Study protocol for the use of time series forecasting and risk analyses to investigate the effect of the COVID-19 pandemic on hospital admissions associated with new-onset disability and frailty in a national, linked electronic health data setting.

INTRODUCTION: Older people were at particular risk of morbidity and mortality during COVID-19. Consequently, they experienced formal (externally imposed) and informal (self-imposed) periods of social isolation and quarantine. This is hypothesised to have led to physical deconditioning, new-onset disability and frailty. Disability and frailty are not routinely collated at population level but are associated with increased risk of falls and fractures, which result in hospital admissions. First, we will examine incidence of falls and fractures during COVID-19 (January 2020-March 2022), focusing on differences between incidence over time against expected rates based on historical data, to determine whether there is evidence of new-onset disability and frailty. Second, we will examine whether those with reported SARS-CoV-2 were at higher risk of falls and fractures. METHODS AND ANALYSIS: This study uses the Office for National Statistics (ONS) Public Health Data Asset, a linked population-level dataset combining administrative health records with sociodemographic data of the 2011 Census and National Immunisation Management System COVID-19 vaccination data for England. Administrative hospital records will be extracted based on specific fracture-centric International Classification of Diseases-10 codes in years preceding COVID-19 (2011-2020). Historical episode frequency will be used to predict expected admissions during pandemic years using time series modelling, if COVID-19 had not occurred. Those predicted admission figures will be compared with actual admissions to assess changes in hospital admissions due to public health measures comprising the pandemic response. Hospital admissions in prepandemic years will be stratified by age and geographical characteristics and averaged, then compared with pandemic year admissions to assess more granular changes. Risk modelling will assess risk of experiencing a fall, fracture or frail fall and fracture, if they have reported a positive case of COVID-19. The combination of these techniques will provide insight into changes in hospital admissions from the COVID-19 pandemic. ETHICS AND DISSEMINATION: This study has approval from the National Statistician's Data Ethics Advisory Committee (NSDEC(20)12). Results will be made available to other researchers via academic publication and shared via the ONS website.

Ethnic differences in COVID-19 mortality in the second and third waves of the pandemic in England during the vaccine rollout: a retrospective, population-based cohort study.

BACKGROUND: Ethnic minority groups in England have been disproportionately affected by the COVID-19 pandemic and have lower vaccination rates than the White British population. We examined whether ethnic differences in COVID-19 mortality in England have continued since the vaccine rollout and to what extent differences in vaccination rates contributed to excess COVID-19 mortality after accounting for other risk factors. METHODS: We conducted a retrospective, population-based cohort study of 28.8 million adults aged 30-100 years in England. Self-reported ethnicity was obtained from the 2011 Census. The outcome was death involving COVID-19 during the second (8 December 2020 to 12 June 2021) and third wave (13 June 2021 to 1 December 2021). We calculated hazard ratios (HRs) for death involving COVID-19, sequentially adjusting for age, residence type, geographical factors, sociodemographic characteristics, pre-pandemic health, and vaccination status. RESULTS: Age-adjusted HRs of death involving COVID-19 were elevated for most ethnic minority groups during both waves, particularly for groups with lowest vaccination rates (Bangladeshi, Pakistani, Black African, and Black Caribbean). HRs were attenuated after adjusting for geographical factors, sociodemographic characteristics, and pre-pandemic health. Further adjusting for vaccination status substantially reduced residual HRs for Black African, Black Caribbean, and Pakistani groups in the third wave. Fully adjusted HRs only remained elevated for the Bangladeshi group (men: 2.19 [95% CI 1.72-2.78]; women: 2.12 [1.58-2.86]) and Pakistani men (1.24 [1.06-1.46]). CONCLUSIONS: Lower COVID-19 vaccination uptake in several ethnic minority groups may drive some of the differences in COVID-19 mortality compared to White British. Public health strategies to increase vaccination uptake in ethnic minority groups would help reduce inequalities in COVID-19 mortality, which have remained substantial since the start of the vaccination campaign.

Religious affiliation and COVID-19-related mortality: a retrospective cohort study of prelockdown and postlockdown risks in England and Wales.

BACKGROUND: COVID-19 mortality risk is associated with demographic and behavioural factors; furthermore, religious gatherings have been linked with the spread of COVID-19. We sought to understand the variation in risk of COVID-19-related death across religious groups in England and Wales both before and after the first national lockdown. METHODS: We conducted a retrospective cohort study of usual residents in England and Wales enumerated at the 2011 Census (n=47 873 294, estimated response rate 94%) for risk of death involving COVID-19 using linked death certificates. Cox regression models were estimated to compare risks between religious groups. Time-dependent coefficients were added to the model allowing HRs before and after lockdown period to be estimated separately. RESULTS: Compared with Christians, all religious groups had an elevated risk of death involving COVID-19; the largest age-adjusted HRs were for Muslim and Jewish males at 2.5 (95% CI 2.3 to 2.7) and 2.1 (95% CI 1.9 to 2.5), respectively. The corresponding HRs for Muslim and Jewish females were 1.9 (95% CI 1.7 to 2.1) and 1.5 (95% CI 1.7 to 2.1), respectively. The difference in risk between groups contracted after lockdown. Those who affiliated with no religion had the lowest risk of COVID-19-related death before and after lockdown. CONCLUSION: The majority of the variation in COVID-19 mortality risk was explained by controlling for sociodemographic and geographic determinants; however, those of Jewish affiliation remained at a higher risk of death compared with all other groups. Lockdown measures were associated with reduced differences in COVID-19 mortality rates between religious groups; further research is required to understand the causal mechanisms.