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Background Since 2008, the Improving Access to Psychological Therapies (IAPT) programme has offered adults in England evidence-based psychological treatments for common mental disorders (CMDs) such as depression and anxiety disorders. However, inequalities in access have not been explored at the national level. Methods Using a unique individual patient dataset that linked 2011 Census information of English residents to national IAPT data collected between April 2017 and March 2018, we estimated the rate of access by a wide range of socio-demographic characteristics that are not routinely available. A large household survey was used to estimate the prevalence of probable CMDs by these socio-demographic characteristics. We estimated the probability of access to IAPT amongst people with CMDs by comparing the rates of access from IAPT data and the estimates of prevalence of CMDs from the household survey. Both unadjusted and adjusted (for important patient characteristics) access rates were estimated in logistic regression models. Results As a proportion of those with a probable CMD, access to IAPT varied markedly by socio-demographic characteristics. Older adults, males, people born outside of the UK, people with religious beliefs, people from Asian ethnic backgrounds, people reporting a disability and those without any academic or professional qualifications were underrepresented in IAPT services nationally, in adjusted models. Conclusions The identification of patients who may be underrepresented in IAPT provides an opportunity for services to target outreach and engagement with these groups. Further understanding of barriers to access should help increase equity in access.

ObjectiveTo estimate vaccine effectiveness (VE) for preventing COVID-19 hospital admission in women first infected with SARS-CoV-2 during pregnancy, and assess how this compares to VE among women of reproductive age who were not pregnant when first infected.DesignPopulation-based cohort study using national, linked Census and administrative data.SettingEngland, United Kingdom, from 8th December 2020 to 31st August 2021.Participants815,4777 women aged 18 to 45 years (mean age, 30.4 years) who had documented evidence of a first SARS-CoV-2 infection in NHS Test and Trace data or Hospital Episode Statistics.Main outcome measuresA hospital inpatient episode where COVID-19 was recorded as the primary diagnosis. Cox proportional hazards models, adjusted for calendar time of infection and sociodemographic factors related to vaccine uptake and risk of severe COVID-19, were used to estimate VE as the complement of the hazard ratio for COVID-19 hospital admission.ResultsCompared with unvaccinated pregnant women, the adjusted rate of COVID-19 hospital admission was 76% (95% confidence interval 69% to 82%) lower for single-vaccinated pregnant women and 83% (75% to 88%) lower for double-vaccinated pregnant women. These estimates were similar to those found for non-pregnant women: 79% (76% to 81%) for single-vaccinated and 82% (80% to 83%) for double-vaccinated. Among those vaccinated more than 90 days before infection, being double-vaccinated was associated with a greater reduction in risk than being single-vaccinated.ConclusionsCOVID-19 vaccination is associated with reduced rates of severe illness in pregnant women infected with SARS-CoV-2, and the reduction in risk is similar to that for non-pregnant women. Waning of vaccine effectiveness occurs more quickly after one dose of a vaccine than two doses.What is already known on this topicBeing pregnant is a risk factor for severe illness and mortality following infection with SARS-CoV-2.Existing evidence suggests that COVID-19 vaccines are effective for preventing severe outcomes in pregnant women.However, research directly comparing vaccine effectiveness between pregnant and non-pregnant women of reproductive age at the population level are lacking.What this study addsOur study provides real-world evidence that COVID-19 vaccination reduces the risk of hospital admission by a similar amount for both women infected with SARS-CoV-2 during pregnancy and women who were not pregnant when infected, during the Alpha and Delta dominant periods in England.

ObjectiveTo examine sociodemographic inequalities in people with SARS-CoV-2 during the second (alpha) and third (delta) waves of the covid-19 pandemic.DesignRetrospective, population based cohort study.SettingResident population of England.Participants39 006 194 people aged 10 years and older who were enumerated in the 2011 census, registered with the NHS, and alive on 1 September 2020.Main outcome measuresAge standardised SARS-CoV-2 case rates (ie, the number of people who received a positive test result per 100 000 person weeks at risk) during the second wave (1 September 2020 to 22 May 2021) or third wave (23 May to 10 December 2021) of the pandemic. Age standardised rates were calculated by sociodemographic characteristics and adjusted rate ratios were estimated using generalised linear regression models with a Poisson distribution (models were adjusted for covariates including sex, age, geographical variables, and sociodemographic characteristics).ResultsDuring the study period, 5 767 584 people (14.8% of the study population) tested positive for SARS-CoV-2. In the second wave, the fully adjusted relative risks of having a positive test were highest for the Bangladeshi and Pakistani ethnic groups compared with the white British group, with rate ratios of 1.75 (95% confidence interval 1.73 to 1.77) and 1.69 (1.68 to 1.70), respectively. Muslim and Sikh religious groups had fully adjusted rate ratios of 1.51 (1.50 to 1.51) and 1.64 (1.63 to 1.66), respectively, compared with the Christian group. Greater area deprivation, disadvantaged socioeconomic position, living in a care home, and low English language proficiency were also associated with higher relative risk of having a positive test. However, the inequalities among groups varied over time. Being Christian, white British, without a disability, and from a more advantaged socioeconomic position were associated with increased relative risk of testing positive during the third wave.ConclusionResearch is urgently needed to understand the large sociodemographic inequalities in SARS-CoV-2 case rates in order to inform policy interventions in future waves or pandemics.

Background Although most adults infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) fully recover, a proportion have ongoing symptoms, or post-COVID conditions (PCC), after infection. The objective of this analysis was to estimate the number of United States (US) adults with activity-limiting PCC on 1 November 2021. Methods We modeled the prevalence of PCC using reported infections occurring from 1 February 2020 to 30 September 2021, and population-based, household survey data on new activity-limiting symptoms ≥1 month following SARS-CoV-2 infection. From these data sources, we estimated the number and proportion of US adults with activity-limiting PCC on 1 November 2021 as 95% uncertainty intervals, stratified by sex and age. Sensitivity analyses adjusted for underascertainment of infections and uncertainty about symptom duration. Results On 1 November 2021, at least 3.0–5.0 million US adults, or 1.2%–1.9% of the US adult population, were estimated to have activity-limiting PCC of ≥1 month’s duration. Population prevalence was higher in females (1.4%–2.2%) than males. The estimated prevalence after adjusting for underascertainment of infections was 1.7%–3.8%. Conclusions Millions of US adults were estimated to have activity-limiting PCC. These estimates can support future efforts to address the impact of PCC on the US population.

BackgroundLittle is known about the risk of Long Covid following reinfection with SARS-CoV-2. We estimated the likelihood of new-onset, self-reported Long Covid after a second SARS-CoV-2 infection, and compared to a first infection.MethodsWe included UK COVID-19 Infection Survey participants who tested positive for SARS-CoV-2 between 1 November 2021 and 8 October 2022. The primary outcome was self-reported Long Covid 12 to 20 weeks after each infection. Separate analyses were performed for those ResultsOverall, Long Covid was reported by those ≥16 years after 4.0% and 2.4% of first and second infections, respectively; the corresponding estimates among those ConclusionsThe risk of new-onset Long Covid after a second SARS-CoV-2 infection is lower than that after a first infection for those ≥16 years, though there is no evidence of a difference in risk for those

BackgroundRisk of suicide is complex and often a result of multiple interacting factors. It is vital research identifies predictors of suicide to provide a strong evidence base for targeted interventions.MethodsUsing linked Census and population level mortality data we estimated rates of suicide across different groups in England and Wales and examine which factors are independently associated with the risk of suicide.FindingsThe highest rates of suicide were amongst those who reported an impairment affecting their day-to-day activities, those who were long term unemployed or never had worked, or those who were single or separated. Rates of suicide were highest in the White and Mixed/multiple ethnic groups compared to other ethnicities, and in people who reported a religious affiliation compared with those who had no religion. Comparison of minimally adjusted models (predictor, sex and age) with fully-adjusted models (sex, age, ethnicity, region, partnership status, religious affiliation, day-to-day impairments, armed forces membership and socioeconomic status) identified key predictors which remain important risk factors after accounting for other characteristics; day-to-day impairments were still found to increase the incidence of suicide relative to those whose activities were not impaired after adjusting for employment status. Overall, rates of suicide were higher in men compared to females across all ages, with the highest rates in 40-to-50-year-olds.InterpretationThe findings of this work provide novel population level insights into the risk of suicide by sociodemographic characteristics. Understanding the interaction between key risk factors for suicide has important implications for national suicide prevention strategies.FundingThis study received no specific funding.Research in contextEvidence before this studyPrevious studies have identified key risk factors for suicide; being male and being aged 40 to 50 years of age have the highest rates of suicide. Suicide is a major public health concern, with prevention strategies imperative to minimising events.Added value of this studyFor the first time we make population level estimates of suicide rates in England and Wales using death registration data linked to 2011 Census.Furthermore, we calculate incidence rate ratios for fully adjusted models which provide novel insights into the interplay between different risk factors. For instance, we see that people who report having day-to-day impairments risk of suicide is 2- to 3-times higher for men and women respectively compared to people who do not report day-to-day impairments, after adjusting for other characteristics such as socioeconomic status which are likely associated with impairments.Implications of this studyUnderstanding the groups most at risk of suicide is imperative for national suicide prevention strategies. This work provides novel population level insights into the risk of suicide by sociodemographic characteristics.

BackgroundEvidence on the long-term employment consequences of SARS-CoV-2 infection is lacking. We used data from a large, community-based sample in the UK to estimate associations between Long Covid and subsequent employment outcomes.MethodsThis was an observational, longitudinal study using a pre-post design. We included UK COVID-19 Infection Survey participants who completed questionnaires on Long Covid from 3 February 2021 to 30 September 2022 when they were aged 16 to 64 years and not in full-time education. We used conditional logit modelling to explore the time-varying relationship between Long Covid status ≥12 weeks after a first test-confirmed SARS-CoV-2 infection (reference: pre-infection) and labour market inactivity (neither working nor looking for work) or workplace absence lasting ≥4 weeks.ResultsOf 206,299 included participants (mean age 45 years, 54% female, 92% white), 15% were ever inactive in the labour market and 10% were ever long-term absent during follow-up. Compared with pre-infection, inactivity was higher in participants reporting Long Covid 30 to ConclusionsLong Covid is likely to have contributed to reduced levels of participation in the UK labour market, though it is unlikely to be the sole driver. Further research is required to quantify the contribution of other factors, such as indirect health effects of the pandemic.

BackgroundThe risk of COVID-19 severity and mortality differs markedly by age, socio-demographic characteristics and pre-existing health status. Various studies have suggested that higher air pollution exposures also increase the likelihood of dying from COVID-19.Objectives: To assess the association between long-term outdoor air pollution (NO2, NOx, PM10and PM2.5) concentrations and the risk of death involving COVID-19, using a large individual-level dataset.MethodsWe used comprehensive individual-level data from the Office for National Statistics’ Public Health Data Asset for September 2020 to January 2022 and London Air Quality Network modelled air pollution concentrations available for 2016. Using Cox proportional hazard regression models, we adjusted for potential confounders including age, sex, vaccination status, dominant virus variants, geographical factors (such as population density), ethnicity, area and household-level deprivation, and health comorbidities.ResultsThere were 737,356 confirmed COVID-19 cases including 9,315 COVID-related deaths. When only adjusting for age, sex, and vaccination status, there was an increased risk of dying from COVID-19 with increased exposure to all air pollutants studied (NO2: HR 1.07 [95% confidence interval: 1.04-1.12] per 10 μg/m3; NOx: 1.05[1.02-1.09] per 20 μg/m3; PM10: 1.32[1.15-1.51] per 10 μg/m3; PM2.5: 1.29[1.12-1.49] per 5 μg/m3). However, after adjustment including ethnicity and socio-economic factors the HRs were close to unity (NO2: 0.98[0.90-1.06]; NOx: 0.99[0.94-1.04]; PM10: 0.95[0.74-1.22]; PM2.5: 0.90[0.67-1.20]). Additional adjustment for dominant variant or pre-existing health comorbidities did not alter the results.ConclusionsObserved associations between long-term outdoor air pollution exposure and COVID-19 mortality in London are strongly confounded by geography, ethnicity and deprivation.SummaryUsing a large individual-level dataset, we found that a positive association between long-term outdoor air pollution and COVID-19 mortality in London did not persist after adjusting for confounders including population density, ethnicity and deprivation.

The diagnosis of a severe physical health condition can cause psychological distress and lead to severe depression. The association between severe physical health conditions and the risk of suicide, and how the risk of suicide changes in the months following diagnosis, are not clear.We estimated whether a diagnosis of severe physical health conditions is associated with an increase in the risk of death by suicide using a dataset based on the 2011 Census linked to hospital records and death registration records covering 47,354,696 people alive on 1 January 2017 in England. Patients diagnosed with a low-survival cancer, chronic ischaemic heart disease, chronic obstructive pulmonary disease, or degenerative neurological condition were matched to individuals using socio-demographic characteristics from the Census. Using the Aalen-Johansen estimator, we estimated the cumulative incidence of death by suicide occurring between 1 January 2017 and 31 December 2021 (registered by 31 December 2021) in patients and matched controls, adjusted for other potential confounders using inverse probability weighting.Diagnosis of severe conditions was associated with an increased risk of dying by suicide. One year after diagnosis, the rate of suicide was 21.6 (95% confidence intervals: 14.9-28.4, number of events (N): 39) per 100,000 low-survival cancer patients compared to 9.5 (5.6-14.6, N:16) per 100,000 matched controls. For COPD patients, the one-year suicide rate was 22.4 (19.4-25.5, N:208) per 100,000 COPD patients (matched controls: 10.6, 8.3-13.0, N:85), for ischaemic heart disease 16.1 (14.1-18.2, N:225) per 100,000 patients (matched controls: 8.8, 7.1-10.4, N:128), for degenerative neurological conditions 114.5 (49.6-194.7, N:11) per 100,000 patients. The increase in risk was more pronounced in the first six months after diagnosis or first treatment.A diagnosis of severe physical illness is associated with higher suicide risk. The interaction of physical and mental illness emphasises the importance of collaborative physical and mental health care in these patients.The Office for National Statistics. KES is the Laing Galazka chair in palliative care at King's College London, funded by an endowment from Cicely Saunders International and the Kirby Laing Foundation.

BackgroundEstimating real-world vaccine effectiveness is vital to assess the impact of the vaccination programme on the pandemic and inform the ongoing policy response. However, estimating vaccine effectiveness using observational data is inherently challenging because of the non-randomised design and the potential for unmeasured confounding.MethodsWe used a Regression Discontinuity Design (RDD) to estimate vaccine effectiveness against COVID-19 mortality in England, exploiting the discontinuity in vaccination rates resulting from the UK’s age-based vaccination priority groups. We used the fact that people aged 80 or over were prioritised for the vaccine roll-out in the UK to compare the risk of COVID-19 and non-COVID-19 death in people aged 75–79 and 80–84.FindingsThe prioritisation of vaccination of people aged 80 or above led to a large discrepancy in vaccination rates in people 80–84 compared to those 75–79 at the beginning of the vaccination campaign. We found a corresponding difference in COVID-19 mortality, but not in non-COVID-19 mortality, suggesting that our approach appropriately addresses the issue of unmeasured confounding factors. Our results suggest that the first vaccine dose reduced the risk of COVID-19 death by 52.6% (95% Cl 26.6–84.2) in those aged 80.InterpretationsOur results support existing evidence that a first dose of a COVID-19 vaccine has a strong protective effect against COVID-19 mortality in older adults. The RDD estimate of vaccine effectiveness is comparable to previously published studies using different methods, suggesting that unmeasured confounding factors are unlikely to substantially bias these studies.FundingOffice for National Statistics.Research in ContextEvidence before this studyWe searched PubMed for studies reporting on the ‘real-world’ effectiveness of the COVID-19 vaccination on risk of death using terms such as “COVID-19”, “vaccine effectiveness”, “mortality” and “death”. The relevant published studies on this topic report vaccine effectiveness estimates against risk of death ranging from 64.2% to 98.7%, for varying times post-vaccination. All of these are observational studies and therefore potentially subject to bias from unmeasured confounding. We found no studies that used a quasi-experimental method such as regression discontinuity design, which is not subject to bias from unmeasured confounding, to calculate the effectiveness of the COVID-19 vaccination on risk of COVID-19 death, or on other outcomes such as hospitalisation or infection.Added value of this studyThe estimates of vaccine effectiveness based on observational data may be biased by unmeasured confounding. This study uses a regression discontinuity design to estimate vaccine effectiveness, exploiting the fact that the vaccination campaign in the UK was rolled out following age-based priority groups. This enables the calculation of an unbiased estimate of the effectiveness of the COVID-19 vaccine against risk of death.The vaccine effectiveness estimate of 52.6% (95% Cl 26.6–84.2) is slightly lower but similar to previously published estimates, therefore suggesting that these estimates are not substantially affected by unmeasured confounding factors and confirming the effectiveness of the COVID-19 vaccine against risk of COVID-19 death.Implications of all the available evidenceObtaining an unbiased estimate of COVID-19 vaccine effectiveness is of vital importance in informing policy for lifting COVID-19 related measures. The regression discontinuity design provides confidence that the existing estimates from observational studies are unlikely to be substantially biased by unmeasured confounding.

We investigated long COVID incidence by vaccination status in a random sample of UK adults from April 2020 to November 2021. Persistent symptoms were reported by 9.5% of 3090 breakthrough severe acute respiratory syndrome coronavirus 2 infections and 14.6% of unvaccinated controls (adjusted odds ratio, 0.59 [95% confidence interval, .50–.69]), emphasizing the need for public health initiatives to increase population-level vaccine uptake.

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 age-based 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 (1 February 2020–31 August 2020) and 2 731 427 in Wave 2 (1 September 2020–31 January 2021). Results 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 three other generations vs 67+-year-olds only: White hazard ratio (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. There was also an increased risk of severe COVID-19 in Wave 1 associated with living alone for White (HR 1.35 95% CI 1.30–1.41), South Asian (HR 1.47 95% CI 1.18–1.84) and Other (HR 1.72 95% CI 0.99–2.97) ethnicities, an effect that persisted for White older people in Wave 2. Conclusions Both multigenerational living and living alone were 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, whereas a substantial proportion of White older people live alone. 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.

ObjectiveTo assess the risk of death involving COVID-19 following infection from Omicron (B.1.1.539/BA.1) relative to Delta (B.1.617.2).DesignRetrospective cohort study.SettingEngland, UK, 1 December 2021 to 25 January 2022.Participants1,035,163 people aged 18-100 years who tested positive for SARS-CoV-2 in the national surveillance programme, and had an infection identified as either Omicron- or Delta compatible.Main outcome measuresDeath involving COVID-19 as identified from death certification records. The exposure of interest was the SARS-CoV-2 variant identified from NHS Test and Trace PCR positive tests taken in the community (pillar 2) and analysed by Lighthouse laboratories. Cause-specific Cox proportional hazard regression models were adjusted for sex, age, vaccination status, previous infection, calendar time, ethnicity, Index of Multiple Deprivation rank, household deprivation, university degree, keyworker status, country of birth, main language, region, disability, and comorbidities. Additionally, we tested for interactions between variant and sex, age, vaccination status and comorbidities.ResultsThe risk of death involving COVID-19 was 67% lower for Omicron compared to Delta and the reduction in the risk of death involving COVID-19 for Omicron compared to Delta was more pronounced in males than in females and in people under 70 years old than in people aged 70 years or over. Regardless of age, reduction of the risk of death from Omicron relative to Delta more was more pronounced in people who had received a booster than in those having received only two doses.ConclusionsOur results support early work showing the relative reduction in severity of Omicron compared to Delta in terms of hospitalisation and extends this research to assess COVID-19 mortality. Our work also highlights the importance of the vaccination booster campaign, where the reduction in risk of death involving COVID-19 is most pronounced in individuals who had received a booster.What is already known on this topicThe Omicron variant, which refers to the whole lineage (BA.1, BA.2, BA.3) had already been shown to be more transmissible than the Delta variant, but there is emerging evidence suggests that the risk of hospitalisation and risk of death within 28 days after a SARS-COV-2 test is lower. However, with a highly transmissible infection and high levels of population testing, definition of death within 28 days is more likely to be susceptible to misclassification bias due to asymptomatic or co-incidental infection. There is no study so far comparing the risk of COVID-19 death as identified from death certification records, with the cause of death assessed by the physician who attended the patient in the last illness.What this study addsUsing data from a large cohort of COVID-19 infections that occurred in December 2021, we examined the difference in the risk COVID-19 death, as identified from death certification records, between the Delta and Omicron BA.1 variant. Our study shows that risk of death involving COVID-19 was reduced by 67% following infection with the Omicron BA.1 variant relative to the Delta variant after adjusting for a wide range of potential confounders, including vaccination status and comorbidities. Importantly, we found that the relative risk of COVID-19 mortality following Omicron versus Delta infection varied by age and sex, with lower relative risk in younger individuals and for males than females. The reduction in risk of death involving COVID-19 was also most pronounced in individuals who had received a booster.

No abstract available.

ObjectiveTo estimate associations between covid-19 vaccination and long covid symptoms in adults with SARS-CoV-2 infection before vaccination.DesignObservational cohort study.SettingCommunity dwelling population, UK.Participants28 356 participants in the Office for National Statistics COVID-19 Infection Survey aged 18-69 years who received at least one dose of an adenovirus vector or mRNA covid-19 vaccine after testing positive for SARS-CoV-2 infection.Main outcome measurePresence of long covid symptoms at least 12 weeks after infection over the follow-up period 3 February to 5 September 2021.ResultsMean age of participants was 46 years, 55.6% (n=15 760) were women, and 88.7% (n=25 141) were of white ethnicity. Median follow-up was 141 days from first vaccination (among all participants) and 67 days from second vaccination (83.8% of participants). 6729 participants (23.7%) reported long covid symptoms of any severity at least once during follow-up. A first vaccine dose was associated with an initial 12.8% decrease (95% confidence interval −18.6% to −6.6%, PConclusionsThe likelihood of long covid symptoms was observed to decrease after covid-19 vaccination and evidence suggested sustained improvement after a second dose, at least over the median follow-up of 67 days. Vaccination may contribute to a reduction in the population health burden of long covid, although longer follow-up is needed.

Although most adults infected with SARS-CoV-2 fully recover, a proportion have ongoing symptoms, or post-COVID conditions (PCC), after infection. The objective of this analysis was to estimate the number of US adults with activity-limiting PCC on November 1, 2021.We modeled the prevalence of PCC using reported infections occurring from February 1, 2020 - September 30, 2021, and population-based, household survey data on new activity-limiting symptoms ≥1 month following SARS-CoV-2 infection. From these data sources, we estimated the number and proportion of US adults with activity-limiting PCC on November 1, 2021, as 95% uncertainty intervals, stratified by sex and age. Sensitivity analyses adjusted for under-ascertainment of infections and uncertainty about symptom duration.On November 1, 2021, at least 3.0-5.0 million US adults were estimated to have activity-limiting PCC of ≥1 month duration, or 1.2%-1.9% of US adults. Population prevalence was higher in females (1.4%-2.2%) than males. The estimated prevalence after adjusting for under-ascertainment of infections was 1.7%-3.8%.Millions of US adults were estimated to have activity-limiting PCC. These estimates can support future efforts to address the impact of PCC on the U.S. population.

Summary Objective To assess the association between household size and risk of non-severe or severe COVID-19. Design A longitudinal observational study. Setting This study utilised UK Biobank linked to national SARS-CoV-2 laboratory test data. Participants 401,910 individuals with available data on household size in UK Biobank. Main outcome measures Household size was categorised as single occupancy, two-person households and households of three or more. Severe COVID-19 was defined as a positive SARS-CoV-2 test on hospital admission or death with COVID-19 recorded as the underlying cause; and non-severe COVID-19 as a positive test from a community setting. Logistic regression models were fitted to assess associations, adjusting for potential confounders. Results Of 401,910 individuals, 3612 (1%) were identified as having suffered from a severe COVID-19 infection and 11,264 (2.8%) from a non-severe infection, between 16 March 2020 and 16 March 2021. Overall, the odds of severe COVID-19 was significantly higher among individuals living alone (adjusted odds ratio: 1.24 [95% confidence interval: 1.14 to 1.36], or living in a household of three or more individuals (adjusted odds ratio: 1.28 [1.17 to 1.39], when compared to individuals living in a household of two. For non-severe COVID-19 infection, individuals living in a single-occupancy household had lower odds compared to those living in a household of two (adjusted odds ratio: 0.88 [0.82 to 0.93]. Conclusions Odds of severe or non-severe COVID-19 infection were associated with household size. Increasing understanding of why certain households are more at risk is important for limiting spread of the infection.

ObjectivesTo assess whether there is a change in the incidence of cardiac and all-cause death in young people following COVID-19 vaccination or SARS-CoV-2 infection in unvaccinated individuals.DesignSelf-controlled case series.SettingNational, linked electronic health record data in England.Study populationIndividuals aged 12-29 who had received at least one dose of COVID-19 vaccination and died between 8 December 2020 and 2 February 2022 and registered by 16 February 2022 within 12 weeks of COVID-19 vaccination; Individuals aged 12-29 who died within 12 weeks of testing positive for SARS-CoV-2.Main outcome measuresCardiac and all-cause deaths occurring within 12 weeks of vaccination or SARS-CoV-2 infection.ResultsCompared to the baseline period, there was no evidence of a change in the incidence of cardiac death in the six weeks after vaccination, whether for each of weeks 1 to 6 or the whole six-week period. There was a decrease in the risk of all-cause death in the first week after vaccination and no change in each of weeks 2 to 6 after vaccination or whole six-week period after vaccination. Subgroup analyses by sex, age, vaccine type, and last dose also showed no change in the risk of death in the first six weeks after vaccination. There was a large increase in the incidence of cardiac and all-cause death in the overall risk period after SARS-CoV-2 infection among the unvaccinated.ConclusionThere is no evidence of an association between COVID-19 vaccination and an increased risk of death in young people. By contrast, SARS-CoV-2 infection was associated with substantially higher risk of cardiac related death and all-cause death.What is already known on this topicSeveral studies have highlighted the association between COVID-19 vaccination and the risk of myocarditis, myopericarditis, and other cardiac problems, especially in young people, but associated risk of mortality is unclear. Since younger people have lower risk of COVID-19 hospitalisation and mortality, the mortality risk associated with vaccination is potentially more important to them in balancing the risk and benefit of vaccination.What this study addsAlthough there is a risk of myocarditis or myopericarditis with COVID-19, there is no evidence of increased risk of cardiac or all-cause mortality following COVID-19 vaccination in young people aged 12 to 29. Given the increased risk of mortality following SARS-CoV-2 infection in this group, the risk-benefit analysis favours COVID-19 vaccination for this age group.

ObjectiveTo examine socio-demographic disparities in SARS-CoV-2 case rates during the second (Alpha) and third (Delta) waves of the COVID-19 pandemic.DesignRetrospective, population-based cohort study.SettingResident population of England.Participants39,006,194 people aged 10 years and over who were enumerated at the 2011 Census, registered with the National Health Service (NHS) and alive on 1 September 2020.Main outcome measuresTesting positive for SARS-CoV-2 during the second wave (1 September 2020 to 22 May 2021) or third wave (23 May to 10 December 2021) of the pandemic. We calculated age-standardised case rates by socio-demographic characteristics and used logistic regression models to estimate adjusted odds ratios (ORs).ResultsDuring the study period, 5,767,584 individuals tested positive for SARS-CoV-2. In the second wave, the fully-adjusted odds of having a positive test, relative to the White British group, were highest for the Bangladeshi (OR: 1.88, 95% CI 1.86 to 1.90) and Pakistani (1.81, 1.79 to 1.82) ethnic groups. Relative to the Christian group, Muslim and Sikh religious groups had fully-adjusted ORs of 1.58 (1.57 to 1.59) and 1.74 (1.72 to 1.76), respectively. Greater area deprivation, disadvantaged socio-economic position, living in a care home and low English language proficiency were also associated with higher odds of having a positive test. However, the disparities between groups varied over time. Being Christian, White British, non-disabled, and from a more advantaged socio-economic position were all associated with increased odds of testing positive during the third wave.ConclusionThere are large socio-demographic disparities on SARS-CoV-2 cases which have varied between different waves of the pandemic. Research is now urgently needed to understand why these disparities exist to inform policy interventions in future waves or pandemics.What is already known on this topicPeople with pre-existing health conditions or disability, ethnic minority groups, the elderly, some religious groups, people with low socio-economic status, and those living in deprived areas have been disproportionately affected by the COVID-19 pandemic in terms of risk of infection and adverse outcomes.What this study addsUsing linked data on 39 million people in England, we found that during the second wave, COVID-19 case rates were highest among the Bangladeshi and Pakistani ethnic groups, the Muslim religious group, individuals from deprived areas and of low socio-economic position; during the third wave, being Christian, White British, non-disabled, and from a more advantaged socio-economic position were all associated with increased odds of receiving a positive testAdjusting for geographical factors, socio-demographic characteristics, and pre-pandemic health status explained some, but not all, of the excess riskWhen stratifying the dataset by broad age groups, the odds of receiving a positive test remained higher among the Bangladeshi and Pakistani ethnic groups aged 65 years and over during the third wave, which may partly explain the continued elevated mortality rates in these groups

BackgroundIt is unclear whether receiving two COVID-19 vaccinations before SARS-CoV-2 infection reduces the risk of developing Long Covid symptoms. We examined whether the likelihood of symptoms 12 weeks after infection differed by vaccination status.MethodsWe included COVID-19 Infection Survey participants aged 18-69 years who tested positive for SARS-CoV-2 between 26 April 2020 and 30 November 2021; we excluded participants who, before their first test-confirmed infection, had suspected COVID-19 or Long Covid symptoms, or were single-vaccinated. Participants who were double-vaccinated ≥14 days before infection were 1:1 propensity-score matched, based on socio-demographic characteristics and time from infection to follow-up for Long Covid, to those unvaccinated at time of infection. We estimated adjusted odds ratios (aOR) of Long Covid symptoms ≥12 weeks post-infection, comparing double-vaccinated with unvaccinated (reference group) participants.ResultsThe study sample comprised 3,090 double-vaccinated participants (mean age 49 years, 54% female, 92% white, median follow-up from infection 96 days) and matched control participants. Long Covid symptoms were reported by 294 double-vaccinated participants (prevalence 9.5%) compared with 452 unvaccinated participants (14.6%), corresponding to an aOR for Long Covid symptoms of 0.59 (95% CI: 0.50 to 0.69). There was no evidence of heterogeneity by adenovirus vector versus messenger ribonucleic acid vaccines (p=0.25).ConclusionsCOVID-19 vaccination is associated with reduced risk of Long Covid, emphasising the need for public health initiatives to increase population-level vaccine uptake. Longer follow-up is needed, as is the assessment of further vaccine doses and the Omicron variant.

Aims Cardiovascular diseases (CVDs) increase mortality risk from coronavirus infection (COVID-19). There are also 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 and results We used (i) national mortality data for England and Wales to investigate trends in non-COVID-19 and CVD excess deaths; (ii) routine data from hospitals in England (n = 2), Italy (n = 1), and China (n = 5) to assess indirect pandemic effects on referral, diagnosis, and treatment services for CVD; and (iii) population-based electronic health records from 3 862 012 individuals in England to investigate pre- and post-COVID-19 mortality for people with incident and prevalent CVD. We incorporated pre-COVID-19 risk (by age, sex, and comorbidities), estimated population COVID-19 prevalence, and estimated relative risk (RR) of mortality in those with CVD and COVID-19 compared with CVD and non-infected (RR: 1.2, 1.5, 2.0, and 3.0). Mortality data suggest indirect effects on CVD will be delayed rather than contemporaneous (peak RR 1.14). CVD service activity decreased by 60–100% compared with pre-pandemic levels in eight hospitals across China, Italy, and England. 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. For total CVD (incident and prevalent), at 10% COVID-19 prevalence, we estimated direct impact of 31 205 and 62 410 excess deaths in England (RR 1.5 and 2.0, respectively), and indirect effect of 49 932 to 99 865 deaths. Conclusion Supply and demand for CVD services have dramatically reduced across countries with potential for substantial, but avoidable, excess mortality during and after the pandemic., Graphical Abstract Graphical Abstract

ObjectiveTo estimate associations between COVID-19 vaccination and Long Covid symptoms in adults who were infected with SARS-CoV-2 prior to vaccination.DesignObservational cohort study using individual-level interrupted time series analysis.SettingRandom sample from the community population of the UK.Participants28,356 COVID-19 Infection Survey participants (mean age 46 years, 56% female, 89% white) aged 18 to 69 years who received at least their first vaccination after test-confirmed infection.Main outcome measuresPresence of long Covid symptoms at least 12 weeks after infection over the follow-up period 3 February to 5 September 2021.ResultsMedian follow-up was 141 days from first vaccination (among all participants) and 67 days from second vaccination (84% of participants). First vaccination was associated with an initial 12.8% decrease (95% confidence interval: −18.6% to −6.6%) in the odds of Long Covid, but increasing by 0.3% (−0.6% to +1.2%) per week after the first dose. Second vaccination was associated with an 8.8% decrease (−14.1% to −3.1%) in the odds of Long Covid, with the odds subsequently decreasing by 0.8% (−1.2% to −0.4%) per week. There was no statistical evidence of heterogeneity in associations between vaccination and Long Covid by socio-demographic characteristics, health status, whether hospitalised with acute COVID-19, vaccine type (adenovirus vector or mRNA), or duration from infection to vaccination.ConclusionsThe likelihood of Long Covid symptoms reduced after COVID-19 vaccination, and the improvement was sustained over the follow-up period after the second dose. Vaccination may contribute to a reduction in the population health burden of Long Covid, though longer follow-up time is needed.Summary boxWhat is already known on this topicCOVID-19 vaccines are effective at reducing rates of SARS-CoV-2 infection, transmission, hospitalisation, and deathThe incidence of Long Covid may be reduced if infected after vaccination, but the relationship between vaccination and pre-existing long COVID symptoms is unclear, as published studies are generally small and with self-selected participantsWhat this study addsThe likelihood of Long Covid symptoms reduced after COVID-19 vaccination, and the improvement was sustained over the follow-up period after the second doseThere was no evidence of differences in this relationship by socio-demographic characteristics, health-related factors, vaccine type, or duration from infection to vaccinationAlthough causality cannot be inferred from this observational evidence, vaccination may contribute to a reduction in the population health burden of Long Covid; further research is needed to understand the biological mechanisms that may ultimately contribute to the development of therapeutics for Long Covid

BackgroundMonitoring differences in COVID-19 vaccination uptake in different groups is crucial to help inform the policy response to the pandemic. A key gap is the absence of data on uptake by occupation.MethodsUsing nationwide population-level data, we calculated the proportion of people who had received two doses of a COVID-19 vaccine (assessed on 31 August 2021) by detailed occupational categories in adults aged 40-64 and estimated adjusted odds ratios to examine whether these differences were driven by occupation or other factors, such as education. We also examined whether vaccination rates differed by ability to work from home.ResultsOur study population included 14,298,147 adults 40-64. Vaccination rates differed markedly by occupation, being higher in administrative and secretarial occupations (90.8%); professional occupations (90.7%); and managers, directors and senior officials (90.6%); and lowest (83.1%) in people working in elementary occupations. We found substantial differences in vaccination rates looking at finer occupational groups even after adjusting for confounding factors, such as education. Vaccination rates were higher in occupations which can be done from home and lower in those which cannot. Many occupations with low vaccination rates also involved contact with the public or with vulnerable peopleConclusionsIncreasing vaccination coverage in occupations with low vaccination rates is crucial to help protecting the public and control infection, especially in occupations that cannot be done from home and involve contacts with the public. Policies such as ‘work from home if you can’ may only have limited future impact on hospitalisations and deathsWhat is already known on this subject?Whilst several studies highlight differences in vaccination coverage by ethnicity, religion, socio-demographic factors and certain underlying health conditions, there is very little evidence on how vaccination coverage varies by occupation, in the UK and elsewhere. The few study looking at occupational differences in vaccine hesitancy focus on healthcare workers or only examined broad occupational groups. There is currently no large-scale study on occupational differences in COVID-19 vaccination coverage in the UK.What this study adds?Using population-level linked data combining the 2011 Census, primary care records, mortality and vaccination data, we found that the vaccination rates of adults aged 40 to 64 years in England differed markedly by occupation. Vaccination rates were high in administrative and secretarial occupations, professional occupations and managers, directors and senior officials and low in people working in elementary occupations. Adjusting for other factors likely to be linked to occupation and vaccination, such as education, did not substantially alter the results. Vaccination rates were also associated with the ability to work from home, with the vaccination rate being higher in occupations which can be done performed from home. Policies aiming to increase vaccination rates in occupations that cannot be done from home and involve contacts with the public should be priorities

Background Updatable estimates of COVID-19 onset, progression, and trajectories underpin pandemic mitigation efforts. To identify and characterise disease trajectories, we aimed to define and validate ten COVID-19 phenotypes from nationwide linked electronic health records (EHR) using an extensible framework. Methods In this cohort study, we used eight linked National Health Service (NHS) datasets for people in England alive on Jan 23, 2020. Data on COVID-19 testing, vaccination, primary and secondary care records, and death registrations were collected until Nov 30, 2021. We defined ten COVID-19 phenotypes reflecting clinically relevant stages of disease severity and encompassing five categories: positive SARS-CoV-2 test, primary care diagnosis, hospital admission, ventilation modality (four phenotypes), and death (three phenotypes). We constructed patient trajectories illustrating transition frequency and duration between phenotypes. Analyses were stratified by pandemic waves and vaccination status. Findings Among 57 032 174 individuals included in the cohort, 13 990 423 COVID-19 events were identified in 7 244 925 individuals, equating to an infection rate of 12·7% during the study period. Of 7 244 925 individuals, 460 737 (6·4%) were admitted to hospital and 158 020 (2·2%) died. Of 460 737 individuals who were admitted to hospital, 48 847 (10·6%) were admitted to the intensive care unit (ICU), 69 090 (15·0%) received non-invasive ventilation, and 25 928 (5·6%) received invasive ventilation. Among 384 135 patients who were admitted to hospital but did not require ventilation, mortality was higher in wave 1 (23 485 [30·4%] of 77 202 patients) than wave 2 (44 220 [23·1%] of 191 528 patients), but remained unchanged for patients admitted to the ICU. Mortality was highest among patients who received ventilatory support outside of the ICU in wave 1 (2569 [50·7%] of 5063 patients). 15 486 (9·8%) of 158 020 COVID-19-related deaths occurred within 28 days of the first COVID-19 event without a COVID-19 diagnoses on the death certificate. 10 884 (6·9%) of 158 020 deaths were identified exclusively from mortality data with no previous COVID-19 phenotype recorded. We observed longer patient trajectories in wave 2 than wave 1. Interpretation Our analyses illustrate the wide spectrum of disease trajectories as shown by differences in incidence, survival, and clinical pathways. We have provided a modular analytical framework that can be used to monitor the impact of the pandemic and generate evidence of clinical and policy relevance using multiple EHR sources. Funding British Heart Foundation Data Science Centre, led by Health Data Research UK.

IntroductionThe coronavirus pandemic has been particularly severe in the UK, with high infection and death rates, including among working age population.ObjectiveTo estimate occupational differences in COVID-19 mortality, taking into account confounding factors, such as regional differences, ethnicity, education, deprivation and pre-pandemic health.MethodsWe used data on 14,295,900 individuals who completed the UK Census in 2011, who were alive on 24 January 2020, were employed and aged 31–55 years in 2011. Data were linked to death and other health records. We examined differences between occupational groups in the risk of COVID-19 death from 24 January to 28 December 2020. We estimated age-standardised mortality rates per 100,000 person-years at risk stratified by sex and occupations. To estimate the effect of occupation due to work-related exposures, we used Cox proportional hazard models to adjust for confounding factors.ResultsThere is wide variation between occupations in COVID-19 mortality. Several occupations, particularly those involving contact with patients or the public, show three- or four-fold risks. These elevated risks were greatly attenuated after adjustment for confounding and mediating factors. For example, the hazard ratio (HR) for men working as taxi and cab drivers or chauffeurs changed from 4.60 [95%CI 3.62–5.84] to 1.47 [1.14–1.89] after adjustment. The overall HR for men working in essential occupations compared with men in non-essential occupations changed from 1.45 [1.34 - 1.56] to 1.22 [1.13 - 1.32] after adjustment. For most occupations, confounding and other mediating factors explained about 70% to 80% of the age-adjusted hazard ratios.ConclusionsWorking conditions are likely to play a role in COVID-19 mortality, particularly in occupations involving contact with COVID-19 patients or the public. However, there is also a substantial contribution from non-workplace factors, including regional factors, socio-demographic factors, and pre-pandemic health.

BackgroundThe UK began an ambitious COVID-19 vaccination programme on 8th December 2020. This study describes variation in vaccination coverage by sociodemographic characteristics between December 2020 and August 2021.MethodsUsing population-level administrative records linked to the 2011 Census, we estimated monthly first dose vaccination rates by age group and sociodemographic characteristics amongst adults aged 18 years or over in England. We also present a tool to display the results interactively.FindingsOur study population included 35,223,466 adults. A lower percentage of males than females were vaccinated in the young and middle age groups (18-59 years) but not in the older age groups. Vaccination rates were highest among individuals of White British and Indian ethnic backgrounds and lowest among Black Africans (aged ≥80 years) and Black Caribbeans (18-79 years). Differences by ethnic group emerged as soon as vaccination roll-out commenced and widened over time. Vaccination rates were also lower among individuals who identified as Muslim, lived in more deprived areas, reported having a disability, did not speak English as their main language, lived in rented housing, belonged to a lower socio-economic group, and had fewer qualifications.InterpretationWe found inequalities in COVID-19 vaccination rates by sex, ethnicity, religion, area deprivation, disability status, English language proficiency, socio-economic position, and educational attainment, but some of these differences varied by age group. Research is urgently needed to understand why these inequalities exist and how they can be addressed.Research in contextEvidence before this studyWe searched PubMed for publications on sociodemographic inequalities in COVID-19 vaccination coverage. Several studies have reported differences in coverage by characteristics such as ethnicity and religion, however these have focused on older adults and the clinically vulnerable who were initially prioritized for vaccination. There is little evidence on sociodemographic inequalities in vaccination coverage among younger adults and evidence is also lacking on coverage by a wider range of characteristics such as sex, disability status, English language proficiency, socio-economic position, and educational attainment.Added value of this studyThis study provides the first evidence for sociodemographic inequalities in COVID-19 vaccination coverage among the entire adult population in England, using population-level administrative records linked to the 2011 Census. By disaggregating the data by age group, we were able to show that disparities in coverage by some sociodemographic characteristics differed by age group. For example, a lower proportion of males than females were vaccinated in the young and middle age groups (18-59 years) but not in the older age groups, and vaccination rates were lowest among Black Africans in those aged ≥80 years but lowest among Black Caribbeans for all other age groups. Vaccination rates were also lower among individuals who identified as Muslim, lived in more deprived areas, reported having a disability, did not speak English as their main language, lived in rented housing, belonged to a lower socio-economic group, and had fewer qualifications.Implications of all the available evidenceMany of the groups with the lowest rates of COVID-19 vaccination are also the groups that have been disproportionately affected by the pandemic, including severe illness and mortality. Research is urgently needed to understand why these disparities exist and how they can be addressed, for example through public health or community engagement programmes. Since the relationships between sociodemographic characteristics and vaccination coverage may differ by age group, it is important for future research to disaggregate by age group when examining these inequalities.

ImportanceObesity and ethnicity are well characterised risk factors for severe COVID-19 outcomes, but the differential effects of obesity on COVID-19 outcomes by race/ethnicity has not been examined robustly in the general population.ObjectiveTo investigate the association between body mass index (BMI) and COVID-19 mortality across different ethnic groups.Design, Setting, and ParticipantsThis is a retrospective cohort study using linked national Census, electronic health records and mortality data for English adults aged 40 years or older who were alive at the start of pandemic (24th January 2020).ExposuresBMI obtained from electronic health records. Self-reported ethnicity (white, black, South Asian, other) was the effect-modifying variable.Main Outcomes and MeasuresCOVID-19 related death identified by ICD-10 codes U07.1 or U07.2 mentioned on the death certificate from 24th January 2020 until December 28th 2020.ResultsThe analysis included white (n = 11,074,708; mean age 61.9 [±13.4] years; 54% women), black (n = 416,542; 56.4 [±11.7] years; 57% women), South Asian (621,691; 55.7 [±12.4] years; 51% women) and other (n = 478,196; 55.3 [±11.6] years; 55% women) ethnicities with linked BMI data. The association between BMI and COVID-19 mortality was stronger in ethnic minority groups. Compared to a BMI of 22.5 kg/m2 in white ethnicities, the adjusted HR for COVID-19 mortality at a BMI of 30 kg/m2 in white, black, South Asian and other ethnicities was 0.95 (95% CI: 0.87-1.03), 1.72 (1.52-1.94), 2.00 (1.78-2.25) and 1.39 (1.21-1.61), respectively. The estimated risk of COVID-19 mortality at a BMI of 40 kg/m2 in white ethnicities (HR = 1.73) was equivalent to the risk observed at a BMI of 30.1 kg/m2, 27.0 kg/m2, and 32.2 kg/m2 in black, South Asian and other ethnic groups, respectively.ConclusionsThis population-based study using linked Census and electronic health care records demonstrates that the risk of COVID-19 mortality associated with obesity is greater in ethnic minority groups compared to white populations.QuestionDoes the association between BMI and COVID-19 mortality vary by ethnicity?FindingsIn this study of 12.6 million adults, BMI was associated with COVID-19 in all ethnicities, but with stronger associations in ethnic minority populations such that the risk of COVID-19 mortality for a BMI of 40 kg/m2 in white ethnicities was observed at a BMI of 30.1 kg/m2, 27.0 kg/m2, and 32.2 kg/m2 in black, South Asian and other ethnicities, respectively.MeaningBMI is a stronger risk factor for COVID-19 mortality in ethnic minorities. Obesity management is therefore a priority in these populations.

ObjectiveTo examine inequalities in COVID-19 vaccination rates among elderly adults in England.DesignCohort study.SettingPeople living in private households and communal establishments in England.Participants6 655 672 adults aged ≥70 years (mean 78.8 years, 55.2% women) who were alive on 15 March 2021.Main outcome measuresHaving received the first dose of a vaccine against COVID-19 by 15 March 2021. We calculated vaccination rates and estimated unadjusted and adjusted ORs using logistic regression models.ResultsBy 15 March 2021, 93.2% of people living in England aged 70 years and over had received at least one dose of a COVID-19 vaccine. While vaccination rates differed across all factors considered apart from sex, the greatest disparities were seen between ethnic and religious groups. The lowest rates were in people of black African and black Caribbean ethnic backgrounds, where only 67.2% and 73.8% had received a vaccine, with adjusted odds of not being vaccinated at 5.01 (95% CI 4.86 to 5.16) and 4.85 (4.75 to 4.96) times greater than the white British group. The proportion of individuals self-identifying as Muslim and Buddhist who had received a vaccine was 79.1% and 84.1%, respectively. Older age, greater area deprivation, less advantaged socioeconomic position (proxied by living in a rented home), being disabled and living either alone or in a multigenerational household were also associated with higher odds of not having received the vaccine.ConclusionResearch is now urgently needed to understand why disparities exist in these groups and how they can best be addressed through public health policy and community engagement.

BackgroundEthnic minorities have experienced disproportionate COVID-19 mortality rates in the UK and many other countries. We compared the differences in the risk of COVID-19 related death between ethnic groups in the first and second waves the of COVID-19 pandemic in England. We also investigated whether the factors explaining differences in COVID-19 death between ethnic groups changed between the two waves.MethodsUsing data from the Office for National Statistics Public Health Data Asset on individuals aged 30-100 years living in private households, we conducted an observational cohort study to examine differences in the risk of death involving COVID-19 between ethnic groups in the first wave (from 24th January 2020 until 31st August 2020) and second wave (from 1st September to 28th December 2020). We estimated age-standardised mortality rates (ASMR) in the two waves stratified by ethnic groups and sex. We also estimated hazard ratios (HRs) for ethnic-minority groups compared with the White British population, adjusted for geographical factors, socio-demographic characteristics, and pre-pandemic health conditions.ResultsThe study population included over 28.9 million individuals aged 30-100 years living in private households. In the first wave, all ethnic minority groups had a higher risk of COVID-19 related death compared to the White British population. In the second wave, the risk of COVID-19 death remained elevated for people from Pakistani (ASMR: 339.9 [95% CI: 303.7 – 376.2] and 166.8 [141.7 – 191.9] deaths per 100,000 population in men and women) and Bangladeshi (318.7 [247.4 – 390.1] and 127.1 [91.1 – 171.3] in men and women)background but not for people from Black ethnic groups. Adjustment for geographical factors explained a large proportion of the differences in COVID-19 mortality in the first wave but not in the second wave. Despite an attenuation of the elevated risk of COVID-19 mortality after adjusting for sociodemographic characteristics and health status, the risk was substantially higher in people from Bangladeshi and Pakistani background in both the first and the second waves.ConclusionBetween the first and second waves of the pandemic, the reduction in the difference in COVID-19 mortality between people from Black ethnic background and people from the White British group shows that ethnic inequalities in COVID-19 mortality can be addressed. The continued higher rate of mortality in people from Bangladeshi and Pakistani background is alarming and requires focused public health campaign and policy changes.*VN and NI contributed equally to this paperResearch in contextEvidence before this studyA recent systematic review by Pan and colleagues demonstrated that people of ethnic minority background in the UK and the USA have been disproportionately affected by the Coronavirus (COVID-19) pandemic, compared to White populations. While several studies have investigated whether adjusting for socio-demographic and economic factors and medical history reduces the estimated difference in risk of mortality and hospitalisation, the reasons for the differences in the risk of experiencing harms from COVID-19 are still being explored during the course of the pandemic. Studies so far have analysed the ethnic differences in COVID-19 mortality in the first wave of the pandemic. The evidence on the temporal trend of ethnic inequalities in COVID-19 mortality, especially those from the second wave of the pandemic, is scarce.Added value of this studyUsing data from the Office for National Statistics (ONS) Public Health Data Asset on 29 million adults aged 30-100 years living in private households in England, we conducted an observational cohort study to examine the differences in the risk of death involving COVID-19 between ethnic groups in the first wave (from 24th January 2020 until 31st August 2020) and second wave (from 1st September to 28th December 2020). We find that in the first wave all ethnic minority groups were at elevated risk of COVID-19 related death compared to the White British population. In the second wave, the differences in the risk of COVID-19 related death attenuated for Black African and Black Caribbean groups, remained substantially higher in people from Bangladeshi background, and worsened in people from Pakistani background. We also find that some of the factors explaining these differences in mortality have changed in the two waves.Implications of all the available evidenceThe risk of COVID-19 mortality during the first wave of the pandemic was elevated in people from ethnic minority background. An appreciable reduction in the difference in COVID-19 mortality in the second wave of the pandemic between people from Black ethnic background and people from the White British group is reassuring, but the continued higher rate of mortality in people from Bangladeshi and Pakistani background is alarming and requires focused public health campaign and policy response. Focusing on treating underlying conditions, although important, may not be enough in reducing the inequalities in COVID-19 mortality. Focused public health policy as well as community mobilisation and participatory public health campaign involving community leaders may help reduce the existing and widening inequalities in COVID-19 mortality.

ObjectiveTo estimate occupational differences in COVID-19 mortality, and test whether these are confounded by factors, such as regional differences, ethnicity and education or due to non-workplace factors, such as deprivation or pre-pandemic health.DesignRetrospective cohort studySettingPeople living in private households EnglandParticipants14,295,900 people aged 40-64 years (mean age 52 years, 51% female) who were alive on 24 January 2020, living in private households in England in 2019, were employed in 2011, and completed the 2011 census.Main outcome measuresCOVID-19 related death, assessed between 24 January 2020 and 28 December 2020. We estimated age-standardised mortality rates per 100,000 person-years at risk (ASMR) stratified by sex and occupations. To estimate the effect of occupation due to work-related exposures, we used Cox proportional hazard models to adjust for confounding (region, ethnicity, education), as well as non-workplace factors that are related to occupation.ResultsThere is wide variation between occupations in COVID-19 mortality. Several occupations, particularly those involving contact with patients or the public, show three-fold or four-fold risks. These elevated risks were greatly attenuated after adjustment for confounding and mediating non-workplace factors. For example, the hazard ratio (HR) for men working as taxi and cab drivers or chauffeurs changed from 4.60 [95%CI 3.62-5.84] to 1.47 [1.14-1.89] after adjustment. More generally, the overall HR for men working in essential occupations compared with men in non-essential occupations changed from 1.45 [1.34 - 1.56] to 1.22 [1.13 - 1.32] after adjustment. For most occupations, confounding and other mediating factors explained about 70% to 80% of the age-adjusted hazard ratios.ConclusionsWorking conditions are likely to play a role in COVID-19 mortality, particularly in occupations involving contact with COVID-19 patients or the public. However, there is also a substantial contribution from non-workplace factors, including regional factors, socio-demographic factors, and pre-pandemic health.

ObjectiveTo quantify rates of organ specific dysfunction in individuals with covid-19 after discharge from hospital compared with a matched control group from the general population.DesignRetrospective cohort study.SettingNHS hospitals in England.Participants47 780 individuals (mean age 65, 55% men) in hospital with covid-19 and discharged alive by 31 August 2020, exactly matched to controls from a pool of about 50 million people in England for personal and clinical characteristics from 10 years of electronic health records.Main outcome measuresRates of hospital readmission (or any admission for controls), all cause mortality, and diagnoses of respiratory, cardiovascular, metabolic, kidney, and liver diseases until 30 September 2020. Variations in rate ratios by age, sex, and ethnicity.ResultsOver a mean follow-up of 140 days, nearly a third of individuals who were discharged from hospital after acute covid-19 were readmitted (14 060 of 47 780) and more than 1 in 10 (5875) died after discharge, with these events occurring at rates four and eight times greater, respectively, than in the matched control group. Rates of respiratory disease (Pv4.6 (4.3 to 4.8) for age ≥70, and 11.4 (9.8 to 13.3) for non-whitev5.2 (5.0 to 5.5) for white individuals).ConclusionsIndividuals discharged from hospital after covid-19 had increased rates of multiorgan dysfunction compared with the expected risk in the general population. The increase in risk was not confined to the elderly and was not uniform across ethnicities. The diagnosis, treatment, and prevention of post-covid syndrome requires integrated rather than organ or disease specific approaches, and urgent research is needed to establish the risk factors.

BackgroundEthnic minorities have experienced disproportionate COVID-19 mortality rates. We estimated associations between household composition and COVID-19 mortality in older adults (≥ 65 years) using a newly linked census-based dataset, and investigated whether living in a multi-generational household explained some of the elevated COVID-19 mortality amongst ethnic minority groups.MethodsUsing retrospective data from the 2011 Census linked to Hospital Episode Statistics (2017-2019) and death registration data (up to 27th July 2020), we followed adults aged 65 years or over living in private households in England from 2 March 2020 until 27 July 2020 (n=10,078,568). We estimated hazard ratios (HRs) for COVID-19 death for people living in a multi-generational household compared with people living with another older adult, adjusting for geographical factors, socio-economic characteristics and pre-pandemic health. We conducted a causal mediation analysis to estimate the proportion of ethnic inequalities explained by living in a multi-generational household.ResultsLiving in a multi-generational household was associated with an increased risk of COVID-19 death. After adjusting for confounding factors, the HRs for living in a multi-generational household with dependent children were 1.13 [95% confidence interval 1.01-1.27] and 1.17 [1.01-1.35] for older males and females. The HRs for living in a multi-generational household without dependent children were 1.03 [0.97 - 1.09] for older males and 1.22 [1.12 - 1.32] for older females. Living in a multi-generational household explained between 10% and 15% of the elevated risk of COVID-19 death among older females from South Asian background, but very little for South Asian males or people in other ethnic minority groups.ConclusionOlder adults living with younger people are at increased risk of COVID-19 mortality, and this is a notable contributing factor to the excess risk experienced by older South Asian females compared to White females. Relevant public health interventions should be directed at communities where such multi-generational households are highly prevalent.FundingThis research was funded by the Office for National Statistics.