Association between household composition and severe COVID-19 outcomes in older people by ethnicity: an observational cohort study using the OpenSAFELY platform (preprint)

Background Ethnic differences in the risk of severe COVID-19 may be linked to household composition. We quantified the association between household composition and risk of severe COVID-19 by ethnicity for older individuals. Methods With the approval of NHS England, we analysed ethnic differences in the association between household composition and severe COVID-19 in people aged 67 or over in England. We defined households by number of generations living together, and used multivariable Cox regression stratified by location and wave of the pandemic and accounted for age, sex, comorbidities, smoking, obesity, housing density and deprivation. We included 2 692 223 people over 67 years in wave 1 (01/02/2020-31/08/2020) and 2 731 427 in wave 2 (01/09/2020-31/01/2021). Findings Multigenerational living was associated with increased risk of severe COVID-19 for White and South Asian older people in both waves (e.g. wave 2, 67+ living with 3 other generations vs 67+ year olds only: White HR 1.61 95% CI 1.38-1.87, South Asian HR 1.76 95% CI 1.48-2.10), with a trend for increased risks of severe COVID-19 with increasing generations in wave 2. Interpretation Multigenerational living was associated with severe COVID-19 in older adults. Older South Asian people are over-represented within multigenerational households in England, especially in the most deprived settings. The number of generations in a household, number of occupants, ethnicity and deprivation status are important considerations in the continued roll-out of COVID-19 vaccination and targeting of interventions for future pandemics. Funding This research was funded in part, by the Wellcome Trust. For the purpose of open access, the author has applied a CC-BY public copyright licence to any Author Accepted Manuscript version arising from this submission.

OpenSAFELY: Risks of COVID-19 hospital admission and death for people with learning disabilities - a cohort study. (preprint)

ObjectivesTo assess the association between learning disability and risk of hospitalisation and mortality from COVID-19 in England among adults and children. DesignWorking on behalf of NHS England, two cohort studies using patient-level data for >17 million people from primary care electronic health records were linked with death data from the Office for National Statistics and hospitalization data from NHS Secondary Uses Service using the OpenSAFELY platform. SettingGeneral practices in England which use TPP software. ParticipantsParticipants were males and females, aged up to 105 years, from two cohorts: (1) wave 1, registered with a TPP practice as of 1st March 2020 and followed until 31st August, 2020; (2) wave 2 registered 1st September 2020 and followed until 31st December 2020 (for admissions) or 8th February 2021 (for deaths). The main exposure group was people included on a general practice learning disability register (LDR), with a subgroup of people classified as having profound or severe learning disability. We also identified patients with Down syndrome and cerebral palsy (whether or not on the learning disability register). Main outcome measures(i) COVID-19 related death, (ii) COVID-19 related hospitalisation. Non-COVID-19 related death was also explored. ResultsIn wave 1, of 14,301,415 included individuals aged 16 and over, 90,095 (0.63%) were identified as being on the LDR. 30,173 COVID-related hospital admissions, 13,919 COVID-19 related deaths and 69,803 non-COVID deaths occurred; of which 538 (1.8%), 221 (1.6%) and 596 (0.85%) were among individuals on the LDR, respectively. In wave 2, 27,611 COVID-related hospital admissions, 17,933 COVID-19 related deaths and 54,171 non-COVID deaths occurred; of which 383 (1.4%), 260 (1.4%) and 470 (0.87%) were among individuals on the LDR. Wave 1 hazard ratios for individuals on the LDR, adjusted for age, sex, ethnicity and geographical location, were 5.3 (95% confidence interval (CI) 4.9, 5.8) for COVID-19 related hospital admissions and 8.2 (95% CI: 7.1, 9.4) for COVID-19 related death. Wave 2 produced similar estimates. Associations were stronger among those classed as severe-profound and among those in residential care. Down syndrome and cerebral palsy were associated with increased hazard of both events in both waves; Down syndrome to a much greater extent. Hazards of non-COVID-19 related death followed similar patterns with weaker associations. ConclusionsPeople with learning disabilities have markedly increased risks of hospitalisation and mortality from COVID-19. This raised risk is over and above that seen for non-COVID causes of death. Ensuring prompt access to Covid-19 testing and health care and consideration of prioritisation for COVID-19 vaccination and other targeted preventive measures are warranted.

Predicting COVID-19 related death using the OpenSAFELY platform (preprint)

Objectives To compare approaches for obtaining relative and absolute estimates of risk of 28-day COVID-19 mortality for adults in the general population of England in the context of changing levels of circulating infection. Design Three designs were compared. (A) case-cohort which does not explicitly account for the time-changing prevalence of COVID-19 infection, (B) 28-day landmarking, a series of sequential overlapping sub-studies incorporating time-updating proxy measures of the prevalence of infection, and (C) daily landmarking. Regression models were fitted to predict 28-day COVID-19 mortality. Setting Working on behalf of NHS England, we used clinical data from adult patients from all regions of England held in the TPP SystmOne electronic health record system, linked to Office for National Statistics (ONS) mortality data, using the OpenSAFELY platform. Participants Eligible participants were adults aged 18 or over, registered at a general practice using TPP software on 1st March 2020 with recorded sex, postcode and ethnicity. 11,972,947 individuals were included, and 7,999 participants experienced a COVID-19 related death. The study period lasted 100 days, ending 8th June 2020. Predictors A range of demographic characteristics and comorbidities were used as potential predictors. Local infection prevalence was estimated with three proxies: modelled based on local prevalence and other key factors; rate of A&E COVID-19 related attendances; and rate of suspected COVID-19 cases in primary care. Main outcome measures COVID-19 related death. Results All models discriminated well between patients who did and did not experience COVID-19 related death, with C-statistics ranging from 0.92-0.94. Accurate estimates of absolute risk required data on local infection prevalence, with modelled estimates providing the best performance. Conclusions Reliable estimates of absolute risk need to incorporate changing local prevalence of infection. Simple models can provide very good discrimination and may simplify implementation of risk prediction tools in practice.

OpenSAFELY NHS Service Restoration Observatory 1: describing trends and variation in primary care clinical activity for 23.3 million patients in England during the first wave of COVID-19 (preprint)

BackgroundThe COVID-19 pandemic has disrupted healthcare activity globally. The NHS in England stopped most non-urgent work by March 2020, but later recommended that services should be restored to near-normal levels before winter where possible. The authors are developing the OpenSAFELY NHS Service Restoration Observatory, using data to describe changes in service activity during COVID-19, and reviewing signals for action with commissioners, researchers and clinicians. Here we report phase one: generating, managing, and describing the data. ObjectiveTo describe the volume and variation of coded clinical activity in English primary care across 23.8 million patients records, taking respiratory disease and laboratory procedures as key examples. MethodsWorking on behalf of NHS England we developed an open source software framework for data management and analysis to describe trends and variation in clinical activity across primary care EHR data on 23.8 million patients; and conducted a population cohort-based study to describe activity using CTV3 coding hierarchy and keyword searches from January 2019-September 2020. ResultsMuch activity recorded in general practice declined to some extent during the pandemic, but largely recovered by September 2020, with some exceptions. There was a large drop in coded activity for commonly used laboratory tests, with broad recovery to pre-pandemic levels by September. One exception was blood coagulation tests such as International Normalised Ratio (INR), with a smaller reduction (median tests per 1000 patients in 2020: February 8.0; April 6.2; September 7.0). The overall pattern of recording for respiratory symptoms was less affected, following an expected seasonal pattern and classified as "no change" from the previous year. Respiratory tract infections exhibited a sustained drop compared with pre-pandemic levels, not returning to pre-pandemic levels by September 2020. Various COVID-19 codes increased through the period. We observed a small decline associated with high level codes for long-term respiratory conditions such as chronic obstructive pulmonary disease (COPD) and asthma. Asthma annual reviews experienced a small drop but since recovered, while COPD annual reviews remain below baseline. ConclusionsWe successfully delivered an open source software framework to describe trends and variation in clinical activity across an unprecedented scale of primary care data. The COVD-19 pandemic led to a substantial change in healthcare activity. Most laboratory tests showed substantial reduction, largely recovering to near-normal levels by September 2020, with some important tests less affected. Records of respiratory infections decreased with the exception of codes related to COVID-19, whilst activity of other respiratory disease codes was mixed. We are expanding the NHS Service Restoration Observatory in collaboration with clinicians, commissioners and researchers and welcome feedback.

OpenSAFELY: impact of national guidance on switching from warfarin to direct oral anticoagulants (DOACs) in early phase of COVID-19 pandemic in England (preprint)

BackgroundEarly in the COVID-19 pandemic the NHS recommended that appropriate patients anticoagulated with warfarin should be switched to direct acting oral anticoagulants (DOACs), requiring less frequent blood testing. Subsequently, a national safety alert was issued regarding patients being inappropriately co-prescribed two anticoagulants following a medication change, and associated monitoring. ObjectiveTo describe which people were switched from warfarin to DOACs; identify potentially unsafe co-prescribing of anticoagulants; and assess whether abnormal clotting results have become more frequent during the pandemic. MethodsWorking on behalf of NHS England we conducted a population cohort based study using routine clinical data from >17 million adults in England. Results20,000 of 164,000 warfarin patients (12.2%) switched to DOACs between March and May 2020, most commonly to edoxaban and apixaban. Factors associated with switching included: older age, recent renal function test, higher number of recent INR tests recorded, atrial fibrillation diagnosis and care home residency. There was a sharp rise in co-prescribing of warfarin and DOACs from typically 50-100 per month to 246 in April 2020, 0.06% of all people receiving a DOAC or warfarin. INR testing fell by 14% to 506.8 patients tested per 1000 warfarin patients each month. We observed a very small increase in elevated INRs (n=470) during April compared with January (n=420). ConclusionsIncreased switching of anticoagulants from warfarin to DOACs was observed at the outset of the COVID-19 pandemic in England following national guidance. There was a small but substantial number of people co-prescribed warfarin and DOACs during this period. Despite a national safety alert on the issue, a widespread rise in elevated INR test results was not found. Primary care has responded rapidly to changes in patient care during the COVID-19 pandemic.

Quality of life and depressive symptoms among Peruvian university students during the COVID-19 pandemic (preprint)

ObjectivesCharacterize the quality of life and depressive symptoms of university students in Peru during the COVID-19 pandemic and to determine the associated factors. MethodsMulti-centre study in 1634 university students recruited by convenience sampling. Quality of life (QoL) was assessed with the European Quality of Life-5 Dimensions at three levels (EQ-5D-3L) and depressive symptoms with the Patient Health Questionarie-9 (PHQ-9). To evaluate factors associated with QoL and depressive symptoms, linear and adjusted regressions were used, with robust variance reporting coefficients ({beta}). ResultsThe percentage of participants most affected by QoL dimension was: anxiety/depression (47.2%) and pain/discomfort (35.6%). Regarding the Visual Analog Scale (EQ-VAS) of QoL, the score was 76.0 + 25.6. Those who had family economic decline during quarantine ({beta}=-3.4, IC95%=-6.5 to -0.3) or family with chronic diseases ({beta}=-3.7, IC95%=-6.1 to -1.4) presented significantly lower scores in their QoL. Regarding depressive symptomatology, the university students reported a moderate to severe level (28.9%). A higher risk of depressive symptoms was found in residents of Ayacucho ({beta}=0.8, IC95%=0.1 to 1.5), those who were released from quarantine ({beta}=0.7, IC95%=0.2 to 1.2) and those who had a family member with chronic disease ({beta}=1.5, IC95%=1.0 to 2.1). ConclusionsAlmost half and one third of participants reported anxiety/depression, and pain/discomfort in their QoL respectively. Nearly a third presented moderate and severe depressive symptoms. The deterioration of QoL was worse in those who had a decrease in income and a family member with chronic illness. The presence of depressive symptoms was found in students in Ayacucho, those who left home during quarantine and those who had a family member with chronic diseases.

First-described recently discovered non-toxic vegetal-derived furocoumarin preclinical efficacy against SARS-CoV-2: a promising antiviral herbal drug. (preprint)

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the aetiology of coronavirus disease 2019 (COVID19) pandemic. ICEP4 purified compound (ICEP4) is a recently discovered furocoumarin-related purified compound derived from the roots and seeds of Angelica archangelica (herbal drug). ICEP4-related herbal preparations have been extensively used as active herbal ingredients in traditional medicine treatments in several European countries. Extraction method of patent pending ICEP4 (patent application no. GB2017123.7) has previously shown strong manufacturing robustness, long-lasting stability, and repeated chemical consistency. Here we show that ICEP4 presents a significant in vitro cytoprotective effect in highly virulent-SARS-CoV-2 challenged Vero E6 cellular cultures, using doses of 34.5 and 69 M. No dose-related ICEP4 toxicity was observed in Vero E6 cells, M0 macrophages, B, CD4+ T and CD8+ T lymphocytes, Natural Killer (NK) or Natural Killer T (NKT) cells. No dose-related ICEP4 inflammatory response was observed in M0 macrophages quantified by IL6 and TNF release in cell supernatant. No decrease in survival rate was observed after either 24 hr acute or 21-day chronic exposure in in vivo toxicity studies performed in C. elegans. Therefore, ICEP4 toxicological profile has demonstrated marked differences compared to others vegetal furocoumarins. Successful ICEP4 doses against SARS-CoV-2-challenged cells are within the maximum threshold of toxicity concern (TTC) of furocoumarins as herbal preparation, stated by European Medicines Agency (EMA). The characteristic chemical compounding of ICEP4, along with its safe TTC, allow us to assume that the first-observation of a natural antiviral compound has occurred. The potential druggability of a new synthetic ICEP4-related compound remains to be elucidated. However, well-established historical use of ICEP4-related compounds as herbal preparations may point towards an already-safe, widely extended remedy, which may be ready-to-go for large-scale clinical trials under the EMA emergency regulatory pathway. To the best of the authors knowledge, ICEP4-related herbal drug can be postulated as a promising therapeutic treatment for COVID19.

Elevated temperature inhibits SARS-CoV-2 replication in respiratory epithelium independently of the induction of IFN-mediated innate immune defences (preprint)

The pandemic spread of SARS-CoV-2, the etiological agent of COVID-19, represents a significant and ongoing international health crisis. A key symptom of SARS-CoV-2 infection is the onset of fever, with a hyperthermic temperature range of 38 to 41{degrees}C. Fever is an evolutionarily conserved host response to microbial infection and inflammation that can influence the outcome of viral pathogenicity and regulation of host innate and adaptive immune responses. However, it remains to be determined what effect elevated temperature has on SARS-CoV-2 tropism and replication. Utilizing a 3D air-liquid interface (ALI) model that closely mimics the natural tissue physiology and cellular tropism of SARS-CoV-2 infection in the respiratory airway, we identify tissue temperature to play an important role in the regulation of SARS-CoV-2 infection. We show that temperature elevation induces wide-spread transcriptome changes that impact upon the regulation of multiple pathways, including epigenetic regulation and lncRNA expression, without disruption of general cellular transcription or the induction of interferon (IFN)-mediated antiviral immune defences. Respiratory tissue incubated at temperatures >37{degrees}C remained permissive to SARS-CoV-2 infection but severely restricted the initiation of viral transcription, leading to significantly reduced levels of intraepithelial viral RNA accumulation and apical shedding of infectious virus. To our knowledge, we present the first evidence that febrile temperatures associated with COVID-19 inhibit SARS-CoV-2 replication. Our data identify an important role for temperature elevation in the epithelial restriction of SARS-CoV-2 that occurs independently of the induction of canonical IFN-mediated antiviral immune defences and interferon-stimulated gene (ISG) expression.

Ivermectin reduces coronavirus infection in vivo: a mouse experimental model (preprint)

SARS-CoV2 is a single strand RNA virus member of the type 2 coronavirus family, responsible for causing COVID-19 disease in humans. The objective of this study was to test the ivermectin drug in a murine model of coronavirus infection using a type 2 family RNA coronavirus similar to SARS-CoV2, the mouse hepatitis virus (MHV). BALB/cJ female mice were infected with 6,000 PFU of MHV-A59 (Group Infected; n=20) and immediately treated with one single dose of 500 ug/kg of ivermectin (Group Infected + IVM; n=20), or were not infected and treated with PBS (Control group; n=16). Five days after infection/treatment, mice were euthanized to obtain different tissues to check general health status and infection levels. Overall results demonstrated that viral infection induces the typical MHV disease in infected animals, with livers showing severe hepatocellular necrosis surrounded by a severe lymphoplasmacytic inflammatory infiltration associated with a high hepatic viral load (52,158 AU), while ivermectin administration showed a better health status with lower viral load (23,192 AU; p<0.05) and few livers with histopathological damage (p<0.05), not showing statistical differences with control mice (P=NS). Furthermore, serum transaminase levels (aspartate aminotransferase and alanine aminotransferase) were significantly lower in treated mice compared to infected animals. In conclusion, ivermectin seems to be effective to diminish MHV viral load and disease in mice, being a useful model for further understanding new therapies against coronavirus diseases.

Association between living with children and outcomes from COVID-19: an OpenSAFELY cohort study of 12 million adults in England (preprint)

Background: Close contact with children may provide cross-reactive immunity to SARs-CoV-2 due to more frequent prior coryzal infections from seasonal coronaviruses. Alternatively, close contact with children may increase risk of SARs-CoV-2 infection. We investigated whether risk of infection with SARs-CoV-2 and severe outcomes differed between adults living with and without children. Methods: Working on behalf of NHS England, we conducted a population-based cohort study using primary care data and pseudonymously-linked hospital and intensive care admissions, and death records, from patients registered in general practices representing 40% of England. Using multivariable Cox regression, we calculated fully-adjusted hazard ratios (HR) of outcomes from 1st February-3rd August 2020 comparing adults living with and without children in the household. Findings: Among 9,157,814 adults [≤]65 years, living with children 0-11 years was not associated with increased risks of recorded SARS-CoV-2 infection, COVID-19 related hospital or ICU admission but was associated with reduced risk of COVID-19 death (HR 0.75, 95%CI 0.62-0.92). Living with children aged 12-18 years was associated with a small increased risk of recorded SARS-CoV-2 infection (HR 1.08, 95%CI 1.03-1.13), but not associated with other COVID-19 outcomes. Living with children of any age was also associated with lower risk of dying from non-COVID-19 causes. Among 2,567,671 adults >65 years there was no association between living with children and outcomes related to SARS-CoV-2. We observed no consistent changes in risk following school closure. Interpretation: For adults living with children there is no evidence of an increased risk of severe COVID-19 outcomes. These findings have implications for determining the benefit-harm balance of children attending school in the COVID-19 pandemic. Funding This work was supported by the Medical Research Council MR/V015737/1.

Robust SARS-CoV-2-specific T-cell immunity is maintained at 6 months following primary infection (preprint)

The immune response to SARS-CoV-2 is critical in both controlling primary infection and preventing re-infection. However, there is concern that immune responses following natural infection may not be sustained and that this may predispose to recurrent infection. We analysed the magnitude and phenotype of the SARS-CoV-2 cellular immune response in 100 donors at six months following primary infection and related this to the profile of antibody level against spike, nucleoprotein and RBD over the previous six months. T-cell immune responses to SARS-CoV-2 were present by ELISPOT or ICS analysis in all donors and are characterised by predominant CD4+ T cell responses with strong IL-2 cytokine expression. Median T-cell responses were 50% higher in donors who had experienced an initial symptomatic infection indicating that the severity of primary infection establishes a set-point for cellular immunity that lasts for at least 6 months. The T-cell responses to both spike and nucleoprotein/membrane proteins were strongly correlated with the peak antibody level against each protein. The rate of decline in antibody level varied between individuals and higher levels of nucleoprotein-specific T cells were associated with preservation of NP-specific antibody level although no such correlation was observed in relation to spike-specific responses. In conclusion, our data are reassuring that functional SARS-CoV-2-specific T-cell responses are retained at six months following infection although the magnitude of this response is related to the clinical features of primary infection.

COVID-19 collateral: Indirect acute effects of the pandemic on physical and mental health in the UK (preprint)

Background: Concerns have been raised that the response to the UK COVID-19 pandemic may have worsened physical and mental health, and reduced use of health services. However, the scale of the problem is unquantified, impeding development of effective mitigations. We asked what has happened to general practice contacts for acute physical and mental health outcomes during the pandemic? Methods: Using electronic health records from the Clinical Research Practice Datalink (CPRD) Aurum (2017-2020), we calculated weekly primary care contacts for selected acute physical and mental health conditions (including: anxiety, depression, acute alcohol-related events, asthma and chronic obstructive pulmonary disease [COPD] exacerbations, cardiovascular and diabetic emergencies). We used interrupted time series (ITS) analysis to formally quantify changes in conditions after the introduction of population-wide restrictions ('lockdown') compared to the period prior to their introduction in March 2020. Findings: The overall population included 9,863,903 individuals on 1st January 2017. Primary care contacts for all conditions dropped dramatically after introduction of population-wide restrictions. By July 2020, except for unstable angina and acute alcohol-related events, contacts for all conditions had not recovered to pre-lockdown levels. The largest reductions were for contacts for: diabetic emergencies (OR: 0.35, 95% CI: 0.25-0.50), depression (OR: 0.53, 95% CI: 0.52-0.53), and self-harm (OR: 0.56, 95% CI: 0.54-0.58). Interpretation: There were substantial reductions in primary care contacts for acute physical and mental conditions with restrictions, with limited recovery by July 2020. It is likely that much of the deficit in care represents unmet need, with implications for subsequent morbidity and premature mortality. The conditions we studied are sufficiently severe that any unmet need will have substantial ramifications for the people experiencing the conditions and healthcare provision. Maintaining access must be a key priority in future public health planning (including further restrictions). Funding: Wellcome Trust Senior Fellowship (SML), Health Data Research UK.

MMGB/SA Consensus Estimate of the Binding Free Energy Between the Novel Coronavirus Spike Protein to the Human ACE2 Receptor (preprint)

The ability to estimate protein-protein binding free energy in a computationally efficient via a physics-based approach is beneficial to research focused on the mechanism of viruses binding to their target proteins. Implicit solvation methodology may be particularly useful in the early stages of such research, as it can offer valuable insights into the binding process, quickly. Here we evaluate the potential of the related molecular mechanics generalized Born surface area (MMGB/SA) approach to estimate the binding free energy {Delta}Gbind between the SARS-CoV-2 spike receptor-binding domain and the human ACE2 receptor. The calculations are based on a recent flavor of the generalized Born model, GBNSR6. Two estimates of {Delta}Gbind are performed: one based on standard bondi radii, and the other based on a newly developed set of atomic radii (OPT1), optimized specifically for protein-ligand binding. We take the average of the resulting two {Delta}Gbind values as the consensus estimate. For the well-studied Ras-Raf protein-protein complex, which has similar binding free energy to that of the SARS-CoV-2/ACE2 complex, the consensus {Delta}Gbind = -11.8 {+/-} 1 kcal/mol, vs. experimental -9.7 {+/-} 0.2 kcal/mol. The consensus estimates for the SARS-CoV-2/ACE2 complex is {Delta}Gbind = -9.4 {+/-} 1.5 kcal/mol, which is in near quantitative agreement with experiment (-10.6 kcal/mol). The availability of a conceptually simple MMGB/SA-based protocol for analysis of the SARS-CoV-2 /ACE2 binding may be beneficial in light of the need to move forward fast.

UK prevalence of underlying conditions which increase the risk of severe COVID-19 disease: a point prevalence study using electronic health records (preprint)

BackgroundThis study aimed to describe the population at risk of severe COVID-19 due to underlying health conditions across the United Kingdom in 2019. MethodsWe used anonymised electronic health records from the Clinical Practice Research Datalink GOLD to describe the point prevalence on 5 March 2019 of the at-risk population following national guidance. Prevalence for any risk condition and for each individual condition is given overall and stratified by age and region. We repeated the analysis on 5 March 2014 for full regional representation and to describe prevalence of underlying health conditions in pregnancy. We additionally described the population of cancer survivors, and assessed the value of linked secondary care records for ascertaining COVID-19 at-risk status. FindingsOn 5 March 2019, 24{middle dot}4% of the UK population were at risk due to a record of at least one underlying health condition, including 8{middle dot}3% of school-aged children, 19{middle dot}6% of working-aged adults, and 66{middle dot}2% of individuals aged 70 years or more. 7{middle dot}1% of the population had multimorbidity. The size of the at-risk population was stable over time comparing 2014 to 2019, despite increases in chronic liver disease and diabetes and decreases in chronic kidney disease and current asthma. Separately, 1{middle dot}6% of the population had a new diagnosis of cancer in the past five years. InterpretationThe population at risk of severe COVID-19 (aged [≥]70 years, or with an underlying health condition) comprises 18.5 million individuals in the UK, including a considerable proportion of school-aged and working-aged individuals. FundingNIHR HPRU in Immunisation Research in contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched Pubmed for peer-reviewed articles, preprints, and research reports on the size and distribution of the population at risk of severe COVID. We used the terms (1) risk factor or co-morbidity or similar (2) COVID or SARS or similar and (3) prevalence to search for studies aiming to quantify the COVID-19 at-risk UK population published in the previous year to 19 July 2020, with no language restrictions. We found one study which modelled prevalence of risk factors based on the Global Burden of Disease (which included the UK) and one study which estimated that 8.4 million individuals aged [≥]30 years in the UK were at risk based on prevalence of a subset of relevant conditions in England. There were no studies which described the complete COVID-19 at-risk population across the UK. Added value of this studyWe used a large, nationally-representative dataset based on electronic health records to estimate prevalence of increased risk of severe COVID-19 across the United Kingdom, including all conditions in national guidance. We stratified by age, sex and region to enable regionally-tailored prediction of COVID-19-related healthcare burden and interventions to reduce transmission of infection, and planning and modelling of vaccination of the at-risk population. We also quantified the value of linked secondary care records to supplement primary care records. Implications of all the available evidenceIndividuals at moderate or high risk of severe COVID-19 according to current national guidance (aged [≥]70 years, or with a specified underlying health condition) comprise 18{middle dot}5 million individuals in the United Kingdom, rather than the 8.43 million previously estimated. The 8{middle dot}3% of school-aged children and 19{middle dot}6% of working-aged adults considered at-risk according to national guidance emphasises the need to consider younger at-risk individuals in shielding policies and when re-opening schools and workplaces, but also supports prioritising vaccination based on age and condition-specific mortality risk, rather than targeting all individuals with underlying conditions, who form a large population even among younger age groups. Among individuals aged [≥]70 years, 66{middle dot}2% had at least one underlying health condition, suggesting an age-targeted approach to vaccination may efficiently target individuals at risk of severe COVID-19. These national estimates broadly support the use of Global Burden of Disease modelled estimates and age-targeted vaccination strategies in other countries.

OpenSAFELY: factors associated with COVID-19-related hospital death in the linked electronic health records of 17 million adult NHS patients. (preprint)

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.