Changes in the trajectory of Long Covid symptoms following COVID-19 vaccination: community-based cohort study

OBJECTIVE: To estimate associations between COVID-19 vaccination and Long Covid symptoms in adults who were infected with SARS-CoV-2 prior to vaccination. DESIGN: Observational cohort study using individual-level interrupted time series analysis. SETTING: Random sample from the community population of the UK. PARTICIPANTS: 28,356 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 MEASURES: Presence of Long Covid symptoms at least 12 weeks after infection over the follow-up period 3 February to 5 September 2021. RESULTS: Median 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%, p<0.001) in the odds of Long Covid, with the data being compatible with both increases and decreases in the trajectory (+0.3% per week, 95% CI: -0.6% to +1.2% per week, p=0.51) after this. Second vaccination was associated with an 8.8% decrease (95% CI: -14.1% to -3.1%, p=0.003) in the odds of Long Covid, with the odds subsequently decreasing by 0.8% (-1.2% to -0.4%, p<0.001) 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. CONCLUSIONS: : The likelihood of Long Covid symptoms reduced after COVID-19 vaccination, and there was evidence of a sustained improvement after the second dose, at least over the median follow-up time of 67 days. Vaccination may contribute to a reduction in the population health burden of Long Covid, though longer follow-up time is needed

Assessing the reliability of ethnicity data recorded in health-related administrative datasets in England.

Objectives During the COVID-19 pandemic, higher mortality among some ethnic minority groups was identified and has become the subject of significant public and government interest, highlighting an urgent requirement to quantify the reliability of ethnicity classification across health administrative data sets, which are utilised in health analysis and pandemic planning. Approach The aim of our work was to assess how ethnicity data recorded in Census and health admin records varied across ethnicities and provide recommendations for how missingness can be accounted for by statisticians. Combining population level data from general practice (GP) records with hospital episode statistics (HES) for patients in England, we created a linked data set with Census 2011 data to reliably assess coverage and missingness between data sources. Most recent and modal ethnicity classifications were derived on a person-level from both HES and GP administrative data for comparison to gold-standard Census 2011 records. Results Agreement rates were calculated to assess the reliability of ethnicity data recorded in health administrative datasets compared to Census data. We found that the agreement rates vary by ethnic group and other demographic characteristics. Furthermore, we highlighted groups of people who exist in one health-admin source, but not Census, and vice versa, illustrating the importance of accounting for the sample bias in health analysis when relying solely on primary or secondary care data sources. Implementation of techniques to account for bias and missingness were tested to propose methodology to improve reliability of ethnicity estimates from both HES and GP data, in order to ensure estimates of health disparities are as accurate as possible. Conclusion We have linked GP records to Census 2011 and HES data to provide population-based ethnicity estimates of coverage, missingness and bias between data sources, in order to improve our understanding of ethnicity data quality. This work aims to inform policies tackling ethnic health inequalities in England

Inequalities in SARS-CoV-2 case rates by ethnicity, religion, measures of socioeconomic position, English proficiency, and self-reported disability: cohort study of 39 million people in England during the alpha and delta waves

Objective: To examine sociodemographic inequalities in people with SARS-CoV-2 during the second (alpha) and third (delta) waves of the covid-19 pandemic. / Design: Retrospective, population based cohort study. / Setting: Resident population of England. / Participants: 39 006 194 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 measures: Age 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). / Results: During 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. / Conclusion: Research 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

Risk of Long Covid in people infected with SARS-CoV-2 after two doses of a COVID-19 vaccine: community-based, matched cohort study

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 3,090 breakthrough SARS-CoV-2 infections and 14.6% of unvaccinated controls (adjusted odds ratio 0.59, 95% CI: 0.50-0.69), emphasising the need for public health initiatives to increase population-level vaccine uptake

Deaths involving COVID-19 by self-reported disability status during the first two waves of the COVID-19 pandemic in England: a retrospective, population-based cohort study.

BACKGROUND: People with learning disabilities are at substantially increased risk of COVID-19 mortality, but evidence on risks of COVID-19 mortality for disabled people more generally is limited. We aimed to use population-level data to estimate the association between self-reported disability and death involving COVID-19 during the first two waves of the COVID-19 pandemic in England. METHODS: We conducted a retrospective, population-based cohort study of adults aged 30-100 years living in private households or communal establishments in England, using data from the Office for National Statistics Public Health Data Asset. Participants were present at the 2011 Census and alive on Jan 24, 2020. Participants reported being limited a lot in their daily activities, limited a little, or not limited at all, in response to a question from the 2011 Census. The outcome was death involving COVID-19, occurring between Jan 24, 2020, and Feb 28, 2021. We used Cox proportional hazards regression to calculate hazard ratios (HRs) for the association between disability and death involving COVID-19, sequentially adjusting for age, residence type (private household, care home, or other communal establishment), geographical characteristics (local authority district and population density), sociodemographic characteristics (ethnicity, highest qualification, Index of Multiple Deprivation decile, household characteristics [National Statistics Socio-economic Classification of the household reference person, tenure of household, household size, family status, household composition, and key worker in household], key worker type, individual and household exposure to disease, and individual and household proximity to others), and health status (pre-existing health conditions, body-mass index, and number of admissions to hospital and days spent in hospital over the previous 3 years). FINDINGS: 29 293 845 adults were included in the study (13 806 623 [47%] men, 15 487 222 [53%] women), of whom 3 038 772 (10%) reported being limited a little and 2 011 576 (7%) reported being limited a lot. During follow-up, 105 213 people died from causes involving COVID-19 in England, 61 416 (58%) of whom were disabled. Age-adjusted analyses showed higher mortality involving COVID-19 among disabled people who were limited a lot (HR 3·05 [95% CI 2·98-3·11] for men; 3·48 [3·41-3·56] for women) and disabled people who were limited a little (HR 1·88 [1·84-1·92] for men; 2·03 [1·98-2·08] for women) than among non-disabled people. Adjustment for residence type, geography, sociodemographics, and health conditions reduced but did not eliminate the associations between disability and death involving COVID-19 (HR 1·35 [1·32-1·38] for men who were limited a lot; 1·21 [1·18-1·23] for men who were limited a little; 1·55 [1·51-1·59] for women who were limited a lot; and 1·28 [1·25-1·31] for women who were limited a little). INTERPRETATION: Given the association between disability and mortality involving COVID-19, verification of these findings and consideration of recommendations for protective measures are now required. FUNDING: None

Sociodemographic inequality in COVID-19 vaccination coverage among elderly adults in England: a national linked data study.

OBJECTIVE: To examine inequalities in COVID-19 vaccination rates among elderly adults in England. DESIGN: Cohort study. SETTING: People living in private households and communal establishments in England. PARTICIPANTS: 6 655 672 adults aged ≥70 years (mean 78.8 years, 55.2% women) who were alive on 15 March 2021. MAIN OUTCOME MEASURES: Having 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. RESULTS: By 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. CONCLUSION: Research 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

COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records

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

Linked electronic health records for research on a nationwide cohort of more than 54 million people in England: data resource

Abstract: Objective: To describe a novel England-wide electronic health record (EHR) resource enabling whole population research on covid-19 and cardiovascular disease while ensuring data security and privacy and maintaining public trust. Design: Data resource comprising linked person level records from national healthcare settings for the English population, accessible within NHS Digital’s new trusted research environment. Setting: EHRs from primary care, hospital episodes, death registry, covid-19 laboratory test results, and community dispensing data, with further enrichment planned from specialist intensive care, cardiovascular, and covid-19 vaccination data. Participants: 54.4 million people alive on 1 January 2020 and registered with an NHS general practitioner in England. Main measures of interest: Confirmed and suspected covid-19 diagnoses, exemplar cardiovascular conditions (incident stroke or transient ischaemic attack and incident myocardial infarction) and all cause mortality between 1 January and 31 October 2020. Results: The linked cohort includes more than 96% of the English population. By combining person level data across national healthcare settings, data on age, sex, and ethnicity are complete for around 95% of the population. Among 53.3 million people with no previous diagnosis of stroke or transient ischaemic attack, 98 721 had a first ever incident stroke or transient ischaemic attack between 1 January and 31 October 2020, of which 30% were recorded only in primary care and 4% only in death registry records. Among 53.2 million people with no previous diagnosis of myocardial infarction, 62 966 had an incident myocardial infarction during follow-up, of which 8% were recorded only in primary care and 12% only in death registry records. A total of 959 470 people had a confirmed or suspected covid-19 diagnosis (714 162 in primary care data, 126 349 in hospital admission records, 776 503 in covid-19 laboratory test data, and 50 504 in death registry records). Although 58% of these were recorded in both primary care and covid-19 laboratory test data, 15% and 18%, respectively, were recorded in only one. Conclusions: This population-wide resource shows the importance of linking person level data across health settings to maximise completeness of key characteristics and to ascertain cardiovascular events and covid-19 diagnoses. Although this resource was initially established to support research on covid-19 and cardiovascular disease to benefit clinical care and public health and to inform healthcare policy, it can broaden further to enable a wide range of research