The impact of Long COVID on Health-Related Quality-of-life using OpenPROMPT (preprint)

Background: Long COVID is a major problem affecting patient health, the health service, and the workforce. To optimise the design of future interventions against COVID-19, and to better plan and allocate health resources, it is critical to quantify the health and economic burden of this novel condition. Methods With the approval of NHS England, we developed OpenPROMPT, a UK cohort study measuring the impact of long COVID on health-related quality-of-life (HRQoL). OpenPROMPT invited responses to Patient Reported Outcome Measures (PROMs) using a smartphone application and recruited between November 2022 and October 2023. We used the validated EuroQol EQ-5D questionnaire with the UK Value Set to develop disutility scores (1-utility) for respondents with and without Long COVID using linear mixed models, and we calculated subsequent Quality-Adjusted Life-Months (QALMs) for long COVID. Results We used data from 6,070 participants where 24.7% self-reported long COVID. In multivariable regressions, long COVID had a consistent impact on HRQoL, showing a high probability of reporting loss in quality-of-life (OR: 22, 95% CI:12.35-39.29) compared with people who did not report long COVID. Reporting a disability was the largest predictor of losses of HRQoL (OR: 60.2, 95% CI: 27.79-130.57) across survey responses. Self-reported long COVID was associated with an 0.37 QALM loss. Conclusions We found substantial impacts on quality-of-life due to long COVID, representing a major burden on patients and the health service. We highlight the need for continued support and research for long COVID, as HRQoL scores compared unfavourably to patients with conditions such as multiple sclerosis, heart failure, and renal disease.

Fit notes associated with COVID-19 in 24 million patients' primary care records: A cohort study in OpenSAFELY-TPP (preprint)

Background: Fit notes ("sick notes") are issued by general practitioners (GPs) when a person can't work for health reasons and is an indication of the public health and economic burden for people recovering from COVID-19. Methods: With NHS England approval, we used routine clinical data from >24 million patients to compare fit note incidence in people 18-64 years with and without evidence of COVID-19 in 2020, 2021 and 2022. We fit Cox regression models to estimate adjusted hazard ratios, overall and by time post-diagnosis and within demographic subgroups. Results: We identified 365,421, 1,206,555 and 1,321,313 people with evidence of COVID-19 in 2020, 2021 and 2022. The fit note rate was 4.88 per 100 person-months (95%CI 4.83-4.93) in 2020, 2.66 (95%CI 2.64-2.67) in 2021, and 1.73 (95%CI 1.72-1.73) in 2022. Compared with the age, sex and region matched general population, the hazard ratio (HR) adjusted for demographics and clinical characteristics over the follow-up period was 4.07 (95%CI 4.02-4.12) in 2020 decreasing to 1.57 (95%CI 1.56-1.58) in 2022. The HR was highest in the first 30 days in all years. Conclusions: Despite likely underestimation of the fit note rate, we identified a considerable increase among people with COVID-19, even in an era when most people are vaccinated. Most fit notes are associated with the acute phase of the disease, but the increased risk several months post-diagnosis provides further evidence of the long-term impact.

Impact of COVID-19 on recorded blood pressure screening and hypertension management in England: An analysis of monthly changes in Quality and Outcomes Framework indicators in OpenSAFELY (preprint)

Background: Cardiovascular disease management in primary care in England was disrupted during the COVID-19 pandemic. Objective: We aim to describe the impact of the COVID-19 pandemic on blood pressure screening and hypertension management, based upon a national quality of care scheme (Quality and Outcomes Framework, QOF) across key demographic, regional, and clinical subgroups. To this end, we translate complex clinical quality of care schemes from text descriptions into reusable analytic code. Methods: With the approval of NHS England, a population based cohort study was conducted on 25.2 million patient records in situ using OpenSAFELY-TPP. We included all NHS patients registered at general practices using TPP software between March 2019 and March 2023. Individuals that were eligible for blood pressure screening and with a diagnosis of hypertension were identified according to the QOF 2021/22 business rules. We examined monthly changes in recorded blood pressure screening in the preceding 5 years in patients aged [≥] 45, recorded hypertension prevalence, and the recorded percentage of patients treated to target (i.e., [≤] 140/90 mmHg for patients [≤] 79 years and [≤] 150/90 mmHg for patients [≥] 80 years) in the preceding 12 months, within demographic, regional, and clinical subgroups as well as the variation across practices. Results: The overall percentage of patients aged [≥] 45 who had blood pressure screening recorded in the preceding 5 years decreased from 90% in March 2019 to 85% in March 2023. Recorded hypertension prevalence was relatively stable at 15% throughout the study period. The percentage of patients with a record of hypertension treated to target in the preceding 12 months reduced from a maximum of 71% in March 2020 to a minimum of 47% in February 2021 in patients aged [≤] 79 years, and from 85% in March 2020 to a minimum of 58% in February 2021 in patients aged [≥] 80 years before recovering. Blood pressure screening rates in the preceding 5 years remained stable in older age groups, patients with a record of learning disability, or care home status. Conclusions: There was substantial disruption to hypertension management QOF indicators during the pandemic, which can likely be attributed to a general reduction of blood pressure screening. OpenSAFELY can be used to continuously monitor monthly changes in national quality of care schemes to identify changes in key clinical subgroups early and support prioritisation of recovery from disrupted care caused by COVID-19.

Living alone and mental health: parallel analyses in longitudinal population surveys and electronic health records prior to and during the COVID-19 pandemic (preprint)

Objectives: To describe the mental health gap between those who live alone and those who live with others, and to examine whether the COVID-19 pandemic had an impact on this gap. Design: Ten population based prospective cohort studies, and a retrospective descriptive cohort study based on electronic health records (EHRs). Setting: UK Longitudinal population-based surveys (LPS), and primary and secondary care records within the OpenSAFELY-TPP database. Participants: Participants from the LPS were included if they had information on living status in early 2020, valid data on mental ill-health at the closest pre-pandemic assessment and at least once during the pandemic, and valid data on a key minimum set of covariates. The EHR dataset included 16 million adults registered with primary care practices in England using TPP SystmOne software on 1st February 2020, with at least three months of registration, valid address data, and living in households of <16 people. Main outcome measures: In the LPS, self-reported survey measures of psychological distress and life satisfaction were assessed in the nearest pre-pandemic sweep and three periods during the pandemic: April-June 2020, July-October 2020, and November 2020-March 2021. In the EHR analyses, outcomes were morbidity codes recorded in primary or secondary care between March 2018 and January 2022 reflecting the diagnoses of depression, self-harm, anxiety, obsessive compulsive disorder, eating disorders, and severe mental illnesses. Results: The LPS consisted of 37,544 participants (15.2% living alone) and we found greater psychological distress (SMD: 0.09 (95% CI: 0.04, 0.14) and lower life satisfaction (SMD: -0.22 (95% CI: -0.30, -0.15) in those living alone pre-pandemic, and the gap between the two groups stayed similar after the onset of the pandemic. In the EHR analysis of almost 16 million records (21.4% living alone), codes indicating mental health conditions were more common in those who lived alone compared to those who lived with others (e.g., depression 26 and severe mental illness 58 cases more per 100,000). Recording of mental health conditions fell during the pandemic for common mental health disorders and the gap between the two groups narrowed. Conclusions: Multiple sources of data indicate that those who live alone experience greater levels of common and severe mental illnesses, and lower life satisfaction. During the pandemic this gap in need remained, however, there was a narrowing of the gap in service use, suggesting greater barriers to healthcare access for those who live alone.

Comparative effectiveness of Paxlovid versus sotrovimab and molnupiravir for preventing severe COVID-19 outcomes in non-hospitalised patients: observational cohort study using the OpenSAFELY platform (preprint)

Objective: To compare the effectiveness of Paxlovid vs. sotrovimab and molnupiravir in preventing severe COVID-19 outcomes in non-hospitalised high-risk COVID-19 adult patients. Design: With the approval of NHS England, we conducted a real-world cohort study using the OpenSAFELY-TPP platform. Setting: Patient-level electronic health record data were obtained from 24 million people registered with a general practice in England that uses TPP software. The primary care data were securely linked with data on COVID-19 infection and therapeutics, hospital admission, and death within the OpenSAFELY-TPP platform, covering a period where both Paxlovid and sotrovimab were first-line treatment options in community settings. Participants: Non-hospitalised adult COVID-19 patients at high risk of severe outcomes treated with Paxlovid, sotrovimab or molnupiravir between February 11, 2022 and October 1, 2022. Interventions: Paxlovid, sotrovimab or molnupiravir administered in the community by COVID-19 Medicine Delivery Units. Main outcome measure: COVID-19 related hospitalisation or COVID-19 related death within 28 days after treatment initiation. Results: A total of 7683 eligible patients treated with Paxlovid (n=4836) and sotrovimab (n=2847) were included in the main analysis. The mean age was 54.3 (SD=14.9) years; 64% were female, 93% White and 93% had three or more COVID-19 vaccinations. Within 28 days after treatment initiation, 52 (0.68%) COVID-19 related hospitalisations/deaths were observed (33 (0.68%) treated with Paxlovid and 19 (0.67%) with sotrovimab). Cox proportional hazards model stratified by region showed that after adjusting for demographics, high-risk cohort categories, vaccination status, calendar time, body mass index and other comorbidities, treatment with Paxlovid was associated with a similar risk of outcome event as treatment with sotrovimab (HR=1.14, 95% CI: 0.62 to 2.08; P=0.673). Results from propensity score weighted Cox model also showed comparable risks in these two treatment groups (HR=0.88, 95% CI: 0.45 to 1.71; P=0.700). An exploratory analysis comparing Paxlovid users with 802 molnupiravir users (11 (1.37%) COVID-19 related hospitalisations/deaths) showed some evidence in favour of Paxlovid but with variation in the effect estimates between models (HR ranging from 0.26 to 0.61). Conclusion: In routine care of non-hospitalised high-risk adult patients with COVID-19 in England, no substantial difference in the risk of severe COVID-19 outcomes was observed between those who received Paxlovid and sotrovimab between February and October 2022, when different subvariants of Omicron were dominant.

Ethnic differences in the indirect impacts of the COVID-19 pandemic on clinical monitoring and hospitalisations for non-COVID conditions in England: An observational cohort study using OpenSAFELY (preprint)

Background: The COVID-19 pandemic disrupted healthcare and may have impacted ethnic inequalities in healthcare. We aimed to describe the impact of pandemic-related disruption on ethnic differences in clinical monitoring and hospital admissions for non-COVID conditions in England. Methods We conducted a cohort study using OpenSAFELY (2018-2022). We grouped ethnicity (exposure), into five categories: White, South Asian, Black, Other, Mixed. We used interrupted time-series regression to estimate ethnic differences in clinical monitoring frequency (e.g., blood pressure measurements) before and after 23rd March 2020. We used multivariable Cox regression to quantify ethnic differences in hospitalisations related to: diabetes, cardiovascular disease, respiratory disease, and mental health before and after 23rd March 2020. Findings Of 14,930,356 adults in 2020 with known ethnicity (92% of sample): 86.6% were White, 7.3% Asian, 2.6% Black, 1.4% Mixed ethnicity, and 2.2% Other ethnicities. Clinical monitoring did not return to pre-pandemic levels for any ethnic group. Ethnic differences were apparent pre-pandemic, except for diabetes monitoring, and remained unchanged, except for blood pressure monitoring in those with mental health conditions where differences narrowed during the pandemic. For those of Black ethnicity, there were seven additional admissions for diabetic ketoacidosis per month during the pandemic, and relative ethnic differences narrowed during the pandemic compared to White. There was increased admissions for heart failure during the pandemic for all ethnic groups, though highest in White ethnicity. Relatively, ethnic differences narrowed for heart failure admission in those of Asian and Black ethnicity compared to White. For other outcomes the pandemic had minimal impact on ethnic differences. Interpretation Our study suggests ethnic differences in clinical monitoring and hospitalisations remained largely unchanged during the pandemic for most conditions. Key exceptions were hospitalisations for diabetic ketoacidosis and heart failure, which warrant further investigation to understand the causes. Funding LSHTM COVID-19 Response Grant (DONAT15912).

Comparative effectiveness of sotrovimab and molnupiravir for preventing severe COVID-19 outcomes in non-hospitalised patients on kidney replacement therapy: observational cohort study using the OpenSAFELY-UKRR linked platform and SRR database (preprint)

Background Patients on kidney replacement therapy (KRT; dialysis and kidney transplantation) are at the highest risk of severe outcomes from COVID-19. Due to limited inclusion of patients on KRT in clinical trials, information is limited on the effectiveness of sotrovimab (a neutralising monoclonal antibody). We sought to address this by comparing its effectiveness against molnupiravir (an antiviral) in preventing severe COVID-19 outcomes in non-hospitalised adults with symptomatic COVID-19. Methods With the approval of NHS England we used routine clinical data from 24 million patients in England linked to the UK Renal Registry (UKRR) to identify patients on KRT, and data on antiviral treatments, COVID-19 test results, hospitalisation events and death from the OpenSAFELY-TPP data resource. Cox proportional hazards models (stratified for region) were used to estimate hazard ratios of sotrovimab vs. molnupiravir with regards to COVID-19 related hospitalisation or deaths in the subsequent 28 days (as the primary outcome). Further analyses were conducted using propensity score weighting (adjusted for region) and to investigate robustness of results with regards to different time periods, missing data, and adjustment variables. We also conducted a complementary analysis using data from patients in the Scottish Renal Registry (SRR) treated with sotrovimab or molnupiravir, following similar analytical approaches. Results Among the 2367 renal patients treated with sotrovimab (n=1852) or molnupiravir (n=515) between December 16, 2021 and August 1, 2022 in England, 38 cases (1.6%) of COVID-19 related hospitalisations/deaths were observed during the 28 days of follow-up after treatment initiation, with 21 (1.1%) in the sotrovimab group and 17 (3.3%) in the molnupiravir group. In multiple-adjusted analysis sotrovimab was associated with substantially lower risk of 28-day COVID-19 related hospitalisation/death than treatment with molnupiravir (hazard ratio, HR=0.35, 95% CI: 0.17 to 0.71; P=0.004), with results remaining robust in sensitivity analyses. In the SRR cohort, there were 19 cases (1.9%) of COVID-19 related hospitalisations/deaths during the 28 days of follow-up after treatment initiation of sotrovimab (n=723) or molnupiravir (n=270). In multiple-adjusted analysis, sotrovimab showed a trend toward lower risk of 28-day COVID-19 related hospitalisation/death than treatment with molnupiravir (HR=0.40, 95% CI: 0.13 to 1.21; P=0.106). In both datasets, sotrovimab had no evidence of association with other hospitalisation/death compared with molnupiravir (HRs ranging from 0.73-1.20; P>0.05). Conclusions In routine care of non-hospitalised patients with COVID-19 on kidney replacement therapy, those who received sotrovimab had substantially lower risk of severe COVID-19 outcomes than those receiving molnupiravir.

Accident and emergency (AE) attendance in England following infection with SARS-CoV-2 Omicron or Delta (preprint)

The SARS-CoV-2 Omicron variant is increasing in prevalence around the world. Accurate estimation of disease severity associated with Omicron is critical for pandemic planning. We found lower risk of accident and emergency (AE) attendance following SARS-CoV-2 infection with Omicron compared to Delta (HR: 0.39 (95% CI: 0.30 - 0.51; P<.0001). For AE attendances that lead to hospital admission, Omicron was associated with an 85% lower hazard compared with Delta (HR: 0.14 (95% CI: 0.09 - 0.24; P<.0001)). Conflicts of InterestsNothing to declare. Funding statementThis work was supported by the Medical Research Council MR/V015737/1. TPP provided technical expertise and infrastructure within their data centre pro bono in the context of a national emergency. Rosalind Eggo is funded by HDR UK (grant: MR/S003975/1), MRC (grant: MC_PC 19065), NIHR (grant: NIHR200908).

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

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

Trends, regional variation and clinical characteristics of recipients of antivirals and neutralising monoclonal antibodies for non-hospitalised COVID-19: a descriptive cohort study of 23.4 million people in OpenSAFELY (preprint)

ObjectivesAscertain patient eligibility status and describe coverage of antivirals and neutralising monoclonal antibodies (nMAB) as treatment for COVID-19 in community settings in England. DesignCohort study, approved by NHS England. SettingRoutine clinical data from 23.4m people linked to data on COVID-19 infection and treatment, within the OpenSAFELY-TPP database. ParticipantsNon-hospitalised COVID-19 patients at high-risk of severe outcomes. InterventionsNirmatrelvir/ritonavir (Paxlovid), sotrovimab, molnupiravir, casirivimab or remdesivir, administered in the community by COVID-19 Medicine Delivery Units. ResultsWe identified 102,170 non-hospitalised patients with COVID-19 between 11th December 2021 and 28th April 2022 at high-risk of severe outcomes and therefore potentially eligible for antiviral and/or nMAB treatment. Of these patients, 18,210 (18%) received treatment; sotrovimab, 9,340 (51%); molnupiravir, 4,500 (25%); Paxlovid, 4,290 (24%); casirivimab, 50 (<1%); and remdesivir, 20 (<1%). The proportion of patients treated increased from 8% (180/2,380) in the first week of treatment availability to 22% (420/1870) in the latest week. The proportion treated varied by high risk group, lowest in those with Liver disease (12%; 95% CI 11 to 13); by treatment type, with sotrovimab favoured over molnupiravir/Paxlovid in all but three high risk groups: Down syndrome (36%; 95% CI 31 to 40), Rare neurological conditions (46%; 95% CI 44 to 48), and Primary immune deficiencies (49%; 95% CI 48 to 51); by ethnicity, from Black (10%; 95% CI 9 to 11) to White (18%; 95% CI 18 to 19); by NHS Region, from 11% (95% CI 10 to 12) in Yorkshire and the Humber to 23% (95% CI 22 to 24) in the East of England); and by deprivation level, from 12% (95% CI 12 to 13) in the most deprived areas to 21% (95% CI 21 to 22) in the least deprived areas. There was also lower coverage among unvaccinated patients (5%; 95% CI 4 to 7), those with dementia (5%; 95% CI 4 to 6) and care home residents (6%; 95% CI 5 to 6). ConclusionsUsing the OpenSAFELY platform we were able to identify patients who were potentially eligible to receive treatment and assess the coverage of these new treatments amongst these patients. Targeted activity may be needed to address apparent lower treatment coverage observed among certain groups, in particular (at present): different NHS regions, socioeconomically deprived areas, and care homes. What is already known about this topicSince the emergence of COVID-19, a number of approaches to treatment have been tried and evaluated. These have mainly consisted of treatments such as dexamethasone, which were used in UK hospitals,from early on in the pandemic to prevent progression to severe disease. Until recently (December 2021), no treatments have been widely used in community settings across England. What this study addsFollowing the rollout of antiviral medicines and neutralising monoclonal antibodies (nMABs) as treatment for patients with COVID-19, we were able to identify patients who were potentially eligible to receive antivirals or nMABs and assess the coverage of these new treatments amongst these patients, in as close to real-time as the available data flows would support. While the proportion of the potentially eligible patients receiving treatment increased over time, rising from 8% (180/2,380) in the first week of the roll out to 22% (420/1870) in the last week of April 2022, there were variations in coverage between key clinical, geographic, and demographic subgroup. How this study might affect research, practice, or policyTargeted activity may therefore be needed to address lower treatment rates observed among certain geographic areas and key groups including ethnic minorities, people living in areas of higher deprivation, and in care homes.

Describing the population experiencing COVID-19 vaccine breakthrough following second vaccination in England: A cohort study from OpenSAFELY (preprint)

Background While the vaccines against COVID-19 are considered to be highly effective, COVID-19 vaccine breakthrough is likely and a small number of people will still fall ill, be hospitalised, or die from COVID-19, despite being fully vaccinated. With the continued increase in numbers of positive SARS-CoV-2 tests, describing the characters of individuals who have experienced a COVID-19 vaccine breakthrough could be hugely important in helping to determine who may be at greatest risk. Method We conducted a retrospective cohort study using routine clinical data from the OpenSAFELY TPP database of fully vaccinated individuals, linked to secondary care and death registry data, and described the characteristics of those experiencing a COVID-19 vaccine breakthrough. Results As of 30th June 2021, a total of 10,782,870 individuals were identified as being fully vaccinated against COVID-19, with a median follow-up time of 43 days (IQR: 23-64). From within this population, a total of 16,815 (0.1%) individuals reported a positive SARS-CoV-2 test. For every 1000 years of patient follow-up time, the corresponding incidence rate was 12.33 (95% CI 12.14-12.51). There were 955 COVID-19 hospital admissions and 145 COVID-19-related deaths; corresponding incidence rates of 0.70 (95% CI 0.65-0.74) and 0.12 (95% CI 0.1-0.14), respectively. When broken down by the initial priority group, higher rates of hospitalisation and death were seen in those in care homes. Comorbidities with the highest rates of breakthrough COVID-19 included renal replacement therapy, organ transplant, haematological malignancy, and immunocompromised. Conclusion The majority of COVID-19 vaccine breakthrough cases in England were mild with relatively few fully vaccinated individuals being hospitalised or dying as a result. However, some concerning differences in rates of breakthrough cases were identified in several clinical and demographic groups, The continued increase in numbers of positive SARS-CoV-2 tests are concerning and, as numbers of fully vaccinated individuals increases and follow-up time lengthens, so too will the number of COVID-19 breakthrough cases. Additional analyses, aimed at identifying individuals at higher risk, are therefore required.

Comparative effectiveness of ChAdOx1 versus BNT162b2 COVID-19 vaccines in Health and Social Care workers in England: a cohort study using OpenSAFELY (preprint)

Background: The UK COVID-19 vaccination programme delivered both the BNT162b2 mRNA (Pfizer-BioNTech) and the ChAdOx1 (Oxford-AstraZeneca) vaccines during overlapping periods, providing a rare opportunity to emulate a trial that directly compares both vaccines using routinely-collected NHS data. Frontline Health and Social Care workers comprise a useful population to assess comparative effectiveness due to early vaccine eligibility and relatively high post-vaccination transmission risk due to occupational exposure. Methods: With the approval of NHS England we used the OpenSAFELY-TPP database, covering 40% of GP practices in England and linked to national coronavirus surveillance, hospital episodes, and death registry data, to compare the effectiveness of ChAdOx1 versus BNT162b2 in 1/3 million health and social care workers vaccinated between 4 January and 28 February 2021. Recipients were followed-up for 20 weeks. Second-dose effects were estimated under an intention-to-treat strategy. Primary outcomes were recorded SARS-CoV-2 infection, COVID-19-related accident and emergency attendance, and COVID-19-related hospital admission. Results: The cumulative incidence of each outcome was similar for both vaccines during the first 20 weeks post-vaccination. The cumulative incidence of recorded SARS-CoV-2 infection 6 weeks after vaccination with BNT162b2 was 19.2 per 1000 people (95%CI 18.6 to 19.7) and with ChAdOx1 was 18.9 (95%CI 17.6 to 20.3), representing a difference of -0.24 per 1000 people (95%CI -1.71 to 1.22). The difference in the cumulative incidence of COVID-19 accident and emergency attendance at 6 weeks was 0.01 per 1000 people (95%CI -0.27 to 0.28). For COVID-19 hospital admission, this difference was 0.03 per 1000 people (95%CI -0.22 to 0.27). Conclusion: In this cohort of healthcare workers where we would not anticipate vaccine type to be related to health status, we found no substantial differences in the incidence of SARS-CoV-2 infection or COVID-19 disease up to 20 weeks after vaccination. Incidence dropped sharply after 3-4 weeks and there were very few COVID-19 hospital attendance and admission events after this period. This is in line with expected onset of vaccine-induced immunity, and suggests strong protection against COVID-19 disease for both vaccines.

Recording of 'COVID-19 vaccine declined' among vaccination priority groups: a cohort study on 57.9 million NHS patients' primary care records in situ using OpenSAFELY (preprint)

BackgroundAll patients in England within vaccine priority groups were offered a COVID-19 vaccine by mid-April 2021. Clinical record systems contain codes to denote when such an offer has been declined by a patient (although these can in some cases be entered for a variety of other reasons including vaccination delay, or other administrative issues). We set out to describe the patterns of usage of codes for COVID-19 vaccines being declined. MethodsWith the approval of NHS England and using the full pseudonymised primary care records for 57.9 million NHS patients, we identified all patients in key vaccine priority groups: aged over 50, or over 16 and at increased risk from COVID-19 (Clinically Extremely Vulnerable [CEV] or otherwise "at risk"). We describe the proportion of patients recorded as declining a COVID-19 vaccination for each priority group, and by other clinical and demographic factors; whether patients recorded as "declined" subsequently went on to receive a vaccination; and the distribution of code usage across GP practices. ResultsOf 24.5 million patients in priority groups as of May 25th 2021, 89.2% had received a vaccine, 8.8% had neither a vaccination nor a decline recorded, and 663,033 (2.7%) had a decline code recorded. Of patients with a recorded decline, 125,587 (18.9%) were subsequently vaccinated. Subsequent vaccination was slightly more common in the South Asian population than other ethnicities (e.g. 32.3% vs 22.8%, over 65s). The proportion of declining-unvaccinated patients varied strongly with ethnicity (Black 15.3%, South Asian 5.6%, White 1.5% in over 80s); and was higher in patients from more deprived areas. COVID-19 vaccine decline codes were present in almost all practices (98.8%), but with wide variation between practices in rates of usage. Among all priority groups, declining-unvaccinated status was most common in CEV (3.3%). ConclusionsClinical codes indicative of COVID-19 vaccinations being declined are widely used in English general practice. They are substantially more common among Black and South Asian patients, and patients from more deprived areas. There is a need for more detailed survey and/or qualitative research with patients and clinicians to determine the most common reasons for these recorded declines.

Overall and cause-specific hospitalisation and death after COVID-19 hospitalisation in England: cohort study in OpenSAFELY using linked primary care, secondary care and death registration data (preprint)

Background: There is concern about medium to long-term adverse outcomes following acute COVID-19, but little relevant evidence exists. We aimed to investigate whether risks of hospital admission and death, overall and by specific cause, are raised following discharge from a COVID-19 hospitalisation. Methods and Findings: Working on behalf of NHS-England, we used linked primary care and hospital data in OpenSAFELY to compare risks of hospital admission and death, overall and by specific cause, between people discharged from COVID-19 hospitalisation (February-December 2020), and (i) demographically-matched controls from the 2019 general population; (ii) people discharged from influenza hospitalisation in 2017-19. We used Cox regression adjusted for personal and clinical characteristics. 24,673 post-discharge COVID-19 patients, 123,362 general population controls, and 16,058 influenza controls were followed for [≤]315 days. Overall risk of hospitalisation or death (30968 events) was higher in the COVID-19 group than general population controls (adjusted-HR 2.23, 2.14-2.31) but similar to the influenza group (adjusted-HR 0.94, 0.91-0.98). All-cause mortality (7439 events) was highest in the COVID-19 group (adjusted-HR 4.97, 4.58-5.40 vs general population controls and 1.73, 1.60-1.87 vs influenza controls). Risks for cause-specific outcomes were higher in COVID-19 survivors than general population controls, and largely comparable between COVID-19 and influenza patients. However, COVID-19 patients were more likely than influenza patients to be readmitted/die due to their initial infection/other lower respiratory tract infection (adjusted-HR 1.37, 1.22-1.54), and to experience mental health or cognitive-related admission/death (adjusted-HR 1.36, 1.01-2.83); in particular, COVID-19 survivors with pre-existing dementia had higher risk of dementia death. One limitation of our study is that reasons for hospitalisation/death may have been misclassified in some cases due to inconsistent use of codes. Conclusions: People discharged from a COVID-19 hospital admission had markedly higher risks for rehospitalisation and death than the general population, suggesting a substantial extra burden on healthcare. Most risks were similar to those observed after influenza hospitalisations; but COVID-19 patients had higher risks of all-cause mortality, readmissions/death due to the initial infection, and dementia death, highlighting the importance of post-discharge monitoring.

Risk factors for long COVID: analyses of 10 longitudinal studies and electronic health records in the UK (preprint)

The impact of long COVID is increasingly recognised, but risk factors are poorly characterised. We analysed questionnaire data on symptom duration from 10 longitudinal study (LS) samples and electronic healthcare records (EHR) to investigate sociodemographic and health risk factors associated with long COVID, as part of the UK National Core Study for Longitudinal Health and Wellbeing. Methods Analysis was conducted on 6,899 adults self-reporting COVID-19 from 45,096 participants of the UK LS, and on 3,327 cases assigned a long COVID code in primary care EHR out of 1,199,812 adults diagnosed with acute COVID-19. In LS, we derived two outcomes: symptoms lasting 4+ weeks and symptoms lasting 12+ weeks. Associations of potential risk factors (age, sex, ethnicity, socioeconomic factors, smoking, general and mental health, overweight/obesity, diabetes, hypertension, hypercholesterolaemia, and asthma) with these two outcomes were assessed, using logistic regression, with meta-analyses of findings presented alongside equivalent results from EHR analyses. Results Functionally limiting long COVID for 12+ weeks affected between 1.2% (age 20), and 4.8% (age 63) of people reporting COVID-19 in LS. The proportion reporting symptoms overall for 12+ weeks ranged from 7.8 (mean age 28) to 17% (mean age 58) and for 4+ weeks 4.2% (age 20) to 33.1% (age 56). Age was associated with a linear increase in long COVID between age 20-70. Being female (LS: OR=1.49; 95%CI:1.24-1.79; EHR: OR=1.51 [1.41-1.61]), poor pre-pandemic mental health (LS: OR=1.46 [1.17-1.83]; EHR: OR=1.57 [1.47-1.68]) and poor general health (LS: OR=1.62 [1.25-2.09]; EHR: OR=1.26; [1.18-1.35]) were associated with higher risk of long COVID. Individuals with asthma also had higher risk (LS: OR=1.32 [1.07-1.62]; EHR: OR=1.56 [1.46-1.67]), as did those categorised as overweight or obese (LS: OR=1.25 [1.01-1.55]; EHR: OR=1.31 [1.21-1.42]) though associations for symptoms lasting 12+ weeks were less pronounced. Non-white ethnic minority groups had lower 4+ week symptom risk (LS: OR=0.32 [0.22-0.47]), a finding consistent in EHR. Associations were not observed for other risk factors. Few participants in the studies had been admitted to hospital (0.8-5.2%). Conclusions Long COVID is clearly distributed differentially according to several sociodemographic and pre-existing health factors. Establishing which of these risk factors are causal and predisposing is necessary to further inform strategies for preventing and treating long COVID.

Clinical coding of long COVID in English primary care: a federated analysis of 58 million patient records in situ using OpenSAFELY (preprint)

BackgroundLong COVID is a term to describe new or persistent symptoms at least four weeks after onset of acute COVID-19. Clinical codes to describe this phenomenon were released in November 2020 in the UK, but it is not known how these codes have been used in practice. MethodsWorking on behalf of NHS England, we used OpenSAFELY data encompassing 96% of the English population. We measured the proportion of people with a recorded code for long COVID, overall and by demographic factors, electronic health record software system, and week. We also measured variation in recording amongst practices. ResultsLong COVID was recorded for 23,273 people. Coding was unevenly distributed amongst practices, with 26.7% of practices having not used the codes at all. Regional variation was high, ranging between 20.3 per 100,000 people for East of England (95% confidence interval 19.3-21.4) and 55.6 in London (95% CI 54.1-57.1). The rate was higher amongst women (52.1, 95% CI 51.3-52.9) compared to men (28.1, 95% CI 27.5-28.7), and higher amongst practices using EMIS software (53.7, 95% CI 52.9-54.4) compared to TPP software (20.9, 95% CI 20.3-21.4). ConclusionsLong COVID coding in primary care is low compared with early reports of long COVID prevalence. This may reflect under-coding, sub-optimal communication of clinical terms, under-diagnosis, a true low prevalence of long COVID diagnosed by clinicians, or a combination of factors. We recommend increased awareness of diagnostic codes, to facilitate research and planning of services; and surveys of clinicians experiences, to complement ongoing patient surveys.

Association between oral anticoagulants and COVID-19 related outcomes: two cohort studies (preprint)

Objectives: We investigated the role of routinely prescribed oral anticoagulants (OACs) in COVID-19 outcomes, comparing current OAC use versus non-use in Study 1; and warfarin versus direct oral anticoagulants (DOACs) in Study 2. Design: Two cohort studies, on behalf of NHS England. Setting: Primary care data and pseudonymously-linked SARS-CoV-2 antigen testing data, hospital admissions, and death records from England. Participants: Study 1: 70,464 people with atrial fibrillation (AF) and CHA2DS2-VASc score of 2. Study 2: 372,746 people with non-valvular AF. Main outcome measures: Time to test for SARS-CoV-2, testing positive for SARS-CoV-2, COVID-19 related hospital admission, COVID-19 deaths or non-COVID-19 deaths in Cox regression. Results: In Study 1, we included 52,416 current OAC users and 18,048 non-users. We observed no difference in risk of being tested for SARS-CoV-2 associated with current use (adjusted HR, 1.01, 95%CI, 0.96 to 1.05) versus non-use. We observed a lower risk of testing positive for SARS-CoV-2 (adjusted HR, 0.73, 95%CI, 0.60 to 0.90), and COVID-19 deaths (adjusted HR, 0.69, 95%CI, 0.49 to 0.97) associated with current use versus non-use. In Study 2, we included 92,339 warfarin users and 280,407 DOAC users. We observed a lower risk of COVID-19 deaths (adjusted HR, 0.79, 95%CI, 0.76 to 0.83) associated with warfarin versus DOACs. Similar associations were found for all other outcomes. Conclusions: Among people with AF and a CHA2DS2-VASc score of 2, those receiving OACs had a lower risk of receiving a positive COVID-19 test and severe COVID-19 outcomes than non-users; this might be explained by a causal effect of OACs in preventing severe COVID-19 outcomes or more cautious behaviours leading to reduced infection risk. There was no evidence of a higher risk of severe COVID-19 outcomes associated with warfarin versus DOACs in people with non-valvular AF regardless of CHA2DS2-VASc score.

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

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

Case fatality risk of the SARS-CoV-2 variant of concern B.1.1.7 in England (preprint)

The B.1.1.7 variant of concern (VOC) is increasing in prevalence across Europe. Accurate estimation of disease severity associated with this VOC is critical for pandemic planning. We found increased risk of death for VOC compared with non-VOC cases in England (HR: 1.67 (95% CI: 1.34 - 2.09; P

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

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