Mortality In England Research Articles

Risk of Complications in Children With Type 1 Diabetes and Covid-19

Background: There is some data available in adults which suggests that Type 1 diabetes may be associated with higher risk with Covid-19 (1). Limited data has been available in pediatric Type 1 diabetes with Covid-19. Methods: We used TriNetX, with a large COVID-19 database, collecting real-time electronic medical records data. We compared children (0–18 years) who were diagnosed with Covid-19 with and without Type 1 diabetes. This database collected information from 54 health care organizations. Results: Mortality rate in children with Covid-19 and Type 1 diabetes was 0.618% (10/1618). Mortality rate in children with Covid-19 without Type 1 diabetes was 0.102% (257/251517). Relative risk of mortality for children with Covid-19 and Type 1 diabetes was 6.05 with a p value of < 0.0001. Endotracheal intubation rate in children with Covid-19 and Type 1 diabetes was 0.618% (10/1618). Endotracheal intubation rate in children with Covid-19 without Type 1 diabetes was 0.071% (178/251517). Relative risk of endotracheal intubation for children with Covid-19 and Type 1 diabetes was 8.73 with a p value of < 0.0001. Pneumonia rate in children with Covid-19 and Type 1 diabetes was 0.804% (13/1618). Pneumonia rate in children with Covid-19 without Type 1 diabetes was 0.562% (1414/251517). Relative risk of pneumonia for children with Covid-19 and Type 1 diabetes was 1.43 with a p value of < 0.1959. Septic shock rate in children with Covid-19 and Type 1 diabetes was 1.05% (17/1618). Septic shock rate in children with Covid-19 without Type 1 diabetes was 0.293% (737/251517). Relative risk of septic shock for children with Covid-19 and Type 1 diabetes was 3.59 with a p value of < 0.00001. Conclusion: Mortality rate, endotracheal and septic shock were increased in children with Type 1 diabetes and Covid-19 versus children with Covid-19 and no Type 1 diabetes. Further studies with larger sample size are needed to study complication rate of Covid-19 and Type 1 diabetes. References 1) Associations of type 1 and type 2 diabetes with COVID-19-related mortality in England: a whole-population study. Lancet Diabetes Endocrinol 2020 Oct;8(10):813–822. doi: 10.1016/S2213-8587(20)30272-2. Epub 2020 Aug 13.

Corona and coffee on your commute: a spatial analysis of COVID-19 mortality and commuting flows in England in 2020.

BackgroundThe COVID-19 pandemic forced governments to implement lockdown policies to curb the spread of the disease. These policies explicitly encouraged homeworking, hence reducing the number of commuters with the implicit assumption that restricting peoples’ movement reduces risk of infection for travellers and other people in their areas of residence and work. Yet, the spatial interrelation of different areas has been rarely addressed both in the public discourse and in early accounts of the various consequences of COVID-19.MethodsOur study proposes a spatial analysis of the association between commuting flows and COVID-19 mortality in England between March and June 2020, using a range of publicly available area-level data. To account for spatial correlation, we used a structural mobility gravity model to analyze commuting flows between Local Authority Districts. By accounting for these spatial dependencies, we temper concerns of bias and inefficiency affecting simple linear estimates. Additionally, we disentangle the direct and indirect (from other areas) influence of commuting on COVID-19 mortality.ResultsThe results of our spatial regression models suggest that higher commuting flows—in general and particularly by public transport—are associated with higher COVID-19 mortality. Our results are consistent with a reduction in COVID-related mortality after the introduction of a national lockdown in March. The spatial-lag term is statistically significant, highlighting the importance of accounting for spatial dependencies.ConclusionWe suggest that considering spatial interactions through commuting or travel motivations may offer interesting perspectives on the trade-off between health and economic activity during lockdowns.

Patterns of suicide mortality in England and Wales before and after the suicide of the actor Robin Williams

PurposeThere is international evidence supporting an association between sensational reporting of suicide and a subsequent increase in local suicide rates, particularly where reporting the death of a celebrity. We aimed to explore whether the observed increase in suicides in the United States, Canada and Australia in the 5 months following the 2014 suicide of the popular actor Robin Williams was also observed in England and Wales.MethodWe used interrupted time-series analysis and a seasonal autoregressive integrated moving averages (SARIMA) model to estimate the expected number of suicides during the 5 months following Williams’ death using monthly suicide count data for England and Wales from the UK Office for National Statistics (ONS) 2013–2014.ResultsCompared with the observed 2051 suicide deaths in all age groups from August to December 2014, we estimated that we would have expected 1949 suicides over the same period, representing no statistically significant excess.ConclusionsThis finding is an outlier among previous studies and contrasts with the approximately 10% increase in suicides found in similar analyses conducted in other high-income English-speaking countries with established media reporting guidelines.

Recent mortality in Britain: a review of trends and explanations.

The annual percentage improvement in standardised mortality rates in the period 2011-19 was the lowest for 70years, whereas the 2001-10 value was the highest since records began in 1841. A similar slowdown occurred from around 2011 in most European Union countries, although this was generally less severe than in Britain. Life expectancy at birth actually fell in USA for three successive years in period 2014-17. The downturn in Britain since 2011 was wide-ranging, affecting young and old, women and men and the more and the less advantaged to a broadly similar extent. Year-to-year variation in mortality increased mainly due to increased volatility in winter excess mortality from 2011, but all seasons showed lower rates of improvement in underlying longer-term trends. Mortality had started to improve at the end of the decade and the 2019 value was the lowest-ever value in Britain. Two main explanations for these trends have been advanced: UK Government post-2008 austerity policies, especially in the health and social care sectors, and the role of seasonal influenza. However, the evidence for a dominant role for either of these is weak. Longer-term overall trends have been determined principally by trends in cardiovascular rather than non-cardiovascular causes of death, although recent changes in discovery and coding of dementias makes it difficult to draw firm conclusions. Healthy life expectancy trends are also affected by changes in data and methods, but the proportion of life spent in good health for both women and men over age 65 has increased slightly since 2010.

The distributional impact of COVID-19: Geographic variation in mortality in England

Background: By their nature, the impact of epidemics on mortality varies geographically, suggesting that the geographical impact of an epidemic implies a social impact.

Backcasting Mortality in England and Wales, 1600–1840

There have been significant developments in using extrapolative stochastic models for mortality forecasting (forward projection) in the literature. However, little attention has been devoted to mortality backcasting (backward projection). This article proposes a simple mortality backcasting framework that can be used in practice. Research and analysis of English demography in the 17th and 18th centuries have suffered from a lack of mortality data. We attempt to alleviate this problem by developing a technique that runs backward in time and produces estimates of mortality data before the time at which such data became available. After confirming the time reversibility of the mortality data, we compare the backcasting performance of some commonly used stochastic mortality models for the England and Wales data. The original Lee–Carter model is selected for backcasting purpose of this dataset. Finally, we examine the longevity of British artists between the 17th and the 20th centuries using the backcasted population mortality as benchmarks. The results show that artists living in Britain from 1600 to the mid 1800s had life expectancies similar to those of the general population, with a marked increase in longevity after the Industrial Revolution.

Trends in COVID-19-related in-hospital mortality: lessons learned from nationwide samples

Trends in COVID-19-related in-hospital mortality: lessons learned from nationwide samples

Patient factors and temporal trends associated with COVID-19 in-hospital mortality in England: an observational study using administrative data

BackgroundAnalysis of the effect of COVID-19 on the complete hospital population in England has been lacking. Our aim was to provide a comprehensive account of all hospitalised patients with COVID-19 in England during the early phase of the pandemic and to identify the factors that influenced mortality as the pandemic evolved.MethodsThis was a retrospective exploratory analysis using the Hospital Episode Statistics administrative dataset. All patients aged 18 years or older in England who completed a hospital stay (were discharged alive or died) between March 1 and May 31, 2020, and had a diagnosis of COVID-19 on admission or during their stay were included. In-hospital death was the primary outcome of interest. Multilevel logistic regression was used to model the relationship between death and several covariates: age, sex, deprivation (Index of Multiple Deprivation), ethnicity, frailty (Hospital Frailty Risk Score), presence of comorbidities (Charlson Comorbidity Index items), and date of discharge (whether alive or deceased).Findings91 541 adult patients with COVID-19 were discharged during the study period, among which 28 200 (30·8%) in-hospital deaths occurred. The final multilevel logistic regression model accounted for age, deprivation score, and date of discharge as continuous variables, and sex, ethnicity, and Charlson Comorbidity Index items as categorical variables. In this model, significant predictors of in-hospital death included older age (modelled using restricted cubic splines), male sex (1·457 [1·408–1·509]), greater deprivation (1·002 [1·001–1·003]), Asian (1·211 [1·128–1·299]) or mixed ethnicity (1·317 [1·080–1·605]; vs White ethnicity), and most of the assessed comorbidities, including moderate or severe liver disease (5·433 [4·618–6·392]). Later date of discharge was associated with a lower odds of death (0·977 [0·976–0·978]); adjusted in-hospital mortality improved significantly in a broadly linear fashion, from 52·2% in the first week of March to 16·8% in the last week of May.InterpretationReductions in the adjusted probability of in-hospital mortality for COVID-19 patients over time might reflect the impact of changes in hospital strategy and clinical processes. The reasons for the observed improvements in mortality should be thoroughly investigated to inform the response to future outbreaks. The higher mortality rate reported for certain ethnic minority groups in community-based studies compared with our hospital-based analysis might partly reflect differential infection rates in those at greatest risk, propensity to become severely ill once infected, and health-seeking behaviours.FundingNone.

Explaining health system responses to public reporting of cardiac surgery mortality in England and the USA.

Public reporting of clinical performance is increasingly used in many countries to improve quality and enhance accountability of the health system. The assumption is that greater transparency will stimulate improvements by clinicians in response to peer pressure, patient choice or competition. The international diffusion of public reporting might suggest greater similarity between health systems. Alternatively, national and local contexts (including health system imperatives, professional power and organisational culture) might continue to shape its form and impact, implying continued divergence. The paper considers public reporting in the USA and England through the lens of Scott's 'pillars' institutional framework. The USA was arguably the first country to adopt public reporting systematically in the late 1980s. England is a more recent adopter; it is now being widely adopted through the National Health Service (NHS). Drawing on qualitative data from California and England, this paper compares the behavioural and policy responses to public reporting by health system stakeholders at micro, meso and macro levels and through the intersection of ideas, interests, institutions and individuals through. The interplay between the regulative, normative and cultural-cognitive pillars helps explain the observed patterns of on-going divergence.

Excess Mortality in England during the 2019 Summer Heatwaves

There is increasing evidence that rising temperatures and heatwaves in the United Kingdom are associated with an increase in heat-related mortality. However, the Public Health England (PHE) Heatwave mortality monitoring reports, which use provisional death registrations to estimate heat-related mortality in England during heatwaves, have not yet been evaluated. This study aims to retrospectively quantify the impact of heatwaves on mortality during the 2019 summer period using daily death occurrences. Second, using the same method, it quantifies the heat-related mortality for the 2018 and 2017 heatwave periods. Last, it compares the results to the estimated excess deaths for the same period in the PHE Heatwave mortality monitoring reports. The number of cumulative excess deaths during the summer 2019 heatwaves were minimal (161) and were substantially lower than during the summer 2018 heatwaves (1700 deaths) and summer 2017 heatwaves (1489 deaths). All findings were at variance with the PHE Heatwave mortality monitoring reports which estimated cumulative excess deaths to be 892, 863 and 778 during the heatwave periods of 2019, 2018 and 2017, respectively. Issues are identified in the use of provisional death registrations for mortality monitoring and the reduced reliability of the Office for National Statistics (ONS) daily death occurrences database before 2019. These findings may identify more reliable ways to monitor heat mortality during heatwaves in the future.

Comparison of All-Cause Mortality in England With European Countries and the USA: January 2020 Through to February 2021: A Secondary Analysis of Routine Administrative Data

Background: Assessments of mortality continue to inform public health strategies and policy making during the COVID-19 pandemic. All-cause excess mortality is a robust measure of the impact of the pandemic. Our study assesses the relative burden of excess mortality in England during the pandemic compared with 28 European countries and the USA. Methods: Weekly deaths and population estimates were obtained from Eurostat or directly from national statistical and public health agencies. Contextual information on COVID-19 case rates and population-level risk factors were obtained from open-source databases. Weekly directly age-standardised mortality rates (ASMRs) during week 1 2020 to week 7 2021 were calculated and summed cumulatively. These were compared with weekly sums of mean ASMRs observed between 2015 and 2019 and presented relative to the mean cumulative 2015-2019 ASMR averaged over an equivalent period. Findings: By February 2021, England had an overall relative excess mortality of 10·05%. This was the fifth highest out of 29 countries, the USA (14·82%) being the highest. Five countries showed below average mortality, with Norway the lowest (-6·76%). The same statistic for deaths under 65 years showed substantial international variation, with England having the second highest excess of 11·46%. Cumulative COVID-19 case rates explained about half of the international variation in relative excess mortality. Interpretation: England has experienced comparably high all-cause excess mortality during the COVID-19 pandemic. Factors contributing to England’s relative position should be further explored, particularly the association of health inequalities and wider determinants of health on the mortality risk of younger age groups. Funding Information: This study was carried out as part of the PHE’s work during the pandemic and therefore funded by PHE. Declaration of Interests: All authors declare no conflicts of interest. Ethics Approval Statement: This study was carried out as part of the PHE responsibility to manage the COVID-19 pandemic. PHE has legal permission, provided by Regulation 3 of The Health Service (Control of Patient Information) Regulations 2002 to process confidential patient information (http://www.legislation.gov.uk/uksi/2002/1438/regulation/3/made) under Sections 3(i) (a) to (c), 3(i)(d) (i) and (ii) and 3(3) as part of its outbreak response activities. As such this work falls outside the remit for ethical review. The study was subject to an internal review by the PHE Research Ethics and Governance Group and was found to be fully compliant with all regulatory requirements. As a full ethical review is not a requirement for this type of study and as no ethical or regulatory issues had been identified the study was approved.

Will COVID-19 be the coming of age for point-of-care testing?

<h3>Abstract</h3> <h3>Background</h3> Analyses of COVID-19 suggest specific risk factors make communities more or less vulnerable to pandemic related deaths within countries. What is unclear is whether the characteristics affecting vulnerability...

Testosterone replacement to prevent type 2 diabetes? Not just yet

Type 2 diabetes is linked to premature mortality and considerable morbidity. Its worldwide prevalence has risen substantially in the past four decades due to a mixture of rising obesity and increasing life expectancies, with reductions in premature mortality in type 2 diabetes. Diabetes also seems to be a major risk factor for COVID-19-related death. 1 Barron E Bakhai C Kar P et al. Associations of type 1 and type 2 diabetes with COVID-19-related mortality in England: a whole-population study. Lancet Diabetes Endocrinol. 2020; 8: 813-822 Summary Full Text Full Text PDF PubMed Scopus (479) Google Scholar Any novel mechanisms to lessen diabetes development would therefore be helpful. Testosterone treatment to prevent or revert type 2 diabetes in men enrolled in a lifestyle programme (T4DM): a randomised, double-blind, placebo-controlled, 2-year, phase 3b trialTestosterone treatment for 2 years reduced the proportion of participants with type 2 diabetes beyond the effects of a lifestyle programme. Increases in haematocrit might be treatment limiting. Longer-term durability, safety, and cardiovascular effects of the intervention remain to be further investigated. Full-Text PDF

Long-term exposure to air-pollution and COVID-19 mortality in England: A hierarchical spatial analysis

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 mortality in England using high geographical resolution. In this nationwide cross-sectional study in England, we included 38,573 COVID-19 deaths up to June 30, 2020 at the Lower Layer Super Output Area level (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. We find a 0.5% (95% credible interval: −0.2%, 1.2%) and 1.4% (95% CrI: −2.1%, 5.1%) increase in COVID-19 mortality risk for every 1 μg/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 equal to 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. 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.

Visualising regional inequalities in the 1918 Spanish flu pandemic in England and Wales

We examine regional inequalities in mortality from the 1918 pandemic in England and Wales. Crude mortality rates (per 100,000 for June 1918 to May 1919) from the Registrar General’s 1920 report were directly allocated to crude mortality rates for 306 administrative units. A custom GIS ShapeFile was constructed to map the rates first as a choropleth and then as a cartogram. The visualisations show a clear north-south divide in mortality in England with the northern areas and – to a lesser extent – the midlands and Wales having higher rates than the south. It also demonstrates an urban-rural divide with more sparsely populated areas – across both England and Wales – having lower rates.

A case-control study to evaluate the impact of the breast screening programme on mortality in England

BackgroundOver the past 30 years since the implementation of the National Health Service Breast Screening Programme, improvements in diagnostic techniques and treatments have led to the need for an up-to-date evaluation of its benefit on risk of death from breast cancer. An initial pilot case-control study in London indicated that attending mammography screening led to a mortality reduction of 39%.MethodsBased on the same study protocol, an England-wide study was set up. Women aged 47–89 years who died of primary breast cancer in 2010 or 2011 were selected as cases (8288 cases). When possible, two controls were selected per case (15,202 controls) and were matched by date of birth and screening area.ResultsConditional logistic regressions showed a 38% reduction in breast cancer mortality after correcting for self-selection bias (OR 0.62, 95% CI 0.56–0.69) for women being screened at least once. Secondary analyses by age group, and time between last screen and breast cancer diagnosis were also performed.ConclusionsAccording to this England-wide case-control study, mammography screening still plays an important role in lowering the risk of dying from breast cancer. Women aged 65 or over see a stronger and longer lasting benefit of screening compared to younger women.

Spatial inequalities of COVID-19 mortality rate in relation to socioeconomic and environmental factors across England

In this study, we aimed to examine spatial inequalities of COVID-19 mortality rate in relation to spatial inequalities of socioeconomic and environmental factors across England. Specifically, we first explored spatial patterns of COVID-19 mortality rate in comparison to non-COVID-19 mortality rate. Subsequently, we established models to investigate contributions of socioeconomic and environmental factors to spatial variations of COVID-19 mortality rate across England (N = 317). Two newly developed specifications of spatial regression models were established successfully to estimate COVID-19 mortality rate (R2 = 0.49 and R2 = 0.793). The level of spatial inequalities of COVID-19 mortality is higher than that of non-COVID-19 mortality in England. Although global spatial association of COVID-19 mortality and non-COVID-19 mortality is positive, local spatial association of COVID-19 mortality and non-COVID-19 mortality is negative in some areas. Expectedly, hospital accessibility is negatively related to COVID-19 mortality rate. Percent of Asians, percent of Blacks, and unemployment rate are positively related to COVID-19 mortality rate. More importantly, relative humidity is negatively related to COVID-19 mortality rate. Moreover, among the spatial models estimated, the ‘random effects specification of eigenvector spatial filtering model’ outperforms the ‘matrix exponential spatial specification of spatial autoregressive model’.

Scarlet fever and nineteenth‐century mortality trends: a reply to Romola Davenport

AbstractRomola Davenport's recent article is presented as a significant revision of the interpretation of the reasons for rising and then falling urban mortality in Britain in the nineteenth century put forward by Szreter and Mooney, which emphasized the importance of the politics of public health. Davenport's claims that mortality patternsc. 1830–70 were driven by a synchronized rise and fall of scarlet fever across Europe and North America, as well as in rural locations in Britain, are based on frail and inconclusive forms of evidence. The epidemiological evidence presented by Davenport in fact indicates a chronologically lagging—not leading—role for scarlet fever in contributing to the rise in urban death rates before 1850 and the subsequent fall in urban mortality afterc. 1870 in Britain.

Differential association of air pollution exposure with neonatal and postneonatal mortality in England and Wales: A cohort study.

BackgroundMany but not all studies suggest an association between air pollution exposure and infant mortality. We sought to investigate whether pollution exposure is differentially associated with all-cause neonatal or postneonatal mortality, or specific causes of infant mortality.Methods and findingsWe separately investigated the associations of exposure to particulate matter with aerodynamic diameter ≤ 10 μm (PM10), nitrogen dioxide (NO2), and sulphur dioxide (SO2) with all-cause infant, neonatal, and postneonatal mortality, and with specific causes of infant deaths in 7,984,366 live births between 2001 and 2012 in England and Wales. Overall, 51.3% of the live births were male, and there were 36,485 infant deaths (25,110 neonatal deaths and 11,375 postneonatal deaths). We adjusted for the following major confounders: deprivation, birthweight, maternal age, sex, and multiple birth. Adjusted odds ratios (95% CI; p-value) for infant deaths were significantly increased for NO2, PM10, and SO2 (1.066 [1.027, 1.107; p = 0.001], 1.044 [1.007, 1.082; p = 0.017], and 1.190 [1.146, 1.235; p < 0.001], respectively) when highest and lowest pollutant quintiles were compared; however, neonatal mortality was significantly associated with SO2 (1.207 [1.154, 1.262; p < 0.001]) but not significantly associated with NO2 and PM10 (1.044 [0.998, 1.092; p = 0.059] and 1.008 [0.966, 1.052; p = 0.702], respectively). Postneonatal mortality was significantly associated with all pollutants: NO2, 1.108 (1.038, 1.182; p < 0.001); PM10, 1.117 (1.050, 1.188; p < 0.001); and SO2, 1.147 (1.076, 1.224; p < 0.001). Whilst all were similarly associated with endocrine causes of infant deaths (NO2, 2.167 [1.539, 3.052; p < 0.001]; PM10, 1.433 [1.066, 1.926; p = 0.017]; and SO2, 1.558 [1.147, 2.116; p = 0.005]), they were differentially associated with other specific causes: NO2 and PM10 were associated with an increase in infant deaths from congenital malformations of the nervous (NO2, 1.525 [1.179, 1.974; p = 0.001]; PM10, 1.457 [1.150, 1.846; p = 0.002]) and gastrointestinal systems (NO2, 1.214 [1.006, 1.466; p = 0.043]; PM10, 1.312 [1.096, 1.571; p = 0.003]), and NO2 was also associated with deaths from malformations of the respiratory system (1.306 [1.019, 1.675; p = 0.035]). In contrast, SO2 was associated with an increase in infant deaths from perinatal causes (1.214 [1.156, 1.275; p < 0.001]) and from malformations of the circulatory system (1.172 [1.011, 1.358; p = 0.035]). A limitation of this study was that we were not able to study associations of air pollution exposure and infant mortality during the different trimesters of pregnancy. In addition, we were not able to control for all confounding factors such as maternal smoking.ConclusionsIn this study, we found that NO2, PM10, and SO2 were differentially associated with all-cause mortality and with specific causes of infant, neonatal, and postneonatal mortality.

Excess mortality in the first COVID pandemic peak: cross-sectional analyses of the impact of age, sex, ethnicity, household size, and long-term conditions in people of known SARS-CoV-2 status in England.

BackgroundThe SARS-CoV-2 pandemic has passed its first peak in Europe.AimTo describe the mortality in England and its association with SARS-CoV-2 status and other demographic and risk factors.Design and settingCross-sectional analyses of people with known SARS-CoV-2 status in the Oxford RCGP Research and Surveillance Centre (RSC) sentinel network.MethodPseudonymised, coded clinical data were uploaded from volunteer general practice members of this nationally representative network (n = 4 413 734). All-cause mortality was compared with national rates for 2019, using a relative survival model, reporting relative hazard ratios (RHR), and 95% confidence intervals (CI). A multivariable adjusted odds ratios (OR) analysis was conducted for those with known SARS-CoV-2 status (n = 56 628, 1.3%) including multiple imputation and inverse probability analysis, and a complete cases sensitivity analysis.ResultsMortality peaked in week 16. People living in households of ≥9 had a fivefold increase in relative mortality (RHR = 5.1, 95% CI = 4.87 to 5.31, P<0.0001). The ORs of mortality were 8.9 (95% CI = 6.7 to 11.8, P<0.0001) and 9.7 (95% CI = 7.1 to 13.2, P<0.0001) for virologically and clinically diagnosed cases respectively, using people with negative tests as reference. The adjusted mortality for the virologically confirmed group was 18.1% (95% CI = 17.6 to 18.7). Male sex, population density, black ethnicity (compared to white), and people with long-term conditions, including learning disability (OR = 1.96, 95% CI = 1.22 to 3.18, P = 0.0056) had higher odds of mortality.ConclusionThe first SARS-CoV-2 peak in England has been associated with excess mortality. Planning for subsequent peaks needs to better manage risk in males, those of black ethnicity, older people, people with learning disabilities, and people who live in multi-occupancy dwellings.