COVID-19 inequalities in England: a mathematical modelling study of transmission risk and clinical vulnerability by socioeconomic status (preprint)

BackgroundThe COVID-19 pandemic resulted in major inequalities in infection burden between areas of varying socioeconomic deprivation in many countries, including England. Areas of higher deprivation tend to have a different population structure - generally younger - which can increase viral transmission due to higher contact rates in school-going children and working-age adults. Higher deprivation is also associated with higher presence of chronic comorbidities, which were convincingly demonstrated to be risk factors for severe COVID-19 disease. These two major factors need to be combined to better understand and quantify their relative importance in the observed COVID-19 inequalities. MethodsWe used UK Census data on health status and demography stratified by decile of the Index of Multiple Deprivation (IMD), which is a measure of socioeconomic deprivation. We calculated epidemiological impact using an age-stratified COVID-19 transmission model, which incorporated different contact patterns and clinical health profile by decile. To separate the contribution of each factor, we also considered a scenario where the clinical health profile of all deciles was at the level of the least deprived. We also considered the effectiveness of school closures in each decile. ResultsIn the modelled epidemics in urban areas, the most deprived decile experienced 9% more infections, 13% more clinical cases, and a 97% larger peak clinical size than the least deprived; we found similar inequalities in rural areas. 21% of clinical cases and 16% of deaths in England observed under the model assumptions would not occur if all deciles experienced the clinical health profile of the least deprived decile. We found that more deaths were prevented in more affluent areas during school closures. ConclusionsThis study demonstrates that both clinical and demographic factors synergise to generate health inequalities in COVID-19, that improving the clinical health profile of populations would increase health equity, and that some interventions can increase health inequalities.

Healthcare utilisation in people with long COVID: an OpenSAFELY cohort study (preprint)

BackgroundLong COVID, characterised by various symptoms and complications, potentially increases healthcare utilisation and costs. However, its impact on the NHS remains to be determined. ObjectiveThis study aims to assess the healthcare utilisation of individuals with long COVID. MethodsWith the approval of NHS England, we conducted a matched cohort study using primary and secondary care data via OpenSAFELY, a platform for analysing anonymous electronic health records. The long COVID exposure group, defined by diagnostic codes, was matched with five comparators without long COVID between Nov 2020 and Jan 2023. We compared their total healthcare utilisation from GP consultations, prescriptions, hospital admissions, A&E visits, and outpatient appointments. Healthcare utilisation and costs were evaluated using a two-part model adjusting for covariates. Using a difference-in-difference model, we also compared healthcare utilisation after long COVID with pre-pandemic records. ResultsWe identified 52,988 individuals with a long COVID diagnosis, matched to 264,867 comparators without a diagnosis. In the 12 months post-diagnosis, there was strong evidence that those with long COVID were more likely to use healthcare resources (OR: 8.07, 95% CI: 7.54 - 8.64), and have 49% more healthcare utilisation (RR: 1.49, 95% CI: 1.47 - 1.50). Our model estimated that the long COVID group had 30 healthcare visits per year (predicted mean: 29.23, 95% CI: 28.58 - 29.92), compared to 16 in the comparator group (predicted mean visits: 16.04, 95% CI: 15.73 - 16.36). Individuals with long COVID were more likely to have non-zero healthcare expenditures (OR = 7.47, 95% CI = 7.02 - 7.95), with costs being 43% higher than the comparator group (cost ratio = 1.43, 95% CI: 1.38 - 1.49). The long COVID group costs approximately {pound}2,500 per person per year (predicted mean cost: {pound}2,562.50, 95% CI: {pound}2,335.60 - {pound}2,819.22), and the comparator group costs {pound}1,500 (predicted mean cost: {pound}1,527.43, 95% CI: {pound}1,404.33 - 1,664.45.) Historically, individuals with long COVID utilised healthcare resources more frequently, but their average healthcare utilisation increased more after being diagnosed with long COVID, compared to the comparator group. ConclusionLong COVID increases healthcare utilisation and costs. Public health policies should allocate more resources towards preventing, treating, and supporting individuals with long COVID.

Clinical coding of long COVID in primary care 2020-2023 in a cohort of 19 million adults: an OpenSAFELY analysis (preprint)

Background Long COVID is the patient-coined term for the persistent symptoms of COVID-19 illness for weeks, months or years following the acute infection. There is a large burden of long COVID globally from self-reported data, but the epidemiology, causes and treatments remain poorly understood. Primary care is used to help identify and treat patients with long COVID and therefore Electronic Health Records (EHRs) of past COVID-19 patients could be used to help fill these knowledge gaps. We aimed to describe those with long COVID in primary care records in England. Methods With the approval of NHS England we used routine clinical data from over 19 million adults in England linked to SARS-COV-2 test result, hospitalisation and vaccination data to describe trends in the recording of 16 clinical codes related to long COVID between November 2020 and January 2023. We calculated rates per 100,000 person-years and plotted how these changed over time. We compared crude and minimally adjusted rates of recorded long COVID in patient records between different key demographic and vaccination characteristics using negative binomial models. Findings We identified a total of 55,465 people recorded to have long COVID over the study period, with incidence of new long COVID records increasing steadily over 2021, and declining over 2022. The overall rate per 100,000 person-years was 177.5 cases in women (95% CI: 175.5-179) and 100.5 men (99.5-102). In terms of vaccination against COVID-19, the lowest rates were observed in those with 3+ vaccine doses (103.5 [95% CI: 101.5-105]). Finally, the majority of those with a long COVID record did not have a recorded positive SARS-COV-2 test 12 weeks before the long COVID record. Interpretation EHR recorded long COVID remains very low compared and incident records of long COVID declined over 2022. We found the lowest rates of recorded long COVID in people with 3 or more vaccine doses. We summarised several sources of possible bias for researchers using EHRs to study long COVID. Funding This research was supported by the National Institute for Health and Care Research (NIHR) (OpenPROMPT: COV-LT2-0073))

The macroeconomic and epidemiological impacts of Covid-19 in Pakistan. (preprint)

'Coronavirus Disease 2019' (C19) is a respiratory illness caused by 'new Coronavirus' SARS-CoV-2. The C19 pandemic, which engulfed the world in 2021, also caused a national C19 epidemic in Pakistan, who responded with initial forced lockdowns (15-30 March 2020) and a subsequent switch to a smart lockdown strategy, and, by 31 December 2020, Pakistan had managed to limit confirmed cases and case fatalities to 482,506 (456 per 100,000) and 10,176 (4.8 per 100,000). The early switch to a smart lockdown strategy, and successful follow-up move to central coordination and effective communication and enforcement of Standard Operating Procedures, was motivated by a concern over how broad-based forced lockdowns would affect poor households and day-labour. The current study aims to investigate how the national Pakistan C19 epidemic would have unfolded under an uncontrolled baseline scenario and an alternative set of controlled non-pharmaceutical intervention (NPI) policy lockdown scenarios, including health and macroeconomic outcomes. We employ a dynamically-recursive version of the IFPRI Standard Computable General Equilibrium model framework (Lofgren, Lee Harris and Robinson 2002), and a, by now, well-established epidemiological transmission-dynamic model framework (Davies, Klepac et al 2020) using Pakistan-specific 5-year age-group contact matrices on four types of contact rates, including at home, at work, at school, and at other locations (Prem, Cook & Jit 2017), to characterize an uncontrolled spread of disease. Our simulation results indicate that an uncontrolled C19 epidemic, by itself, would have led to a 0.12% reduction in Pakistani GDP (-721mn USD), and a total of 0.65mn critically ill and 1.52mn severely ill C19 patients during 2020-21, while 405,000 Pakistani citizens would have lost their lives. Since the majority of case fatalities and symptomatic cases, respectively 345,000 and 35.9mn, would have occurred in 2020, the case fatality and confirmed case numbers, observed by 31. December 2020 represents an outcome which is far better than the alternative. Case fatalities by 31. December 2020 could possibly have been somewhat improved either via a more prolonged one-off 10 week forced lockdown (66% reduction) or a 1-month forced lockdown/2-months opening intermittent lockdown strategy (33% reduction), but both sets of strategies would have carried significant GDP costs in the order of 2.2%-6.2% of real GDP.

Improving modelling for epidemic responses: reflections from members of the UK infectious disease modelling community on their experiences during the COVID-19 pandemic (preprint)

The COVID-19 pandemic both relied and placed significant burdens on the experts involved from research and public health sectors. The sustained high pressure of a pandemic on responders, such as healthcare workers, can lead to lasting psychological impacts including acute stress disorder, post-traumatic stress disorder, burnout, and moral injury, which can impact individual wellbeing and productivity. As members of the infectious disease modelling community, we convened a reflective workshop to understand the professional and personal impacts of response work on our community and to propose recommendations for future epidemic responses. The attendees represented a range of career stages, institutions, and disciplines. This piece was collectively produced by those present at the session based on our collective experiences. Key issues we identified at the workshop were lack of institutional support, insecure contracts, unequal credit and recognition, and mental health impacts. Our recommendations include rewarding impactful work, fostering academia-public health collaboration, decreasing dependence on key individuals by developing teams, increasing transparency in decision-making, and implementing sustainable work practices. Despite limitations in representation, this workshop provided valuable insights into the UK COVID-19 modelling experience and guidance for future public health crises. Recognising and addressing the issues highlighted here is crucial, in our view, for ensuring the effectiveness of epidemic response work in the future.

Changes in COVID-19-related mortality across key demographic and clinical subgroups: an observational cohort study using the OpenSAFELY platform on 18 million adults in England (preprint)

Objectives To quantify in absolute and relative terms how population-level COVID-19 death rates have changed in demographic and clinical subgroups. Design Retrospective cohort study on behalf of NHS England. Setting Linked primary care and death registry data from the OpenSAFELY-TPP platform, covering the first three pandemic waves in England (wave 1: March 23 to May 30, 2020; wave 2: September 7, 2020 to April 24, 2021; and wave 3, delta: May 28 to December 14, 2021). Participants In total, 18.7, 18.8, and 18.7 million adults were included for waves 1, 2, and 3 respectively. Main outcome measures COVID-19-related mortality based on linked death registry records. Results The crude rate of COVID-19-related death per 1,000 person-years decreased from 4.48 in wave 1 (95%CI 4.41;4.55), to 2.70 in wave 2 (95%CI 2.67;2.73), to 0.64 in wave 3 (95%CI 0.63;0.66). The death rate decreased by 90% between waves 1 and 3 in patients aged 80+, but by only 20% in patients aged 18-39. This higher proportional reduction in death rates was also seen for other groups, such as neurological disease, learning disability and severe mental illness. Conversely, death rates in transplant recipients stayed constant across successive waves at 10 per 1,000 person-years. There was also only a small decrease in death rates between waves in people with kidney disease, haematological malignancies or conditions associated with immunosuppression. Consequently, the relative hazard of COVID-19-related death decreased over time for some variables (e.g. age), remained similar for some (e.g. sex, ethnicity), and increased for others (e.g. transplant). Conclusions COVID-19 death rates decreased over the first three pandemic waves. An especially large decrease was seen in older age groups and people with neurological disease, learning disability or severe mental illness. Some demographic inequalities in death rates persisted over time. Groups more likely to experience impaired vaccine effectiveness did not see the same benefit in COVID-19 mortality reduction.

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

Objective: To compare the effectiveness of sotrovimab (a neutralising monoclonal antibody) vs. molnupiravir (an antiviral) 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 medications were frequently prescribed in community settings. Participants: Non-hospitalised adult COVID-19 patients at high-risk of severe outcomes treated with sotrovimab or molnupiravir between December 16, 2021 and February 10, 2022. Interventions: 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: Patients treated with sotrovimab (n=3288) and molnupiravir (n=2663) were similar with respect to most baseline characteristics. The mean age of all 5951 patients was 52 (SD=16) years; 59% were female, 89% White and 87% had three or more COVID-19 vaccinations. Within 28 days after treatment initiation, 84 (1.4%) COVID-19 related hospitalisations/deaths were observed (31 treated with sotrovimab and 53 with molnupiravir). Cox proportional hazards models stratified by area showed that after adjusting for demographics, high-risk cohort categories, vaccination status, calendar time, body mass index and other comorbidities, treatment with sotrovimab was associated with a substantially lower risk than treatment with molnupiravir (hazard ratio, HR=0.53, 95% CI: 0.32-0.88; P=0.014). Consistent results were obtained from propensity score weighted Cox models (HR=0.51, 95% CI: 0.31-0.83; P=0.007) and when restricted to fully vaccinated people (HR=0.52, 95% CI: 0.30-0.90; P=0.020). No substantial effect modifications by other characteristics were detected (all P values for interaction>0.10). Conclusion: In routine care of non-hospitalised high-risk adult patients with COVID-19 in England, those who received sotrovimab were at lower risk of severe COVID-19 outcomes than those receiving molnupiravir.

Assessing the impacts of timing on the health benefits, cost-effectiveness and relative affordability of COVID-19 vaccination programmes in 27 African Countries (preprint)

Background: The COVID-19 vaccine supply shortage in 2021 constrained rollout efforts in Africa while populations experienced waves of epidemics. As supply picks up, a key question becomes if vaccination remains an impactful and cost-effective strategy given changes in the timing of implementation. Methods: We assessed the impact of timing using an epidemiological and economic model. We fitted our mathematical epidemiological model to reported COVID-19 deaths in 27 African countries to estimate the existing immunity (resulting from infection) before substantial vaccine rollout. We then projected health outcomes for different programme start dates (2021-01-01 to 2021-12-01, n = 12) and roll-out rates (slow, medium, fast; 275, 826, and 2066 doses/ million population-day, respectively) for viral vector and mRNA vaccines. Rollout rates used were derived from observed uptake trajectories. We collected data on vaccine delivery costs by country income group. Lastly, we calculated incremental cost-effectiveness ratios and relative affordability. Findings: Vaccination programmes with early start dates incur the most health benefits and are most cost-effective. While incurring the most health benefits, fast vaccine roll-outs are not always the most cost-effective. At a willingness-to-pay threshold of 0.5xGDP per capita, vaccine programmes starting in August 2021 using mRNA and viral vector vaccines were cost-effective in 6-10 and 17-18 of 27 countries, respectively. Interpretation: African countries with large proportions of their populations unvaccinated by late 2021 may find vaccination programmes less cost-effective than they could have been earlier in 2021. Lower vaccine purchasing costs and/or the emergence of new variants may improve cost-effectiveness. Funding: Bill and Melinda Gates Foundation, World Health Organization, National Institute of Health Research (UK), Health Data Research (UK)

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.

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.

Compositional modelling of immune response and virus transmission dynamics (preprint)

Transmission models for infectious diseases are typically formulated in terms of dynamics between individuals or groups with processes such as disease progression or recovery for each individual captured phenomenologically, without reference to underlying biological processes. Furthermore, the construction of these models is often monolithic: they don't allow one to readily modify the processes involved or include the new ones, or to combine models at different scales. We show how to construct a simple model of immune response to a respiratory virus and a model of transmission using an easily modifiable set of rules allowing further refining and merging the two models together. The immune response model reproduces the expected response curve of PCR testing for COVID-19 and implies a long-tailed distribution of infectiousness reflective of individual heterogeneity. This immune response model, when combined with a transmission model, reproduces the previously reported shift in the population distribution of viral loads along an epidemic trajectory.

Estimating the relationship between mobility, non-pharmaceutical interventions, and COVID-19 transmission in Ghana (preprint)

Governments around the world have implemented non-pharmaceutical interventions (NPIs), e.g. physical distancing and travel restrictions, to limit the transmission of COVID-19. While lockdowns and physical distancing have proven effective for reducing COVID-19 transmission, there is still limited understanding of the degree to which these interventions impact disease transmission, and how they are reflected in measures of human behaviour. Further, there is a lack of understanding about how new sources of data can be used to monitor NPIs, where these data have the potential to augment existing disease surveillance and modelling efforts. In this study, we assess the relationship between indicators of human mobility, NPIs, and estimates of Rt, a real-time measure of the intensity of COVID-19 transmission in subnational districts of Ghana using a multilevel generalised linear mixed model. We demonstrate a relationship between reductions in human mobility and decreases in Rt during the early stages of the COVID-19 epidemic in Ghana, and show how reductions in human mobility relate to increasing stringency of NPIs. We demonstrate the utility of combining local disease surveillance data with large scale human mobility data to augment existing surveillance capacity to estimate and monitor the effect of NPI policies.

Transmission dynamics of SARS-CoV-2 in a strictly-Orthodox Jewish community in the UK (preprint)

Some social settings such as households and workplaces, have been identified as high risk for SARS-CoV-2 transmission. Identifying and quantifying the importance of these settings is critical for designing interventions. A tightly-knit religious community in the UK experienced a very large COVID-19 epidemic in 2020, reaching 64.3% seroprevalence within 10 months, and we surveyed this community both for serological status and individual-level attendance at particular settings. Using these data, and a network model of people and places represented as a stochastic graph rewriting system, we estimated the relative contribution of transmission in households, schools and religious institutions to the epidemic, and the relative risk of infection in each of these settings. All congregate settings were important for transmission, with some such as primary schools and places of worship having a higher share of transmission than others. We found that the model needed a higher general-community transmission rate for women (3.3-fold), and lower susceptibility to infection in children to recreate the observed serological data. The precise share of transmission in each place was related to assumptions about the internal structure of those places. Identification of key settings of transmission can allow public health interventions to be targeted at these locations.

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.

Risk of severe COVID-19 outcomes associated with immune-mediated inflammatory diseases and immune modifying therapies: a nationwide cohort study in the OpenSAFELY platform (preprint)

BackgroundIt is unclear if people with immune-mediated inflammatory diseases (IMIDs) (joint, bowel and skin) and on immune modifying therapy have increased risk of serious COVID-19 outcomes. MethodsWith the approval of NHS England we conducted a cohort study, using OpenSAFELY, analysing routinely-collected primary care data linked to hospital admission, death and previously unavailable hospital prescription data. We used Cox regression (adjusting for confounders) to estimate hazard ratios (HR) comparing risk of COVID-19-death, death/critical care admission, and hospitalisation (March to September 2020) in: 1) people with IMIDs compared to the general population; and 2) people with IMIDs on targeted immune modifying drugs (e.g., biologics) compared to standard systemic treatment (e.g., methotrexate). FindingsWe identified 17,672,065 adults; of 1,163,438 (7%) with IMIDs, 19,119 people received targeted immune modifying drugs, and 200,813 received standard systemics. We saw evidence of increased COVID-19-death (HR 1.23, 95%CI 1.20, 1.27), and COVID-19 hospitalisation (HR 1.32, 95%CI 1.29, 1.35) in individuals with IMIDs overall compared to individuals without IMIDs of the same age, sex, deprivation and smoking status. We saw no evidence of increased COVID-19 deaths with targeted compared to standard systemic treatments (HR 1.03, 95%CI 0.80, 1.33). There was no evidence of increased COVID-19-related death in those prescribed TNF inhibitors, IL-12/23, IL7, IL-6 or JAK inhibitors compared to standard systemics. Rituximab was associated with increased COVID-19 death (HR 1.68, 95%CI 1.11, 2.56); however, this finding may relate to confounding. InterpretationCOVID-19 death and hospitalisation was higher in people with IMIDs. We saw no increased risk of adverse COVID-19 outcomes in those on most targeted immune modifying drugs for IMIDs compared to standard systemics. RESEARCH IN CONTEXTO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed on May 19th, 2021, using the terms "COVID-19", "SARS-CoV-2" and "rheumatoid arthritis", "psoriatic arthritis" "ankylosing spondylitis", "Crohns disease" "ulcerative colitis" "hidradenitis suppurativa" and "psoriasis", to identify primary research articles examining severe COVID-19 outcome risk in individuals with immune-mediated inflammatory diseases (IMIDs) and those on immune modifying therapy. The studies identified (including matched cohort studies and studies in disease-specific registries) were limited by small sample sizes and number of outcomes. Most studies did not show a signal of increased adverse COVID-19 outcomes in those on targeted therapies, with the exception of rituximab. Additionally, disease- specific registries are subject to selection bias and lack denominator populations. Added value of the studyIn our large population-based study of 17 million individuals, including 1 million people with IMIDs and just under 200,000 receiving immune modifying medications, we saw evidence that people with IMIDs had an increased risk of COVID-19-related death compared to the general population after adjusting for potential confounders (age, sex, deprivation, smoking status) (HR 1.23, 95%CI 1.20, 1.27). We saw differences by IMID type, with COVID-19-related death being increased by the most in people with inflammatory joint disease (HR 1.47, 95%CI 1.40, 1.54). We also saw some evidence that those with IMIDs were more likely, compared to the general population, to have COVID-19-related critical care admission/death (HR 1.24, 95%CI 1.21, 1.28) and hospitalisation (HR 1.32, 95%CI 1.29, 1.35). Compared to people with IMIDs taking standard systemics, we saw no evidence of differences in severe COVID-19-related outcomes with TNF inhibitors, IL-17 inhibitors, IL-12/23 inhibitors, IL-6 inhibitors and JAK inhibitors. However, there was some evidence that rituximab was associated with an increased risk of COVID-19-related death (HR 1.68, 95%CI 1.11, 2.56) and death/critical care admission (HR 1.92, 95%CI 1.31, 2.81). We also saw evidence of an increase in COVID-19-related hospital admissions in people prescribed rituximab (HR 1.59, 95%CI 1.16, 2.18) or JAK inhibition (HR 1.81, 95%CI 1.09, 3.01) compared to those on standard systemics, although this could be related to worse underlying health rather than the drugs themselves, and numbers of events were small. This is the first study to our knowledge to use high-cost drug data on medicines supplied by hospitals at a national scale in England (to identify targeted therapies). The availability of these data fills an important gap in the medication record of those with more specialist conditions treated by hospitals creating an important opportunity to generate insights to these conditions and these medications Implications of all of the available evidenceOur study offers insights into future risk mitigation strategies and SARS-CoV-2 vaccination priorities for individuals with IMIDs, as it highlights that those with IMIDs and those taking rituximab may be at risk of severe COVID-19 outcomes. Critically, our study does not show a link between most targeted immune modifying medications compared to standard systemics and severe COVID-19 outcomes. However, the increased risk of adverse COVID-19 outcomes that we saw in people with IMIDs and those treated with rituximab merits further study.

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.

Vaccine Confidence and Hesitancy at the start of COVID-19 vaccine deployment in the UK: An embedded mixed-methods study (preprint)

IntroductionApproval for the use of COVID-19 vaccines has been granted in a number of countries but there are concerns that vaccine uptake may be low amongst certain groups. MethodsThis study used a mixed methods approach based on online survey and an embedded quantitative/qualitative design to explore perceptions and attitudes that were associated with intention to either accept or refuse offers of vaccination in different demographic groups during the early stages of the UKs mass COVID-19 vaccination programme (December 2020). Analysis used multivariate logistic regression, structural text modelling and anthropological assessments. ResultsOf 4,535 respondents, 85% (n=3,859) were willing to have a COVID-19 vaccine. The rapidity of vaccine development and uncertainties about safety were common reasons for COVID-19 vaccine hesitancy. There was no evidence for the widespread influence of mis-information, although broader vaccine hesitancy was associated with intentions to refuse COVID-19 vaccines (OR 20.60, 95% CI 14.20-30.30, p<0.001). Low levels of trust in the decision-making (OR 1.63, 95% CI 1.08, 2.48, p=0.021) and truthfulness (OR 8.76, 95% CI 4.15-19.90, p<0.001) of the UK government were independently associated with higher odds of refusing COVID-19 vaccines. Compared to political centrists, conservatives and liberals were respectively more (OR 2.05, 95%CI 1.51-2.80, p<0.001) and less (OR 0.30, 95% CI 0.22-0.41, p<0.001) likely to refuse offered vaccines. Those who were willing to be vaccinated cited both personal and public protection as reasons, with some alluding to having a sense of collective responsibility. ConclusionDominant narratives of COVID-19 vaccine hesitancy are misconceived as primarily being driven by misinformation. Key indicators of UK vaccine acceptance include prior behaviours, transparency of the scientific process of vaccine development, mistrust in science and leadership and individual political views. Vaccine programmes should leverage the sense of altruism, citizenship and collective responsibility that motivated many participants to get vaccinated.

Mortality among Care Home Residents in England during the first and second waves of the COVID-19 pandemic: an analysis of 4.3 million adults over the age of 65 (preprint)

Background: Residents in care homes have been severely impacted by the COVID-19 pandemic. We describe trends in risk of mortality among care home residents compared to residents in private homes in England. Methods: On behalf of NHS England, we used OpenSAFELY-TPP, an analytics platform running across the linked electronic health records of approximately a third of the English population, to calculate monthly age-standardised risks of death due to all causes and COVID-19 among adults aged >=65 years between 1/2/2019 and 31/03/2021. Care home residents were identified using linkage to the Care and Quality Commission. Findings: We included 4,329,078 people aged 65 years or older on the 1st of February 2019, 2.2% of whom were classified as residing in a care or nursing home. Age-standardised mortality risks were approximately 10 times higher among care home residents compared to non-residents in February 2019 residents (CMF = 10.59, 95%CI = 9.51, 11.81 among women, CMF = 10.82, 95%CI = 9.89, 11.84 among men). This increased to more than 17 times in April 2020 (CMF = 17.52, 95%CI = 16.38, 18.74 among women, CMF = 18.12, 95%CI = 17.17, 19.12 among men) before returning to pre-pandemic levels in June 2020. CMFs did not increase during the second wave, despite a rise in the absolute age-standardised COVID-19 mortality risks. Interpretation: The first COVID-19 wave had a disproportionate impact on care home residents in England compared to older private home residents. A degree of immunity, improved protective measures or changes in the underlying frailty of the populations may explain the lack of an increase in the relative mortality risks during the second wave. The care home population should be prioritised for measures aimed at controlling the spread of COVID-19.