte CD11b/CD18 cell surface density from COVID-19 infected adults who were (i) symptomatic but breathless, (ii) requiring ventilatory support, and (iii) recovering following ICU care for hypoxia. 2020-06-02
Paul M McKeigue; Amanda Weir; Jen Bishop; Stuart McGurnaghan; Sharon Kennedy; David McAllister; Chris Robertson; Rachael Wood; Nazir Lone; Janet Murray; Thomas Caparrotta; Alison Smith-Palmer; David Goldberg; Jim McMenamin; Colin Ramsay; Sharon Hutchinson; Helen M Colhoun Rapid Epidemiological Analysis of Comorbidities andTreatments as risk factors for COVID-19 in Scotland(REACT-SCOT): a population-based case-control study Background -- The objectives of this study were to identify risk factors for severe COVID-19 and to lay the basis for risk stratification based on demographic data and health records. Methods and Findings -- The design was a matched case-control study. Severe COVID-19 was defined as either a positive nucleic acid test for SARS-CoV-2 in the national database followed by entry to a critical care unit or death within 28 days, or a death certificate with COVID-19 as underlying cause. Up to ten controls per case matched for sex, age and primary care practice were selected from the population register. All diagnostic codes from the past five years of hospitalisation records and all drug codes from prescriptions dispensed during the past nine months were extracted. Rate ratios for severe COVID-19 were estimated by conditional logistic regression. There were 4272 severe cases. In a logistic regression using the age-sex distribution of the national population, the odds ratios for severe disease were 2.87 for a 10-year increase in age and 1.63 for male sex. In the case-control analysis, the strongest risk factor was residence in a care home, with rate ratio (95% CI) 21.4 (19.1, 23.9). Univariate rate ratios (95% CIs) for conditions listed by public health agencies as conferring high risk were 2.75 (1.96, 3.88) for Type 1 diabetes, 1.60 (1.48, 1.74) for Type 2 diabetes, 1.49 (1.37, 1.61) for ischemic heart disease, 2.23 (2.08, 2.39) for other heart disease, 1.96 (1.83, 2.10) for chronic lower respiratory tract disease, 4.06 (3.15, 5.23) for chronic kidney disease, 5.4 (4.9, 5.8) for neurological disease, 3.61 (2.60, 5.00) for chronic liver disease and 2.66 (1.86, 3.79) for immune deficiency or suppression. 78% of cases and 52% of controls had at least one listed condition (NA of cases and NA of controls under age 40). Severe disease was associated with encashment of at least one prescription in the past nine months and with at least one hospital admission in the past five years [rate ratios 3.10 (2.59, 3.71)] and 2.75 (2.53, 2.99) respectively] even after adjusting for the listed conditions. In those without listed conditions significant associations with severe disease were seen across many hospital diagnoses and drug categories. Age and sex provided 2.58 bits of information for discrimination. A model based on demographic variables, listed conditions, hospital diagnoses and prescriptions provided an additional 1.25 bits (C-statistic 0.825). A limitation of this study is that records from primary care were not available. Conclusions -- Along with older age and male sex, severe COVID-19 is strongly associated with past medical history across all age groups. Many comorbidities beyond the risk conditions designated by public health agencies contribute to this. A risk classifier that uses all the information available in health records, rather than only a limited set of conditions, will more accurately discriminate between low-risk and high-risk individuals who may require shielding until the epidemic is over. 2020-06-02
Dami A Collier; Sonny M Assennato; Nyarie Sithole; Katherine Sharrocks; Allyson Ritchie; Pooja Ravji; Matt Routledge; Dominic Sparkes; Jordan Skittrall; Ben Warne; Anna smielewska; ISOBEL RAMSEY; NEHA GOEL; MARTIN CURRAN; DAVID ENOCH; RHYS TASSELL; MICHELLE LINEHAM; DEVAN VAGHELA; CLARE LEONG; HOI PING MOK; JOHN BRADLEY; KENNETH GC SMITH; Vivien Mendoza; NIKOS DEMIRIS; MARTIN BESSER; GORDON DOUGAN; PAUL J LEHNER; Mark Siedner; HONGYI ZHANG; CLAIRE WADDINGTON; HELEN LEE; Ravindra K Gupta Rapid point of care nucleic acid testing for SARS-CoV-2 in hospitalised patients: a clinical trial and implementation study Objective To compare a point of care (POC) nucleic acid amplification based platform for rapid diagnosis of COVID-19 against the standard laboratory RT-PCR test and perform an implementation study. Design: prospective clinical trial (COVIDx) and observational study Setting: a large UK teaching hospital Participants: patients presenting to hospital with possible COVID-19 disease and tested on a combined nasal/throat swab using the SAMBA II SARS-CoV-2 rapid POC test and in parallel a combined nasal/throat swab for standard lab RT-PCR testing. Implementation phase participants underwent SARS-CoV-2 POC testing for a range of indications over a ten day period pre and post SAMBA II platform implementation. Main outcome measures: concordance and sensitivity and specificity of POC using the lab test as the reference standard, test turnaround time in trial and implementation periods; time to definitive patient triage from ED, time spent on COVID-19 holding wards, bay closures avoided, proportions of patients in isolation rooms following test, proportions of patients able to be moved to COVID negative areas following test. Results 149 participants were included in the COVIDx trial. 32 (21.5%) tested positive and 117 (78.5%) tested negative by standard lab RT-PCR. Median age was 62.7 (IQR 37 to 79) years and 47% were male. Cohen's kappa correlation between the index and reference tests was 0.96, 95% CI (0.91, 1.00). Sensitivity and specificity of SAMBA against the RT-PCR lab test were 96.9% (95% CI 0.838-0.999) and 99.1% (0.953-0.999) respectively. Median time to result was 2.6 hours (IQR 2.3 to 4.8) for SAMBA II and 26.4 hours (IQR 21.4 to 31.4) for the standard lab RT-PCR test (p<0.001). In the first 10 days of the SAMBA II SARS-CoV-2 test implementation for all hospital COVID-19 testing, analysis of the first 992 tests showed 59.8% of tests were used for ED patients, and the remainder were done for pre-operative screening (11.3%), discharges to nursing homes (10%), in-hospital screening of new symptoms (9.7%), screening in asymptomatic patients requiring hospital admission screening (3.8%) and access to interventions such as dialysis and chemotherapy for high risk patients (1.2%). Use of single occupancy rooms amongst those tested fell from 30.8% before to 21.2% after testing (p=0.03). 11 bay closures were avoided by use of SAMBA over ten days. The post implementation group was then compared with 599 individuals who had a standard lab RT-PCR test in the 10 days prior to SAMBA introduction. Median time to result during implementation fell from 39.4 hours (IQR 24.7-51.3) to 3.6 hours (IQR 2.6-5.8), p<0.0001 and the median time to definitive ward move from ED was significantly reduced from 24.1 hours (9.2-48.6) to 18.5 hours (10.2-28.8), p=0.002. Mean length of stay on a COVID-19 holding ward decreased from 58.5 hours to 29.9 hours (p<0.001) compared to the 10 days prior to implementation. Conclusions SAMBA II SARS-CoV-2 rapid POC test performed as well as standard lab RT-PCR and demonstrated shorter time to result both in trial and real-world settings. It was also associated with faster time to triage from the ED, release of isolation rooms, avoidance of hospital bay closures and movement of patients to COVID negative open green category wards, allowed discharge to care homes and expediting access to hospital investigations and procedures. POC testing will be instrumental in mitigating the impact of COVID-19 on hospital systems by allowing rapid triage and patient movement to safe and appropriate isolation wards in the hospital. This is also likely to reduce delays in patients accessing appropriate investigation and treatment, thereby improving clinical outcomes. 2020-06-02
Alvina G Lai; Laura Pasea; Amitava Banerjee; Spiros Denaxas; Michail Katsoulis; Wai Hoong Chang; Bryan Williams; Deenan Pillay; Mahdad Noursadeghi; David Linch; Derralynn Hughes; Martin D Forster; Clare Turnbull; Natalie K Fitzpatrick; Kathryn Boyd; Graham R Foster; Matt Cooper; Monica Jones; Kathy Pritchard-Jones; Richard Sullivan; Geoff Hall; Charlie Davie; Mark Lawler; Harry Hemingway Estimating excess mortality in people with cancer and multimorbidity in the COVID-19 emergency Background: Cancer and multiple non-cancer conditions are considered by the Centers for Disease Control and Prevention (CDC) as high risk conditions in the COVID-19 emergency. Professional societies have recommended changes in cancer service provision to minimize COVID-19 risks to cancer patients and health care workers. However, we do not know the extent to which cancer patients, in whom multi-morbidity is common, may be at higher overall risk of mortality as a net result of multiple factors including COVID-19 infection, changes in health services, and socioeconomic factors. Methods: We report multi-center, weekly cancer diagnostic referrals and chemotherapy treatments until April 2020 in England and Northern Ireland. We analyzed population-based health records from 3,862,012 adults in England to estimate 1-year mortality in 24 cancer sites and 15 non-cancer comorbidity clusters (40 conditions) recognized by CDC as high-risk. We estimated overall (direct and indirect) effects of COVID-19 emergency on mortality under different Relative Impact of the Emergency (RIE) and different Proportions of the population Affected by the Emergency (PAE). We applied the same model to the US, using Surveillance, Epidemiology, and End Results (SEER) program data. Results: Weekly data until April 2020 demonstrate significant falls in admissions for chemotherapy (45-66% reduction) and urgent referrals for early cancer diagnosis (70-89% reduction), compared to pre-emergency levels. Under conservative assumptions of the emergency affecting only people with newly diagnosed cancer (incident cases) at COVID-19 PAE of 40%, and an RIE of 1.5, the model estimated 6,270 excess deaths at 1 year in England and 33,890 excess deaths in the US. In England, the proportion of patients with incident cancer with [&ge;]1 comorbidity was 65.2%. The number of comorbidities was strongly associated with cancer mortality risk. Across a range of model assumptions, and across incident and prevalent cancer cases, 78% of excess deaths occur in cancer patients with [&ge;]1 comorbidity. Conclusion: We provide the first estimates of potential excess mortality among people with cancer and multimorbidity due to the COVID-19 emergency and demonstrate dramatic changes in cancer services. To better inform prioritization of cancer care and guide policy change, there is an urgent need for weekly data on cause-specific excess mortality, cancer diagnosis and treatment provision and better intelligence on the use of effective treatments for comorbidities. 2020-06-01
Isobel Braithwaite; Tom Callender; Miriam Bullock; Robert W Aldridge Automated and partially-automated contact tracing: a rapid systematic review to inform the control of COVID-19 Background Automated or partially-automated contact tracing tools are being deployed by many countries to contain SARS-CoV-2; however, the evidence base for their use is not well-established. Methods We undertook a rapid systematic review of automated or partially-automated contact tracing, registered with PROSPERO (CRD42020179822). We searched PubMed, EMBASE, OVID Global Health, EBSCO COVID Portal, Cochrane Library, medRxiv, bioRxiv, arXiv and Google Advanced for articles relevant to COVID-19, SARS, MERS, influenza or Ebola from 1/1/2000-14/4/2020. Two authors reviewed all full-text manuscripts. One reviewer extracted data using a pre-piloted form; a second independently verified extracted data. Primary outcomes were the number or proportion of contacts (and/or subsequent cases) identified; secondary outcomes were indicators of outbreak control, app/tool uptake, resource use, cost-effectiveness and lessons learnt. The Effective Public Health Practice Project tool or CHEERS checklist were used in quality assessment. Findings 4,033 citations were identified and 15 were included. No empirical evidence of automated contact tracing's effectiveness (regarding contacts identified or transmission reduction) was identified. Four of seven included modelling studies suggested that controlling COVID-19 requires high population uptake of automated contact-tracing apps (estimates from 56% to 95%), typically alongside other control measures. Studies of partially-automated contact tracing generally reported more complete contact identification and follow-up, and greater intervention timeliness (0.5-5 hours faster), than previous systems. No meta-analyses were possible. Interpretation Automated contact tracing has potential to reduce transmission with sufficient population uptake and usage. However, there is an urgent need for well-designed prospective evaluations as no studies provided empirical evidence of its effectiveness. 2020-05-28
Karla A Lee; Weinjie Ma; Daniel R Sikavi; Jonathon Wolf; Claire J Steves; Tim D Spector; Andrew T Chan Cancer and risk of COVID-19 through a general community survey Background: Data are limited on the risk of coronavirus disease 2019 (COVID-19) among individuals with cancer and whether cancer-related therapy exacerbates this risk. Methods: We evaluated the risk for coronavirus disease 2019 (COVID-19) among patients living with cancer compared to the general community and whether cancer-related treatments influence this risk. Data were collected from the COVID Symptom Study smartphone application since March 24, 2020 (United Kingdom), March 29 (U.S.), and April 29, 2020 (Sweden) through May 8, 2020. We used multivariate-adjusted odds ratios (aORs) of a positive COVID-19 test as well as predicted COVID-19 infection using a validated symptom model. Results: Among 23,266 participants with cancer and 1,784,293 without cancer, we documented 10,404 reports of a positive COVID-19 test. Compared to participants without cancer, those living with cancer had 62% increased risk of a positive COVID-19 test (95% CI: 1.37-1.91). Among patients with cancer, current treatment with chemotherapy/immunotherapy was associated with a nearly 2.5-fold increased risk of a positive test (aOR: 2.42; 95% CI: 1.81-3.25). The association between cancer and COVID-19+ was stronger among participants >65 years (aOR: 1.93; 95%CI: 1.51-2.46) compared to younger participants (aOR: 1.32; 95%CI: 1.06-1.64; Pinteraction<0.001); and among males (aOR: 1.71; 95%CI: 1.36-2.15) compared to females (aOR: 1.43; 95%CI: 1.14-1.79; Pinteraction=0.02). Conclusions: Individuals with cancer had a significantly increased risk of infection compared to the general community. Those treated with chemotherapy or immunotherapy were particularly at-risk of infection. Trial Registration: ClinicalTrials.gov NCT04331509 2020-05-26
Neil SN Graham; Cornelia Junghans; Rawlda Downes; Catherine Sendall; Helen Lai; Annie McKirdy; Paul Elliott; Robert Howard; David Wingfield; Miles Priestman; Marta Ciechonska; Loren Cameron; Marko Storch; Michael Crone; Paul Freemont; Paul Randell; Robert McLaren; Nicola Lang; Shamez Ladhani; Frances Sanderson; David J Sharp SARS-CoV-2 infection, clinical features and outcome of COVID-19 in United Kingdom nursing homes Objectives: To understand SARS-Co-V-2 infection and transmission in UK nursing homes in order to develop preventive strategies for protecting the frail elderly residents. Design: An outbreak investigation. Setting: 4 nursing homes affected by COVID-19 outbreaks in central London. Participants: 394 residents and 70 staff in nursing homes. Interventions: Two point-prevalence surveys one week apart where residents underwent SARS-CoV-2 testing and had relevant symptoms documented. Asymptomatic staff from three of the four homes were also offered SARS-CoV-2 testing. Main outcome measures: All-cause mortality, and mortality attributed to COVID-19 on death certificates. Prevalence of SARS-CoV-2 infection and symptoms in residents and staff. Results: Overall, 26% (95% confidence interval 22 to 31) of residents died over the two-month period. All-cause mortality increased by 203% (95% CI 70 to 336). Systematic testing identified 40% (95% CI 35 to 46) of residents, of whom 43% (95% CI 34 to 52) were asymptomatic and 18% (95% CI 11 to 24) had atypical symptoms, as well as 4% (95% CI -1 to 9) of asymptomatic staff who tested positive for SARS-CoV-2. Conclusions: The SARS-CoV-2 outbreak was associated with a very high mortality rate in residents of nursing homes. Systematic testing of all residents and a representative sample of staff identified high rates of SARS-CoV-2 positivity across the four nursing homes, highlighting a potential for regular screening to prevent future outbreaks. 2020-05-26
Xiao Jiang; James M. Eales; David Scannali; Alicja Nazgiewicz; Priscilla Prestes; Michelle Maier; Matthew J. Denniff; Xiaoguang Xu; Sushant Saluja; Eddie Cano-Gamez; Wojciech Wystrychowski; Monika Szulinska; Andrzej Antczak; Sean Byars; Maciej Glyda; Robert Krol; Joanna Zywiec; Ewa Zukowska-Szczechowska; Louise M. Burrell; Adrian S. Woolf; Adam Greenstein; Pawel Bogdanski; Bernard Keavney; Andrew P. Morris; Anthony Heagerty; Bryan Williams; Stephen B. Harrap; Gosia Trynka; Nilesh J. Samani; Tomasz J. Guzik; Fadi J. Charchar; Maciej Tomaszewski Hypertension and renin-angiotensin system blockers are not associated with expression of Angiotensin Converting Enzyme 2 (ACE2) in the kidney Angiotensin converting enzyme 2 (ACE2) is the cellular entry point for severe acute respiratory syndrome coronavirus (SARS-CoV-2) - the cause of COVID-19 disease. It has been hypothesized that use of renin-angiotensin system (RAS) inhibiting medications in patients with hypertension, increases the expression of ACE2 and thereby increases the risk of COVID-19 infection and severe outcomes or death. However, the effect of RAS-inhibition on ACE2 expression in human tissues of key relevance to blood pressure regulation and COVID-19 infection has not previously been reported. We examined how hypertension, its major metabolic co-phenotypes and antihypertensive medications relate to ACE2 renal expression using information from up to 436 patients whose kidney transcriptomes were characterised by RNA-sequencing. We further validated some of the key observations in other human tissues and/or a controlled experimental model. Our data reveal increasing expression of ACE2 with age in both human lungs and the kidney. We show no association between renal expression of ACE2 and either hypertension or common types of RAS inhibiting drugs. We demonstrate that renal abundance of ACE2 is positively associated with a biochemical index of kidney function and show a strong enrichment for genes responsible for kidney health and disease in ACE2 co-expression analysis. Collectively, our data indicate that neither hypertension nor antihypertensive treatment are likely to alter individual risk of SARS-CoV-2 infection or influence clinical outcomes in COVID-19 through changes of ACE2 expression. Our data further suggest that in the absence of SARS-CoV-2 infection, kidney ACE2 is most likely nephro-protective but the age-related increase in its expression within lungs and kidneys may be relevant to the risk of SARS-CoV-2 infection. 2020-05-26
Priscilla Mathewson; Ben Gordon; Kay Snowley; Clara Fennessy; Alastair Denniston; Neil Sebire Study Data Element Mapping: Feasibility of Defining Common Data Elements Across COVID-19 Studies Background: Numerous clinical studies are now underway investigating aspects of COVID-19. The aim of this study was to identify a selection of national and/or multicentre clinical COVID-19 studies in the United Kingdom to examine the feasibility and outcomes of documenting the most frequent data elements common across studies to rapidly inform future study design and demonstrate proof-of-concept for further subject-specific study data element mapping to improve research data management. Methods: 25 COVID-19 studies were included. For each, information regarding the specific data elements being collected was recorded. Data elements collated were arbitrarily divided into categories for ease of visualisation. Elements which were most frequently and consistently recorded across studies are presented in relation to their relative commonality. Results: Across the 25 studies, 261 data elements were recorded in total. The most frequently recorded 100 data elements were identified across all studies and are presented with relative frequencies. Categories with the largest numbers of common elements included demographics, admission criteria, medical history and investigations. Mortality and need for specific respiratory support were the most common outcome measures, but with specific studies including a range of other outcome measures. Conclusion: The findings of this study have demonstrated that it is feasible to collate specific data elements recorded across a range of studies investigating a specific clinical condition in order to identify those elements which are most common among studies. These data may be of value for those establishing new studies and to allow researchers to rapidly identify studies collecting data of potential use hence minimising duplication and increasing data re-use and interoperability 2020-05-26
Vasilis Kontis; James E Bennett; Robbie M Parks; Theo Rashid; Jonathan Pearson-Stuttard; Perviz Asaria; Michel Guillot; Marta Blangiardo; Majid Ezzati Age- and sex-specific total mortality impacts of the early weeks of the Covid-19 pandemic in England and Wales: Application of a Bayesian model ensemble to mortality statistics Background: The Covid-19 pandemic affects mortality directly through infection as well as through changes in the social, environmental and healthcare determinants of health. The impacts on mortality are likely to vary, in both magnitude and timing, by age and sex. Our aim was to estimate the total mortality impacts of the pandemic, by sex, age group and week. Methods: We developed an ensemble of 16 Bayesian models that probabilistically estimate the weekly number of deaths that would be expected had the Covid-19 pandemic not occurred. The models account for seasonality of death rates, medium-long-term trends in death rates, the impact of temperature on death rates, association of death rates in each week on those in preceding week(s), and the impact of bank holidays. We used data from January 2010 through mid-February 2020 (i.e., week starting 15th February 2020) to estimate the parameters of each model, which was then used to predict the number of deaths for subsequent weeks as estimates of death rates if the pandemic had not occurred. We subtracted these estimates from the actual reported number of deaths to measure the total mortality impact of the pandemic. Results: In the week that began on 21st March, the same week that a national lockdown was put in place, there was a >92% probability that there were more deaths in men and women aged [&ge;]45 years than would occur in the absence of the pandemic; the probability was 100% from the subsequent week. Taken over the entire period from mid-February to 8th May 2020, there were an estimated [~] 49,200 (44,700-53,300) or 43% (37-48) more deaths than would be expected had the pandemic not taken place. 22,900 (19,300-26,100) of these deaths were in females (40% (32-48) higher than if there had not been a pandemic), and 26,300 (23,800-28,700) in males (46% (40-52) higher). The largest number of excess deaths occurred among women aged >85 years (12,400; 9,300-15,300), followed by men aged >85 years (9,600; 7,800-11,300) and 75-84 years (9,000; 7,500-10,300). The cause of death assigned to the majority (37,295) of these excess deaths was Covid-19. There was nonetheless a >99.99% probability that there has been an increase in deaths assigned to other causes in those aged [&ge;]45 years. However, by the 8th of May, the all-cause excess mortality had become virtually equal to deaths assigned to Covid-19, and non-Covid excess deaths had diminished to close to zero, or possibly become negative, in all age-sex groups. Interpretation: The death toll of Covid-19 pandemic, in middle and older ages, is substantially larger than the number of deaths reported as a result of confirmed infection, and was visible in vital statistics when the national lockdown was put in place. When all-cause mortality is considered, the mortality impact of the pandemic on men and women is more similar than when comparing deaths assigned to Covid-19 as underlying cause of death. 2020-05-25
Richard Issitt; John Booth; William Bryant; Anastasia Spiridou; Andrew Taylor; Pascale DuPre; Padmanabhan Ramnarayan; John Hartley; Mario Cortino Borja; Karyn Moshal; Helen Dunn; Harry Hemingway; Neil Sebire Coronavirus (COVID-19) infection in children at a specialist centre: outcome and implications of underlying high-risk comorbidities in a paediatric population Background: There is evolving evidence of significant differences in severity and outcomes of coronavirus disease 2019 (COVID-19) in children compared to adults. Underlying medical conditions associated with increased risk of severe disease are based on adult data, but have been applied across all ages resulting in large numbers of families undertaking social shielding (vulnerable group). We conducted a retrospective analysis of children with suspected COVID-19 at a Specialist Childrens Hospital to determine outcomes based on COVID-19 testing status and underlying health vulnerabilities. Methods: Routine clinical data were extracted retrospectively from the Institutions Electronic Health Record system and Digital Research Environment for patients with suspected and confirmed COVID-19 diagnoses. Data were compared between Sars-CoV-2 positive and negative patients (CoVPos / CoVNeg respectively), and in relation to presence of underlying health vulnerabilities based on Public Health England guidance. Findings: Between 1st March and 15th May 2020, 166 children (<18 years of age) presented to a specialist childrens hospital with clinical features of possible COVID-19 infection. 65 patients (39.2%) tested positive for SARS-CoV-2 virus. CoVPos patients were older (median 9 [0.9-14] years vs median 1 [0.1-5.7.5] years respectively, p<0.001). There was a significantly reduced proportion of vulnerable cases (47.7% vs 72.3%, p=0.002), but no difference in proportion of vulnerable patients requiring ventilation (61% vs 64.3%, p = 0.84) between CoVPos and CoVNeg groups. However, a significantly lower proportion of CoVPos patients required mechanical ventilation support compared to CoVNeg patients (27.7 vs 57.4%, p<0.001). Mortality was not significantly different between CoVPos and CoVNeg groups (1.5 vs 4% respectively, p=0.67) although there were no direct COVID-19 related deaths in this highly preselected paediatric population. Interpretation: COVID-19 infection may be associated with severe disease in childhood presenting to a specialist hospital, but does not appear significantly different in severity to other causes of similar clinical presentations. In children presenting with pre-existing COVID-19 vulnerable medical conditions at a specialist centre, there does not appear to be significantly increased risk of either contracting COVID-19 or severe complications, apart from those undergoing chemotherapy, who are over-represented. 2020-05-25
Russell M Viner; Oliver T Mytton; Chris Bonell; G.J. Melendez-Torres; Joseph L Ward; Lee Hudson; Claire Waddington; James Thomas; Simon Russell; Fiona van der Klis; Jasmina Panovska-Griffiths; Nicholas G Davies; Robert Booy; Rosalind Eggo Susceptibility to and transmission of COVID-19 amongst children and adolescents compared with adults: a systematic review and meta-analysis Background The degree to which children and young people are infected by and transmit the SARS-CoV-2 virus is unclear. Clinical series and testing cohorts based upon screening of symptomatic cases provide biased estimates of susceptibility in children. The role of children and young people in transmission of SARS-CoV-2 is dependent on susceptibility, symptoms, viral load, social contact patterns and behaviour. Methods We undertook a rapid systematic review of contact-tracing studies and population-screening studies to address the question What is the susceptibility to and transmission of SARS-CoV-2 by children and adolescents compared with adults? We searched PubMed and medRxiv on 16 May 2020 and identified 6327 studies, with additional studies identified through handsearching of cited references (2) and professional contacts (4). We assessed quality, summarized findings and undertook a random effects meta-analysis of contact-tracing studies. Results 18 studies met inclusion criteria; 9 contact-tracing, 8 population-screening and 1 systematic-review. Meta-analysis of contact tracing studies showed that the pooled odds ratio of being an infected contact in children compared with adults for all contact tracing studies was 0.44 (0.29, 0.69) with substantial heterogeneity (63%). Findings from a systematic review of household clusters of COVID-19 found 3/31 (10%) were due to a child index case and a population-based school contact tracing study found minimal transmission by child or teacher index cases. Findings from population-screening studies were heterogenous and not suitable for meta-analysis. Large studies from Iceland, the Netherlands and Spain and an Italian municipal study showed markedly lower SARS-CoV-2 prevalence amongst children and young people, however studies from Stockholm, England and municipalities in Switzerland and Germany showed showed no difference in infection prevalence between adults and children. Conclusions There is preliminary evidence that children and young people have lower susceptibility to SARS-CoV-2, with a 56% lower odds of being an infected contact. There is weak evidence that children and young people play a lesser role in transmission of SARS-CoV-2 at a population level. Our study provides no information on the infectivity of children. 2020-05-24
Miriam Mutambudzi; Claire L Niedzwiedz; Ewan B Macdonald; Alastair H Leyland; Frances S Mair; Jana J Anderson; Carlos A Celis-Morales; John Cleland; John Forbes; Jason MR Gill; Claire Hastie; Frederick K Ho; Bhautesh D Jani; Daniel F Mackay; Barbara I Nicholl; Naveed I Sattar; Paul I Welsh; Jill P Pell; Srinivasa Vittal Katikireddi; Evangelia Demou Occupation and risk of COVID-19: prospective cohort study of 120,621 UK Biobank participants Objectives: To investigate COVID-19 risk by occupational group. Design: Prospective study of linked population-based and administrative data. Setting: UK Biobank data linked to SARS-CoV-2 test results from Public Health England from 16 March to 3 May 2020. Participants: 120,621 UK Biobank participants who were employed or self-employed at baseline (2006-2010) and were 65 years or younger in March 2020. Overall, 29% (n=37,890) were employed in essential occupational groups, which included healthcare workers, social and education workers, and other essential workers comprising of police and protective service, food, and transport workers. Poisson regression models, adjusted for baseline sociodemographic, work-related, health, and lifestyle-related risk factors were used to assess risk ratios (RRs) of testing positive in hospital by occupational group as reported at baseline relative to non-essential workers. Main outcome measures: Positive SARS-CoV-2 test within a hospital setting (i.e. as an inpatient or in an Emergency Department). Results: 817 participants were tested for SARS-CoV-2 and of these, 206 (0.2%) individuals had a positive test in a hospital setting. Relative to non-essential workers, healthcare workers (RR 7.59, 95% CI: 5.43 to 10.62) and social and education workers (RR 2.17, 95% CI: 1.37 to 3.46) had a higher risk of testing positive for SARS-CoV-2 in hospital. Using more detailed groupings, medical support staff (RR 8.57, 95% CI: 4.35 to 16.87) and social care workers (RR 2.99, 95% CI: 1.71 to 5.24) had highest risk within the healthcare worker and social and education worker categories, respectively. In general, adjustment for covariates did not substantially change the pattern of occupational differences in risk. Conclusions: Essential workers in health and social care have a higher risk of severe SARS-CoV-2 infection. These findings underscore the need for national and organisational policies and practices that protect and support workers with elevated risk of SARS-CoV-2 infection. 2020-05-23
Sarah Beale; Andrew Hayward; Laura Shallcross; Robert W Aldridge; Ellen Fragaszy A Rapid Review of the Asymptomatic Proportion of PCR-Confirmed SARS-CoV-2 Infections in Community Settings Background: Up to 80% of active SARS-CoV-2 infections are proposed to be asymptomatic based on cross-sectional studies. However, accurate estimates of the asymptomatic proportion require systematic detection and follow-up to differentiate between truly asymptomatic and pre-symptomatic cases. We conducted a rapid review and meta-analysis of current evidence regarding the asymptomatic proportion of PCR-confirmed SARS-CoV-2 infections based on methodologically-appropriate studies in community settings. Methods: We searched Medline and EMBASE for peer-reviewed articles, and BioRxiv and MedRxiv for pre-prints published prior to 05/05/2020. We included studies based in community settings that involved systematic PCR testing on participants and follow-up symptom monitoring regardless of symptom status. We extracted data on study characteristics, frequencies of PCR-confirmed infections by symptom status, and (if available) cycle threshold values and/or duration of viral shedding by symptom status. We computed estimates of the asymptomatic proportion and 95% confidence intervals for each study and overall using random effect meta-analysis. Findings: We screened 270 studies and included 6. The pooled estimate for the asymptomatic proportion of SARS-CoV-2 infections was 11% (95% CI 4%-18%). Estimates of baseline viral load appeared to be similar for asymptomatic and symptomatic cases based on available data in three studies, though detailed reporting of cycle threshold values and natural history of viral shedding by symptom status was limited. Interpretation: The asymptomatic proportion of SARS-CoV-2 infections is relatively low when estimated from methodologically-appropriate studies. Further investigation into the degree and duration of infectiousness for asymptomatic infections is warranted. Funding: Medical Research Council 2020-05-23
Nicola L Boddington; Andre Charlett; Suzanne Elgohari; Jemma L Walker; Helen Mcdonald; Chloe Byers; Laura Coughlan; Tatiana Garcia Vilaplana; Rosie Whillock; Mary Sinnathamby; Nikolaos Panagiotopoulos; Louise Letley; Pauline MacDonald; Roberto Vivancos; Obaghe Edeghere; Joseph Shingleton; Emma Bennett; Daniel J Grint; Helen Strongman; Kathryn E Mansfield; Christopher Rentsch; Caroline Minassian; Ian J Douglas; Rohini Mathur; Maria Peppa; Simon Cottrell; Jim McMenamin; Maria Zambon; Mary Ramsay; Gavin Dabrera; Vanessa Saliba; Jamie Lopez Bernal COVID-19 in Great Britain: epidemiological and clinical characteristics of the first few hundred (FF100) cases: a descriptive case series and case control analysis Objectives: Following detection of the first virologically-confirmed cases of COVID-19 in Great Britain, an enhanced surveillance study was initiated by Public Health England to describe the clinical presentation, course of disease and identify risk factors for infection of the first few hundred cases. Methods: Information was collected on the first COVID-19 cases according to the First Few X WHO protocol. Case-control analyses of the sensitivity, specificity and predictive value of symptoms and risk factors for infection were conducted. Point prevalences of underlying health conditions among the UK general population were presented. Findings: The majority of FF100 cases were imported (51.4%), of which the majority had recent travel to Italy (71.4%). 24.7% were secondary cases acquired mainly through household contact (40.4%). Children had lower odds of COVID-19 infection compared with the general population. The clinical presentation of cases was dominated by cough, fever and fatigue. Non-linear relationships with age were observed for fever, and sensitivity and specificity of symptoms varied by age. Conditions associated with higher odds of COVID-19 infection (after adjusting for age and sex) were chronic heart disease, immunosuppression and multimorbidity. Conclusion: This study presents the first epidemiological and clinical summary of COVID-19 cases in Great Britain. The FFX study design enabled systematic data collection. The study was able to characterize the risk factors for infection with population prevalence estimates setting these relative risks into a public health context. It also provides important evidence for generating case definitions to support public health risk assessment, clinical triage and diagnostic algorithms. 2020-05-22
Nicholas S Hopkinson; Niccolo Rossi; Julia El-Sayed Moustafa; Anthony A Laverty; Jennifer K Quint; Maxim B Freydin; Alessia Visconti; Benjamin Murray; Marc Modat; Sebastien Ourselin; Kerrin Small; Richard Davies; Jonathan Wolf; Timothy Spector; Claire J Steves; Mario Falchi Current tobacco smoking and risk from COVID-19: results from a population symptom app in over 2.4 million people Background: The association between current tobacco smoking, the risk of developing COVID-19 and the severity of illness is an important information gap. Methods: UK users of the COVID Symptom Study app provided baseline data including demographics, anthropometrics, smoking status and medical conditions, were asked to log symptoms daily from 24th March 2020 to 23rd April 2020. Participants reporting that they did not feel physically normal were taken through a series of questions, including 14 potential COVID-19 symptoms and any hospital attendance. The main study outcome was the association between current smoking and the development of classic symptoms of COVID-19 during the pandemic defined as fever, new persistent cough and breathlessness. The number of concurrent COVID-19 symptoms was used as a proxy for severity. In addition, association of subcutaneous adipose tissue expression of ACE2, both the receptor for SARS-CoV-2 and a potential mediator of disease severity, with smoking status was assessed in a subset of 541 twins from the TwinsUK cohort. Results: Data were available on 2,401,982 participants, mean(SD) age 43.6(15.1) years, 63.3% female, overall smoking prevalence 11.0%. 834,437 (35%) participants reported being unwell and entered one or more symptoms. Current smokers were more likely to develop symptoms suggesting a diagnosis of COVID-19; classic symptoms adjusted OR[95%CI] 1.14[1.10 to 1.18]; >5 symptoms 1.29[1.26 to 1.31]; >10 symptoms 1.50[1.42 to 1.58]. Smoking was associated with reduced ACE2 expression in adipose tissue (Beta(SE)= -0.395(0.149); p=7.01x10-3). Interpretation: These data are consistent with smokers having an increased risk from COVID-19. 2020-05-21
Claudio Fronterre; Jonathan M Read; Barry Rowlingson; Jessica Bridgen; Simon Alderton; Peter J Diggle; Chris P Jewell COVID-19 in England: spatial patterns and regional outbreaks Aims: to investigate the spatiotemporal distribution of COVID-19 cases in England; to provide spatial quantification of risk at a high resolution; to provide information for prospective antigen and serological testing. Approach: We fit a spatiotemporal Negative Binomial generalised linear model to Public Health England SARS-CoV-2 testing data at the Lower Tier Local Authority region level. We assume an order-1 autoregressive model for case progression within regions, coupling discrete spatial units via observed commuting data and time-varying measures of traffic flow. We fit the model via maximum likelihood estimation in order to calculate region-specific risk of ongoing transmission, as well as measuring regional uncertainty in incidence. Results: We detect marked heterogeneity across England in COVID-19 incidence, not only in raw estimated incidence, but in the characteristics of within-region and between-region dynamics of PHE testing data. There is evidence for a spatially diverse set of regions having a higher daily increase of cases than others, having accounted for current case numbers, population size, and human mobility. Uncertainty in model estimates is generally greater in rural regions. Conclusions: A wide range of spatial heterogeneity in COVID-19 epidemic distribution and infection rate exists in England currently. Future work should incorporate fine-scaled demographic and health covariates, with continued improvement in spatially-detailed case reporting data. The method described here may be used to measure heterogeneity in real-time as behavioural and social interventions are relaxed, serving to identify "hotspots" of resurgent cases occurring in diverse areas of the country, and triggering locally-intensive surveillance and interventions as needed. Caveats: There is general concern over the ability of PHE testing data to capture the true prevalence of infection within the population, though this approach is designed to provide measures of spatial prevalence based on testing that can be used to guide further future testing effort. Now-casts of epidemic characteristics are presented based on testing data alone (as opposed to "true" prevalence in any one area). The model used in this analysis is phenomenological for ease and speed of principled parameter inference; we choose the model which best fits the current spatial case timeseries, without attempting to enforce "SIR"-type epidemic dynamics. 2020-05-20
Hamish Gibbs; Yang Liu; Carl AB Pearson; Christopher I Jarvis; Chris Grundy; Billy J Quilty; Charlie Diamond; Rosalind M Eggo Changing travel patterns in China during the early stages of the COVID-19 pandemic Understanding changes in human mobility in the early stages of the COVID-19 pandemic is crucial for assessing the impacts of travel restrictions designed to reduce disease spread. Here, relying on data from mainland China, we investigated the spatio-temporal characteristics of human mobility between 1st January and 1st March 2020 and discussed their public health implications. An outbound travel surge from Wuhan before travel restrictions were implemented was also observed across China due to the Lunar New Year, indicating that holiday travel may have played a larger role in mobility changes compared to impending travel restrictions. Holiday travel also shifted healthcare pressure related to COVID-19 towards locations with lower access to care. Network analyses showed no sign of major changes in the transportation network after Lunar New Year. Changes observed were temporary and have not yet led to structural reorganisation of the transportation network at the time of this study. 2020-05-19
Vanesa Bellou; Ioanna Tzoulaki; Evangelos Evangelou; Lazaros Belbasis Risk factors for adverse clinical outcomes in patients with COVID-19: A systematic review and meta-analysis Importance: COVID-19 is a clinically heterogeneous disease of varying severity and prognosis. Clinical characteristics that impact disease course could offer guidance for clinical decision making and future research endeavors and unveil disease pathways. Objective: To examine risk factors associated with adverse clinical outcomes in patients with COVID-19. Data sources: We performed a systematic review in PubMed from January 1 until April 19, 2020. Study selection: Observational studies that examined the association of any clinical characteristic with an adverse clinical outcome were considered eligible. We scrutinized studies for potential overlap. Data extraction and synthesis: Information on the effect of clinical factors on clinical endpoints of patients with COVID-19 was independently extracted by two researchers. When an effect size was not reported, crude odds ratios were calculated based on the available information from the eligible articles. Study-specific effect sizes from non-overlapping studies were synthesized applying the random-effects model. Main outcome and measure: The examined outcomes were severity and progression of disease, admission to ICU, need for mechanical ventilation, mortality, or a composite outcome. Results: We identified 88 eligible articles, and we performed a total of 256 meta-analyses on the association of 98 unique risk factors with five clinical outcomes. Seven meta-analyses presented the strongest epidemiological evidence in terms of statistical significance (P-value <0.005), between-study heterogeneity (I2 <50%), sample size (more than 1000 COVID-19 patients), 95% prediction interval excluded the null value, and absence of small-study effects. Elevated C-reactive protein (OR, 6.46; 95% CI, 4.85 - 8.60), decreased lymphocyte count (OR, 4.16; 95% CI, 3.17 - 5.45), cerebrovascular disease (OR, 2.84; 95% CI, 1.55 - 5.20), chronic obstructive pulmonary disease (OR, 4.44; 95% CI, 2.46 - 8.02), diabetes mellitus (OR, 2.04; 95% CI, 1.54 - 2.70), hemoptysis (OR, 7.03; 95% CI, 4.57 - 10.81), and male sex (OR, 1.51; 95% CI, 1.30 - 1.75) were associated with risk of severe COVID-19. Conclusions and relevance: Our results highlight factors that could be useful for prognostic model building, help guide patients' selection for randomized clinical trials, as well as provide alternative treatment targets by shedding light to disease pathophysiology. 2020-05-19
Nina Trivedy Rogers; Naomi Waterlow; Hannah E Brindle; Luisa Enria; Rosalind M Eggo; Shelley Lees; Chrissy h Roberts Behavioural change towards reduced intensity physical activity is disproportionately prevalent among adults with serious health issues or self-perception of high risk during the UK COVID-19 lockdown. Importance: There are growing concerns that the UK COVID-19 lockdown has reduced opportunities to maintain health through physical activity, placing individuals at higher risk of chronic disease and leaving them more vulnerable to severe sequelae of COVID-19. Objective: To examine whether the UK's lockdown measures have had disproportionate impacts on intensity of physical activity in groups who are, or who perceive themselves to be, at heightened risk from COVID-19. Designs, Setting, Participants: UK-wide survey of adults aged over 20, data collected between 2020-04-06 and 2020-04-22. Exposures: Self-reported doctor-diagnosed obesity, hypertension, type I/II diabetes, lung disease, cancer, stroke, heart disease. Self-reported disabilities and depression. Sex, gender, educational qualifications, household income, caring for school-age children. Narrative data on coping strategies. Main Outcomes and Measures: Change in physical activity intensity after implementation of UK COVID-19 lockdown (self-reported). Results: Most (60%) participants achieved the same level of intensity of physical activity during the lockdown as before the epidemic. Doing less intensive physical activity during the lockdown was associated with obesity (OR 1.21, 95% CI 1.02-1.41), hypertension (OR 1.52, 1.33-1.71), lung disease (OR 1.31,1.13-1.49), depression (OR 2.02, 1.82-2.22) and disability (OR 2.34, 1.99-2.69). Participants who reduced their physical activity intensity also had higher odds of being female, living alone or having no garden, and more commonly expressed sentiments about personal or household risks in narratives on coping. Conclusions and relevance: Groups who reduced physical activity intensity included disproportionate numbers of people with either heightened objective clinical risks or greater tendency to express subjective perceptions of risk. Policy on exercise for health during lockdowns should include strategies to facilitate health promoting levels of physical activity in vulnerable groups, including those with both objective and subjective risks. 2020-05-18
Niloofar Shoari; Majid Ezzati; Jill Baumgartner; Diego Malacarne; Daniela Fecht Accessibility and allocation of public parks and gardens during COVID-19 social distancing in England and Wales Visiting parks and gardens may attenuate the adverse physical and mental health impacts of social distancing implemented to reduce the spread of COVID-19. We quantified access to public parks and gardens in urban areas of England and Wales, and the potential for park crowdedness during periods of high use. We combined data from the Office for National Statistics and Ordnance Survey to quantified (i) the number of parks within 500 and 1,000 metres of urban postcodes (i.e., availability), (ii) the distance of postcodes to the nearest park (i.e., accessibility), and (iii) per-capita space in each park for people living within 1,000m. We examined variability by city and share of flats. Around 25.4 million people can access public parks or gardens within a ten-minute walk, while 3.8 million residents live farther away; of these 21% are children and 13% are elderly. Areas with a higher share of flats on average are closer to a park but people living in these areas are potentially less able to meet social distancing requirements while in parks during periods of high use. Cities in England and Wales can provide residents with access to green space that enables outdoor exercise and play during social distancing. Keeping public parks and gardens open, might require measures such as dedicated park times for different age groups or entry allocation systems that, combined with smartphone apps or drones, can monitor and manage the total number of people using the park. 2020-05-18
Elisa Gremese; Antonella Cingolani; Silvia Laura Bosello; Stefano Alivernini; Barbara Tolusso; Simone Perniola; Francesco Landi; Maurizio Pompili; Rita Murri; Angelo Santoliquido; Matteo Garcovich; Michela Sali; Gennaro De Pascale; Maurizio Gabrielli; Federico Biscetti; Massimo Montalto; Alberto Tosoni; Giovanni Gambassi; Gian Ludovico Rapaccini; Amerigo Iaconelli; Lorenzo Zileri Dal Verme; Luca Petricca; Anna Laura Fedele; Marco Maria Lizzio; Enrica Tamburrini; Gerlando Natalello; Laura Gigante; Dario Bruno; Lucrezia Verardi; Manuela Taddeo; Angelo Calabrese; Francesco Lombardi; Roberto Bernabei; Roberto Cauda; Francesco Franceschi; Raffaele Landolfi; Luca Richeldi; Maurizio Sanguinetti; Massimo Fantoni; Massimo Antonelli; Antonio Gasbarrini Sarilumab use in severe SARS-CoV-2 pneumonia Importance: Interleukin-6 signal blockade has shown preliminary beneficial effects in treating aberrant host inflammatory response against SARS-CoV-2 leading to severe respiratory distress. Objective: to describe the effect of off-label intravenous use of Sarilumab in patients with severe SARS-CoV-2-related pneumonia. Design: Observational clinical cohort study. Setting: Fondazione Policlinico Universitario A. Gemelli IRCCS as Italian Covid reference center. Participants: Patients with laboratory-confirmed SARS-CoV-2 infection and respiratory distress with PaO2/FiO2 ratio<300 treated with Sarilumab between March 23rd - April 4th, 2020. Date of final follow-up was April 18, 2020. Main outcomes and measures: We describe the clinical outcomes of 53 patients with SARS-CoV-2 severe pneumonia treated with intravenous Sarilumab in terms of pulmonary function improvement or Intensive Care Unit (ICU) admission rate in medical wards setting and of live discharge rate in ICU treated patients as well as in terms of safety. Each patient received Sarilumab 400 mg administered intravenously on day 1, with eventual additional infusion based on clinical judgement, and was followed for at least 14 days, unless previously discharged or dead. No gluco-corticosteroids were used at baseline. Results: Of the 53 SARS-CoV-2pos patients receiving Sarilumab, 39 (73.6%) were treated in medical wards (66.7% with a single infusion) while 14 (26.4%) in ICU (92.6% with a second infusion). The median PaO2/FiO2 of patients in the Medical Ward was 146(IQR:120-212) while the median PaO2/FiO2 of patients in ICU was 112(IQR:100-141.5), respectively. Within the medical wards, 7(17.9%) required ICU admission, 4 of whom were re-admitted to the ward within 5-8 days. At 19 days median follow-up, 89.7% of medical inpatients significantly improved (46.1% after 24 hours, 61.5% after 3 days), 70.6% were discharged from the hospital and 85.7% no longer needed oxygen therapy. Within patients receiving Sarilumab in ICU, 64.2% were discharged from ICU to the ward and 35.8% were still alive at the last follow-up. Overall mortality rate was 5.7% after Sarilumab administration: 1(2.5%) patient died in the Medical Ward whilst 2(14.2%) patients died in ICU, respectively. Conclusions and relevance: IL6-R inhibition appears to be a potential treatment strategy for severe SARS-CoV-2 pneumonia and intravenous Sarilumab seems a promising treatment approach showing, in the short term, an important clinical benefit and good safety. 2020-05-18
Zahra Raisi-Estabragh; Celeste McCracken; Maddalena Ardissino; Mae S Bethell; Jackie Cooper; Cyrus Cooper; Nicholas C Harvey; Steffen E Petersen NON-WHITE ETHNICITY, MALE SEX, AND HIGHER BODY MASS INDEX, BUT NOT MEDICATIONS ACTING ON THE RENIN-ANGIOTENSIN SYSTEM ARE ASSOCIATED WITH CORONAVIRUS DISEASE 2019 (COVID-19) HOSPITALISATION: REVIEW OF THE FIRST 669 CASES FROM THE UK BIOBANK Background: Cardiometabolic morbidity and medications, specifically Angiotensin Converting Enzyme inhibitors (ACEi) and Angiotensin Receptor Blockers (ARBs), have been linked with adverse outcomes from coronavirus disease 2019 (COVID-19). This study aims to investigate factors associated with COVID-19 positivity for the first 669 UK Biobank participants; compared with individuals who tested negative, and with the untested, presumed negative, rest of the population. Methods: We studied 1,474 participants from the UK Biobank who had been tested for COVID-19. Given UK testing policy, this implies a hospital setting, suggesting at least moderate to severe symptoms. We considered the following exposures: age, sex, ethnicity, body mass index (BMI), diabetes, hypertension, hypercholesterolaemia, ACEi/ARB use, prior myocardial infarction (MI), and smoking. We undertook comparisons between: 1) COVID-19 positive and COVID-19 tested negative participants; and 2) COVID-19 tested positive and the remaining participants (tested negative plus untested, n=501,837). Logistic regression models were used to investigate univariate and mutually adjusted associations. Results: Among participants tested for COVID-19, non-white ethnicity, male sex, and greater BMI were independently associated with COVID-19 positive result. Non-white ethnicity, male sex, greater BMI, diabetes, hypertension, prior MI, and smoking were independently associated with COVID-19 positivity compared to the remining cohort (test negatives plus untested). However, similar associations were observed when comparing those who tested negative for COVID-19 with the untested cohort; suggesting that these factors associate with general hospitalisation rather than specifically with COVID-19. Conclusions: Among participants tested for COVID-19 with presumed moderate to severe symptoms in a hospital setting, non-white ethnicity, male sex, and higher BMI are associated with a positive result. Other cardiometabolic morbidities confer increased risk of hospitalisation, without specificity for COVID-19. Notably, ACE/ARB use did not associate with COVID-19 status. 2020-05-15
Anton De Spiegeleer; Antoon Bronselaer; James T Teo; Geert Byttebier; Guy De Tre; Luc Belmans; Richard Dobson; Evelien Wynendaele; Christophe Van De Wiele; Filip Vandaele; Diemer Van Dijck; Daniel Bean; David Fedson; Bart De Spiegeleer The effects of ARBs, ACEIs and statins on clinical outcomes of COVID-19 infection among nursing home residents Background. COVID-19 infection has limited preventive or therapeutic drug options at this stage. Some of common existing drugs like angiotensin-converting enzyme inhibitors (ACEi), angiotensin II receptor blockers (ARB) and the HMG-CoA reductase inhibitors (statins) have been hypothesised to impact on disease severity. However, up till now, no studies investigating this association were conducted in the most vulnerable and affected population groups, i.e. older people residing in nursing homes. The purpose of this study has been to explore the association of ACEi/ARB and/or statins with clinical manifestations in COVID-19 infected older people residing in nursing homes. Methods and Findings. We undertook a retrospective multi-centre cohort study in two Belgian nursing homes that experienced similar COVID-19 outbreaks. COVID-19 diagnoses were based on clinical suspicion and/or viral presence using PCR of nasopharyngeal samples. A total of 154 COVID-19 positive subjects was identified. The outcomes were defined as 1) serious COVID-19 defined as a long-stay hospital admission (length of stay [&ge;] 7 days) or death (at hospital or nursing home) within 14 days of disease onset, and 2) asymptomatic, i.e. no disease symptoms in the whole study-period while still being PCR diagnosed. Disease symptoms were defined as any COVID-19-related clinical symptom (e.g. coughing, dyspnoea, sore throat) or sign (low oxygen saturation and fever) for [&ge;] 2 days out of 3 consecutive days. Logistic regression models with Firth corrections were applied on these 154 subjects to analyse the association between ACEi/ARB and/or statin use with the outcomes. Age, sex, functional status, diabetes and hypertension were used as covariates. Sensitivity analyses were conducted to evaluate the robustness of our statistical significant findings. We found a statistically significant association between statin intake and the absence of symptoms during COVID-19 infection (unadjusted OR 2.91; CI 1.27-6.71; p=0.011), which remained statistically significant after adjusting for age, sex, functional status, diabetes mellitus and hypertension. The strength of this association was considerable and clinically important. Although the effects of statin intake on serious clinical outcome (long-stay hospitalisation or death) were in the same beneficial direction, these were not statistically significant (OR 0.75; CI 0.25-1.85; p=0.556). There was also no statistically significant association between ACEi/ARB and asymptomatic status (OR 1.52; CI 0.62-3.50; p=0.339) or serious clinical outcome (OR 0.79; CI 0.26-1.95; p=0.629). Conclusions. Our data indicate that statin intake in old, frail people could be associated with a considerable beneficial effect on COVID-19 related clinical symptoms. The role of statins and any interaction with renin-angiotensin system drugs need to be further explored in larger observational studies as well as randomised clinical trials. 2020-05-15
Lucy Rivett; Sushmita Sridhar; Dominic Sparkes; Matthew Routledge; Nicholas K. Jones; Sally Forrest; Jamie Young; Joana Pereira-Dias; William L Hamilton; Mark Ferris; Estee Torok; Luke Meredith; The CITIID-NIHR COVI Bioresource Collaboration; Martin Curran; Stewart Fuller; Afzal Chaudhry; Ashley Shaw; Richard J. Samsworth; John R. Bradley; Gordon Dougan; Kenneth G. C. Smith; Paul J. Lehner; Nicholas J. Matheson; Giles Wright; Ian Goodfellow; Stephen Baker; Michael P. Weekes Screening of healthcare workers for SARS-CoV-2 highlights the role of asymptomatic carriage in COVID-19 transmission Significant differences exist in the availability of healthcare worker (HCW) SARS-CoV-2 testing between countries, and existing programmes focus on screening symptomatic rather than asymptomatic staff. Over a 3-week period (April 2020), 1,032 asymptomatic HCWs were screened for SARS-CoV-2 in a large UK teaching hospital. Symptomatic staff and symptomatic household contacts were additionally tested. Real-time RT-PCR was used to detect viral RNA from a throat+nose self-swab. 3% of HCWs in the asymptomatic screening group tested positive for SARS-CoV-2. 17/30 (57%) were truly asymptomatic/pauci-symptomatic. 12/30 (40%) had experienced symptoms compatible with coronavirus disease 2019 (COVID-19) >7 days prior to testing, most self-isolating, returning well. Clusters of HCW infection were discovered on two independent wards. Viral genome sequencing showed that the majority of HCWs had the dominant lineage B{middle dot}1. Our data demonstrates the utility of comprehensive screening of HCWs with minimal or no symptoms. This approach will be critical for protecting patients and hospital staff. 2020-05-15
Stephen N. Crooke; Inna G. Ovsyannikova; Richard B. Kennedy; Gregory A. Poland Immunoinformatic identification of B cell and T cell epitopes in the SARS-CoV-2 proteome A novel coronavirus (SARS-CoV-2) emerged from China in late 2019 and rapidly spread across the globe, infecting millions of people and generating societal disruption on a level not seen since the 1918 influenza pandemic. A safe and effective vaccine is desperately needed to prevent the continued spread of SARS-CoV-2; yet, rational vaccine design efforts are currently hampered by the lack of knowledge regarding viral epitopes targeted during an immune response, and the need for more in-depth knowledge on betacoronavirus immunology. To that end, we developed a computational workflow using a series of open-source algorithms and webtools to analyze the proteome of SARS-CoV-2 and identify putative T cell and B cell epitopes. Using increasingly stringent selection criteria to select peptides with significant HLA promiscuity and predicted antigenicity, we identified 41 potential T cell epitopes (5 HLA class I, 36 HLA class II) and 6 potential B cell epitopes, respectively. Docking analysis and binding predictions demonstrated enrichment for peptide binding to HLA-B (class I) and HLA-DRB1 (class II) molecules. Overlays of predicted B cell epitopes with the structure of the viral spike (S) glycoprotein revealed that 4 of 6 epitopes were located in the receptor-binding domain of the S protein. To our knowledge, this is the first study to comprehensively analyze all 10 (structural, non-structural and accessory) proteins from SARS-CoV-2 using predictive algorithms to identify potential targets for vaccine development. Significance StatementThe novel coronavirus SARS-CoV-2 recently emerged from China, rapidly spreading and ushering in a global pandemic. Despite intensive research efforts, our knowledge of SARS-CoV-2 immunology and the proteins targeted by the immune response remains relatively limited, making it difficult to rationally design candidate vaccines. We employed a suite of bioinformatic tools, computational algorithms, and structural modeling to comprehensively analyze the entire SARS-CoV-2 proteome for potential T cell and B cell epitopes. Utilizing a set of stringent selection criteria to filter peptide epitopes, we identified 41 T cell epitopes (5 HLA class I, 36 HLA class II) and 6 B cell epitopes that could serve as promising targets for peptide-based vaccine development against this emerging global pathogen. 2020-05-14
Luke W Meredith; William L Hamilton; Ben Warne; Charlotte J Houldcroft; Myra Hosmillo; Aminu Jahun; Martin D Curran; Surendra Parmar; Laura Caller; Sarah L Caddy; Fahad A Khokhar; Anna Yakovleva; Grant R Hall; Theresa Feltwell; Sally N Forret; Sushmita Sridhar; Michael p Weekes; Stephen Baker; Nicholas Brown; Elinor Moore; Theodore Gouliouris; Ashley Popay; Iain Roddick; Mark Reacher; Sharon Peacock; Gordon Dougan; M. Estee Torok; Ian Goodfellow Rapid implementation of real-time SARS-CoV-2 sequencing to investigate healthcare-associated COVID-19 infections Background The burden and impact of healthcare-associated COVID-19 infections is unknown. We aimed to examine the utility of rapid sequencing of SARS-CoV-2 combined with detailed epidemiological analysis to investigate healthcare-associated COVID-19 infections and to inform infection control measures. Methods We set up rapid viral sequencing of SARS-CoV-2 from PCR-positive diagnostic samples using nanopore sequencing, enabling sample-to-sequence in less than 24 hours. We established a rapid review and reporting system with integration of genomic and epidemiological data to investigate suspected cases of healthcare-associated COVID-19. Results Between 13 March and 24 April 2020 we collected clinical data and samples from 5191 COVID-19 patients in the East of England. We sequenced 1000 samples, producing 747 complete viral genomes. We conducted combined epidemiological and genomic analysis of 299 patients at our hospital and identified 26 genomic clusters involving 114 patients. 66 cases (57.9%) had a strong epidemiological link and 15 cases (13.2%) had a plausible epidemiological link. These results were fed back clinical, infection control and hospital management teams, resulting in infection control interventions and informing patient safety reporting. Conclusions We established real-time genomic surveillance of SARS-CoV-2 in a UK hospital and demonstrated the benefit of combined genomic and epidemiological analysis for the investigation of healthcare-associated COVID-19 infections. This approach enabled us to detect cryptic transmission events and identify opportunities to target infection control interventions to reduce further healthcare-associated infections. 2020-05-14
Daniel Ward; Matthew Higgins; Jody Phelan; Martin L. Hibberd; Susana Campino; Taane G Clark An integrated in silico immuno-genetic analytical platform provides insights into COVID-19 serological and vaccine targets BackgroundThe COVID-19 pandemic is causing a major global health and socio-economic burden, instigating the mobilisation of resources into the development of control tools, such as diagnostics and vaccines. The poor performance of some diagnostic serological tools has emphasised the need for up to date immune-informatic analyses to inform the selection of viable targets for further study. This requires the integration and analysis of genetic and immunological data for SARS-CoV-2 and its homology with other human coronavirus species to understand cross-reactivity. MethodsWe have developed an online tool for SARS-CoV-2 research, which combines an extensive epitope mapping and prediction meta-analysis, with an updated variant database (55,944 non-synonymous mutations) based on 16,087 whole genome sequences, and an analysis of human coronavirus homology. To demonstrate its utility, we present an integrated analysis of the SARS-CoV-2 spike and nucleocapsid proteins, which are candidate vaccine and serological diagnostic targets. ResultsOur analysis reveals that the nucleocapsid protein in its native form appears to be a sub-optimal target for use in serological diagnostic platforms. Whilst, a further analysis suggests that orf3a proteins may be a suitable alternative target for diagnostic assays. ConclusionsThe tool can be accessed online (http://genomics.lshtm.ac.uk/immuno) and will serve as a useful tool for biological discovery in the fight against SARS-CoV-2. Further, it may be adapted to inform on biological targets in future outbreaks, including new human coronaviruses that spill over from animal hosts. 2020-05-13
David Rubin; Jing Huang; Brian T Fisher; Antonio Gasparrini; Vicky Tam; Lihai Song; Xi Wang; Jason Kaufman; Kate Fitzpatrick; Arushi Jain; Heather Griffis; Koby Crammer; Gregory Tasian The Association of Social Distancing, Population Density, and Temperature with the SARS-CoV-2 Instantaneous Reproduction Number in Counties Across the United States Importance: The Covid-19 pandemic has been marked by considerable heterogeneity in outbreaks across the United States. Local factors that may be associated with variation in SARS-CoV-2 transmission have not been well studied. Objective: To examine the association of county-level factors with variation in the SARS-CoV-2 reproduction number over time. Design: Observational study Setting: 211 counties in 46 states and the District of Columbia between February 25, 2020 and April 23, 2020. Participants: Residents within the counties (55% of the US population) Exposures: Social distancing as measured by percent change in visits to non-essential businesses, population density, lagged daily wet bulb temperatures. Main Outcomes and Measures: The instantaneous reproduction number (Rt) which is the estimated number of cases generated by one case at a given time during the pandemic. Results: Median case incidence was 1185 cases and fatality rate was 43.7 deaths per 100,000 people for the top decile of 21 counties, nearly ten times the incidence and fatality rate in the lowest density quartile. Average Rt in the first two weeks was 5.7 (SD 2.5) in the top decile, compared to 3.1 (SD 1.2) in the lowest quartile. In multivariable analysis, a 50% decrease in visits to non-essential businesses was associated with a 57% decrease in Rt (95% confidence interval, 56% to 58%). Cumulative temperature effects over 4 to 10 days prior to case incidence were nonlinear; relative Rt decreased as temperatures warmed above 32F to 53F, which was the point of minimum Rt, then increased between 53F and 66F, at which point Rt began to decrease. At 55F, and with a 70% reduction in visits to non-essential business, 96% of counties were estimated to fall below a threshold Rt of 1.0, including 86% of counties among the top density decile and 98% of counties in the lowest density quartile. Conclusions and Relevance: Social distancing, lower population density, and temperate weather change were associated with a decreased SARS-Co-V-2 Rt in counties across the United States. These relationships can inform selective public policy planning in communities during the SARS-CoV-2 pandemic. 2020-05-12
Helen I McDonald; Elise Tessier; Joanne M White; Matthew Woodruff; Charlotte Knowles; Chris Bates; John Parry; Jemma L Walker; J Anthony Scott; Liam Smeeth; Joanne Yarwood; Mary Ramsay; Michael Edelstein Early impact of the COVID-19 pandemic and social distancing measures on routine childhood vaccinations in England, January to April 2020 Electronic health records were used to assess the early impact of COVID-19 on routine childhood vaccination in England to 26 April 2020. MMR vaccination counts fell from February 2020, and in the three weeks after introduction of social distancing measures were 19.8% lower (95% CI -20.7 to -18.9%) than the same period in 2019, before improving in mid-April. A gradual decline in hexavalent vaccination counts throughout 2020 was not accentuated on introduction of social distancing. 2020-05-11
Benjamin Parcell; Kathryn Brechin; Sarah Allstaff; Meg Park; Wendy Third; Susan Bean; Chris Hind; Rajiv Farmer; James D Chalmers Drive-through testing for SARS-CoV-2 in symptomatic health and social care workers and household members: an observational cohort study in Tayside, Scotland It has been recognised that health and social care workers (HSCW) experience higher rates of infection with SARS-CoV-2. Widespread testing of HSCWs and their symptomatic household contacts (SHCs) has not been fully implemented in the United Kingdom. We describe the results of a testing programme for HSCWs and SHCs in a single UK region (Tayside, Scotland). The testing service was established 17 th March 2020 as the first in the country, and samples were collected at a drive-through testing hub based at a local community hospital. HSCWs with mild symptoms who were self-isolating and the SHCs of HSCWs who would therefore be absent from work attended for testing. From 17 th March 2020 to 11 th April, 1887 HSCWs and SHCs underwent testing. Clinical information was available for 1727 HSCWs and SHCs. 4/155 (2.6%) child contacts, 73/374 (19.5%) adult contacts and 325/1173 (27.7%) HSCWs tested positive for SARS-CoV-2. 15 of 188 undetermined cases were positive (8.0%). We estimate that testing prevented up to 3634 lost work days from HSCW testing, 2795 from adult SHC testing and 1402 lost work days from child SHC testing. The establishment of this testing programme has assisted the infection prevention and control team in their investigation of transmission and supported adequate staffing in health and social care sectors. 2020-05-11
Jon C Emery; Timothy W Russel; Yang Liu; Joel Hellewell; Carl AB Pearson; - CMMID 2019-nCoV working group; Gwen M Knight; Rosalind M Eggo; Adam J Kucharski; Sebastian Funk; Stefan Flasche; Rein M G J Houben The contribution of asymptomatic SARS-CoV-2 infections to transmission - a model-based analysis of the Diamond Princess outbreak Background: Some key gaps in the understanding of SARS-CoV-2 infection remain. One of them is the contribution to transmission from individuals experiencing asymptomatic infections. We aimed to characterise the proportion and infectiousness of asymptomatic infections using data from the outbreak on the Diamond Princess cruise ship. Methods: We used a transmission model of COVID-19 with asymptomatic and presymptomatic states calibrated to outbreak data from the Diamond Princess, to quantify the contribution of asymptomatic infections to transmission. Data available included the date of symptom onset for symptomatic disease for passengers and crew, the number of symptom agnostic tests done each day, and date of positive test for asymptomatic and presymptomatic individuals. Findings: On the Diamond Princess 74% (70-78%) of infections proceeded asymptomatically, i.e. a 1:3.8 case-to-infection ratio. Despite the intense testing 53%, (51-56%) of infections remained undetected, most of them asymptomatic. Asymptomatic individuals were the source for 69% (20-85%) of all infections. While the data did not allow identification of the infectiousness of asymptomatic infections, assuming no or low infectiousness resulted in posterior estimates for the net reproduction number of an individual progressing through presymptomatic and symptomatic stages in excess of 15. Interpretation: Asymptomatic SARS-CoV-2 infections may contribute substantially to transmission. This is essential to consider for countries when assessing the potential effectiveness of ongoing control measures to contain COVID-19. 2020-05-11
Matt J Keeling; Edward Hill; Erin Gorsich; Bridget Penman; Glen Guyver-Fletcher; Alex Holmes; Trystan Leng; Hector McKimm; Massimiliano Tamborrino; Louise Dyson; Michael Tildesley Predictions of COVID-19 dynamics in the UK: short-term forecasting and analysis of potential exit strategies Background: Efforts to suppress transmission of SARS-CoV-2 in the UK have seen non-pharmaceutical interventions being invoked. The most severe measures to date include all restaurants, pubs and cafes being ordered to close on 20th March, followed by a "stay at home" order on the 23rd March and the closure of all non-essential retail outlets for an indefinite period. Government agencies are presently analysing how best to develop an exit strategy from these measures and to determine how the epidemic may progress once measures are lifted. Mathematical models are currently providing short and long term forecasts regarding the future course of the COVID-19 outbreak in the UK to support evidence-based policymaking. Methods: We present a deterministic, age-structured transmission model that uses real-time data on confirmed cases requiring hospital care and mortality to provide up-to-date predictions on epidemic spread in ten regions of the UK. We simulated a suite of scenarios to assess the impact of differing approaches to relaxing social distancing measures from 7th May 2020, on the estimated number of patients requiring inpatient and critical care treatment, and deaths. With regard to future epidemic outcomes, we investigated the impact of reducing compliance, ongoing shielding of elder age groups, reapplying stringent social distancing measures using region based triggers and the role of asymptomatic transmission. Findings: We find that significant relaxation of social distancing measures on 7th May can lead to a rapid resurgence of COVID-19 disease and the health system being quickly overwhelmed by a sizeable, second epidemic wave. In all considered age-shielding based strategies, we projected serious demand on critical care resources during the course of the pandemic. The reintroduction and release of strict measures on a regional basis, based on ICU bed occupancy, results in a long epidemic tail, until the second half of 2021, but ensures that the health service is protected by reintroducing social distancing measures for all individuals in a region when required. Conclusions: Our work supports the decision to apply stringent non-pharmaceutical measures in March 2020 to suppress the epidemic. We provide strong evidence to support the need for a cautious, measured approach to relaxation of lockdown measures, to protect the most vulnerable members of society and support the health service through subduing demand on hospital beds, in particular bed occupancy in intensive care units. 2020-05-11
Jia Huang; Le Zheng; Zhen Li; Shiying Hao; Fangfan Ye; Jun Chen; Xiaoming Yao; Jiayu Liao; Song Wang; Manfei Zeng; Liping Qiu; Fanlan Cen; Yajing Huang; Tengfei Zhu; Zehui Xu; Manhua Ye; Yang Yang; Guowei Wang; Jinxiu Li; Lifei Wang; Jiuxin Qu; Jing Yuan; Wei Zheng; Zheng Zhang; Chunyang Li; John C Whitin; Lu Tian; Henry Chubb; KuoYuan Hwa; Hayley A Gans; Scott R Ceresnak; Wei Zhang; Ying Lu; Yvonne A Maldonado; Harvey J Cohen; Doff B McElhinney; Karl G Sylvester; Qing He; Zhaoqin Wang; Yingxia Liu; Lei Liu; Xuefeng B Ling Recurrence of SARS-CoV-2 PCR positivity in COVID-19 patients: a single center experience and potential implications IMPORTANCE How to appropriately care for patients who become PCR-negative for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is still not known. Patients who have recovered from coronavirus disease 2019 (COVID-19) could profoundly impact the health care system if a subset were to be PCR-positive again with reactivated SARS-CoV-2. OBJECTIVE To characterize a single center COVID-19 cohort with and without recurrence of PCR positivity, and develop an algorithm to identify patients at high risk of retest positivity after discharge to inform health care policy and case management decision-making. DESIGN, SETTING, AND PARTICIPANTS A cohort of 414 patients with confirmed SARS-CoV-2 infection, at The Second Affiliated Hospital of Southern University of Science and Technology in Shenzhen, China from January 11 to April 23, 2020. EXPOSURES Polymerase chain reaction (PCR) and IgM-IgG antibody confirmed SARS-CoV-2 infection. MAIN OUTCOMES AND MEASURES Univariable and multivariable statistical analysis of the clinical, laboratory, radiologic image, medical treatment, and clinical course of admission/quarantine/readmission data to develop an algorithm to predict patients at risk of recurrence of PCR positivity. RESULTS 16.7% (95CI: 13.0%-20.3%) patients retest PCR positive 1 to 3 times after discharge, despite being in strict quarantine. The driving factors in the recurrence prediction model included: age, BMI; lowest levels of the blood laboratory tests during hospitalization for cholinesterase, fibrinogen, albumin, prealbumin, calcium, eGFR, creatinine; highest levels of the blood laboratory tests during hospitalization for total bilirubin, lactate dehydrogenase, alkaline phosphatase; the first test results during hospitalization for partial pressure of oxygen, white blood cell and lymphocyte counts, blood procalcitonin; and the first test episodic Ct value and the lowest Ct value of the nasopharyngeal swab RT PCR results. Area under the ROC curve is 0.786. CONCLUSIONS AND RELEVANCE This case series provides clinical characteristics of COVID-19 patients with recurrent PCR positivity, despite strict quarantine, at a 16.7% rate. Use of a recurrence prediction algorithm may identify patients at high risk of PCR retest positivity of SARS-CoV-2 and help modify COVID-19 case management and health policy approaches. 2020-05-10
Elizabeth Sapey; Suzy Gallier; Chris Mainey; Peter Nightingale; David McNulty; Hannah Crothers; Felicity Evison; Katharine Reeves; Domenico Pagano; Alastair K Denniston; Krishnarajah Nirantharakumar; Peter Diggle; Simon Ball Ethnicity and risk of death in patients hospitalised for COVID-19 infection: an observational cohort study in an urban catchment area Objectives. To determine if specific ethnic groups are at higher risk of mortality from COVID19 infection. Design. Retrospective cohort study Setting. University Hospitals Birmingham NHS Foundation Trust (UHB) in Birmingham, UK Participants. Patients with confirmed SARS CoV 2 infection requiring admission to UHB between 10th March 2020 and 17th April 2020 Exposure. Ethnicity Main outcome measures. Standardised Admission Ratio (SAR) and Standardised Mortality Ratio (SMR) for each ethnicity was calculated using observed sex specific age distributions of COVID19 admissions/deaths and 2011 census data for Birmingham/Solihull. Hazard Ratio (aHR) for mortality was estimated for each ethnic group with white population as reference group, using Cox proportional hazards model adjusting for age, sex, social deprivation and co-morbidities, and propensity score matching. Results. 2217 patients admitted to UHB with a proven diagnosis of COVID19 were included. 58.2% were male, 69.5% White and the majority (80.2%) had co morbidities. 18.5% were of South Asian ethnicity, and these patients were more likely to be younger (median age 61 years vs.77 years), have no co morbidities (27.8% vs. 16.6%) but a higher prevalence of diabetes mellitus (48.0% vs 28.2%) than White patients. SAR and SMR suggested more admissions and deaths in South Asian patients than would be predicted. South Asian patients were also more likely to present with severe disease despite no delay in presentation since symptom onset. South Asian ethnicity was associated with an increased risk of death; both by Cox regression (Hazard Ratio 1.66 (95%CI 1.32 to 2.10)) after adjusting for age, sex, deprivation and comorbidities and by propensity score matching, (Hazard ratio 1.68 (1.33 to 2.13), using the same factors but categorising ethnicity into South Asian or not. Conclusions. Current evidence suggests those of South Asian ethnicity may be at risk of worse COVID19 outcomes, further studies need to establish the underlying mechanistic pathways. 2020-05-09
Bram A.D. van Bunnik; Alex L.K. Morgan; Paul Bessell; Giles Calder-Gerver; Feifei Zhang; Samuel Haynes; Jordan Ashworth; Shengyuan Zhao; Nicola Rose Cave; Meghan R. Perry; Hannah C. Lepper; Lu Lu; Paul Kellam; Aziz Sheikh; Graham F. Medley; Mark E.J. Woolhouse Segmentation and shielding of the most vulnerable members of the population as elements of an exit strategy from COVID-19 lockdown In this study we demonstrate that the adoption of a segmenting and shielding (S&S) strategy could increase scope to partially exit COVID-19 lockdown while limiting the risk of an overwhelming second wave of infection. The S&S strategy has an antecedent in the "cocooning" of infants by immunisation of close family members (Forsyth et al., 2015), and forms a pillar of infection, prevention and control (IPC) strategies (RCN, 2017). We are unaware of it being proposed as a major public health initiative previously. We illustrate the S&S strategy using a mathematical model that segments the vulnerable population and their closest contacts, the "shielders". We explore the effects on the epidemic curve of a gradual ramping up of protection for the vulnerable population and a gradual ramping down of restrictions on the non-vulnerable population over a period of 12 weeks after lockdown. The most important determinants of outcome are: i) post-lockdown transmission rates within the general population segment and between the general and vulnerable segments; ii) the fraction of the population in the vulnerable and shielder segments; iii) adherence with need to be protected; and iv) the extent to which population immunity builds up in all segments. We explored the effects of extending the duration of lockdown and faster or slower transition to post-lockdown conditions and, most importantly, the trade-off between increased protection of the vulnerable segment and fewer restrictions on the general population. We illustrate how the potential for the relaxation of restrictions interacts with specific policy objectives. We show that the range of options for relaxation in the general population can be increased by maintaining restrictions on the shielder segment and by intensive routine screening of shielders. We find that the outcome of any future policy is strongly influenced by the contact matrix between segments and the relationships between physical distancing measures and transmission rates. These relationships are difficult to quantify so close monitoring of the epidemic would be essential during and after the exit from lockdown. More generally, S&S has potential applications for any infectious disease for which there are defined proportions of the population who cannot be treated or who are at risk of severe outcomes. 2020-05-08
Dan Lewer; Isobel Braithwaite; Miriam Bullock; Max T Eyre; Robert W Aldridge COVID-19 and homelessness in England: a modelling study of theCOVID-19 pandemic among people experiencing homelessness, and theimpact of a residential intervention to isolate vulnerable people andcare for people with symptoms Background: There is an ongoing pandemic of the viral respiratory disease COVID-19. People experiencing homelessness are vulnerable to infection and severe disease. Health and housing authorities in England have developed a residential intervention that aims to isolate those vulnerable to severe disease (COVID-PROTECT) and care for people with symptoms (COVID CARE). Methods: We used a discrete-time Markov chain model to forecast COVID-19 infections among people experiencing homelessness, given strong containment measures in the general population and some transmission among 35,817 people living in 1,065 hostels, and 11,748 people sleeping rough (the 'do nothing' scenario). We then estimated demand for beds if those eligible are offered COVID-PROTECT and COVID-CARE. We estimated the reduction in the number of COVID-19 cases, deaths, and hospital admissions that could be achieved by these interventions. We also conducted sensitivity and scenario analyses to identify programme success factors. Results: In a 'do nothing' scenario, we estimate that 34% of the homeless population could get COVID-19 between March and August 2020, with 364 deaths, 4,074 hospital admissions and 572 critical care admissions. In our 'base intervention' scenario, demand for COVID-PROTECT peaks at 9,934 beds, and demand for COVID-CARE peaks at 1,366 beds. The intervention could reduce transmission by removing symptomatic individuals from the community, and preventing vulnerable individuals from being infected. This could lead to a reduction of 164 deaths, 2,624 hospital admissions, and 248 critical care admissions over this period. Sensitivity analyses showed that the number of deaths is sensitive to transmission of COVID-19 in COVID-PROTECT. If COVID-PROTECT capacity is limited, scenario analyses show the benefit of prioritising people who are vulnerable to severe disease. Conclusion: Supportive accommodation can mitigate the impact of the COVID-19 pandemic on the homeless population of England, and reduce the burden on acute hospitals. 2020-05-08
Nicholas G Davies; Sedona Sweeney; Sergio Torres-Rueda; Fiammetta Bozzani; Nichola Kitson; Edwine Barasa; Simon Procter; Matthew Quaife; - LSHTM Centre for Mathematical Modelling of Infectious Diseases COVID-19 Working Group; Rosalind M Eggo; Anna Vassall; Mark Jit The impact of Coronavirus disease 2019 (COVID-19) on health systems and household resources in Africa and South Asia Background. Coronavirus disease 2019 (COVID-19) epidemics strain health systems and households. Health systems in Africa and South Asia may be particularly at risk due to potential high prevalence of risk factors for severe disease, large household sizes and limited healthcare capacity. Methods. We investigated the impact of an unmitigated COVID-19 epidemic on health system resources and costs, and household costs, in Karachi, Delhi, Nairobi, Addis Ababa and Johannesburg. We adapted a dynamic model of SARS-CoV-2 transmission and disease to capture country-specific demography and contact patterns. The epidemiological model was then integrated into an economic framework that captured city-specific health systems and household resource use. Findings. The cities severely lack intensive care beds, healthcare workers and financial resources to meet demand during an unmitigated COVID-19 epidemic. A highly mitigated COVID-19 epidemic, under optimistic assumptions, may avoid overwhelming hospital bed capacity in some cities, but not critical care capacity. Interpretation. Viable mitigation strategies encompassing a mix of responses need to be established to expand healthcare capacity, reduce peak demand for healthcare resources, minimise progression to critical care and shield those at greatest risk of severe disease. 2020-05-08
Yan Wu; Feiran Wang; Chenguang Shen; Weiyu Peng; Delin Li; Cheng Zhao; Zhaohui Li; Shihua Li; Yuhai Bi; Yang Yang; Yuhuan Gong; Haixia Xiao; Zheng Fan; Shuguang Tan; Guizhen Wu; Wenjie Tan; Xuancheng Lu; Changfa Fan; Qihui Wang; Yingxia Liu; Jianxun Qi; George Fu Gao; Feng Gao; Lei Liu A non-competing pair of human neutralizing antibodies block COVID-19 virus binding to its receptor ACE2 Neutralizing antibodies could be antivirals against COVID-19 pandemics. Here, we report the isolation of four human-origin monoclonal antibodies from a convalescent patient in China. All of these isolated antibodies display neutralization abilities in vitro. Two of them (B38 and H4) block the binding between RBD and vial cellular receptor ACE2. Further competition assay indicates that B38 and H4 recognize different epitopes on the RBD, which is ideal for a virus-targeting mAb-pair to avoid immune escape in the future clinical applications. Moreover, therapeutic study on the mouse model validated that these two antibodies can reduce virus titers in the infected mouse lungs. Structure of RBD-B38 complex revealed that most residues on the epitope are overlapped with the RBD-ACE2 binding interface, which explained the blocking efficacy and neutralizing capacity. Our results highlight the promise of antibody-based therapeutics and provide the structural basis of rational vaccine design. 2020-05-07
- The OpenSAFELY Collaborative; Elizabeth Williamson; Alex J Walker; Krishnan J Bhaskaran; Seb Bacon; Chris Bates; Caroline E Morton; Helen J Curtis; Amir Mehrkar; David Evans; Peter Inglesby; Jonathan Cockburn; Helen I Mcdonald; Brian MacKenna; Laurie Tomlinson; Ian J Douglas; Christopher T Rentsch; Rohini Mathur; Angel Wong; Richard Grieve; David Harrison; Harriet Forbes; Anna Schultze; Richard T Croker; John Parry; Frank Hester; Sam Harper; Rafael Perera; Stephen Evans; Liam Smeeth; Ben Goldacre OpenSAFELY: factors associated with COVID-19-related hospital death in the linked electronic health records of 17 million adult NHS patients. Background Establishing who is at risk from a novel rapidly arising cause of death, and why, requires a new approach to epidemiological research with very large datasets and timely data. Working on behalf of NHS England we therefore set out to deliver a secure and pseudonymised analytics platform inside the data centre of a major primary care electronic health records vendor establishing coverage across detailed primary care records for a substantial proportion of all patients in England. The following results are preliminary. Data sources Primary care electronic health records managed by the electronic health record vendor TPP, pseudonymously linked to patient-level data from the COVID-19 Patient Notification System (CPNS) for death of hospital inpatients with confirmed COVID-19, using the new OpenSAFELY platform. Population 17,425,445 adults. Time period 1st Feb 2020 to 25th April 2020. Primary outcome Death in hospital among people with confirmed COVID-19. Methods Cohort study analysed by Cox-regression to generate hazard ratios: age and sex adjusted, and multiply adjusted for co-variates selected prospectively on the basis of clinical interest and prior findings. Results There were 5683 deaths attributed to COVID-19. In summary after full adjustment, death from COVID-19 was strongly associated with: being male (hazard ratio 1.99, 95%CI 1.88-2.10); older age and deprivation (both with a strong gradient); uncontrolled diabetes (HR 2.36 95% CI 2.18-2.56); severe asthma (HR 1.25 CI 1.08-1.44); and various other prior medical conditions. Compared to people with ethnicity recorded as white, black people were at higher risk of death, with only partial attenuation in hazard ratios from the fully adjusted model (age-sex adjusted HR 2.17 95% CI 1.84-2.57; fully adjusted HR 1.71 95% CI 1.44-2.02); with similar findings for Asian people (age-sex adjusted HR 1.95 95% CI 1.73-2.18; fully adjusted HR 1.62 95% CI 1.43-1.82). Conclusions We have quantified a range of clinical risk factors for death from COVID-19, some of which were not previously well characterised, in the largest cohort study conducted by any country to date. People from Asian and black groups are at markedly increased risk of in-hospital death from COVID-19, and contrary to some prior speculation this is only partially attributable to pre-existing clinical risk factors or deprivation; further research into the drivers of this association is therefore urgently required. Deprivation is also a major risk factor with, again, little of the excess risk explained by co-morbidity or other risk factors. The findings for clinical risk factors are concordant with policies in the UK for protecting those at highest risk. Our OpenSAFELY platform is rapidly adding further NHS patients' records; we will update and extend these results regularly. Keywords COVID-19, risk factors, ethnicity, deprivation, death, informatics. 2020-05-07
Juan Juan; Maria M Gil; Zhihui Rong; Yuanzhen Zhang; Huixia Yang; Liona Chiu Yee Poon Effects of Coronavirus Disease 2019 (COVID-19) on Maternal, Perinatal and Neonatal Outcomes: a Systematic Review of 266 Pregnancies Objective: To perform a systematic review of available published literature on pregnancies affected by COVID-19 to evaluate the effects of COVID-19 on maternal, perinatal and neonatal outcomes. Methods: We performed a systematic review to evaluate the effects of COVID-19 on pregnancy, perinatal and neonatal outcomes. We conducted a comprehensive literature search using PubMed, EMBASE, Cochrane library, China National Knowledge Infrastructure Database and Wan Fang Data until April 20, 2020 (studies were identified through PubMed alert after April 20, 2020). For the research strategy, combinations of the following keywords and MeSH terms were used: SARS-CoV-2, COVID-19, coronavirus disease 2019, pregnancy, gestation, maternal, mothers, vertical transmission, maternal-fetal transmission, intrauterine transmission, neonates, infant, delivery. Eligibility criteria included laboratory-confirmed and/or clinically diagnosed COVID-19, patient was pregnant on admission, availability of clinical characteristics, including maternal, perinatal or neonatal outcomes. Exclusion criteria were unpublished reports, unspecified date and location of the study or suspicion of duplicate reporting, and unreported maternal or perinatal outcomes. No language restrictions were applied. Results: We identified several case-reports and case-series but only 19 studies, including a total of 266 pregnant women with COVID-19, met eligibility criteria and were finally included in the review. In the combined data from seven case-series, the maternal age ranged from 20 to 41 years and the gestational age on admission ranged from 5 to 41 weeks. The most common symptoms at presentation were fever, cough, dyspnea/shortness of breath and fatigue. The rate of severe pneumonia was relatively low, with the majority of the cases requiring intensive care unit admission. Almost all cases from the case-series had positive computer tomography chest findings. There were six and 22 cases that had nucleic-acid testing in vaginal mucus and breast milk samples, respectively, which were negative for SARS-CoV-2. Only a few cases had spontaneous miscarriage or abortion. 177 cases had delivered, of which the majority by Cesarean section. The gestational age at delivery ranged from 28 to 41 weeks. Apgar scores at 1 and 5 minutes ranged from 7 to 10 and 8 to 10, respectively. A few neonates had birthweight less than 2500 grams and over one-third of cases were transferred to neonatal intensive care unit. There was one case each of neonatal asphyxia and neonatal death. There were 113 neonates that had nucleic-acid testing in throat swab, which was negative for SARS-CoV-2. From the case-reports, two maternal deaths among pregnant women with COVID-19 were reported. Conclusions: The clinical characteristics of pregnant women with COVID-19 are similar to those of nonpregnant adults with COVID-19. Currently, there is no evidence that pregnant women with COVID-19 are more prone to develop severe pneumonia, in comparison to nonpregnant patients. The subject of vertical transmission of SARS-CoV-2 remains controversial and more data is needed to investigate this possibility. Most importantly, in order to collect meaningful pregnancy and perinatal outcome data, we urge researchers and investigators to reference previously published cases in their publications and to record such reporting when the data of a case is being entered into a registry or several registries. 2020-05-06
James T Teo; Daniel Bean; Rebecca Bendayan; Richard Dobson; Ajay Shah Impact of ethnicity on outcome of severe COVID-19 infection. Data from an ethnically diverse UK tertiary centre During the current COVID-19 pandemic, it has been suggested that BAME background patients may be disproportionately affected compared to White but few detailed data are available. We took advantage of near real-time hospital data access and analysis pipelines to look at the impact of ethnicity in 1200 consecutive patients admitted between 1st March 2020 and 12th May 2020 to Kings College Hospital NHS Trust in London (UK). Our key findings are firstly that BAME patients are significantly younger and have different co-morbidity profiles than White individuals. Secondly, there is no significant independent effect of ethnicity on severe outcomes (death or ITU admission) within 14-days of symptom onset, after adjustment for age, sex and comorbidities. 2020-05-06
Jonine Figueroa; Paul Brennan; Evropi Theodoratou; Michael Poon; Karin Purshouse; Farhat Din; Kai Jin; Ines Mesa-Eguiagaray; Malcolm G Dunlop; Peter S Hall; David Cameron; Sarah Wild; Cathie LM Sudlow Trends in excess cancer and cardiovascular deaths in Scotland during the COVID-19 pandemic 30 December 2019 to 20 April 2020 Understanding the trends in causes of death for different diseases during the current COVID-19 pandemic is important to determine whether there are excess deaths beyond what is normally expected. Using the most recent report from National Records Scotland (NRS) on 29 April 2020, we examined the percentage difference in crude numbers of deaths in 2020 compared to the average for 2015-2019 by week of death within calendar year. To determine if trends were similar, suggesting underreporting/underdiagnosed COVID-19 related deaths, we also looked at the trends in % differences for cardiovascular disease deaths. From the first 17 weeks' of data, we found a peak in excess deaths between weeks 14 of 2020, about four weeks after the first case in Scotland was detected on 1 March 2020-- but by week 17 these excesses had diminished around the time lockdown in the UK began. Similar observations were seen for cardiovascular disease-related deaths. These observations suggest that the short-term increase in excess cancer and cardiovascular deaths might be associated with undetected/unconfirmed deaths related to COVID-19. Both of these conditions make patients more susceptible to infection and lack of widespread access to testing for COVID-19 are likely to have resulted in under-estimation of COVID-19 mortality. These data further suggest that the cumulative toll of COVID-19 on mortality is likely undercounted. More detailed analysis is needed to determine if these excesses were directly or indirectly related to COVID-19. Disease specific mortality will need constant monitoring for the foreseeable future as changes occur in increasing capacity and access to testing, reporting criteria, changes to health services and different measures are implemented to control the spread of the COVID-19. Multidisciplinary, multi-institutional, national and international collaborations for complementary and population specific data analysis is required to respond and mitigate adverse effects of the COVID-19 pandemic and to inform planning for future pandemics. 2020-05-06
Kali A Barrett; Yoshiko Nakamachi; Terra Ierasts; Yasin Khan; Stephen Mac; David Naimark; Nathan Stall; Raphael Ximenes; Andrew Morris; Beate Sander A model to estimate demand for personal protective equipment for Ontario acute care hospitals during the COVID-19 pandemic In addition to instituting public health measures for COVID-19, managing healthcare resources is important for outcomes. The experiences in Italy and New York have shown that personal protective equipment (PPE) shortages can cause increased morbidity and mortality. We demonstrate a method to predict PPE demand across a health care system. 2020-05-05
Long H. Nguyen; David Alden Drew; Amit D. Joshi; Chuan-Guo Guo; Wenjie Ma; Raaj S. Mehta; Daniel R. Sikavi; Chun-Han Lo; Sohee Kwon; Mingyang Song; Lorelei A. Mucci; Meir Stampfer; Walter C. Willett; A. Heather Eliassen; Jaime Hart; Jorge E. Chavarro; Janet Rich-Edwards; Richard Davies; Joan Capdevila; Karla A. Lee; Mary Ni Lochlainn; Thomas Varsavsky; Mark Graham; Carol H. Sudre; M. Jorge Cardoso; Jonathan Wolf; Sebastien Ourselin; Claire Steves; Timothy Spector; Andrew T. Chan Risk of symptomatic Covid-19 among frontline healthcare workers Background: Data for frontline healthcare workers (HCWs) and risk of SARS-CoV-2 infection are limited and whether personal protective equipment (PPE) mitigates this risk is unknown. We evaluated risk for COVID-19 among frontline HCWs compared to the general community and the influence of PPE. Methods: We performed a prospective cohort study of the general community, including frontline HCWs, who reported information through the COVID Symptom Study smartphone application beginning on March 24 (United Kingdom, U.K.) and March 29 (United States, U.S.) through April 23, 2020. We used Cox proportional hazards modeling to estimate multivariate-adjusted hazard ratios (aHRs) of a positive COVID-19 test. Findings: Among 2,035,395 community individuals and 99,795 frontline HCWs, we documented 5,545 incident reports of a positive COVID-19 test over 34,435,272 person-days. Compared with the general community, frontline HCWs had an aHR of 11.6 (95% CI: 10.9 to 12.3) for reporting a positive test. The corresponding aHR was 3.40 (95% CI: 3.37 to 3.43) using an inverse probability weighted Cox model adjusting for the likelihood of receiving a test. A symptom-based classifier of predicted COVID-19 yielded similar risk estimates. Compared with HCWs reporting adequate PPE, the aHRs for reporting a positive test were 1.46 (95% CI: 1.21 to 1.76) for those reporting PPE reuse and 1.31 (95% CI: 1.10 to 1.56) for reporting inadequate PPE. Compared with HCWs reporting adequate PPE who did not care for COVID-19 patients, HCWs caring for patients with documented COVID-19 had aHRs for a positive test of 4.83 (95% CI: 3.99 to 5.85) if they had adequate PPE, 5.06 (95% CI: 3.90 to 6.57) for reused PPE, and 5.91 (95% CI: 4.53 to 7.71) for inadequate PPE. Interpretation: Frontline HCWs had a significantly increased risk of COVID-19 infection, highest among HCWs who reused PPE or had inadequate access to PPE. However, adequate supplies of PPE did not completely mitigate high-risk exposures. 2020-05-05
Amit Sud; Michael Jones; John Broggio; Stephen Scott; Chey Loveday; Bethany Torr; Alice Garrett; David L. Nicol; Shaman Jhanji; Stephen A. Boyce; Matthew Williams; Georgios Lyratzopoulos; Claire Barry; Elio Riboli; Emma Kipps; Ethna McFerran; Mark Lawler; David C. Muller; Muti Abulafi; Richard Houlston; Clare Ann Turnbull Quantifying and mitigating the impact of the COVID-19 pandemic on outcomes in colorectal cancer Background: The COVID-19 pandemic has caused disruption across cancer pathways for diagnosis and treatment. In England, 32% of colorectal cancer (CRC) is diagnosed via urgent symptomatic referral from primary care, the "2-week-wait" (2WW) pathway. Access to routine endoscopy is likely to be a critical bottleneck causing delays in CRC management due to chronic limitation in capacity, acute competition for physician time, and safety concerns. Methods: We used age-specific, stage-specific 10 year CRC survival for England 2007-2017 and 2WW CRC cases volumes. We used per-day hazard ratios of CRC survival generated from observational studies of CRC diagnosis-to-treatment interval to model the effect of different durations of per-patient delay. We utilised data from a large London observational study of faecal immunochemical testing (FIT) in symptomatic patients to model FIT-triage to mitigate delay to colonoscopy. Findings: Modest delays result in significant reduction in survival from CRC with a 4-month delay resulting across age groups in [&ge;]20% reduction in survival in Stage 3 disease and in total over a year, 1,419 attributable deaths across the 11,266 CRC patients diagnosed via the 2WW pathway. FIT triage of >10 ug Hb/g would salvage 1,292/1,419 of the attributable deaths and reduce colonoscopy requirements by >80%. Diagnostic colonoscopy offers net survival in all age groups, providing nosocomial COVID-19 infection rates are kept low (<2.5%). Interpretation To avoid significant numbers of avoidable deaths from CRC, normal diagnostic and surgical throughput must be maintained. An accrued backlog of cases will present to primary care following release of lockdown, supranormal endoscopy capacity will be required to manage this without undue delays. FIT-triage of symptomatic cases provides a rational approach by which to avoid patient delay and mitigate pressure on capacity in endoscopy. This would also reduce exposure to nosocomial COVID-19 infection, relevant in particular to older patient groups. Funding: Breast Cancer Now, Cancer Research UK, Bobby Moore Fund for Cancer Research, National Institute for Health Research (NIHR). 2020-05-05
Kevin van Zandvoort; Christopher I Jarvis; Carl Pearson; Nicholas G Davies; CMMID COVID-19 working group; Timothy W Russell; Adam J Kucharski; Mark J Jit; Stefan Flasche; Rosalind M Eggo; Francesco Checchi Response strategies for COVID-19 epidemics in African settings: a mathematical modelling study Background The health impact of COVID-19 may differ in African settings as compared to countries in Europe or China due to demographic, epidemiological, environmental and socio-economic factors. We evaluated strategies to reduce SARS-CoV-2 burden in African countries, so as to support decisions that balance minimising mortality, protecting health services and safeguarding livelihoods. Methods We used a Susceptible-Exposed-Infectious-Recovered mathematical model, stratified by age, to predict the evolution of COVID-19 epidemics in three countries representing a range of age distributions in Africa (from oldest to youngest average age: Mauritius, Nigeria and Niger), under various effectiveness assumptions for combinations of different non-pharmaceutical interventions: self-isolation of symptomatic people, physical distancing, and shielding (physical isolation) of the high-risk population. We adapted model parameters to better represent uncertainty about what might be expected in African populations, in particular by shifting the distribution of severity risk towards younger ages and increasing the case-fatality ratio. Results We predicted median clinical attack rates over the first 12 months of 17% (Niger) to 39% (Mauritius), peaking at 2-4 months, if epidemics were unmitigated. Self-isolation while symptomatic had a maximum impact of about 30% on reducing severe cases, while the impact of physical distancing varied widely depending on percent contact reduction and R 0 . The effect of shielding high-risk people, e.g. by rehousing them in physical isolation, was sensitive mainly to residual contact with low-risk people, and to a lesser extent to contact among shielded individuals. Response strategies incorporating self-isolation of symptomatic individuals, moderate physical distancing and high uptake of shielding reduced predicted peak bed demand by 46% to 54% and mortality by 60% to 75%. Lockdowns delayed epidemics by about 3 months. Estimates were sensitive to differences in age-specific social mixing patterns, as published in the literature. Discussion In African settings, as elsewhere, current evidence suggests large COVID-19 epidemics are expected. However, African countries have fewer means to suppress transmission and manage cases. We found that self-isolation of symptomatic persons and general physical distancing are unlikely to avert very large epidemics, unless distancing takes the form of stringent lockdown measures. However, both interventions help to mitigate the epidemic. Shielding of high-risk individuals can reduce health service demand and, even more markedly, mortality if it features high uptake and low contact of shielded and unshielded people, with no increase in contact among shielded people. Strategies combining self-isolation, moderate physical distancing and shielding will probably achieve substantial reductions in mortality in African countries. Temporary lockdowns, where socioeconomically acceptable, can help gain crucial time for planning and expanding health service capacity. 2020-05-03
Huayu Zhang; Ting Shi; Xiaodong Wu; Xin Zhang; Kun Wang; Daniel Bean; Richard Dobson; James T Teo; Jiaxing Sun; Pei Zhao; Chenghong Li; Kevin Dhaliwal; Honghan Wu; Qiang Li; Bruce Guthrie Risk prediction for poor outcome and death in hospital in-patients with COVID-19: derivation in Wuhan, China and external validation in London, UK Background Accurate risk prediction of clinical outcome would usefully inform clinical decisions and intervention targeting in COVID-19. The aim of this study was to derive and validate risk prediction models for poor outcome and death in adult inpatients with COVID-19. Methods Model derivation using data from Wuhan, China used logistic regression with death and poor outcome (death or severe disease) as outcomes. Predictors were demographic, comorbidity, symptom and laboratory test variables. The best performing models were externally validated in data from London, UK. Findings 4.3% of the derivation cohort (n=775) died and 9.7% had a poor outcome, compared to 34.1% and 42.9% of the validation cohort (n=226). In derivation, prediction models based on age, sex, neutrophil count, lymphocyte count, platelet count, C-reactive protein and creatinine had excellent discrimination (death c-index=0.91, poor outcome c-index=0.88), with good-to-excellent calibration. Using two cut-offs to define low, high and very-high risk groups, derivation patients were stratified in groups with observed death rates of 0.34%, 15.0% and 28.3% and poor outcome rates 0.63%, 8.9% and 58.5%. External validation discrimination was good (c-index death=0.74, poor outcome=0.72) as was calibration. However, observed rates of death were 16.5%, 42.9% and 58.4% and poor outcome 26.3%, 28.4% and 64.8% in predicted low, high and very-high risk groups. Interpretation Our prediction model using demography and routinely-available laboratory tests performed very well in internal validation in the lower-risk derivation population, but less well in the much higher-risk external validation population. Further external validation is needed. Collaboration to create larger derivation datasets, and to rapidly externally validate all proposed prediction models in a range of populations is needed, before routine implementation of any risk prediction tool in clinical care. 2020-05-03
Christoph B. Messner; Vadim Demichev; Daniel Wendisch; Laura Michalick; Matthew White; Anja Freiwald; Kathrin Textoris-Taube; Spyros I. Vernardis; Anna-Sophia Egger; Marco Kreidl; Daniela Ludwig; Christiane Kilian; Federica Agostini; Aleksej Zelezniak; Charlotte Thibeault; Moritz Pfeiffer; Stefan Hippenstiel; Andreas Hocke; Christof von Kalle; Archie Campbell; Caroline Hayward; David J. Porteous; Riccardo E. Marioni; Claudia Langenberg; Kathryn S. Lilley; Wolfgang M. Kuebler; Michael Muelleder; Christian Drosten; Martin Witzenrath; Florian Kurth; Leif Erik Sander; Markus Ralser Clinical classifiers of COVID-19 infection from novel ultra-high-throughput proteomics The COVID-19 pandemic is an unprecedented global challenge. Highly variable in its presentation, spread and clinical outcome, novel point-of-care diagnostic classifiers are urgently required. Here, we describe a set of COVID-19 clinical classifiers discovered using a newly designed low-cost high-throughput mass spectrometry-based platform. Introducing a new sample preparation pipeline coupled with short-gradient high-flow liquid chromatography and mass spectrometry, our methodology facilitates clinical implementation and increases sample throughput and quantification precision. Providing a rapid assessment of serum or plasma samples at scale, we report 27 biomarkers that distinguish mild and severe forms of COVID-19, of which some may have potential as therapeutic targets. These proteins highlight the role of complement factors, the coagulation system, inflammation modulators as well as pro-inflammatory signalling upstream and downstream of Interleukin 6. Application of novel methodologies hence transforms proteomics from a research tool into a rapid-response, clinically actionable technology adaptable to infectious outbreaks. 2020-05-03
Frederick K Ho; Carlos A Celis-Morales; Stuart R Gray; Srinivasa Vittal Katikireddi; Claire L Niedzwiedz; Claire Hastie; Donald M. Lyall; Lyn D. Ferguson; Colin Berry; Daniel F. Mackay; Jason M.R. Gill; Jill P. Pell; Naveed Sattar; Paul I Welsh Modifiable and non-modifiable risk factors for COVID-19: results from UK Biobank Background Information on risk factors for COVID-19 is sub-optimal. We investigated demographic, lifestyle, socioeconomic, and clinical risk factors, and compared them to risk factors for pneumonia and influenza in UK Biobank. Methods UK Biobank recruited 37-70 year olds in 2006-2010 from the general population. The outcome of confirmed COVID-19 infection (positive SARS-CoV-2 test) was linked to baseline UK Biobank data. Incident influenza and pneumonia were obtained from primary care data. Poisson regression was used to study the association of exposure variables with outcomes. Findings Among 428,225 participants, 340 had confirmed COVID-19. After multivariable adjustment, modifiable risk factors were higher body mass index (RR 1.24 per SD increase), smoking (RR 1.38), slow walking pace as a proxy for physical fitness (RR 1.66) and use of blood pressure medications as a proxy for hypertension (RR 1.40). Non-modifiable risk factors included older age (RR 1.10 per 5 years), male sex (RR 1.64), black ethnicity (RR 1.86), socioeconomic deprivation (RR 1.26 per SD increase in Townsend Index), longstanding illness (RR 1.38) and high cystatin C (RR 1.24 per 1 SD increase). The risk factors overlapped with pneumonia somewhat; less so for influenza. The associations with modifiable risk factors were generally stronger for COVID-19, than pneumonia or influenza. Interpretation These findings suggest that modification of lifestyle may help to reduce the risk of COVID-19 and could be a useful adjunct to other interventions, such as social distancing and shielding of high risk. Funding British Heart Foundation, Medical Research Council, Chief Scientist Office. 2020-05-02
Mary Ni Lochlainn; Karla A Lee; Carole H Sudre; Thomas Varsavsky; M. Jorge Cardoso; Cristina Menni; Ruth C. E. Bowyer; Long H. Nguyen; David Alden Drew; Sajaysurya Ganesh; Julien Lavigne du Cadet; Alessia Visconti; Maxim B Freydin; Marc Modat; Mark S Graham; Joan Capdevila Pujol; Benjamin Murray; Julia S El-Sayed Moustafa; Xinyuan Zhang; Richard Davies; Mario Falchi; Timothy D Spector; Andrew T Chan; Sebastien Ourselin; Claire J Steves Key predictors of attending hospital with COVID19: An association study from the COVID Symptom Tracker App in 2,618,948 individuals Objectives: We aimed to identify key demographic risk factors for hospital attendance with COVID-19 infection. Design: Community survey Setting: The COVID Symptom Tracker mobile application co-developed by physicians and scientists at Kings College London, Massachusetts General Hospital, Boston and Zoe Global Limited was launched in the UK and US on 24th and 29th March 2020 respectively. It captured self-reported information related to COVID-19 symptoms and testing. Participants: 2,618,948 users of the COVID Symptom Tracker App. UK (95.7%) and US (4.3%) population. Data cut-off for this analysis was 21st April 2020. Main outcome measures: Visit to hospital and for those who attended hospital, the need for respiratory support in three subgroups (i) self-reported COVID-19 infection with classical symptoms (SR-COVID-19), (ii) self-reported positive COVID-19 test results (T-COVID-19), and (iii) imputed/predicted COVID-19 infection based on symptomatology (I-COVID-19). Multivariate logistic regressions for each outcome and each subgroup were adjusted for age and gender, with sensitivity analyses adjusted for comorbidities. Classical symptoms were defined as high fever and persistent cough for several days. Results: Older age and all comorbidities tested were found to be associated with increased odds of requiring hospital care for COVID-19. Obesity (BMI >30) predicted hospital care in all models, with odds ratios (OR) varying from 1.20 [1.11; 1.31] to 1.40 [1.23; 1.60] across population groups. Pre-existing lung disease and diabetes were consistently found to be associated with hospital visit with a maximum OR of 1.79 [1.64,1.95] and 1.72 [1.27; 2.31]) respectively. Findings were similar when assessing the need for respiratory support, for which age and male gender played an additional role. Conclusions: Being older, obese, diabetic or suffering from pre-existing lung, heart or renal disease placed participants at increased risk of visiting hospital with COVID-19. It is of utmost importance for governments and the scientific and medical communities to work together to find evidence-based means of protecting those deemed most vulnerable from COVID-19. Trial registration: The App Ethics have been approved by KCL ethics Committee REMAS ID 18210, review reference LRS-19/20-18210 2020-04-29
Jody Phelan; Wouter Deelder; Daniel Ward; Susana Campino; Martin L Hibberd; Taane G Clark Controlling the SARS-CoV-2 outbreak, insights from large scale whole genome sequences generated across the world BackgroundSARS-CoV-2 most likely evolved from a bat beta-coronavirus and started infecting humans in December 2019. Since then it has rapidly infected people around the world, with more than 4.5 million confirmed cases by the middle of May 2020. Early genome sequencing of the virus has enabled the development of molecular diagnostics and the commencement of therapy and vaccine development. The analysis of the early sequences showed relatively few evolutionary selection pressures. However, with the rapid worldwide expansion into diverse human populations, significant genetic variations are becoming increasingly likely. The current limitations on social movement between countries also offers the opportunity for these viral variants to become distinct strains with potential implications for diagnostics, therapies and vaccines. MethodsWe used the current sequencing archives (NCBI and GISAID) to investigate 15,487 whole genomes, looking for evidence of strain diversification and selective pressure. ResultsWe used 6,294 SNPs to build a phylogenetic tree of SARS-CoV-2 diversity and noted strong evidence for the existence of two major clades and six sub-clades, unevenly distributed across the world. We also noted that convergent evolution has potentially occurred across several locations in the genome, showing selection pressures, including on the spike glycoprotein where we noted a potentially critical mutation that could affect its binding to the ACE2 receptor. We also report on mutations that could prevent current molecular diagnostics from detecting some of the sub-clades. ConclusionThe worldwide whole genome sequencing effort is revealing the challenge of developing SARS-CoV-2 containment tools suitable for everyone and the need for data to be continually evaluated to ensure accuracy in outbreak estimations. 2020-04-29
Ewan Carr; Rebecca Bendayan; Daniel Bean; Matthew Stammers; Wenjuan Wang; Huayu Zhang; Thomas Searle; Zeljko Kraljevic; Anthony Shek; Hang T T Phan; Walter Muruet; Anthony J Shinton; Ting Shi; Xin Zhang; Andrew Pickles; Daniel Stahl; Rosita Zakeri; Kevin O'Gallagher; Amos Folarin; Lukasz Roguski; Florina Borca; James Batchelor; Xiaodong Wu; Jiaxing Sun; Ashwin Pinto; Bruce Guthrie; Cormac Breen; Abdel Douiri; Honghan Wu; Vasa Curcin; James T Teo; Ajay Shah; Richard Dobson Supplementing the National Early Warning Score (NEWS2) for anticipating early deterioration among patients with COVID-19 infection Objectives: To evaluate the National Early Warning Score (NEWS2), currently recommended in the UK for risk-stratification of severe COVID-19 outcomes, and subsequently identify and validate a minimal set of common parameters taken at hospital admission that improve the score. Design: Retrospective observational cohort with internal and multi-hospital external validation. Setting: Secondary care. Interventions: Not applicable. Participants: Training and temporal external validation cohorts comprised 1464 patients admitted to King's College Hospital NHS Foundation Trust (KCH) with COVID-19 disease from 1st March to 30th April 2020. External validation cohorts included 3869 patients from two UK NHS Trusts (Guys and St Thomas' Hospitals, GSTT and University Hospitals Southampton, UHS) and two hospitals in Wuhan, China (Wuhan Sixth Hospital and Taikang Tongji Hospital). Main outcome measures: The primary outcome was patient status at 14 days after symptom onset categorised as severe disease (transferred to intensive care unit or death). Age, physiological measures, blood biomarkers, sex, ethnicity and comorbidities (hypertension, diabetes, cardiovascular, respiratory and kidney diseases) were included. Results: NEWS2 score on admission was a weak predictor of severe COVID-19 infection (AUC = 0.628). Adding age and common blood tests (CRP, neutrophil count, estimated GFR and albumin) provided substantial improvements to a risk stratification model, particularly in relation to sensitivity, but performance was only moderate (AUC = 0.753). Improvement over NEWS2 remained robust and generalisable in GSTT (AUC = 0.817), UHS (AUC = 0.835) and Wuhan hospitals (AUC = 0.918). Conclusions: Adding age and a minimal set of blood parameters to NEWS2 improves the detection of patients likely to develop severe COVID-19 outcomes. This finding was replicated across NHS and non-UK hospitals. Adding a few common parameters to a pre-existing acuity score allows rapid and easy implementation of this risk-scoring system. 2020-04-29
Claire L Niedzwiedz; Bhautesh D Jani; Evangelia Demou; Frederick K Ho; Carlos Celis-Morales; Barbara I Nicholl; Frances Mair; Paul Welsh; Naveed Sattar; Jill Pell; Srinivasa Vittal Katikireddi Ethnic and socioeconomic differences in SARS-CoV2 infection in the UK Biobank cohort study Background Understanding of the role of ethnicity and socioeconomic position in the risk of developing SARS-CoV-2 infection is limited. We investigated this in the UK Biobank study. Methods The UK Biobank study recruited 40-70 year olds in 2006-2010 from the general population, collecting information about self-defined ethnicity and socioeconomic variables (including area-level socioeconomic deprivation and educational attainment). SARS-CoV-2 test results from Public Health England were linked to baseline UK Biobank data. Poisson regression with robust standard errors was used to assess risk ratios (RRs) between the exposures and dichotomous variables for: being tested, having a positive test and testing positive in hospital. We also investigated whether ethnicity and socioeconomic position were associated with having a positive test amongst those tested. We adjusted for covariates including age, sex, social variables (including healthcare work and household size), behavioural risk factors and baseline health. Results Among 428,225 participants in England, 1,474 had been tested and 669 tested positive between 16 March and 13 April 2020. Black, south Asian and white Irish people were more likely to have confirmed infection (RR 4.01 (95%CI 2.92-5.12); RR 2.11 (95%CI 1.43-3.10); and RR 1.60 (95% CI 1.08-2.38) respectively) and were more likely to be hospital cases compared to the White British. While they were more likely to be tested, they were also more likely to test positive. Adjustment for baseline health and behavioural risk factors led to little change, with only modest attenuation when accounting for socioeconomic variables. Socioeconomic deprivation and having no qualifications were consistently associated with a higher risk of confirmed infection (RR 2.26 (95%CI 1.76-2.90); and RR 1.91 (95%CI 1.53-2.38) respectively). Conclusions Some minority ethnic groups have a higher risk of confirmed SARS-CoV-2 infection in the UK Biobank study which was not accounted for by differences in socioeconomic conditions, measured baseline health or behavioural risk factors. An urgent response to addressing these elevated risks is required. 2020-04-27
Ruth Bowyer; Thomas Varsavsky; Carole H Sudre; Benjamin Murray; Maxim Freidin; Darioush Yarand; Sajaysurya Ganesh; Joan Capdevila; Ellen J Thompson; Elco Bakker; M Jorge Cardoso; Richard Davies; Jonathan Wolf; Tim D Spector; Sebastien Ourselin; Claire J Steves; Cristina Menni Geo-social gradients in predicted COVID-19 prevalence and severity in Great Britain: results from 2,266,235 users of the COVID-19 Symptoms Tracker app Understanding the geographical distribution of COVID-19 through the general population is key to the provision of adequate healthcare services. Using self-reported data from 2,266,235 unique GB users of the COVID Symptom Tracker app, we find that COVID-19 prevalence and severity became rapidly distributed across the UK within a month of the WHO declaration of the pandemic, with significant evidence of urban hot-spots. We found a geo-social gradient associated with disease severity and prevalence suggesting resources should focus on urban areas and areas of higher deprivation. Our results demonstrate use of self-reported data to inform public health policy and resource allocation. 2020-04-27
Frances MK Williams; Maxim Freydin; Massimo Mangino; Simon Couvreur; Alessia Visconti; Ruth CE Bowyer; Caroline I Le Roy; Mario Falchi; Carole Sudre; Richard Davies; Christopher Hammond; Cristina Menni; Claire Steves; Tim Spector Self-reported symptoms of covid-19 including symptoms most predictive of SARS-CoV-2 infection, are heritable Susceptibility to infection such as SARS-CoV-2 may be influenced by host genotype. TwinsUK volunteers (n=2633) completing the C-19 Covid symptom tracker app allowed classical twin studies of covid-19 symptoms including predicted covid-19, a symptom-based algorithm predicting true infection derived in app users tested for SARS-CoV-2. We found heritability for fever = 41 (95% confidence intervals 12-70)%; anosmia 47 (27-67)%; delirium 49 (24-75)%; and predicted covid-19 gave heritability = 50 (29-70)%. 2020-04-24
David A Leon; Christopher I Jarvis; Anne M Johnson; Liam Smeeth; Vladimir M Shkolnikov What can trends in hospital deaths from COVID-19 tell us about the progress and peak of the pandemic? An analysis of death counts from England announced up to 20 April 2020 Background. Reporting of daily hospital COVID-19 deaths in the UK are promoted by the government and scientific advisers alike as a key metric for assessing the progress in the control of the epidemic. These data, however, have certain limitations, among which one of the most significant concerns the fact that the daily totals span deaths that have occurred between 1 and 10 days or more in the past. Data and methods. We obtained daily data published published by NHS England up to and including April 25 in the form of Excel spreadsheets in which deaths counts are presented by date of death according to age and region. Simple descriptive analyses were conducted and presented in graphical and tabular form which were aimed at illustrating the biases inherent in focussing on daily counts regardless of when the deaths occurred. We then looked at how a less biased picture could be obtained by looking at trends in death counts stratifying by individual period of delay in days between occurrence of death and when the death was included in the daily announcement. Findings. The number of hospital COVID-19 deaths announced daily overestimates the maximum number of deaths actually occurring so far in the epidemic in the UK, and also obscures the pattern of decline in deaths. Taking account of reporting delays suggests that for England as a whole a peak in hospital COVID-19 deaths may have been reached on April 8 with a subsequent gradual decline suggested. The same peak is also seen among those aged 60-79 and 80+, although there is slightly shallower decline in the oldest age group (80+ years). Among those aged 40-59 years a later peak on April 11 is evident. London shows a peak on April 8 and a clearer and steeper pattern of subsequent decline compared to England as a whole. Interpretation. Analyses of mortality trends must take account of delay, and in communication with the public more emphasis should be placed on looking at trends based on deaths that occurred 5 or more days prior to the announcement day. The slightly weaker decline seen at age 80+ may reflect increased hospitalisation of people from care homes, whereas the later peak under the age of 60 years may reflect the higher proportions at these younger ages being admitted to critical care resulting in an extension of life of several days. 2020-04-24
Yue-qiang Fu; Yue-lin Sun; Si-wei Lu; Yang Yang; Yi Wang; Feng Xu Impact of blood analysis and immune function on the prognosis of patients with COVID-19 Introduction: This retrospective study investigated the implications of changes in blood parameters and cellular immune function in patients with 2019-coronavirus infected disease (COVID-19). Methods: Records were reviewed of 85 patients with COVID-19 between February 4 and 16, 2020. The primary outcome was in-hospital mortality at 28 days. Results: Fourteen patients died. The baseline leukocyte count, neutrophil count and hemoglobin was significantly higher in non-survivors compared with survivors, while the reverse was true of lymphocyte count, platelet, PaO2/FiO2, CD3+ count and CD4+ count. The percentage of neutrophil count > 6.3*109/L in death group was significantly higher than that in survival group, and multivariate logistic regression showed neutrophil count was independently associated with mortality. However, there were not significant difference in IgG, IgM, IgA, C3, C4 and the percentage of IgE > 100 IU/ml between the death group and survival group. Areas under the receiver operating characteristic curves of the following at baseline could significantly predict mortality: leukocyte, neutrophil, lymphocyte, CD3+ and CD4+ counts. Conclusions: For patients with COVID-19, lymphocyte, CD3+ and CD4+ counts that marked decrease suggest a poor outcome. A high neutrophil count is independently associated with mortality. At admission, leukocyte, neutrophil, lymphocyte, CD3+ and CD4+ counts should receive added attention. 2020-04-22
Andrew Clark; Mark Jit; Charlotte Warren-Gash; Bruce Guthrie; Harry HX Wang; Stewart W Mercer; Colin Sanderson; Martin McKee; Christopher Troeger; Kanyin I Ong; Francesco Checchi; Pablo Perel; Sarah Joseph; Hamish P Gibbs; Amitava Banerjee; LSHTM CMMID COVID-19 working group; Rosalind M Eggo How many are at increased risk of severe COVID-19 disease? Rapid global, regional and national estimates for 2020 Background The risk of severe COVID-19 disease is known to be higher in older individuals and those with underlying health conditions. Understanding the number of individuals at increased risk of severe COVID-19 illness, and how this varies between countries may inform the design of possible strategies to shield those at highest risk. Methods We estimated the number of individuals at increased risk of severe COVID-19 disease by age (5-year age groups), sex and country (n=188) based on prevalence data from the Global Burden of Disease (GBD) study for 2017 and United Nations population estimates for 2020. We also calculated the number of individuals without an underlying condition that could be considered at-risk because of their age, using thresholds from 50-70 years. The list of underlying conditions relevant to COVID-19 disease was determined by mapping conditions listed in GBD to the guidelines published by WHO and public health agencies in the UK and US. We analysed data from two large multimorbidity studies to determine appropriate adjustment factors for clustering and multimorbidity. Results We estimate that 1.7 (1.0 - 2.4) billion individuals (22% [15-28%] of the global population) are at increased risk of severe COVID-19 disease. The share of the population at increased risk ranges from 16% in Africa to 31% in Europe. Chronic kidney disease (CKD), cardiovascular disease (CVD), diabetes and chronic respiratory disease (CRD) were the most prevalent conditions in males and females aged 50+ years. African countries with a high prevalence of HIV/AIDS and Island countries with a high prevalence of diabetes, also had a high share of the population at increased risk. The prevalence of multimorbidity (>1 underlying conditions) was three times higher in Europe than in Africa (10% vs 3%). Conclusion Based on current guidelines and prevalence data from GBD, we estimate that one in five individuals worldwide has a condition that is on the list of those at increased risk of severe COVID-19 disease. However, for many of these individuals the underlying condition will be undiagnosed or not severe enough to be captured in health systems, and in some cases the increase in risk may be quite modest. There is an urgent need for robust analyses of the risks associated with different underlying conditions so that countries can identify the highest risk groups and develop targeted shielding policies to mitigate the effects of the COVID-19 pandemic. 2020-04-22
Billy J Quilty; Charlie Diamond; Yang Liu; Hamish Gibbs; Timothy W Russell; Christopher I Jarvis; Kiesha Prem; Carl A B Pearson; Samuel J Clifford; Stefan Flasche; CMMID COVID-19 working group; Petra Klepac; Rosalind M Eggo; Mark Jit The effect of inter-city travel restrictions on geographical spread of COVID-19: Evidence from Wuhan, China Background: To contain the spread of COVID-19, a cordon sanitaire was put in place in Wuhan prior to the Lunar New Year, on 23 January 2020, restricting travel to other parts of China. We assess the efficacy of the cordon sanitaire to delay the introduction and onset of local transmission of COVID-19 in other major cities in mainland China. Methods: We estimated the number of infected travellers from Wuhan to other major cities in mainland China from November 2019 to March 2020 using previously estimated COVID-19 prevalence in Wuhan and publicly available mobility data. We focused on Beijing, Chongqing, Hangzhou, and Shenzhen as four representative major cities to identify the potential independent contribution of the cordon sanitaire and holiday travel. To do this, we simulated outbreaks generated by infected arrivals in these destination cities using stochastic branching processes. We also modelled the effect of the cordon sanitaire in combination with reduced transmissibility scenarios representing the effect of local non-pharmaceutical interventions. Findings: In the four cities, given the potentially high prevalence of COVID-19 in Wuhan between Dec 2019 and early Jan 2020, local transmission may have been seeded as early as 2 - 8 January 2020. By the time the cordon sanitaire was imposed, simulated case counts were likely in the hundreds. The cordon sanitaire alone did not substantially affect the epidemic progression in these cities, although it may have had some effect in smaller cities. Interpretation: Our results indicate that the cordon sanitaire may not have prevented COVID-19 spread in major Chinese cities; local non-pharmaceutical interventions were likely more important for this. 2020-04-21
Amitava Banerjee; Michail Katsoulis; Alvina G Lai; Laura Pasea; Thomas A Treibel; Charlotte Manisty; Spiros Denaxas; Giovanni Quarta; Harry Hemingway; Joao Cavalcante; Mahdad Nousardeghi; James C Moon Clinical academic research in the time of Corona: a simulation study in England and a call for action Background: Coronavirus (COVID-19) poses health system challenges in every country. As with any public health emergency, a major component of the global response is timely, effective science. However, particular factors specific to COVID-19 must be overcome to ensure that research efforts are optimised. We aimed to model the impact of COVID-19 on the clinical academic response in the UK, and to provide recommendations for COVID-related research. Methods: We constructed a simple stochastic model to determine clinical academic capacity in the UK in four policy approaches to COVID-19 with differing population infection rates: Italy model (6%), mitigation (10%), relaxed mitigation (40%) and do-nothing (80%) scenarios. The ability to conduct research in the COVID-19 climate is affected by the following key factors: (i) infection growth rate and population infection rate (from UK COVID-19 statistics and WHO); (ii) strain on the healthcare system (from published model); and (iii) availability of clinical academic staff with appropriate skillsets affected by frontline clinical activity and sickness (from UK statistics). Findings: In Italy model, mitigation, relaxed mitigation and do-nothing scenarios, from 5 March 2020 the duration (days) and peak infection rates (%) are 95(2.4%), 115(2.5%), 240(5.3%) and 240(16.7%) respectively. Near complete attrition of academia (87% reduction, less than 400 clinical academics) occurs 35 days after pandemic start for 11, 34, 62, 76 days respectively, with no clinical academics at all for 37 days in the do-nothing scenario. Restoration of normal academic workforce (80% of normal capacity) takes 11,12, 30 and 26 weeks respectively. Interpretation: Pandemic COVID-19 crushes the science needed at system level. National policies mitigate, but the academic community needs to adapt. We highlight six key strategies: radical prioritisation (eg 3-4 research ideas per institution), deep resourcing, non-standard leadership (repurposing of key non-frontline teams), rationalisation (profoundly simple approaches), careful site selection (eg protected sites with large academic backup) and complete suspension of academic competition with collaborative approaches. 2020-04-17
Xueyan Mei; Hao-Chih Lee; Kaiyue Diao; Mingqian Huang; Bin Lin; Chenyu Liu; Zongyu Xie; Yixuan Ma; Philip M. Robson; Michael Chung; Adam Bernheim; Venkatesh Mani; Claudia Calcagno; Kunwei Li; Shaolin Li; Hong Shan; Jian Lv; Tongtong Zhao; Junli Xia; Qihua Long; Sharon Steinberger; Adam Jacobi; Timothy Deyer; Marta Luksza; Fang Liu; Brent P. Little; Zahi A. Fayad; Yang Yang Artificial intelligence for rapid identification of the coronavirus disease 2019 (COVID-19) For diagnosis of COVID-19, a SARS-CoV-2 virus-specific reverse transcriptase polymerase chain reaction (RT-PCR) test is routinely used. However, this test can take up to two days to complete, serial testing may be required to rule out the possibility of false negative results, and there is currently a shortage of RT-PCR test kits, underscoring the urgent need for alternative methods for rapid and accurate diagnosis of COVID-19 patients. Chest computed tomography (CT) is a valuable component in the evaluation of patients with suspected SARS-CoV-2 infection. Nevertheless, CT alone may have limited negative predictive value for ruling out SARS-CoV-2 infection, as some patients may have normal radiologic findings at early stages of the disease. In this study, we used artificial intelligence (AI) algorithms to integrate chest CT findings with clinical symptoms, exposure history, and laboratory testing to rapidly diagnose COVID-19 positive patients. Among a total of 905 patients tested by real-time RT-PCR assay and next-generation sequencing RT-PCR, 419 (46.3%) tested positive for SARS-CoV-2. In a test set of 279 patients, the AI system achieved an AUC of 0.92 and had equal sensitivity as compared to a senior thoracic radiologist. The AI system also improved the detection of RT-PCR positive COVID-19 patients who presented with normal CT scans, correctly identifying 17 of 25 (68%) patients, whereas radiologists classified all of these patients as COVID-19 negative. When CT scans and associated clinical history are available, the proposed AI system can help to rapidly diagnose COVID-19 patients. 2020-04-17
Qin-Long Jing; Ming-Jin Liu; Jun Yuan; Zhou-Bin Zhang; An-Ran Zhang; Natalie E Dean; Lei Luo; Meng-Meng Ma; Ira Longini; Eben Kenah; Ying Lu; Yu Ma; Neda Jalali; Li-Qun Fang; Zhi-Cong Yang; Yang Yang Household Secondary Attack Rate of COVID-19 and Associated Determinants Background: As of April 2, 2020, the global reported number of COVID-19 cases has crossed over 1 million with more than 55,000 deaths. The household transmissibility of SARS-CoV-2, the causative pathogen, remains elusive. Methods: Based on a comprehensive contact-tracing dataset from Guangzhou, we estimated both the population-level effective reproductive number and individual-level secondary attack rate (SAR) in the household setting. We assessed age effects on transmissibility and the infectivity of COVID-19 cases during their incubation period. Results: A total of 195 unrelated clusters with 212 primary cases, 137 nonprimary (secondary or tertiary) cases and 1938 uninfected close contacts were traced. We estimated the household SAR to be 13.8% (95% CI: 11.1-17.0%) if household contacts are defined as all close relatives and 19.3% (95% CI: 15.5-23.9%) if household contacts only include those at the same residential address as the cases, assuming a mean incubation period of 4 days and a maximum infectious period of 13 days. The odds of infection among children (<20 years old) was only 0.26 (95% CI: 0.13-0.54) times of that among the elderly ([&ge;]60 years old). There was no gender difference in the risk of infection. COVID-19 cases were at least as infectious during their incubation period as during their illness. On average, a COVID-19 case infected 0.48 (95% CI: 0.39-0.58) close contacts. Had isolation not been implemented, this number increases to 0.62 (95% CI: 0.51-0.75). The effective reproductive number in Guangzhou dropped from above 1 to below 0.5 in about 1 week. Conclusion: SARS-CoV-2 is more transmissible in households than SARS-CoV and MERS-CoV, and the elderly [&ge;]60 years old are the most vulnerable to household transmission. Case finding and isolation alone may be inadequate to contain the pandemic and need to be used in conjunction with heightened restriction of human movement as implemented in Guangzhou. 2020-04-15
Samuel P C Brand; Rabia Aziza; Ivy K Kombe; Charles N Agoti; Joe Hilton; Kat S Rock; Andrea Parisi; D James Nokes; Matt Keeling; Edwine Barasa Forecasting the scale of the COVID-19 epidemic in Kenya Background The first COVID-19 case in Kenya was confirmed on March 13th, 2020. Here, we provide forecasts for the potential incidence rate, and magnitude, of a COVID-19 epidemic in Kenya based on the observed growth rate and age distribution of confirmed COVID-19 cases observed in China, whilst accounting for the demographic and geographic dissimilarities between China and Kenya. Methods We developed a modelling framework to simulate SARS-CoV-2 transmission in Kenya, KenyaCoV. KenyaCoV was used to simulate SARS-CoV-2 transmission both within, and between, different Kenyan regions and age groups. KenyaCoV was parameterized using a combination of human mobility data between the defined regions, the recent 2019 Kenyan census, and estimates of age group social interaction rates specific to Kenya. Key epidemiological characteristics such as the basic reproductive number and the age-specific rate of developing COVID-19 symptoms after infection with SARS-CoV-2, were adapted for the Kenyan setting from a combination of published estimates and analysis of the age distribution of cases observed in the Chinese outbreak. Results We find that if person-to-person transmission becomes established within Kenya, identifying the role of subclinical, and therefore largely undetected, infected individuals is critical to predicting and containing a very significant epidemic. Depending on the transmission scenario our reproductive number estimates for Kenya range from 1.78 (95% CI 1.44 - 2.14) to 3.46 (95% CI 2.81-4.17). In scenarios where asymptomatic infected individuals are transmitting significantly, we expect a rapidly growing epidemic which cannot be contained only by case isolation. In these scenarios, there is potential for a very high percentage of the population becoming infected (median estimates: >80% over six months), and a significant epidemic of symptomatic COVID-19 cases. Exceptional social distancing measures can slow transmission, flattening the epidemic curve, but the risk of epidemic rebound after lifting restrictions is predicted to be high. 2020-04-14
Dipender Gill; Marios Arvanitis; Paul Carter; Ana I Hernandez Cordero; Brian Jo; Ville Karhunen; Susanna C Larsson; Xuan Li; Sam M Lockhart; Amy M Mason; Evanthia Pashos; Ashis Saha; Vanessa Tan; Verena Zuber; Yohan Bosse; Sarah Fahle; Ke Hao; Tao Jiang; Philippe Joubert; Alan C Lunt; Willem hendrik Ouwehand; David J Roberts; Wim Timens; Maarten van den Berge; Nicholas A Watkins; Alexis Battle; Adam S Butterworth; John Danesh; Barbara E Engelhard; James E Peters; Don Sin; Stephen Burgess ACE inhibition and cardiometabolic risk factors, lung ACE2 and TMPRSS2 gene expression, and plasma ACE2 levels: a Mendelian randomization study Objectives: To use human genetic variants that proxy angiotensin-converting enzyme (ACE) inhibitor drug effects and cardiovascular risk factors to provide insight into how these exposures affect lung ACE2 and TMPRSS2 gene expression and circulating ACE2 levels. Design: Two-sample Mendelian randomization (MR) analysis. Setting: Summary-level genetic association data. Participants: Participants were predominantly of European ancestry. Variants that proxy ACE inhibitor drug effects and cardiometabolic risk factors (body mass index, chronic obstructive pulmonary disease, lifetime smoking index, low-density lipoprotein cholesterol, systolic blood pressure and type 2 diabetes mellitus) were selected from publicly available genome-wide association study data (sample sizes ranging from 188,577 to 898,130 participants). Genetic association estimates for lung expression of ACE2 and TMPRSS2 were obtained from the Gene-Tissue Expression (GTEx) project (515 participants) and the Lung eQTL Consortium (1,038 participants). Genetic association estimates for circulating plasma ACE2 levels were obtained from the INTERVAL study (4,947 participants). Main outcomes and measures: Lung ACE2 and TMPRSS2 expression and plasma ACE2 levels. Results: There were no association of genetically proxied ACE inhibition with any of the outcomes considered here. There was evidence of a positive association of genetic liability to type 2 diabetes mellitus with lung ACE2 gene expression in GTEx (p = 4x10-4) and with circulating plasma ACE2 levels in INTERVAL (p = 0.03), but not with lung ACE2 expression in the Lung eQTL Consortium study (p = 0.68). There were no associations between genetically predicted levels of the other cardiometabolic traits with the outcomes. Conclusions: This study does not provide evidence to support that ACE inhibitor antihypertensive drugs affect lung ACE2 and TMPRSS2 expression or plasma ACE2 levels. In the current COVID-19 pandemic, our findings do not support a change in ACE inhibitor medication use without clinical justification. 2020-04-14
Daniel Bean; Zeljko Kraljevic; Thomas Searle; Rebecca Bendayan; Andrew Pickles; Amos Folarin; Lukasz Roguski; Kawsar Noor; Anthony Shek; Rosita Zakeri; Ajay Shah; James Teo; Richard JB Dobson Treatment with ACE-inhibitors is associated with less severe disease with SARS-Covid-19 infection in a multi-site UK acute Hospital Trust Aims: The SARS-Cov2 virus binds to the ACE2 receptor for cell entry. It has been suggested that ACE- inhibitors (ACEi) and Angiotensin-2 Blockers (ARB), which are commonly used in patients with hypertension or diabetes and may raise ACE2 levels, could increase the risk of severe COVID19 infection. Methods and Results: We evaluated this hypothesis in a consecutive cohort of 1200 acute inpatients with COVID19 at two hospitals with a multi-ethnic catchment population in London (UK). The mean age was 68+-17 years (57% male) and 74% of patients had at least 1 comorbidity. 415 patients (34.6%) reached the primary endpoint of death or transfer to a critical care unit for organ support within 21-days of symptom onset. 399 patients (33.3 %) were taking ACEi or ARB. Patients on ACEi/ARB were significantly older and had more comorbidities. The odds ratio (OR) for the primary endpoint in patients on ACEi and ARB, after adjustment for age, sex and co-morbidities, was 0.63 (CI 0.47-0.84, p<0.01). Conclusions: There was no evidence for increased severity of COVID19 disease in hospitalised patients on chronic treatment with ACEi or ARB. A trend towards a beneficial effect of ACEi/ARB requires further evaluation in larger meta-analyses and randomised clinical trials. 2020-04-11
Lilin Ye; Xiangyu Chen; Ren Li; Zhiwei Pan; Chunfeng Qian; Yang Yang; Renrong You; Jing Zhao; Leiqong Gao; Zhirong Li; Qizhao Huang; Lifan Xu; Jianfang Tang; Qin Tian; Wei Yao; Li Hu; Xiaofeng Yan; Xinyuan Zhou; Pinghuang Liu; Yuzhang Wu; Kai Deng; Zheng Zhang; Yaokai Chen; Zhaohui Qian Human monoclonal antibodies block the binding of SARS-CoV-2 spike protein to angiotensin converting enzyme 2 receptor The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a global pandemic of novel corona virus disease (COVID-19). To date, no prophylactic vaccines or approved therapeutic agents are available for preventing and treating this highly transmittable disease. Here we report two monoclonal antibodies (mAbs) cloned from memory B cells of patients recently recovered from COVID-19, and both mAbs specifically bind to the spike (S) protein of SARS-CoV-2, block the binding of receptor binding domain (RBD) of SARS-CoV-2 to human angiotensin converting enzyme 2 (hACE2), and effectively neutralize S protein-pseudotyped virus infection. These human mAbs hold the promise for the prevention and treatment of the ongoing pandemic of COVID-19. 2020-04-11
Jane Cheatley; Sabine Vuik; Marion Devaux; Stefano Scarpetta; Mark Pearson; Francesca Colombo; Michele Cecchini The effectiveness of non-pharmaceutical interventions in containing epidemics: a rapid review of the literature and quantitative assessment The number of confirmed COVID-19 cases has rapidly increased since discovery of the disease in December 2019. In the absence of medical countermeasures to stop the spread of the disease (i.e. vaccines), countries have responded by implementing a suite of non-pharmaceutical interventions (NPIS) to contain and mitigate COVID-19. Individual NPIs range in intensity (e.g. from lockdown to public health campaigns on personal hygiene), as does their impact on reducing disease transmission. This study uses a rapid review approach and investigates evidence from previous epidemic outbreaks to provide a quantitative assessment of the effectiveness of key NPIs used by countries to combat the COVID-19 pandemic. Results from the study are designed to help countries enhance their policy response as well as inform transition strategies by identifying which policies should be relaxed and which should not. 2020-04-10
Kathryn Tuttle; Ross Minter; Katherine Waugh; Paula Araya; Michael Ludwig; Colin Sempeck; Keith Smith; Zdenek Andrysik; Matthew Burchill; Beth Tamburini; David Orlicky; Kelly D Sullivan; Joaquin Espinosa JAK1 inhibition blocks lethal sterile immune responses:implications for COVID-19 therapy Cytokine storms are drivers of pathology and mortality in myriad viral infections affecting the human population. In SARS-CoV-2-infected patients, the strength of the cytokine storm has been associated with increased risk of acute respiratory distress syndrome, myocardial damage, and death. However, the therapeutic value of attenuating the cytokine storm in COVID-19 remains to be defined. Here, we report results obtained using a novel mouse model of lethal sterile anti-viral immune responses. Using a mouse model of Down syndrome (DS) with a segmental duplication of a genomic region encoding four of the six interferon receptor genes (Ifnrs), we demonstrate that these animals overexpress Ifnrs and are hypersensitive to IFN stimulation. When challenged with viral mimetics that activate Toll-like receptor signaling and IFN anti-viral responses, these animals overproduce key cytokines, show exacerbated liver pathology, rapidly lose weight, and die. Importantly, the lethal immune hypersensitivity, accompanying cytokine storm, and liver hyperinflammation are blocked by treatment with a JAK1-specific inhibitor. Therefore, these results point to JAK1 inhibition as a potential strategy for attenuating the cytokine storm and consequent organ failure during overdrive immune responses. Additionally, these results indicate that people with DS, who carry an extra copy of the IFNR gene cluster encoded on chromosome 21, should be considered at high risk during the COVID-19 pandemic. One Sentence SummaryInhibition of the JAK1 kinase prevents pathology and mortality caused by a rampant innate immune response in mice. 2020-04-09
Cristina Menni; Ana Valdes; Maxim B Freydin; Sajaysurya Ganesh; Julia El-Sayed Moustafa; Alessia Visconti; Pirro Hysi; Ruth C E Bowyer; Massimo Mangino; Mario Falchi; Jonathan Wolf; Claire Steves; Tim Spector Loss of smell and taste in combination with other symptoms is a strong predictor of COVID-19 infection Importance: A strategy for preventing further spread of the ongoing COVID-19 epidemic is to detect infections and isolate infected individuals without the need of extensive bio-specimen testing. Objectives: Here we investigate the prevalence of loss of smell and taste among COVID-19 diagnosed individuals and we identify the combination of symptoms, besides loss of smell and taste, most likely to correspond to a positive COVID-19 diagnosis in non-severe cases. Design: Community survey. Setting and Participants: Subscribers of RADAR COVID-19, an app that was launched for use among the UK general population asking about COVID-19 symptoms. Main Exposure: Loss of smell and taste. Main Outcome Measures: COVID-19. Results: Between 24 and 29 March 2020, 1,573,103 individuals reported their symptoms via the app; 26% reported suffering from one or more symptoms of COVID-19. Of those, n=1702 reported having had a RT-PCR COVID-19 test and gave full report on symptoms including loss of smell and taste; 579 were positive and 1123 negative. In this subset, we find that loss of smell and taste were present in 59% of COVID-19 positive individuals compared to 18% of those negative to the test, yielding an odds ratio (OR) of COVID-19 diagnosis of OR[95%CI]=6.59[5.25; 8.27], P= 1.90x10-59 . We also find that a combination of loss of smell and taste, fever, persistent cough, fatigue, diarrhoea, abdominal pain and loss of appetite is predictive of COVID-19 positive test with sensitivity 0.54[0.44; 0.63], specificity 0.86[0.80; 0.90], ROC-AUC 0.77[0.72; 0.82] in the test set, and cross-validation ROC-AUC 0.75[0.72; 0.77]. When applied to the 410,598 individuals reporting symptoms but not formally tested, our model predicted that 13.06%[12.97%;13.15] of these might have been already infected by the virus. Conclusions and Relevance: Our study suggests that loss of taste and smell is a strong predictor of having been infected by the COVID-19 virus. Also, the combination of symptoms that could be used to identify and isolate individuals includes anosmia, fever, persistent cough, diarrhoea, fatigue, abdominal pain and loss of appetite. This is particularly relevant to healthcare and other key workers in constant contact with the public who have not yet been tested for COVID-19. 2020-04-07
Eran Segal; Feng Zhang; Xihong Lin; Gary King; Ophir Shalem; Smadar Shilo; William E. Allen; Yonatan H. Grad; Casey S. Greene; Faisal Alquaddoomi; Simon Anders; Ran Balicer; Tal Bauman; Ximena Bonilla; Gisel Booman; Andrew T. Chan; Ori Ori Cohen; Silvano Coletti; Natalie Davidson; Yuval Dor; David A. Drew; Olivier Elemento; Georgina Evans; Phil Ewels; Joshua Gale; Amir Gavrieli; Benjamin Geiger; Iman Hajirasouliha; Roman Jerala; Andre Kahles; Olli Kallioniemi; Ayya Keshet; Gregory Landua; Tomer Meir; Aline Muller; Long H. Nguyen; Matej Oresic; Svetlana Ovchinnikova; Hedi Peterson; Jay Rajagopal; Gunnar Ratsch; Hagai Rossman; Johan Rung; Andrea Sboner; Alexandros Sigaras; Tim Spector; Ron Steinherz; Irene Stevens; Jaak Vilo; Paul Wilmes; CCC (Coronavirus Census Collective) Building an International Consortium for Tracking Coronavirus Health Status Information is the most potent protective weapon we have to combat a pandemic, at both the individual and global level. For individuals, information can help us make personal decisions and provide a sense of security. For the global community, information can inform policy decisions and offer critical insights into the epidemic of COVID-19 disease. Fully leveraging the power of information, however, requires large amounts of data and access to it. To achieve this, we are making steps to form an international consortium, Coronavirus Census Collective (CCC, coronaviruscensuscollective.org), that will serve as a hub for integrating information from multiple data sources that can be utilized to understand, monitor, predict, and combat global pandemics. These sources may include self-reported health status through surveys (including mobile apps), results of diagnostic laboratory tests, and other static and real-time geospatial data. This collective effort to track and share information will be invaluable in predicting hotspots of disease outbreak, identifying which factors control the rate of spreading, informing immediate policy decisions, evaluating the effectiveness of measures taken by health organizations on pandemic control, and providing critical insight on the etiology of COVID-19. It will also help individuals stay informed on this rapidly evolving situation and contribute to other global efforts to slow the spread of disease. In the past few weeks, several initiatives across the globe have surfaced to use daily self-reported symptoms as a means to track disease spread, predict outbreak locations, guide population measures and help in the allocation of healthcare resources. The aim of this paper is to put out a call to standardize these efforts and spark a collaborative effort to maximize the global gain while protecting participant privacy. 2020-04-06
David A. Drew; Long H. Nguyen; Claire J. Steves; Jonathan Wolf; Tim D. Spector; Andrew T. Chan; COPE Consortium Rapid implementation of mobile technology for real-time epidemiology of COVID-19 The rapid pace of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic (COVID-19) presents challenges to the robust collection of population-scale data to address this global health crisis. We established the COronavirus Pandemic Epidemiology (COPE) consortium to bring together scientists with expertise in big data research and epidemiology to develop a COVID-19 Symptom Tracker mobile application that we launched in the UK on March 24, 2020 and the US on March 29, 2020 garnering more than 2.25 million users to date. This mobile application offers data on risk factors, herald symptoms, clinical outcomes, and geographical hot spots. This initiative offers critical proof-of-concept for the repurposing of existing approaches to enable rapidly scalable epidemiologic data collection and analysis which is critical for a data-driven response to this public health challenge. 2020-04-06
Nicholas G Davies; Adam J Kucharski; Rosalind M Eggo; Amy Gimma; - CMMID COVID-19 Working Group; W. John Edmunds The effect of non-pharmaceutical interventions on COVID-19 cases, deaths and demand for hospital services in the UK: a modelling study Background Non-pharmaceutical interventions have been implemented to reduce transmission of SARS-CoV-2 in the UK. Projecting the size of an unmitigated epidemic and the potential effect of different control measures has been critical to support evidence-based policymaking during the early stages of the epidemic. Methods We used a stochastic age-structured transmission model to explore a range of intervention scenarios, including the introduction of school closures, social distancing, shielding of elderly groups, self-isolation of symptomatic cases, and extreme "lockdown"-type restrictions. We simulated different durations of interventions and triggers for introduction, as well as combinations of interventions. For each scenario, we projected estimated new cases over time, patients requiring inpatient and critical care (intensive care unit, ICU) treatment, and deaths. Findings We found that mitigation measures aimed at reducing transmission would likely have decreased the reproduction number, but not sufficiently to prevent ICU demand from exceeding NHS availability. To keep ICU bed demand below capacity in the model, more extreme restrictions were necessary. In a scenario where "lockdown"-type interventions were put in place to reduce transmission, these interventions would need to be in place for a large proportion of the coming year in order to prevent healthcare demand exceeding availability. Interpretation The characteristics of SARS-CoV-2 mean that extreme measures are likely required to bring the epidemic under control and to prevent very large numbers of deaths and an excess of demand on hospital beds, especially those in ICUs. 2020-04-06
Marc F Osterdahl; Karla A Lee; Mary Ni Lochlainn; Stuart Wilson; Sam Douthwaite; Rachel Horsfall; Alyce Sheedy; Simon D Goldenberg; Christoper J Stanley; Tim D Spector; Claire Steves Detecting SARS-CoV-2 at point of care: Preliminary data comparing Loop-mediated isothermal amplification (LAMP) to PCR Background: The need for a fast and reliable test for COVID-19 is paramount in managing the current pandemic. A cost effective and efficient diagnostic tool as near to the point of care (PoC) as possible would be a game changer in current testing. We tested reverse transcription loop mediated isothermal amplification (RT-LAMP), a method which can produce results in under 30 minutes, alongside standard methods in a real-life clinical setting. Methods: This service improvement project piloted a research RT-LAMP method on nasal and pharyngeal swabs on 21 residents in an NHS Category 1 care home, with two index COVID-19 cases, and compared it to multiplex tandem reverse transcription polymerase chain reaction (RT-PCR). We calculated the sensitivity, specificity, positive and negative predictive values of a single RT-LAMP swab compared to RT-PCR, as per STARD guidelines. We also recorded vital signs of patients to correlate clinical and laboratory information. Findings: The novel method accurately detected 8/10 PCR positive cases and identified a further 3 positive cases. Eight further cases were negative using both methods. Using repeated RT-PCR as a 'gold standard', the sensitivity and specificity of the novel test were 80% and 73% respectively. Positive predictive value (PPV) was 73% and negative predictive value (NPV) was 83%. We also observed hypothermia to be a significant early clinical sign in a number of COVID-19 patients in this setting. Interpretation: RT-LAMP testing for SARS-CoV-2 was found to be promising, fast, easy to use and to work equivalently to RT-PCR methods. Definitive studies to evaluate this method in larger cohorts are underway. RT-LAMP has the potential to transform COVID-19 detection, bringing rapid and accurate testing to the point of care. This method could be deployed in mobile testing units in the community, care homes and hospitals to detect disease early and prevent spread. 2020-04-04
Andrew Francis; Yi Guo; Paul Hurley; Oliver Obst; Laurence A. F. Park; Mark Tanaka; Russell Thomson; Rosalind Wang Projected ICU and Mortuary load due to COVID-19 in Sydney The spread of COVID-19 is expected to put a large strain on many hospital resources, including ICU bed space, and mortuary capacity. In this report we study the possible demands on ICU and mortuary capacity in Sydney, Australia, using an adapted SEIR epidemiological model. 2020-04-03
Tom Jefferson; Mark Jones; Lubna A Al Ansari; Ghada Bawazeer; Elaine Beller; Justin Clark; John Conly; Chris Del Mar; Elisabeth Dooley; Eliana Ferroni; Paul Glasziou; Tammy Hoffman; Sarah Thorning; Mieke Van Driel Physical interventions to interrupt or reduce the spread of respiratory viruses. Part 1 - Face masks, eye protection and person distancing: systematic review and meta-analysis Abstract OBJECTIVE: To examine the effectiveness of eye protection, face masks, or person distancing on interrupting or reducing the spread of respiratory viruses. DESIGN: Update of a Cochrane review that included a meta-analysis of observational studies during the SARS outbreak of 2003. DATA SOURCES: Eligible trials from the previous review; search of Cochrane Central Register of Controlled Trials, PubMed, Embase and CINAHL from October 2010 up to 1 April 2020; and forward and backward citation analysis. DATA SELECTION: Randomised and cluster-randomised trials of people of any age, testing the use of eye protection, face masks, or person distancing against standard practice, or a similar physical barrier. Outcomes included any acute respiratory illness and its related consequences. DATA EXTRACTION AND ANALYSIS: Six authors independently assessed risk of bias using the Cochrane tool and extracted data. We used a generalised inverse variance method for pooling using a random-effects model and reported results with risk ratios and 95% Confidence Intervals (CI). RESULTS: We included 15 randomised trials investigating the effect of masks (14 trials) in healthcare workers and the general population and of quarantine (1 trial). We found no trials testing eye protection. Compared to no masks there was no reduction of influenza-like illness (ILI) cases (Risk Ratio 0.93, 95%CI 0.83 to 1.05) or influenza (Risk Ratio 0.84, 95%CI 0.61-1.17) for masks in the general population, nor in healthcare workers (Risk Ratio 0.37, 95%CI 0.05 to 2.50). There was no difference between surgical masks and N95 respirators: for ILI (Risk Ratio 0.83, 95%CI 0.63 to 1.08), for influenza (Risk Ratio 1.02, 95%CI 0.73 to 1.43). Harms were poorly reported and limited to discomfort with lower compliance. The only trial testing quarantining workers with household ILI contacts found a reduction in ILI cases, but increased risk of quarantined workers contracting influenza. All trials were conducted during seasonal ILI activity. CONCLUSIONS: Most included trials had poor design, reporting and sparse events. There was insufficient evidence to provide a recommendation on the use of facial barriers without other measures. We found insufficient evidence for a difference between surgical masks and N95 respirators and limited evidence to support effectiveness of quarantine. Based on observational evidence from the previous SARS epidemic included in the previous version of our Cochrane review we recommend the use of masks combined with other measures. 2020-03-30
Nicholas G Davies; Petra Klepac; Yang Liu; Kiesha Prem; Mark Jit; CMMID COVID-19 working group; Rosalind M Eggo Age-dependent effects in the transmission and control of COVID-19 epidemics The COVID-19 pandemic has shown a markedly low proportion of cases among children. Age disparities in observed cases could be explained by children having lower susceptibility to infection, lower propensity to show clinical symptoms, or both. We evaluate these possibilities by fitting an age-structured mathematical model to epidemic data from six countries. We estimate that clinical symptoms occur in 25% (95% CrI: 19-32%) of infections in 10-19-year-olds, rising to 76% (68-82%) in over-70s, and that susceptibility to infection in under-20s is approximately half that of older adults. Accordingly, we find that interventions aimed at children may have a relatively small impact on total cases, particularly if the transmissibility of subclinical infections is low. The age-specific clinical fraction and susceptibility we have estimated has implications for the expected global burden of COVID-19 because of demographic differences across settings: in younger populations, the expected clinical attack rate would be lower, although it is likely that comorbidities in low-income countries will affect disease severity. Without effective control measures, regions with older populations may see disproportionally more clinical cases, particularly in the later stages of the pandemic. 2020-03-27
HANMING FANG; LONG WANG; YANG YANG Human Mobility Restrictions and the Spread of the Novel Coronavirus (2019-nCoV) in China We quantify the causal impact of human mobility restrictions, particularly the lockdown of the city of Wuhan on January 23, 2020, on the containment and delay of the spread of the Novel Coronavirus (2019-nCoV). We employ a set of difference-in-differences (DID) estimations to disentangle the lockdown effect on human mobility reductions from other confounding effects including panic effect, virus effect, and the Spring Festival effect. We find that the lockdown of Wuhan reduced inflow into Wuhan by 76.64%, outflows from Wuhan by 56.35%, and within-Wuhan movements by 54.15%. We also estimate the dynamic effects of up to 22 lagged population inflows from Wuhan and other Hubei cities, the epicenter of the 2019-nCoV outbreak, on the destination cities' new infection cases. We find, using simulations with these estimates, that the lockdown of the city of Wuhan on January 23, 2020 contributed significantly to reducing the total infection cases outside of Wuhan, even with the social distancing measures later imposed by other cities. We find that the COVID-19 cases would be 64.81% higher in the 347 Chinese cities outside Hubei province, and 52.64% higher in the 16 non-Wuhan cities inside Hubei, in the counterfactual world in which the city of Wuhan were not locked down from January 23, 2020. We also find that there were substantial undocumented infection cases in the early days of the 2019-nCoV outbreak in Wuhan and other cities of Hubei province, but over time, the gap between the officially reported cases and our estimated "actual" cases narrows significantly. We also find evidence that enhanced social distancing policies in the 63 Chinese cities outside Hubei province are effective in reducing the impact of population inflows from the epicenter cities in Hubei province on the spread of 2019-nCoV virus in the destination cities elsewhere. 2020-03-26
Amitava Banerjee; Laura Pasea; Steve Harris; Arturo Gonzalez-Izquierdo; Ana Torralbo; Laura Shallcross; Mahdad Noursadeghi; Deenan Pillay; Christina Pagel; Wai Keong Wong; Claudia Langenberg; Bryan Williams; Spiros Denaxas; Harry Hemingway Estimating excess 1- year mortality from COVID-19 according to underlying conditions and age in England: a rapid analysis using NHS health records in 3.8 million adults RAPID COMMUNICATION 22 March 2020 Estimating excess 1- year mortality from COVID-19 according to underlying conditions and age in England: a rapid analysis using NHS health records in 3.8 million adults Background: The medical, health service, societal and economic impact of the COVID-19 emergency has unknown effects on overall population mortality. Previous models of population mortality are based on death over days among infected people, nearly all of whom (to date at least) have underlying conditions. Models have not incorporated information on high risk conditions or their longer term background (pre-COVID-19) mortality. We estimated the excess number of deaths over 1 year under different COVID-19 incidence rates and differing mortality impacts. Methods: Using population based linked primary and secondary care electronic health records in England (HDR UK - CALIBER), we report the prevalence of underlying conditions defined by UK Public Health England COVID-19 guidelines (16 March 2020) in 3,862,012 individuals aged [&ge;]30 years from 1997-2017. We used previously validated phenotypes, openly available (https://caliberresearch.org/portal), for each condition using ICD-10 diagnosis, Read, procedure and medication codes. We estimated the 1-year mortality in each condition, and developed simple models of excess COVID-19-related deaths assuming relative risk (RR) of the impact of the emergency (compared to background mortality) of 1.2, 1.5 and 2.0. Findings: 20.0% of the population are at risk according to current PHE guidelines, of which; 13.7% were age>70 years and 6.3% aged [&le;]70 years with [&ge;]1 underlying condition (cardiovascular disease (2.3%), diabetes (2.2%), steroid therapy (1.9%), severe obesity (0.9%), chronic kidney disease (0.6%) and chronic obstructive pulmonary disease, COPD (0.5%). Multimorbidity (co-occurrence of [&ge;]2 conditions in an individual) was common (10.1%). The 1-year mortality in the at-risk population was 4.46%, and age and underlying conditions combine to influence background risk, varying markedly across conditions (5.9% in age>70 years, 8.6% for COPD and 13.1% in those with [&ge;]3 or more conditions). In a suppression scenario (at SARS CoV2 rates of 0.001% of the UK population), there would be minimal excess deaths (3 and 7 excess deaths at relative risk, RR, 1.5 and 2.0 respectively). At SARS CoV2 rates of 10% of the UK population (mitigation) the model estimates the numbers of excess deaths as: 13791, 34479 and 68957 (at RR 1.2, 1.5 and 2.0 respectively). At SARS CoV2 rates of 80% in the UK population (do-nothing), the model estimates the number of excess deaths as 110332, 275,830 and 551,659 (at RR 1.2, 1.5 and 2.0) respectively. Interpretation: We provide the public, researchers and policy makers a simple model to estimate the excess mortality over 1 year from COVID-19, based on underlying conditions at different ages. If the relative mortality impact of COVID-19 were to be about 20% (similar magnitude as the established winter vs summer mortality excess), then the excess deaths would be 0 when 1 in 100 000 (suppression), 13791 when 1 in 10 (mitigation) and 110332 when 8 in 10 are infected (do nothing) scenario. However, the relative impact of COVID-19 is unknown. If the emergency were to double the mortality risk, then we estimate 7, 68957 and 551,659 excess deaths in the same scenarios. These results may inform the need for more stringent suppression measures as well as efforts to target those at highest risk for a range of preventive interventions. 2020-03-24
Ellen Brooks-Pollock; Jonathan M Read; Thomas House; Graham Medley; Matt J Keeling; Leon Danon The Population Attributable Fraction (PAF) of cases due to gatherings and groups with relevance to COVID-19 mitigation strategies Background Many countries have banned groups and gatherings as part of their response to the pandemic caused by the coronavirus, SARS-CoV-2. Although there are outbreak reports involving mass gatherings, the contribution to overall transmission is unknown. Methods We used data from a survey of social contact behaviour that specifically asked about contact with groups to estimate the Population Attributable Fraction (PAF) due to groups as the relative change in the Basic Reproduction Number when groups are prevented. Findings We estimate that PAF due to groups of 50+ people is 2.2% (95%CI 1.1%, 3.6%); the PAF due to groups of 20+ people is 6.4% (5.0%, 8.0%); the PAF due to groups of 10+ is 11.3% (9.9%, 13.0%) Interpretation Large groups of individuals have a small epidemiological impact; small and medium sized groups between 10 and 50 people have a larger impact on an epidemic. 2020-03-23
Thibaut Jombart; Kevin van Zandvoort; Tim Russell; Christopher Jarvis; Amy Gimma; Sam Abbott; Samuel Clifford; Sebastian Funk; Hamish Gibbs; Yang Liu; Carl Pearson; Nikos Bosse; Centre for the Mathematical Modelling of Infectious Diseases COVID-19 Working Group; Rosalind M Eggo; Adam J Kucharski; John Edmunds Inferring the number of COVID-19 cases from recently reported deaths We estimate the number of COVID-19 cases from newly reported deaths in a population without previous reports. Our results suggest that by the time a single death occurs, hundreds to thousands of cases are likely to be present in that population. This suggests containment via contact tracing will be challenging at this point, and other response strategies should be considered. Our approach is implemented in a publicly available, user-friendly, online tool. 2020-03-13
Kiesha Prem; Yang Liu; Tim Russell; Adam J Kucharski; Rosalind M Eggo; Nicholas Davies; Centre for the Mathematical Modelling of Infectious Diseases COVID-19 Working Group; Mark Jit; Petra Klepac The effect of control strategies that reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China BACKGROUND: In December 2019, a novel strain of SARS-CoV-2 emerged in Wuhan, China. Since then, the city of Wuhan has taken unprecedented measures and efforts in response to the outbreak. METHODS: We quantified the effects of control measures on population contact patterns in Wuhan, China, to assess their effects on the progression of the outbreak. We included the latest estimates of epidemic parameters from a transmission model fitted to data on local and internationally exported cases from Wuhan in the age-structured epidemic framework. Further, we looked at the age-distribution of cases. Lastly, we simulated lifting of the control measures by allowing people to return to work in a phased-in way, and looked at the effects of returning to work at different stages of the underlying outbreak. FINDINGS: Changes in mixing patterns may have contributed to reducing the number of infections in mid-2020 by 92% (interquartile range: 66-97%). There are benefits to sustaining these measures until April in terms of reducing the height of the peak, overall epidemic size in mid-2020 and probability that a second peak may occur after return to work. However, the modelled effects of social distancing measures vary by the duration of infectiousness and the role school children play in the epidemic. INTERPRETATION: Restrictions on activities in Wuhan, if maintained until April, would likely contribute to the reduction and delay the epidemic size and peak, respectively. However, there are some limitations to the analysis, including large uncertainties around estimates of R0 and the duration of infectiousness. 2020-03-12
Timothy W Russell; Joel Hellewell; Christopher I Jarvis; Kevin van-Zandvoort; Sam Abbott; Ruwan Ratnayake; CMMID nCov working group; Stefan Flasche; Rosalind M Eggo; Adam J Kucharski Estimating the infection and case fatality ratio for COVID-19 using age-adjusted data from the outbreak on the Diamond Princess cruise ship Adjusting for delay from confirmation-to-death, we estimated case and infection fatality ratios (CFR, IFR) for COVID-19 on the Diamond Princess ship as 1.2% (0.38-2.7%) and 2.3% (0.75%-5.3%). Comparing deaths onboard with expected deaths based on naive CFR estimates using China data, we estimate IFR and CFR in China to be 0.5% (95% CI: 0.2-1.2%) and 1.1% (95% CI: 0.3-2.4%) respectively. 2020-03-08
Tao Suo; Xinjin Liu; Jiangpeng Feng; Ming Guo; Wenjia Hu; Dong Guo; Hafiz Ullah; Yang Yang; Qiuhan Zhang; Xin Wang; Muhanmmad Sajid; Zhixiang Huang; Liping Deng; Tielong Chen; Fang Liu; Ke Xu; Yuan Liu; Qi Zhang; Yingle Liu; Yong Xiong; Guozhong Chen; Ke Lan; Yu Chen ddPCR: a more sensitive and accurate tool for SARS-CoV-2 detection in low viral load specimens Real time fluorescent quantitative PCR (RT-PCR) is widely used as the gold standard for clinical detection of SARS-CoV-2. However, due to the low viral load in patient throats and the limitations of RT-PCR, significant numbers of false negative reports are inevitable, which results in failure to timely diagnose, early treat, cut off transmission, and assess discharge criteria. To improve this situation, an optimized droplet digital PCR (ddPCR) was used for detection of SARS-CoV-2, which showed that the limit of detection of ddPCR is significantly lower than that of RT-PCR. We further explored the feasibility of ddPCR to detect SARS-CoV-2 nucleic acid from 77 clinical throat swab samples, including 63 suspected outpatients with fever and 14 supposed convalescents who were about to discharge after treatment, and compared with RT-PCR in terms of the diagnostic accuracy. In this double-blind study, we tested, surveyed subsequently and statistically analyzed 77 clinical samples. According to our study, 26 samples from COVID-19 patients with RT-PCR negative were detected as positive by ddPCR. No FPRs of RT-PCR and ddPCR were observed. The sensitivity, specificity, PPV, NPV, NLR and accuracy were improved from 40% (95% CI: 27-55%), 100% (95% CI: 54-100%), 100%, 16% (95% CI: 13-19%), 0.6 (95% CI: 0.48-0.75) and 47% (95% CI: 33-60%) for RT-PCR to 94% (95% CI: 83-99%), 100% (95% CI: 48-100%), 100%, 63% (95% CI: 36-83%), 0.06 (95% CI: 0.02-0.18) and 95% (95% CI: 84-99%) for ddPCR, respectively. Moreover, 14 (42.9 %) convalescents still carry detectable SARS-CoV-2 after discharge. Overall, ddPCR shows superiority for clinical diagnosis of SARS-CoV-2 to reduce the false negative reports, which could be a powerful complement to the current standard RT-PCR. It also suggests that the current clinical practice that the convalescent after discharge continues to be quarantined for at least 2 weeks is completely necessary which can prevent potential viral transmission. 2020-03-06
Yang Yang; Chenguang Shen; Jinxiu Li; Jing Yuan; Minghui Yang; Fuxiang Wang; Guobao Li; Yanjie Li; Li Xing; Ling Peng; Jinli Wei; Mengli Cao; Haixia Zheng; Weibo Wu; Rongrong Zou; Delin Li; Zhixiang Xu; Haiyan Wang; Mingxia Zhang; Zheng Zhang; Lei Liu; Yingxia Liu Exuberant elevation of IP-10, MCP-3 and IL-1ra during SARS-CoV-2 infection is associated with disease severity and fatal outcome The outbreak of Coronavirus Disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in Wuhan, December 2019, and continuously poses a serious threat to public health. Our previous study has shown that cytokine storm occurred during SARS-CoV-2 infection, while the detailed role of cytokines in the disease severity and progression remained unclear due to the limited case number. In this study, we examined 48 cytokines in the plasma samples from 53 COVID-19 cases, among whom 34 were severe cases, and the others moderate. Results showed that 14 cytokines were significantly elevated upon admission in COVID-19 cases. Moreover, IP-10, MCP-3, and IL-1ra were significantly higher in severe cases, and highly associated with the PaO2/FaO2 and Murray score. Furthermore, the three cytokines were independent predictors for the progression of COVID-19, and the combination of IP-10, MCP-3 and IL-1ra showed the biggest area under the curve (AUC) of the receiver-operating characteristics (ROC) calculations. Serial detection of IP-10, MCP-3 and IL-1ra in 14 severe cases showed that the continuous high levels of these cytokines were associated with disease deterioration and fatal outcome. In conclusion, we report three cytokines that closely associated with disease severity and outcome of COVID-19. These findings add to our understanding of the immunopathologic mechanisms of SARS-CoV-2 infection, which suggested novel therapeutic targets and strategy. 2020-03-06
Joe Hilton; Matt J Keeling Estimation of country-level basic reproductive ratios for novel Coronavirus (COVID-19) using synthetic contact matrices The outbreak of novel coronavirus (COVID-19) has the potential for global spread, infecting large numbers in all countries. In this case, estimating the country-specific basic reproductive ratio is a vital first step in public-health planning. The basic reproductive ratio (R0) is determined by both the nature of pathogen and the network of contacts through which the disease can spread - with this network determined by socio-demographics including age-structure and household composition. Here we focus on the age-structured transmission within the population, using data from China to inform age-dependent susceptibility and synthetic age-mixing matrices to inform the contact network. This allows us to determine the country-specific basic reproductive ratio as a multiplicative scaling of the value from China. We predict that R0 will be highest across Eastern Europe and Japan, and lowest across Africa, Central America and South-Western Asia. This pattern is largely driven by the ratio of children to older adults in each country and the observed propensity of clinical cases in the elderly. 2020-02-27
Matt J Keeling; T. Deirdre Hollingsworth; Jonathan M Read The Efficacy of Contact Tracing for the Containment of the 2019 Novel Coronavirus (COVID-19). Contact tracing is a central public health response to infectious disease outbreaks, especially in the early stages of an outbreak when specific treatments are limited. Importation of novel Coronavirus (COVID-19) from China and elsewhere into the United Kingdom highlights the need to understand the impact of contact tracing as a control measure. Using detailed survey information on social encounters coupled to predictive models, we investigate the likely efficacy of the current UK definition of a close contact (within 2 meters for 15 minutes or more) and the distribution of secondary cases that may go untraced. Taking recent estimates for COVID-19 transmission, we show that less than 1 in 5 cases will generate any subsequent untraced cases, although this comes at a high logistical burden with an average of 36.1 individuals (95th percentiles 0-182) traced per case. Changes to the definition of a close contact can reduce this burden, but with increased risk of untraced cases; we estimate that any definition where close contact requires more than 4 hours of contact is likely to lead to uncontrolled spread. 2020-02-17
Leon Danon; Ellen Brooks-Pollock; Mick Bailey; Matt J Keeling A spatial model of CoVID-19 transmission in England and Wales: early spread and peak timing Background: An outbreak of a novel coronavirus, named CoVID-19, was first reported in China on 31 December 2019. As of 9 February 2020, cases have been reported in 25 countries, including probable cases of human-to-human transmission in England. Methods: We adapted an existing national-scale metapopulation model to capture the spread of CoVID-19 in England and Wales. We used 2011 census data to capture population sizes and population movement, together with parameter estimates from the current outbreak in China. Results: We predict that a CoVID-19 outbreak will peak 126 to 147 days (~4 months) after the start of person-to-person transmission in England and Wales in the absence of controls, assuming biological parameters remain unchanged. Therefore, if person-to-person transmission persists from February, we predict the epidemic peak would occur in June. The starting location has minimal impact on peak timing, and model stochasticity varies peak timing by 10 days. Incorporating realistic parameter uncertainty leads to estimates of peak time ranging from 78 days to 241 days after person-to-person transmission has been established. Seasonal changes in transmission rate substantially impact the timing and size of the epidemic peak, as well as the total attack rate. Discussion: We provide initial estimates of the potential course of CoVID-19 in England and Wales in the absence of control measures. These results can be refined with improved estimates of epidemiological parameters, and permit investigation of control measures and cost effectiveness analyses. Seasonal changes in transmission rate could shift the timing of the peak into winter months, which will have important implications for healthcare capacity planning. 2020-02-14
Samuel J Clifford; Carl A B Pearson; Petra Klepac; Kevin Van Zandvoort; Billy J Quilty; - CMMID COVID-19 working group; Rosalind M Eggo; Stefan Flasche Interventions targeting air travellers early in the pandemic may delay local outbreaks of SARS-CoV-2 Background: We evaluated if interventions aimed at air travellers can delay local SARS-CoV-2 community transmission in a previously unaffected country. Methods: We simulated infected air travellers arriving into countries with no sustained SARS-CoV-2 transmission or other introduction routes from affected regions. We assessed the effectiveness of syndromic screening at departure and/or arrival & traveller sensitisation to the COVID-2019-like symptoms with the aim to trigger rapid self-isolation and reporting on symptom onset to enable contact tracing. We assumed that syndromic screening would reduce the number of infected arrivals and that traveller sensitisation reduces the average number of secondary cases. We use stochastic simulations to account for uncertainty in both arrival and secondary infections rates, and present sensitivity analyses on arrival rates of infected travellers and the effectiveness of traveller sensitisation. We report the median expected delay achievable in each scenario and an inner 50% interval. Results: Under baseline assumptions, introducing exit and entry screening in combination with traveller sensitisation can delay a local SARS-CoV-2 outbreak by 8 days (50% interval: 3-14 days) when the rate of importation is 1 infected traveller per week at time of introduction. The additional benefit of entry screening is small if exit screening is effective: the combination of only exit screening and traveller sensitisation can delay an outbreak by 7 days (50% interval: 2-13 days). In the absence of screening, with less effective sensitisation, or a higher rate of importation, these delays shrink rapidly to less than 4 days. Conclusion: Syndromic screening and traveller sensitisation in combination may have marginally delayed SARS-CoV-2 outbreaks in unaffected countries. 2020-02-13
Yang Yang; Minghui Yang; Chenguang Shen; Fuxiang Wang; Jing Yuan; Jinxiu Li; Mingxia Zhang; Zhaoqin Wang; Li Xing; Jinli Wei; Ling Peng; Gary Wong; Haixia Zheng; Mingfeng Liao; Kai Feng; Jianming Li; Qianting Yang; Juanjuan Zhao; Zheng Zhang; Lei Liu; Yingxia Liu Laboratory diagnosis and monitoring the viral shedding of 2019-nCoV infections Background: The outbreak of novel coronavirus pneumonia (NCP) caused by 2019-nCoV spread rapidly, and elucidation the diagnostic accuracy of different respiratory specimens is crucial for the control and treatment of this diseases. Methods: Respiratory samples including nasal swabs, throat swabs, sputum and bronchoalveolar lavage fluid (BALF) were collected from Guangdong CDC confirmed NCP patients, and viral RNAs were detected using a CFDA approved detection kit. Results were analyzed in combination with sample collection date and clinical information. Finding: Except for BALF, the sputum possessed the highest positive rate (74.4%~88.9%), followed by nasal swabs (53.6%~73.3%) for both severe and mild cases during the first 14 days after illness onset (d.a.o). For samples collected [&ge;] 15 d.a.o, sputum and nasal swabs still possessed a high positive rate ranging from 42.9%~61.1%. The positive rate of throat swabs collected [&ge;] 8 d.a.o was low, especially in samples from mild cases. Viral RNAs could be detected in all the lower respiratory tract of severe cases, but not the mild cases. CT scan of cases 02, 07 and 13 showed typical viral pneumonia with ground glass opacity, while no viral RNAs were detected in first three or all the upper respiratory samples. Interpretation: Sputum is most accurate for laboratory diagnosis of NCP, followed by nasal swabs. Detection of viral RNAs in BLAF is necessary for diagnosis and monitoring of viruses in severe cases. CT scan could serve as an important make up for the diagnosis of NCP. Funding National Science and Technology Major Project, Sanming Project of Medicine and China Postdoctoral Science Foundation. 2020-02-12
Joel Hellewell; Sam Abbott; Amy Gimma; Nikos I Bosse; Christopher I Jarvis; Timothy W Russell; James D Munday; Adam J Kucharski; W John Edmunds; CMMID nCoV working group; Sebastian Funk; Rosalind M Eggo Feasibility of controlling 2019-nCoV outbreaks by isolation of cases and contacts Background: To assess the viability of isolation and contact tracing to control onwards transmission from imported cases of 2019-nCoV. Methods: We developed a stochastic transmission model, parameterised to the 2019-nCoV outbreak. We used the model to quantify the potential effectiveness of contact tracing and isolation of cases at controlling a 2019 nCoV-like pathogen. We considered scenarios that varied in: the number of initial cases; the basic reproduction number R0; the delay from symptom onset to isolation; the probability contacts were traced; the proportion of transmission that occurred before symptom onset, and the proportion of subclinical infections. We assumed isolation prevented all further transmission in the model. Outbreaks were deemed controlled if transmission ended within 12 weeks or before 5000 cases in total. We measured the success of controlling outbreaks using isolation and contact tracing, and quantified the weekly maximum number of cases traced to measure feasibility of public health effort. Findings: While simulated outbreaks starting with only 5 initial cases, R0 of 1.5 and little transmission before symptom onset could be controlled even with low contact tracing probability, the prospects of controlling an outbreak dramatically dropped with the number of initial cases, with higher R0, and with more transmission before symptom onset. Across different initial numbers of cases, the majority of scenarios with an R0 of 1.5 were controllable with under 50% of contacts successfully traced. For R0 of 2.5 and 3.5, more than 70% and 90% of contacts respectively had to be traced to control the majority of outbreaks. The delay between symptom onset and isolation played the largest role in determining whether an outbreak was controllable for lower values of R0. For higher values of R0 and a large initial number of cases, contact tracing and isolation was only potentially feasible when less than 1% of transmission occurred before symptom onset. Interpretation: We found that in most scenarios contact tracing and case isolation alone is unlikely to control a new outbreak of 2019-nCov within three months. The probability of control decreases with longer delays from symptom onset to isolation, fewer cases ascertained by contact tracing, and increasing transmission before symptoms. This model can be modified to reflect updated transmission characteristics and more specific definitions of outbreak control to assess the potential success of local response efforts. 2020-02-11
Yang Yang; Qingbin Lu; Mingjin Liu; Yixing Wang; Anran Zhang; Neda Jalali; Natalie Dean; Ira Longini; M. Elizabeth Halloran; Bo Xu; Xiaoai Zhang; Liping Wang; Wei Liu; Liqun Fang Epidemiological and clinical features of the 2019 novel coronavirus outbreak in China Our manuscript was based on surveillance cases of COVID-19 identified before January 26, 2020. As of February 20, 2020, the total number of confirmed cases in mainland China has reached 18 times of the number in our manuscript. While the methods and the main conclusions in our original analyses remain solid, we decided to withdraw this preprint for the time being, and will replace it with a more up-to-date version shortly. Should you have any comments or suggestions, please feel free to contact the corresponding author. 2020-02-11
Adam J Kucharski; Timothy W Russell; Charlie Diamond; Yang Liu; CMMID nCoV working group; John Edmunds; Sebastian Funk; Rosalind M Eggo Early dynamics of transmission and control of 2019-nCoV: a mathematical modelling study Background: An outbreak of the novel coronavirus SARS-CoV-2 has led to 46,997 confirmed cases as of 13th February 2020. Understanding the early transmission dynamics of the infection and evaluating the effectiveness of control measures is crucial for assessing the potential for sustained transmission to occur in new areas. Methods: We combined a stochastic transmission model with data on cases of novel coronavirus disease (COVID-19) in Wuhan and international cases that originated in Wuhan to estimate how transmission had varied over time during January and February 2020. Based on these estimates, we then calculated the probability that newly introduced cases might generate outbreaks in other areas. Findings: We estimated that the median daily reproduction number, Rt , declined from 2.35 (95% CI: 1.15-4.77) one week before travel restrictions were introduced on 23rd January to 1.05 (95% CI: 0.413-2.39) one week after. Based on our estimates of Rt,we calculated that in locations with similar transmission potential as Wuhan in early January, once there are at least four independently introduced cases, there is a more than 50% chance the infection will establish within that population. Interpretation: Our results show that COVID-19 transmission likely declined in Wuhan during late January 2020, coinciding with the introduction of control measures. As more cases arrive in international locations with similar transmission potential to Wuhan pre-control, it is likely many chains of transmission will fail to establish initially, but may still cause new outbreaks eventually. 2020-02-02
Billy Quilty; Sam Clifford; Stefan Flasche; Rosalind M Eggo Effectiveness of airport screening at detecting travellers infected with 2019-nCoV As the number of novel coronavirus cases grows both inside and outside of China, public health authorities require evidence on the effectiveness of control measures such as thermal screening of arrivals at airports. We evaluated the effectiveness of exit and entry screening for 2019-nCoV infection. In our baseline scenario, we estimated that 46.5% (95%CI: 35.9 to 57.7) of infected travellers would not be detected, depending on the incubation period, sensitivity of exit and entry screening, and the proportion of cases which are asymptomatic. Airport screening is unlikely to detect a sufficient proportion of 2019-nCoV infected travellers to avoid entry of infected travellers. We developed an online tool so that results can be updated as new information becomes available. 2020-02-02
Vespignani A, Tian H, Dye C, Lloyd-Smith JO, Eggo RM, Shrestha M, Scarpino SV, Gutierrez B, Kraemer MUG, Wu J, Leung K, Leung GM. Modelling COVID-19. Nature Reviews Physics
Banerjee A, Pasea L, Harris S, Gonzalez-Izquierdo A, Torralbo A, Shallcross L, Noursadeghi M, Pillay D, Sebire N, Holmes C, Pagel C, Wong WK, Langenberg C, Williams B, Denaxas S, Hemingway H. Estimating excess 1-year mortality associated with the COVID-19 pandemic according to underlying conditions and age: a population-based cohort study. Lancet (London, England) 2020
Prem K, Liu Y, Russell TW, Kucharski AJ, Eggo RM, Davies N, Centre for the Mathematical Modelling of Infectious Diseases COVID-19 Working Group, Jit M, Klepac P. The effect of control strategies to reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China: a modelling study. The Lancet. Public health 2020
Hellewell J, Abbott S, Gimma A, Bosse NI, Jarvis CI, Russell TW, Munday JD, Kucharski AJ, Edmunds WJ, Centre for the Mathematical Modelling of Infectious Diseases COVID-19 Working Group, Funk S, Eggo RM. Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts. The Lancet. Global health 2020
Drew DA, Nguyen LH, Steves CJ, Menni C, Freydin M, Varsavsky T, Sudre CH, Cardoso MJ, Ourselin S, Wolf J, Spector TD, Chan AT, COPE Consortium. Rapid implementation of mobile technology for real-time epidemiology of COVID-19. Science (New York, N.Y.) 2020
Quilty BJ, Clifford S, Flasche S, Eggo RM, CMMID nCoV working group. Effectiveness of airport screening at detecting travellers infected with novel coronavirus (2019-nCoV). Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin 2020
Hastie CE, Mackay DF, Ho F, Celis-Morales CA, Katikireddi SV, Niedzwiedz CL, Jani BD, Welsh P, Mair FS, Gray SR, O'Donnell CA, Gill JM, Sattar N, Pell JP. Vitamin D concentrations and COVID-19 infection in UK Biobank. Diabetes & metabolic syndrome 2020
Jit M, Jombart T, Nightingale ES, Endo A, Abbott S, LSHTM Centre for Mathematical Modelling of Infectious Diseases COVID-19 Working Group, Edmunds WJ. Estimating number of cases and spread of coronavirus disease (COVID-19) using critical care admissions, United Kingdom, February to March 2020. Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin 2020
Russell TW, Hellewell J, Jarvis CI, van Zandvoort K, Abbott S, Ratnayake R, Cmmid Covid-Working Group, Flasche S, Eggo RM, Edmunds WJ, Kucharski AJ. Estimating the infection and case fatality ratio for coronavirus disease (COVID-19) using age-adjusted data from the outbreak on the Diamond Princess cruise ship, February 2020. Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin 2020
Been JV, Sheikh A. COVID-19 must catalyse key global natural experiments. Journal of global health 2020
Jarvis CI, Van Zandvoort K, Gimma A, Prem K, CMMID COVID-19 working group, Klepac P, Rubin GJ, Edmunds WJ. Quantifying the impact of physical distance measures on the transmission of COVID-19 in the UK. BMC medicine 2020
Polonsky JA, Baidjoe A, Kamvar ZN, Cori A, Durski K, Edmunds WJ, Eggo RM, Funk S, Kaiser L, Keating P, de Waroux OLP, Marks M, Moraga P, Morgan O, Nouvellet P, Ratnayake R, Roberts CH, Whitworth J, Jombart T. Outbreak analytics: a developing data science for informing the response to emerging pathogens. Philosophical transactions of the Royal Society of London. Series B, Biological sciences 2019
Mizen A, Lyons J, Milojevic A, Doherty R, Wilkinson P, Carruthers D, Akbari A, Lake I, Davies GA, Al Sallakh M, Fry R, Dearden L, Rodgers SE. Impact of air pollution on educational attainment for respiratory health treated students: A cross sectional data linkage study. Health & place 2020
GBD 2017 Lower Respiratory Infections Collaborators. Quantifying risks and interventions that have affected the burden of lower respiratory infections among children younger than 5 years: an analysis for the Global Burden of Disease Study 2017. The Lancet. Infectious diseases 2020
Lewandowski K, Xu Y, Pullan ST, Lumley SF, Foster D, Sanderson N, Vaughan A, Morgan M, Bright N, Kavanagh J, Vipond R, Carroll M, Marriott AC, Gooch KE, Andersson M, Jeffery K, Peto TEA, Crook DW, Walker AS, Matthews PC. Metagenomic Nanopore Sequencing of Influenza Virus Direct from Clinical Respiratory Samples. Journal of clinical microbiology 2019
Global Burden of Disease Health Financing Collaborator Network. Health sector spending and spending on HIV/AIDS, tuberculosis, and malaria, and development assistance for health: progress towards Sustainable Development Goal 3. Lancet (London, England) 2020
Total COVID-19 Research Questions: 137
Question Author Topics
Could we compare the outcomes data for patients who are receiving / not immunosuppressants and validate whether this population group are more vulnerable? HDR UK COVID-19 Team RQ39
SAGE Priority Area: Other conditions
Prioritisation Score(s): 8
Prioritisation Rounds: 1
Funnel Stage: Identify Resource
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A.I. analytics of laboratory variables to predict clinical outcome after Covid-19 Clara Fennessy
Are patients who received a shortened course of immunotherapy less likely to present with severe COVID-19/ have worse outcomes? HDR UK COVID-19 Team RQ44
SAGE Priority Area: Other conditions
Prioritisation Score(s): 6
Prioritisation Rounds: 1
Funnel Stage: Prioritise
COVID-19
SAGE Report
Are there any concomitant treatments/ongoing prescribed medication which are making the outcomes of coronavirus infection worse for patients? HDR UK COVID-19 Team RQ40
SAGE Priority Area: Other conditions
Prioritisation Score(s): 8
Prioritisation Rounds: 1
Funnel Stage: Prioritise
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Are there any treatments which show evidence of improving outcomes for patients infected with coronavirus? HDR UK COVID-19 Team RQ41
SAGE Priority Question: Clinical Health Care Management (SQ20)
SAGE Priority Area: Direct Impact
Prioritisation Score(s): 9
Prioritisation Rounds: 1
Funnel Stage: Prioritise
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Are we systematically recording the barriers we are facing to answer the above resarch questions? HDR UK COVID-19 Team RQ45
SAGE Priority Area: Other
Prioritisation Rounds: 1
Funnel Stage: Sort
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Asymptomatic carriers: do they exist, and what proportion of the population fit into this category? Does this differ with age? Immunology and serology (SQ 1 & SQ6) HDR UK COVID-19 Team RQ51
SAGE Priority Question: Immunology and serology (SQ4, SQ6)
SAGE Priority Area: Indirect impact - socio-economic
Prioritisation Score(s): 8
Prioritisation Rounds: 1
Funnel Stage: Prioritise
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BREATHE: COVID-19 Symptom Checker - Camden & Islington Public Health Chris Orton
BREATHE: COVID-19 Symptom Tracker - Brighton and Sussex Medical School Chris Orton
BREATHE: COVID-19 Symptom Tracker - Cardiff University Chris Orton
BREATHE: COVID-19 Symptom Tracker - DHSC/SPI-M Chris Orton
BREATHE: COVID-19 Symptom Tracker - Dorset Council Chris Orton
BREATHE: COVID-19 Symptom Tracker - Food Standards Agency Chris Orton
BREATHE: COVID-19 Symptom Tracker - Frimley Health Foundation Trust Chris Orton
BREATHE: COVID-19 Symptom Tracker - GSST - NHS Chris Orton
BREATHE: COVID-19 Symptom Tracker - Grampian Data Safe Haven Chris Orton
BREATHE: COVID-19 Symptom Tracker - King's College Hospital Chris Orton
BREATHE: COVID-19 Symptom Tracker - King's College London Chris Orton
BREATHE: COVID-19 Symptom Tracker - Liverpool Women's Hospital Chris Orton
BREATHE: COVID-19 Symptom Tracker - Manchester University Chris Orton
BREATHE: COVID-19 Symptom Tracker - MoD Chris Orton
BREATHE: COVID-19 Symptom Tracker - National Centre for Geospatial Intelligence Chris Orton
BREATHE: COVID-19 Symptom Tracker - Newcastle Chris Orton
BREATHE: COVID-19 Symptom Tracker - Northumberland County Council Chris Orton
BREATHE: COVID-19 Symptom Tracker - Oxford University Chris Orton
BREATHE: COVID-19 Symptom Tracker - Public Health Wales (1095) Chris Orton
BREATHE: COVID-19 Symptom Tracker - Public Health Wales (1128) Chris Orton
BREATHE: COVID-19 Symptom Tracker - Somerset and Dorset NHS Chris Orton
BREATHE: COVID-19 Symptom Tracker - South Warwickshire CCG Chris Orton
BREATHE: COVID-19 Symptom Tracker – CMO NERVTAG Chris Orton
BREATHE: COVID-19 Symptom Tracker – CORSE Inria Research Team Chris Orton
BREATHE: COVID-19 Symptom Tracker – Calderdale Chris Orton
BREATHE: COVID-19 Symptom Tracker – Kirklees Chris Orton
BREATHE: COVID-19 Symptom Tracker – London School of Hygiene and Tropical Medicine Chris Orton
BREATHE: COVID-19 Symptom Tracker – Office for National Statistics Chris Orton
BREATHE: COVID-19 Symptom Tracker – Sheffield Community Contact Tracing Project Chris Orton
BREATHE: COVID-19 Symptom Tracker – Ulster University Chris Orton
BREATHE: COVID-19 Symptom Tracker – University of Exeter Chris Orton
BREATHE: COVID-19 Symptom Tracker – University of Strathclyde Chris Orton
BREATHE: COVID-19 Symptoms Tracker - Department of Education Chris Orton
BREATHE: COVID-19 Symptoms Tracker - Welsh Government Chris Orton
BREATHE: Machine learning to discover new multi-morbidity phenotype's associated with poorer outcomes, health, resilience and wellbeing Chris Orton
BREATHE: Rapid Assistance in Modelling the Pandemic Chris Orton
BREATHE: UK Public Health Emergency Response: COVID-19 Symptom Tracker Chris Orton
BREATHE: Understanding limitations and bias within the ZOE symptom tracker dataset Chris Orton
BREATHE: ZOE COVID-19 Symptom Tracker – UK Public Health Emergency Response Chris Orton
COG-UK: Can study of the whole virus genome enable scientists to monitor changes at a national scale, reveal how the virus is spreading and whether different strains are emerging? (RQ01) HDR UK COVID-19 Team RQ01
SAGE Priority Question: Virology (SQ11)
SAGE Priority Area: Direct Impact
Prioritisation Score(s): Auto-prioritised
Funnel Stage: Analysis, User Management
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virus genome
virus strain
Funnel Stage: Published Insights
Can a web-based intervention reduce anxiety and worry for people shielding indefinitely with long-term conditions? HDR UK COVID-19 Team RQ58
SAGE Priority Area: Direct Impact
Prioritisation Score(s): 7
Prioritisation Rounds: 1
Funnel Stage: Prioritise
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Can the UK agree on a uniform way COVID-19 is recorded in EHRs? HDR UK COVID-19 Team RQ08
SAGE Priority Area: Other
Funnel Stage: Sort
COVID-19
Prioritisation Rounds: 0
EHR
data recording
Can we analyse doctors' notes in medical records of COVID-19 patients, using natural language processing (NLP), to gain insights onto the disease? HDR UK COVID-19 Team RQ15
SAGE Priority Area: Direct Impact
Prioritisation Rounds: 1
Funnel Stage: Sort
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Can we better engage the public in our COVID-19 research and innovation activities? HDR UK COVID-19 Team RQ21
SAGE Priority Area: Other
Prioritisation Rounds: 1
Funnel Stage: Sort
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Can we create dummy datasets on the EHR COVID data for analyses and model set up? HDR UK COVID-19 Team RQ12
SAGE Priority Area: Other
Prioritisation Rounds: 1
Funnel Stage: Sort
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Can we have support in setting up a national platform for appropriately reviewed publications on COVID? HDR UK COVID-19 Team RQ13
SAGE Priority Area: Indirect Impact - healthcare pressures
Prioritisation Rounds: 1
Funnel Stage: Sort
COVID-19
SAGE Report
Can we identify vulnerable groups from users of the UK's largest mental health service provider? HDR UK COVID-19 Team RQ09
SAGE Priority Area: Direct Impact
Prioritisation Score(s): 6
Funnel Stage: Prioritise
COVID-19
SAGE Priority Area: Other conditions
vulnerable patients
mental health
Prioritisation Rounds: 2
Can we predict the likelihood of an individual’s risk of complications/hospital admission/mortality upon contracting or suspected to have contracted COVID-19 given demographics, pre-existing conditions, symptoms and vital sign data collected from a smartphone app? HDR UK COVID-19 Team RQ26
SAGE Priority Area: Indirect Impact - socio-economic
Prioritisation Score(s): 7.5
Prioritisation Rounds: 1
Funnel Stage: Prioritise
COVID-19
SAGE Report
Can we set up a national COVID-19 surveillance platform? HDR UK COVID-19 Team RQ06
SAGE Priority Area: Other
Funnel Stage: Sort
COVID-19
surveillance
Prioritisation Rounds: 0
Can we simply provide an daily symptom journal app to provide geospatial tracking of pre-covid symptoms? HDR UK COVID-19 Team RQ16
SAGE Priority Area: Direct Impact
Prioritisation Score(s): 7.5
Prioritisation Rounds: 2
Funnel Stage: Analysis, User Management
COVID-19
SAGE Report
Can we use longitudinal peripheral blood measurements, such as leukocyte counts, liver fucntion readouts etc., to predect time of progression in disease severity using machine learning methods? HDR UK COVID-19 Team RQ49
SAGE Priority Area: Direct Impact
Prioritisation Score(s): 7
Prioritisation Rounds: 1
Funnel Stage: Prioritise
COVID-19
SAGE Report
Cancer and COVID-19; how do we manage cancer optimally through a public health crisis? HDR UK COVID-19 Team RQ48
SAGE Priority Question: Clinical Health Care Management (SQ23)
SAGE Priority Area: Direct Impact
Prioritisation Score(s): 8
Prioritisation Rounds: 1
Funnel Stage: Prioritise
COVID-19
SAGE Report
Could we analyse COVID mortality/hospitalisations/need for ICU amongst patients taking monoclonal antibodies versus those not taking them? HDR UK COVID-19 Team RQ85
SAGE Priority Area: Direct Impact
Prioritisation Score(s): 7
Prioritisation Rounds: 1
Funnel Stage: Prioritise
COVID-19
SAGE Report
Could we analyse NHS resilience analysis from linked disease status; hospital treatment; and critical care data to facilitate improved models? HDR UK COVID-19 Team RQ73
SAGE Priority Area: Direct Impact, Indirect Impact - healthcare pressures
Prioritisation Score(s): 6
Prioritisation Rounds: 1
Funnel Stage: Prioritise
COVID-19
SAGE Report
Could we analyse the biological interventions prescribed by class in COVID-19 positive patients? HDR UK COVID-19 Team RQ82
SAGE Priority Area: Direct Impact
Prioritisation Score(s): 6
Prioritisation Rounds: 1
Funnel Stage: Prioritise
COVID-19
SAGE Report
Could we analyse the different clinical pathway approaches to COVID-19 positive patients? Ronan Lyons RQ79
SAGE Priority Area: Other
Prioritisation Score(s): 8
Prioritisation Rounds: 1
Funnel Stage: Prioritise
COVID-19
SAGE Report
Could we analyse the impact of COVID-19 by Occupational Group (to help address the limitation of ONS data), with a focus on key workers? Ronan Lyons RQ77
SAGE Priority Area: Direct Impact
Prioritisation Score(s): 8
Prioritisation Rounds: 1
Funnel Stage: Prioritise
COVID-19
SAGE Report
occupational group
key workers
Could we analyse the incidence of COVID-19 on severe mental health vulnerable groups and subgroups - e.g. schizophrenia and treatment resistant schizophrenia HDR UK COVID-19 Team RQ81
SAGE Priority Area: Direct Impact
Prioritisation Score(s): 8
Prioritisation Rounds: 1
Funnel Stage: Prioritise
COVID-19
SAGE Report
Could we analyse the mediating factors to better understand the impact of health inequalities on COVID-19 incidence? Ronan Lyons RQ72
SAGE Priority Area: Indirect Impact-socioeconomic, other conditions
Prioritisation Score(s): 8
Prioritisation Rounds: 1
Funnel Stage: Prioritise
COVID-19
SAGE Report
health inequalities
Could we analyse the readmission rates for COVID-19? HDR UK COVID-19 Team RQ78
SAGE Priority Area: Direct Impact, Indirect Impact - healthcare pressures
Prioritisation Score(s): 8
Prioritisation Rounds: 1
Funnel Stage: Prioritise
COVID-19
SAGE Report
readmission
Could we attempt to correlate frailty as measured by the electronic frailty index (eFI) as a possible predictor of COVID-19 hospitalisation, ICU/ITU and death? Ronan Lyons RQ80
SAGE Priority Area: Other
Prioritisation Score(s): 8
Prioritisation Rounds: 1
Funnel Stage: Prioritise
COVID-19
SAGE Report
electronic frailty index
ICU
eFI
Could we investigate the impact of COVID-19 on Acute Kidney Injury (AKI)? HDR UK COVID-19 Team RQ84
SAGE Priority Area: Direct Impact
Prioritisation Score(s): 6
Prioritisation Rounds: 1
Funnel Stage: Prioritise
COVID-19
SAGE Report
Could we link the incidence and prevalence data from Zoe Symptom Tracker app and the patient journies through the health systems with the potential to link to outcomes? HDR UK COVID-19 Team RQ76
SAGE Priority Area: Other
Prioritisation Score(s): 6
Prioritisation Rounds: 1
Funnel Stage: Prioritise
COVID-19
SAGE Report
Could we study the long-term impact of COVID-19 on critical care planning and future wave preparation? HDR UK COVID-19 Team RQ75
SAGE Priority Area: Other
Prioritisation Score(s): 7
Prioritisation Rounds: 1
Funnel Stage: Prioritise
COVID-19
SAGE Report
Could we track the patient flow metrics from incidence, adminssion through to ITU and outcome? HDR UK COVID-19 Team RQ74
SAGE Priority Area: Other
Prioritisation Score(s): 5
Prioritisation Rounds: 1
Funnel Stage: Prioritise
COVID-19
SAGE Report
CovidLife Survey HDR UK COVID-19 Team RQ64
SAGE Priority Area: Indirect Impact - socio-economic
Prioritisation Score(s): N/A (as sub question to RQ22)
Prioritisation Rounds: 1
Funnel Stage: Prioritise(d) as subset to RQ22
COVID-19
SAGE Report
DATA-CAN: Cancer Real Time data network (COVID-19) HDR UK COVID-19 Team DATA-CAN Gateway
Does COVID-19 incidence, hospitalisation and mortility rates differ for patients taking Non-steroidal Anti-inflammatory Drugs (NSAID) and controls? HDR UK COVID-19 Team RQ83
SAGE Priority Area: Direct Impact
Prioritisation Score(s): 6
Prioritisation Rounds: 1
Funnel Stage: Prioritise
COVID-19
SAGE Report
Does air quality affect susceptibility to COVID-19? How is the COVID-19 pandemic affecting air quality? HDR UK COVID-19 Team RQ37
SAGE Priority Area: Direct Impact
Prioritisation Score(s): 5.5
Prioritisation Rounds: 1
Funnel Stage: Prioritise
COVID-19
SAGE Report
Does having oestrogen lead to a reduction in the severity and mortality of COVID-19? HDR UK COVID-19 Team RQ60
SAGE Priority Area: Direct Impact
Prioritisation Score(s): 6.5
Prioritisation Rounds: 1
Funnel Stage: Prioritise
COVID-19
SAGE Report
Does oxytocin explain the morbidity and susceptibility patterns in COVID-19? HDR UK COVID-19 Team RQ65
SAGE Priority Area: Direct Impact
Prioritisation Score(s): 6
Prioritisation Rounds: 1
Funnel Stage: Prioritise
COVID-19
SAGE Report
Does receiving androgen-deprivation therapies for prostate cancer lower the risk of infection by SARS-CoV-2? HDR UK COVID-19 Team RQ70
SAGE Priority Area: Other conditions
Prioritisation Score(s): 6
Prioritisation Rounds: 1
Funnel Stage: Prioritise
COVID-19
SAGE Report
Ethnicity and outcomes in COVID-19 Clara Fennessy
Ethnicity and risk of death in patients hospitalised for COVID-19 infection in the UK: an observational cohort study in an urban catchment area. Clara Fennessy
Given Hong Kong/Singapore past experience with Mass Thermal Imaging at major hubs why not extend it into schools, airports and other industries? HDR UK COVID-19 Team RQ66
SAGE Priority Area: Direct Impact
Prioritisation Score(s): 5
Prioritisation Rounds: 1
Funnel Stage: Prioritise
COVID-19
SAGE Report
How can data best support the recovery and restoration of cancer/health and care services: including ongoing treatment, diagnostic tests, appointments, screening services and palliative care (factoring in regional variation of impact)? HDR UK COVID-19 Team SAGE Report
Prioritisation Score(s): 8.5
SAGE Priority Area: Indirect Impact - healthcare pressures
SAGE Priority Area: Other conditions
RQ89
Funnel Stage: Prioritise
COVID-19
recovery
cancer
healthcare services
health professionals
ongoing treatment
palliative care
regional variation
How can we build from existing studies (e.g. Kings and internationally) that have looked at the effect of ACE inhibitors and Angiotensin Receptor Blockers on predisposition to COVID-19? HDR UK COVID-19 Team RQ57
SAGE Priority Area: Direct Impact
Prioritisation Score(s): 8
Prioritisation Rounds: 1
Funnel Stage: Identify Resource
COVID-19
SAGE Report
How can we ensure that we fully understand variations in response to COVID-19 infection at the molecular, environmental, social and economic levels, by effectively coordinating the UK's longtidudinal population stuides to gain a much richer understanding of disease progression and outcomes? HDR UK COVID-19 Team David Porteous RQ35
SAGE Priority Question: Clinical and Health Care Management (SQ17)
SAGE Priority Area: Direct impact
Prioritisation Score(s): 8
Prioritisation Rounds: 1
COVID-19
SAGE Report
Funnel Stage: 7 - Analysis, User Management
response to COVID-19
longtidudinal population studies
patient outcomes
How can we explain the differences in COVID-19 cases and deaths by key socio-demographic factors of age, sex, socioeconomic status, geographical location and ethnicity (BME groups)? HDR UK COVID-19 Team RQ34
SAGE Priority Area: Direct impact
Prioritisation Score(s): 10
Prioritisation Rounds: 1
Funnel Stage: Published Insights
COVID-19
SAGE Report
ethnicity
BAME
socio-demographic factors
How can we maximise the speed and power of host genomic studies internationally to inform drug development? HDR UK COVID-19 Team RQ36
SAGE Priority Area: Direct Impact
Prioritisation Score(s): 8
Prioritisation Rounds: 2
Funnel Stage: Analysis, User Management
COVID-19
SAGE Report
How can we measure the ongoing prevalnce of COVID-19 following idenitifcation of a "good enough" antibody diagnosic? HDR UK COVID-19 Team RQ04
SAGE Priority Question: Epidemiology (SQ1)
SAGE Priority Area: Direct Impact
Prioritisation Score(s): 9
Prioritisation Rounds: 1
Funnel Stage: Prioritise
COVID-19
SAGE Report
antibodies
antibody diagnostic
vulnerable patients
representative sampling
How can we use health data to determine the proportion of the population not susceptible to COVID-19 (e.g. groups who have tested positive but haven’t shown any symptoms)? What is the potential scale of this and how can this information be used to inform decision making around the management of the disease? HDR UK COVID-19 Team COVID-19
SAGE Report
SAGE Priority Area: Direct Impact
Prioritisation Score(s): 8
Funnel Stage: Prioritise
testing
population
susceptibility to COVID-19
RQ104
How has the delivery of primary care to vulnerable patient groups changed during the NHS response to the COVID-19 pandemic? HDR UK COVID-19 Team RQ62
SAGE Priority Area: Indirect Impact - healthcare pressures
Prioritisation Score(s): 8
Prioritisation Rounds: 1
Funnel Stage: Identify Resource
COVID-19
SAGE Report
How long will immunity last following infection, and what level of protection is available against different mutant strains? What is the most effective approach for identifying people as recovered/immune? HDR UK COVID-19 Team RQ50
SAGE Priority Area: Direct Impact
Prioritisation Score(s): 9
COVID-19
SAGE Report
Prioritisation Rounds: 2
Funnel Stage: Analysis, User Management
immunity
INSIGHT: COVID-19 Exemplar Clara Fennessy
ISARIC-CCP: What are the clinical characteristics of COVID-19 positive patients; what are the determinants (genetic, other omic, prior medical history, other) of good and poor outcome; and how can knowledge of this help to target clinical and public health strategies? (RQ05) HDR UK COVID-19 Team RQ05
SAGE Priority Area: Direct Impact
Prioritisation Score(s): Auto-prioritised
COVID-19
SAGE Report
SAGE Priority Area: Other Conditions
Research Funnel Stage: 7 - Analysis, User Management
characteristics
determinants
genetic
omic
medical history
CCP-UK
Is it possible to predict the likelihood of ICU admission and provide real time data on outcomes per COVID-19 admission? HDR UK COVID-19 Team Jose Sousa RQ11
SAGE Priority Question: Clinical Health Care Management (SQ16 & SQ23)
SAGE Priority Area: Direct Impact
Prioritisation Score(s): 8.5
Prioritisation Rounds: 2
Funnel Stage: Analysis, User Management
COVID-19
SAGE Report
SAGE Priority Area: Indirect Impact - healthcare pressures
SAGE Priority Area: Other conditions
SAGE Priority Area: Indirect Impact - socio-economic
EHR
ICU
age
demographics
pre-existing conditions
symptoms
clinical data
hospital data
Is the Clinical Frailty Index (recorded at hospital presentation) acting as a useful for likely ICU referral? HDR UK COVID-19 Team RQ43
SAGE Priority Area: Direct Impact
Prioritisation Score(s): 6.5
Prioritisation Rounds: 1
Funnel Stage: Prioritise
COVID-19
SAGE Report
Is the use of C-pap/Bi-Pap a useful lower acuity intervention before intubation? HDR UK COVID-19 Team RQ56
SAGE Priority Area: Direct Impact
Prioritisation Score(s): 7.5, 6.5
Prioritisation Rounds: 1
Funnel Stage: Prioritise
COVID-19
SAGE Report
LTC COVID HDR UK COVID-19 Team Alice Turnbull
LTC COVID HDR UK COVID-19 Team Alice Turnbull
NHSX would like to create a national database of chest X-rays images that enables the validation and supports development of automated diagnosis technologies in response to the COVID-19 pandemic HDR UK COVID-19 Team RQ25
SAGE Priority Area: Direct Impact
Prioritisation Rounds: 1
Funnel Stage: Sort
COVID-19
SAGE Report
PIONEER: A.I. analytics of laboratory variables to predict clinical outcome after Covid-19 Clara Fennessy Shekha Modhwadia
PIONEER: Ethnicity and outcomes in COVID19 Clara Fennessy Shekha Modhwadia
PIONEER: Ethnicity and risk of death in patients hospitalised for COVID-19 infection in the UK: an observational cohort study in an urban catchment area Clara Fennessy Shekha Modhwadia
PIONEER: Prognostic models for COVID-19 in secondary care Clara Fennessy Shekha Modhwadia
PIONEER: Secondary bacterial infections in COVID 19 Clara Fennessy Shekha Modhwadia
Prognostic models for COVID-19 in secondary care Clara Fennessy
RECOVERY: Can Lopinavir-Ritonavir vs Interferon β vs lowdose corticosteroids be effective in treating COVID 19 test +ve hospitalised patients? (RQ18) HDR UK COVID-19 Team RQ18
SAGE Priority Question: Treatments & Preventative Measures (SQ26)
SAGE Priority Area: Direct Impact
Prioritisation Score(s): Auto-prioritised
Funnel Stage: Analysis, User Management
COVID-19
SAGE Report
Risk stratification for patients treated with drugs affecting the immune system: a) In patients receiving drugs affecting the immune system (e.g. patients with gastrointestinal/liver conditions and/or patients with dermatological conditions) and who have been infected by COVID-19, what factors are associated with an increased risk of poor outcomes?b) Compared to individuals infected by COVID-19 who are not receiving drugs affecting the immune system, do individuals infected by COVID-19 who are receiving drugs affecting the immune system have an increased risk of severe illness from COVID? (RQ102) HDR UK COVID-19 Team Brett Doble Prioritisation Score(s): 8
SAGE Report
RQ102
SAGE Priority Area: Other Conditions
Prioritisation Rounds: 1
risk stratification
co-morbidities
immune system
severe COVID-19
Secondary bacterial infections in COVID 19 Clara Fennessy
Socioeconomic inequalities: Analysis by postcode IMD. What's the best way to provide targeted and tailored messages to diverse communities? HDR UK COVID-19 Team RQ23
SAGE Priority Question: Behavioural Science (SQ39)
SAGE Priority Area: Direct Impact
Prioritisation Score(s): 8
Prioritisation Rounds: 1
Funnel Stage: Identify Resource
COVID-19
SAGE Report
To create and use a high resolution COVID-19 data resource based on data from digitally mature hospital trusts to enable near real time advanced data analytics, producing predictive tools to guide clinical decision making (DeCOVID) HDR UK COVID-19 Team RQ31
SAGE Priority Area: Direct Impact
Prioritisation Score(s): 8.5
Prioritisation Rounds: 1
Funnel Stage: Prioritise
COVID-19
SAGE Report
To what extent can key workers be protected by immunoglobulin extracted from sick patients? Can this be feasibly scaled? HDR UK COVID-19 Team RQ54
SAGE Priority Area: Direct Impact
Prioritisation Score(s): 8
Prioritisation Rounds: 1
Funnel Stage: Prioritise
COVID-19
SAGE Report
To what extent does the strain in the UK match international profiles, and so will genomic research in the UK be universally applicable? HDR UK COVID-19 Team RQ53
SAGE Priority Area: Direct Impact
Prioritisation Score(s): 7.5
Prioritisation Rounds: 1
Funnel Stage: Prioritise
COVID-19
SAGE Report
Two initiatives in relation to a mortality heat map and analysis of COVID mortality relating to ethnicity and deprivation HDR UK COVID-19 Team RQ68
SAGE Priority Area: Indirect Impact - healthcare pressures, Indirect Impact - socio-economic, Other conditions
Prioritisation Rounds: 1
COVID-19
SAGE Report
Funnel Stage: Prioritise
Prioritisation Score: 9
ethnicity
BAME
mortality
Understanding vulnerable patients: How are underlying conditions defined, and what is the impact of infection on a range of outcomes, and what are the benefits of 'shielding' and other preventive interventions? Linked question: COVID-19 Risk prediction (Relevant to “How do we best understand and protect vulnerable populations?”) HDR UK COVID-19 Team RQ32
SAGE Priority Area: Direct Impact
Prioritisation Score(s): 9
Prioritisation Rounds: 1
COVID-19
SAGE Report
Funnel Stage: Analysis, User Management
vulnerable groups
underlying conditions
risk prediction
Visual research of CoV familiy of viruses (CoVID-19, SARS, MERS) as seen through SEM/TEM/hematology analyzer? HDR UK COVID-19 Team RQ02
SAGE Priority Area: Direct Impact
Prioritisation Score(s): 4.5
Funnel Stage: Prioritise
COVID-19
virus strain
SEM/TEM/hematology analyzer
Prioritisation Rounds: 2
We should include social determinants, including social norms and discourse in different communities in any epidemiological questions raised HDR UK COVID-19 Team RQ17
SAGE Priority Area: Indirect Impact - socio-economic
Prioritisation Rounds: 1
Funnel Stage: Sort
COVID-19
SAGE Report
What are 30 day and longer term outcomes of patients with and without infection admitted to hospital? There are important biases in considering only inhospital deaths; the health consequences of infection after discharge are poorly understood. HDR UK COVID-19 Team RQ33
SAGE Priority Area: Direct Impact
Prioritisation Score(s): 7, 6
Prioritisation Rounds: 1
Funnel Stage: Prioritise
COVID-19
SAGE Report
What are the COVID-19 impacts on shielded individuals? HDR UK COVID-19 Team RQ71
SAGE Priority Area: Direct Impact
Prioritisation Score(s): 7.5
Prioritisation Rounds: 1
Funnel Stage: Prioritise
COVID-19
SAGE Report
What are the consequences of COVID-19 infection on respiratory health and disease as assessed in (i) general populations previously characterised for respiratoiry health (including spirometry) and (ii) among people discharged after severe COVID-19? HDR UK COVID-19 Team RQ38
SAGE Priority Area: Other conditions
Prioritisation Score(s): 7.5, 6
Prioritisation Rounds: 1
Funnel Stage: Prioritise
COVID-19
SAGE Report
What are the consequences of COVID-19 on pregnancy outcomes for both mothers & babies? HDR UK COVID-19 Team RQ46
SAGE Priority Area: Indirect Impact - socio-economic
Prioritisation Score(s): 7.5, 6.5
Prioritisation Rounds: 1
Funnel Stage: Prioritise
COVID-19
SAGE Report
What are the direct and indirect effects of SARS-Cov2/COVID-19 on incidence, presentation, diagnosis, management, and prognosis of cancer patients and which patients are most susceptible to these direct and indirect effects? HDR UK COVID-19 Team RQ59
SAGE Priority Question: Clinical Health Care Management (SQ23)
SAGE Priority Area: Direct Impact
Prioritisation Score(s): 8.5
Prioritisation Rounds: 2
Funnel Stage: Analysis, User Management
COVID-19
SAGE Report
What are the direct and indirect impacts of COVID-19 on care home residents? HDR UK COVID-19 Team RQ63
SAGE Priority Area: Direct Impact
Prioritisation Score(s): 8
Prioritisation Rounds: 1
Funnel Stage: Prioritise
COVID-19
SAGE Report
care homes
What are the efects of COVID-19 on people affected by Multiple Sclerosis? HDR UK COVID-19 Team RQ20
SAGE Priority Area: Other conditions
Prioritisation Score(s): 6
Funnel Stage: Prioritise
COVID-19
SAGE Report
What are the long-lasting indirect implications for clinical outcomes and healthcare workload (within primary and secondary care) as a result of the alteration of health-seeking behaviours from the COVID-19 lockdown? Initiative: Monitoring Attendance, INvestigation, Referral, and OUTcomEs in Primary Care: impact of and recovery from COVID-19 lockdown (MAINROUTE) HDR UK COVID-19 Team MAINROUTE
lockdown
behaviours
recovery
SAGE Report
COVID-19
RQ94
Prioritisation Rounds: 1
Prioritisation Score(s): 9
SAGE Priority Area: Indirect Impact - healthcare pressures
SAGE Priority Area: Indirect Impact - socio-economic
Funnel Stage: Prioritise
What are the long-term mental health impacts of COVID-19 social isolation measures? HDR UK COVID-19 Team RQ24
SAGE Priority Question: Clinical/healthcare management (SQ23)
SAGE Priority Area: Indirect Impact - socio-economic
Prioritisation Score(s): 8
Prioritisation Rounds: 1
Funnel Stage: Prioritise
COVID-19
SAGE Report
What are the psychological, social and economic consequences of policies to limit the spread and flatten the peak of COVID 19? HDR UK COVID-19 Team David Porteous RQ22
SAGE Priority Question: Behavioural Science (SQ45)
SAGE Priority Area: Indirect Impact - socio-economic
Prioritisation Score(s): 8
Prioritisation Rounds: 2
Funnel Stage: Analysis, User Management
COVID-19
SAGE Report
What is the best route for understanding the number of people in vulnerable categories? HDR UK COVID-19 Team RQ10
SAGE Priority Area: Direct Impact
Prioritisation Score(s): 7
Funnel Stage: Prioritise
COVID-19
location
vulnerable patients
HES
CRPD
Prioritisation Rounds: 2
What is the diagnostic accuracy of multiple current and emerging Point-of-Care-Tests (POCTS) for active and past COVID-19 infection in the community setting? HDR UK COVID-19 Team COVID-19
SAGE Report
Prioritisation Score(s): 9
SAGE Priority Area: Direct Impact
SAGE Priority Area: Indirect Impact - socio-economic
SAGE Priority Area: Indirect Impact - healthcare pressures
RQ95
Prioritisation Rounds: 1
serology
POCTs
RAPTOR-C19
Funnel Stage: Prioritise
What is the impact of starting inhaled corticosteroids early in the course of COVID-19 illness (first 7 days of symptoms) in preventing the deterioration of illness, which then leads to ED presentation and hospitalisation? HDR UK COVID-19 Team COVID-19
SAGE Report
SAGE Priority Area: Direct Impact
SAGE Priority Area: Indirect Impact - healthcare pressures
Prioritisation Score(s): 8
Prioritisation Rounds: 1
Funnel Stage: Prioritise
corticosteriods
hospitalisation
What is the influence of COVID 19 epidemic in the UK and the NHS response to this on presentation, management and prognosis of non-COVID disease, in particular cardiovascular diseases such as MI and stroke? HDR UK COVID-19 Team RQ29
SAGE Priority Question: Clinical Health Care Management (SQ16 & SQ23)
SAGE Priority Area: Indirect Impact- healthcare pressures
Prioritisation Score(s): 8.5
Prioritisation Rounds: 4
Funnel Stage: Ethics, Funding, Access, Decision Making
COVID-19
SAGE Report
What is the influence of COVID-19 on subsequent cardiovascular disease outcomes? HDR UK COVID-19 Team RQ28
SAGE Priority Area: Other conditions
Prioritisation Score(s): 7
Prioritisation Rounds: 1
Funnel Stage: Prioritise
COVID-19
SAGE Report
What is the influence of diabetes as an independent risk factor for infection and poorer outcomes of COVID-19? HDR UK COVID-19 Team RQ67
SAGE Priority Area: Other conditions
Prioritisation Score(s): 7.5
Prioritisation Rounds: 1
Funnel Stage: Prioritise
COVID-19
SAGE Report
What is the influence of pre-existing cardiovascular disease on outcomes of COVID-19 infection? Linked question: What is the influence of pre-existing cancer impact on outcomes of COVID-19 infection? HDR UK COVID-19 Team RQ30
SAGE Priority Area: Other conditions
Prioritisation Score(s): 8
Prioritisation Rounds: 1
Funnel Stage: Identify Resource
COVID-19
SAGE Report
What is the outcome (hospital admission / ITU admission / death) for patients with Inflammatory bowel disease / IBD on immunosuppressant or anti-TNF therapies who test +ve for Covid19? HDR UK COVID-19 Team RQ61
SAGE Priority Area: Direct Impact
Prioritisation Score(s): 5
Prioritisation Rounds: 1
Funnel Stage: Prioritise
COVID-19
SAGE Report
What is the time delay between first symptom development (as self-reported by patients), hospital presentation. Does this time delay influence rates of ICU referral and mortality? HDR UK COVID-19 Team RQ42
SAGE Priority Area: Direct Impact
Prioritisation Score(s): 6.5
Prioritisation Rounds: 1
Funnel Stage: Prioritise
COVID-19
SAGE Report
Which antibodies treatments reduce lung damage in cytokine release storms? HDR UK COVID-19 Team RQ55
SAGE Priority Area: Direct Impact
Prioritisation Score(s): 8
Prioritisation Rounds: 1
Funnel Stage: Prioritise
COVID-19
SAGE Report
antibody treatments
cykotine release storms
Which people in the high risk/shielded patients list could directly benefit from vaccination? HDR UK COVID-19 Team RQ69
SAGE Priority Area: Direct Impact
Prioritisation Score(s): 7
Prioritisation Rounds: 1
Funnel Stage: Prioritise
COVID-19
SAGE Report
Total COVID-19 Tools: 15
Author Tool name Topics Features
Susheel Varma Global Coronavirus COVID-19 Clinical Trial Tracker COVID-19
Clinical Trial
Community Tracking
HDR UK COVID-19 Team COVID-19 Symptom Tracker App COVID-19 Symptom Tracker
HDR UK COVID-19 Team COVID-19 CovidSim Microsimulation Model COVID-19 Modelling
Spiros Denaxas OurRisk.CoV COVID-19 Risk Calculator
electronic health records
HDR UK COVID-19 Team COVID-19 Phenomics COVID-19 Phenomics
HDR UK COVID-19 Team BSTI COVID-19 Imaging Database COVID-19
HDR UK COVID-19 Team COVID-19 Contact Tracing App - iOS COVID-19 Contact Tracing
iOS
HDR UK COVID-19 Team COVID-19 Contact Tracing App - Android COVID-19 Contact Tracing
Android
HDR UK COVID-19 Team Public Health England COVID-19 Tracker COVID-19
HDR UK COVID-19 Team C19 Track COVID-19 Community Tracking
Susheel Varma ISARIC 4C prognostic score COVID-19
Respiratory
Infection
Risk Calculator
HDR UK COVID-19 Team CMMID Interactive Applications COVID-19 Modelling
Visualisation
Clara Fennessy Shekha Modhwadia MS SQL / SSIS Blood
Cancer and neoplasms
Congenital disorders
COVID-19
Ear
Infection
Inflammatory and immune system
Injuries and accidents
Mental health
Metabolic and Endocrine
Musculoskeletal
Neurological
Oral and Gastrointestinal
Renal and Urogenital
Respiratory
Skin
Stroke
Association Rules
Bayesian Statistics
Collaborative Filtering
Data management
Graphs
Indexation / Cataloguing
Search Engine
Susheel Varma ggquickeda COVID-19
Infection
Clara Fennessy Chris Orton SAIL Databank Blood
Cancer and neoplasms
Cardiovascular
Congenital disorders
Clinical Trial
COVID-19
Eye
Ear
Haemodynamics
Infection
Inflammatory and immune system
Injuries and accidents
Mental health
Metabolic and Endocrine
Musculoskeletal
Neurological
Oral and Gastrointestinal
Renal and Urogenital
Reproductive health and childbirth
Respiratory
Skin
Stroke
Repository
Service
Software
Virtual Machine
Arbitrage
Attribution Modeling
Bayesian Statistics
Clustering
Community Tracking
Data management
Deep Learning
Geospatial Modeling
Graphs
Indexation / Cataloguing
Linear Regression
Linkage Analysis
Logistic Regression
Modelling
Monte-Carlo Simulation
Naive Bayes
Phenomics
Predictive Modeling
Risk Calculator
Survival Analysis
Symptom Tracker
Total entries: 75
National TREs Datasets Available for Linkage Data within TREs Metadata on Gateway
Wales (SAIL Databank) ADBE Annual District Birth Extract (ONS Births) Available Yes
Wales (SAIL Databank) ADDD Annual District Death Daily (ONS Deaths) Available Yes (see ADDE)
Wales (SAIL Databank) ADDE Annual District Death Extract (ONS Deaths) Available Yes
Wales (SAIL Databank) CAPD – Cancelled Admitted Procedures Dataset Available Yes
Wales (SAIL Databank) CARE Care homes index Available No
Wales (SAIL Databank) CARS Congenital Anomaly Register and Information Services for Wales Available (but needs update) Yes
Wales (SAIL Databank) CCDS Critical Care Data Set Available Yes
Wales (SAIL Databank) CDDS Consolidated Death Data Source Available No
Wales (SAIL Databank) CVSD COVID-19 Sequence Data Agreed - data being acquired No
Wales (SAIL Databank) CVST Zoe Symptom Tracker App (Linkable version) Available Yes
Wales (SAIL Databank) CVST Zoe Symptom Tracker App (Unlinkable version) Available Yes
Wales (SAIL Databank) CVVP COVID-19 Vulnerable People list Available No
Wales (SAIL Databank) CYFI Cystic Fibrosis Register Agreed - data being updated No
Wales (SAIL Databank) DATW – Diagnostics And Therapy services Waiting times Available Yes
Wales (SAIL Databank) EDDD Emergency Department Data Daily Available See EDDS
Wales (SAIL Databank) EDDS Emergency Department Data Set Available Yes
Wales (SAIL Databank) EDUW Education data on schools and pupils Available No
Wales (SAIL Databank) ICNC ICNARC – Intensive Care National Audit & Research Centre Available No
Wales (SAIL Databank) LIMS Laboratory Information Management System (COVID test results) Available No
Wales (SAIL Databank) NICO – NICOR audits and Registers Permission being sought No
Wales (SAIL Databank) NCCH National Community Child Health database Available No
Wales (SAIL Databank) NHSO NHS 111 Call data (telephony, activity, 999) Agreed - data being acquired No
Wales (SAIL Databank) NSWD National Survey for Wales Dataset Available No
Wales (SAIL Databank) ONSC Office of National Statistics Census Permission being sought No
Wales (SAIL Databank) OPDW Out Patient Dataset for Wales Available Yes
Wales (SAIL Databank) OPRD – Outpatient Referral Dataset Available Yes
Wales (SAIL Databank) PEDW Patient Episode Database for Wales Available Yes
Wales (SAIL Databank) RTTD – Referral to Treatment Times Available Yes
Wales (SAIL Databank) WAST Welsh Ambulance DataSet Available No
Wales (SAIL Databank) WCSU Welsh Cancer Incidence Surveillance Unit Available (but needs update) Yes
Wales (SAIL Databank) WDDS Wales Dispensing DataSet Available No
Wales (SAIL Databank) WDSD Welsh Demographic Service Dataset Available Yes
Wales (SAIL Databank) WHSD Welsh Health Survey Dataset Available No
Wales (SAIL Databank) WLGP Welsh Longitudinal General Practice (Daily COVID codes only) Available Yes
Wales (SAIL Databank) WLGP Welsh Longitudinal General Practice Available Yes
Wales (SAIL Databank) WRRS Wales Results Reporting Service Available (but needs update) No
Scotland (National Data Safe Haven) NHS Scotland General Practice Permission to access still to be agreed with the GP Community No
Scotland (National Data Safe Haven) NHS Scotland COVID-19 lab testing data Available No
Scotland (National Data Safe Haven) Scotland Prescribing Data Available Yes
Scotland (National Data Safe Haven) Death registrations Available Yes
Scotland (National Data Safe Haven) Acute hospital records (inpatient, outpatient and ITU) Available Yes
Scotland (National Data Safe Haven) ISARIC-CCP Currently being collated No
Scotland (National Data Safe Haven) NRS Stillbirths Available Yes
Scotland (National Data Safe Haven) NRS Births Available Yes
Scotland (National Data Safe Haven) SMR02 Available Yes
Scotland (National Data Safe Haven) SICSAG Daily (ICU) Available No
Scotland (National Data Safe Haven) SICSAG Episodes (ICU) Available No
Scotland (National Data Safe Haven) Diabetes Covariates Available No
Scotland (National Data Safe Haven) Emergency Department attendances (A&E) Available Yes
Scotland (National Data Safe Haven) NHS24 (111 Calls) Available Yes
Scotland (National Data Safe Haven) GP Out of Hours Available Yes
Scotland (National Data Safe Haven) Scottish Ambulance Service (SAS) Available Yes
Scotland (National Data Safe Haven) SBR Available Yes
England (NHS Digital) Pillar 1 COVID-19 Swab Testing Data (NHS LIMS/PHE Second Generation Surveillance System) Available No
England (NHS Digital) CHESS: COVID-19 Hospitalisation in England Surveillance System (CHESS) Available No
England (NHS Digital) PDS: Personal Demographic Service Available Yes
England (NHS Digital) HES: Hospital Episode Statistics Available Yes
England (NHS Digital) SUS: Secondary Uses Service Available Yes
England (NHS Digital) Community Prescribing Agreed - data being acquired No
England (NHS Digital) Death registry Available Yes
England (NHS Digital) Primary Care Available from 8 Jun '20 No
England (NHS Digital) Pillar 2 COVID-19 Testing data (UKGov swab testing) Agreed - data being acquired No
England (NHS Digital) ICNARC: Intensive Care National Audit and Research Centre Agreed - data being acquired No
England (NHS Digital) Myocardial Infarction National Audit Project Available for NHS Digital contracted staff only Yes
England (NHS Digital) Percutaneous Coronary Intervention audit Available for NHS Digital contracted staff only Yes
England (NHS Digital) Cardiac Surgery audit Available for NHS Digital contracted staff only Yes
England (NHS Digital) Heart Failure audit Available for NHS Digital contracted staff only Yes
England (NHS Digital) Cardiac Rhythm audit Available for NHS Digital contracted staff only Yes
England (NHS Digital) Congenital Heart Disease audit Available for NHS Digital contracted staff only Yes
England (NHS Digital) Left Atrial Appendage Occlusion audit Available for NHS Digital contracted staff only No
England (NHS Digital) Percutaneous Mitral Valve Leaflet Repair audit Available for NHS Digital contracted staff only No
England (NHS Digital) Transcutaneous Aortic Valve Implantation audit Available for NHS Digital contracted staff only No
England (NHS Digital) Patent Foramen Ovale closure audit Available for NHS Digital contracted staff only No
England (NHS Digital) Sentinel Stroke National Audit Programme Available for NHS Digital contracted staff only Yes
England (NHS Digital) Vascular Procedure Registries Available for NHS Digital contracted staff only Yes