Impact of COVID-19 on mental illness in vaccinated and unvaccinated people: a population-based cohort study in OpenSAFELY (preprint)

Background: COVID-19 is associated with subsequent mental illness in both hospital- and population-based studies. Evidence regarding effects of COVID-19 vaccination on mental health consequences of COVID-19 is limited. Methods: With the approval of NHS England, we used linked electronic health records (OpenSAFELY-TPP) to conduct analyses in a 'pre-vaccination' cohort (17,619,987 people) followed during the wild-type/Alpha variant eras (January 2020-June 2021), and 'vaccinated' and 'unvaccinated' cohorts (13,716,225 and 3,130,581 people respectively) during the Delta variant era (June-December 2021). We estimated adjusted hazard ratios (aHRs) comparing the incidence of mental illness after diagnosis of COVID-19 with the incidence before or without COVID-19. Outcomes: We considered eight outcomes: depression, serious mental illness, general anxiety, post-traumatic stress disorder, eating disorders, addiction, self-harm, and suicide. Incidence of most outcomes was elevated during weeks 1-4 after COVID-19 diagnosis, compared with before or without COVID-19, in each cohort. Vaccination mitigated the adverse effects of COVID-19 on mental health: aHRs (95% CIs) for depression and for serious mental illness during weeks 1-4 after COVID-19 were 1.93 (1.88-1.98) and 1.42 (1.24-1.61) respectively in the pre-vaccination cohort and 1.79 (1.68-1.91) and 2.21 (1.99-2.45) respectively in the unvaccinated cohort, compared with 1.16 (1.12-1.20) and 0.91 (0.84-0.98) respectively in the vaccinated cohort. Elevation in incidence was higher, and persisted for longer, after hospitalised than non-hospitalised COVID-19. Interpretation: Incidence of mental illness is elevated for up to a year following severe COVID-19 in unvaccinated people. Vaccination mitigates the adverse effect of COVID-19 on mental health. Funding: Medical Research Council (MC_PC_20059) and NIHR (COV-LT-0009).

Group A streptococcal cases and treatments during the COVID-19 pandemic and 2022 outbreak: a retrospective cohort study in England using OpenSAFELY-TPP (preprint)

ObjectiveTo investigate the impact of the COVID-19 pandemic on Group A streptococcal (GAS) cases and related antibiotic prescriptions. DesignA retrospective cohort study with supporting dashboards with the approval of NHS England. SettingPrimary care practices in England using TPP SystmOne software from January 2018 through March 2023. ParticipantsPatients included were those registered at a TPP practice for each month of the study period. Patients with missing sex or age were excluded, resulting in a population of 23,816,470 in January 2018, increasing to 25,541,940 by March 2023. Main outcome measuresWe calculated monthly counts and crude rates of GAS cases (sore throat/tonsillitis, scarlet fever, invasive group A strep) and prescriptions linked with a GAS case, before (pre-April 2020), during and after (post-April 2021) COVID-19 restrictions. We calculated the maximum and minimum count and rate for each season (years running September-August), and the rate ratio (RR) of the 2022/23 season to the last comparably high season (2017/18). ResultsRecording of GAS cases and antibiotic prescription linked with a GAS case peaked in December 2022, higher than the 2017/2018 peak. The peak rate of monthly sore throat/tonsillitis (possible group A strep throat) recording was 5.33 per 1,000 (RR 2022/23 versus 2017/18 1.39 (CI: 1.38 to 1.40)). Scarlet fever recording peaked at 0.51 per 1,000 (RR 2.68 (CI: 2.59 to 2.77)), and invasive group A streptococcal infection (iGAS) at 0.01 per 1,000 (RR 4.37 (CI: 2.94 to 6.48)). First line antibiotics with a record of a GAS infection peaked at 2.80 per 1,000 (RR 1.37 (CI:1.35 to 1.38)), alternative antibiotics at 2.03 per 1,000 (RR 2.30 (CI:2.26 to 2.34)), and reserved antibiotics at 0.09 per 1,000 (RR 2.42 (CI:2.24 to 2.61). For individual antibiotics, azithromycin with GAS indication showed the greatest relative increase (RR 7.37 (CI:6.22 to 8.74)).This followed a sharp drop in recording of cases and associated prescriptions during the period of COVID-19 restrictions where the maximum count and rates were lower than any pre COVID-19 minimum. More detailed demographic breakdowns can be found in our regularly updated dashboard report. ConclusionsRates of scarlet fever, sore throat/tonsillitis and iGAS recording and associated antibiotic prescribing peaked in December 2022. Primary care data can supplement existing infectious disease surveillance through linkages with relevant prescribing data and detailed clinical and demographic subgroups. What is knownDuring the COVID-19 pandemic there has been a substantial change to the pattern of circulating viruses and bacteria that cause illnesses. A spike in group A streptococcal infections in England starting December 2022 was associated with 426 deaths, including 48 children as of 7th May 2023. Increased demand for antibiotics in this period led to medicines shortages and the introduction of Serious Shortage Protocols (SSPs). Existing surveillance systems such as notifiable disease reports and GP in-hours surveillance bulletins describe clinical events, but they do not link to relevant prescribing data. What this study adds- This study supports the findings of routine surveillance reports which indicated a drop in GAS infections during the COVID-19 restrictions, followed by a spike in December 2022, demonstrating that the OpenSAFELY platform and primary care data can be used to rapidly describe not only clinical events but also relevant prescribing in the case of future outbreaks. - Antibiotic prescribing with a GAS indication, particularly for phenoxymethylpenicillin alternatives and reserved antibiotics, was higher in the December 2022 peak than in the 2017/2018 peak.

Diabetes following SARS-CoV-2 infection: Incidence, persistence, and implications of COVID-19 vaccination. A cohort study of fifteen million people. (preprint)

Background Type 2 diabetes (T2DM) incidence is increased after diagnosis of COVID-19. The impact of vaccination on this increase, for how long it persists, and the effect of COVID-19 on other types of diabetes remain unclear. Methods With NHS England approval, we studied diabetes incidence following COVID-19 diagnosis in pre-vaccination (N=15,211,471, January 2020-December 2021), vaccinated (N =11,822,640), and unvaccinated (N=2,851,183) cohorts (June-December 2021), using linked electronic health records. We estimated adjusted hazard ratios (aHRs) comparing diabetes incidence post-COVID-19 diagnosis with incidence before or without diagnosis up to 102 weeks post-diagnosis. Results were stratified by COVID-19 severity (hospitalised/non-hospitalised) and diabetes type. Findings In the pre-vaccination cohort, aHRS for T2DM incidence after COVID-19 (compared to before or without diagnosis) declined from 3.01 (95% CI: 2.76,3.28) in weeks 1-4 to 1.24 (1.12,1.38) in weeks 53-102. aHRS were higher in unvaccinated than vaccinated people (4.86 (3.69,6.41)) versus 1.42 (1.24,1.62) in weeks 1-4) and for hospitalised COVID-19 (pre-vaccination cohort 21.1 (18.8,23.7) in weeks 1-4 declining to 2.04 (1.65,2.51) in weeks 52-102), than non-hospitalised COVID-19 (1.45 (1.27,1.64) in weeks 1-4, 1.10 (0.98,1.23) in weeks 52-102). T2DM persisted for 4 months after COVID-19 for ~73% of those diagnosed. Patterns were similar for Type 1 diabetes, though excess incidence did not persist beyond a year post-COVID-19. Interpretation Elevated T2DM incidence after COVID-19 is greater, and persists longer, in hospitalised than non-hospitalised people. It is markedly less apparent post-vaccination. Testing for T2DM after severe COVID-19 and promotion of vaccination are important tools in addressing this public health problem.

The impact of COVID-19 on medication reviews in English primary care. An OpenSAFELY-TPP analysis of 20 million adult electronic health records. (preprint)

Background The COVID-19 pandemic caused significant disruption to routine activity in primary care. Medication reviews are an important primary care activity to ensure safety and appropriateness of ongoing prescribing and a disruption could have significant negative implications for patient care. Aim Using routinely collected data, our aim was to i) describe the SNOMED CT codes used to report medication review activity ii) report the impact of COVID-19 on the volume and variation of medication reviews. Design and setting With the approval of NHS England, we conducted a cohort study of 20 million adult patient records in general practice, in-situ using the OpenSAFELY platform. Method For each month between April 2019 - March 2022, we report the percentage of patients with a medication review coded monthly and in the previous 12 months. These measures were broken down by regional, clinical and demographic subgroups and amongst those prescribed high risk medications. Results In April 2019, 32.3% of patients had a medication review coded in the previous 12 months. During the first COVID-19 lockdown, monthly activity substantially decreased (-21.1% April 2020), but the rate of patients with a medication review coded in the previous 12 months was not substantially impacted according to our classification (-10.5% March 2021). There was regional and ethnic variation (March 2022 - London 21.9% vs North West 33.6%; Chinese 16.8% vs British 33.0%). Following the introduction of "structured medication reviews", the rate of structured medication review in the last 12 months reached 2.9% by March 2022, with higher percentages in high risk groups (March 2022 - care home residents 34.1%, 90+ years 13.1%, high risk medications 10.2%). The most used SNOMED CT medication review code across the study period was Medication review done - 314530002 (59.5%). Conclusion We have reported a substantial reduction in the monthly rate of medication reviews during the pandemic but rates recovered by the end of the study period.

Patient characteristics associated with clinically coded long COVID: an OpenSAFELY study using electronic health records (preprint)

Despite reports of post-COVID-19 syndromes (long COVID) are rising, clinically coded long COVID cases are incomplete in electronic health records. It is unclear how patient characteristics may be associated with clinically coded long COVID. With the approval of NHS England, we undertook a cohort study using electronic health records within the OpenSAFELY-TPP platform in England, to study patient characteristics associated with clinically coded long COVID from 29 January 2020 to 31 March 2022. We estimated age-sex adjusted hazard ratios and fully adjusted hazard ratios for coded long COVID. Patient characteristics included demographic factors, and health behavioural and clinical factors. Among 17,986,419 adults, 36,886 (0.21%) were clinically coded with long COVID. Patient characteristics associated with coded long COVID included female sex, younger age (under 60 years), obesity, living in less deprived areas, ever smoking, greater consultation frequency, and history of diagnosed asthma, mental health conditions, pre-pandemic post-viral fatigue, or psoriasis. The strength of these associations was attenuated following two-dose vaccination compared to before vaccination. The incidence of coded long COVID was higher after hospitalised than non-hospitalised COVID-19. These results should be interpreted with caution given that long COVID was likely under-recorded in electronic health records.

Primary care coding activity related to the use of online consultation systems or remote consulting: an analysis of 53 million peoples' health records using OpenSAFELY (preprint)

Objective: We aimed to explore general practice coding activity associated with the use of online consultation systems in terms of trends, COVID-19 effect, variation and quality. The pandemic accelerated work by the NHS in England to enable and stimulate use of online consultation systems across all practices, for improved access to primary care. Methods: With the approval of NHS England, OpenSAFELY-TPP and OpenSAFELY-EMIS were used to query and analyse in situ records of electronic health record systems of over 53 million patients in over 6,400 practices, mainly in 2019-2020. SNOMED CT codes relevant to online consultation systems and written online consultations were identified. Coded events were described by volumes, practice coverage, trends pre- and post-COVID-19 and inter-practice and sociodemographic variation. Results: 3,550,762 relevant coding events were found in TPP practices, with code eConsultation detected in 84% of practices. Coding activity related to digital forms of interaction increased rapidly from March 2020 at the onset of the COVID-19 pandemic, though we found large variation in coding instance rates among practices in England. Code instances were more commonly found among females, those aged 18-40, those least deprived or white. eConsultation coded activity was more commonly found recorded among patients with a history of asthma or depression. Conclusions: We successfully queried general practice coding activity relevant to the use of online consultation systems, showing increased adoption as well as key areas of variation during the COVID-19 pandemic. The work can be expanded to support monitoring of coding quality and underlying activity. In future, large-scale impact evaluation studies can be implemented within the platform, namely looking at resource utilisation and patient outcomes.

The impact of the COVID-19 pandemic on Antipsychotic Prescribing in individuals with autism, dementia, learning disability, serious mental illness or living in a care home: A federated analysis of 59 million patients primary care records in situ using OpenSAFELY (preprint)

Background: The COVID-19 pandemic significantly affected health and social care services. We aimed to explore whether this impacted the prescribing rates of antipsychotics within at-risk populations. Methods With the approval of NHS England, we completed a retrospective cohort study, using the OpenSAFELY platform to explore primary care data of 59 million patients. We identified patients in five at-risk groups: autism, dementia, learning disability, serious mental illness and care home residents. We then calculated the monthly prevalence of antipsychotic prescribing in the population, as well as the incidence of new prescriptions in each month over the study period (Jan 2019-Dec 2021). Results The average monthly rate of antipsychotic prescribing increased in dementia from 82.75 patients prescribed an antipsychotic per 1000 patients (95% CI 82.30-83.19) in Q1 2019 to 90.1 (95% CI 89.68-90.60) in Q4 2021 and from 154.61 (95% CI 153.79-155.43) in Q1 2019 to 166.95 (95% CI 166.23-167.67) in Q4 2021 in care homes . There were notable spikes in the rate of new prescriptions issued to patients with dementia and in care homes. In learning disability and autism groups, the average monthly rate of prescribing per 1000 decreased from 122.97 (95% CI 122.29-123.66) in Q1 2019 to 119.29 (95% CI 118.68-119.91) in Q4 2021, and from 54.91 (95% CI 54.52-55.29) in Q1 2019 to 51.04 (95% CI 50.74-51.35) in Q4 2021 respectively. Conclusions During each of the lockdowns in 2020, we observed a significant spike in antipsychotic prescribing in the dementia and care home groups. We have shown that these peaks are likely due to prescribing of antipsychotics for palliative care purposes and may have been linked to pre-emptive prescribing, when on-site medical visits would have been restricted. Over the study period, we observed gradual increases in antipsychotic use in patients with dementia and in care homes and a decrease in their use in patients with learning disability or autism.

Healthcare in England was affected by the COVID-19 pandemic across the pancreatic cancer pathway: a cohort study using OpenSAFELY-TPP (preprint)

Background Healthcare across all sectors, in the UK and globally, was negatively affected by the COVID-19 pandemic. We investigated the effect of the COVID-19 pandemic on the quantity of healthcare services delivered to people with pancreatic cancer. Methods With the approval of NHS England, and drawing from a nationally representative OpenSAFELY-TPP dataset of 24 million patients (over 40% of the English population), we undertook a cohort study of people diagnosed with pancreatic cancer. We queried electronic healthcare records for information on the provision of healthcare services across the pancreatic cancer pathway. To estimate the effect of the COVID-19 pandemic, we predicted the rates of healthcare services if the pandemic had not happened. We used generalised linear models (GLM) and the pre-pandemic data from January 2015 to February 2020 to predict rates in March 2020 to September 2022. The 95% confidence intervals of the predicted values were used to estimate the significance of the difference between the predicted and observed rates. Results The rate of pancreatic cancer and diabetes diagnoses in the cohort was not affected by the pandemic. There were 24,500 people diagnosed with pancreatic cancer from January 2015 to September 2022. The mean age at diagnosis was 72 (SD 11), 48% of people were female, 95% were of White ethnicity and 39% were diagnosed with diabetes. We found a reduction in surgical resections by nearly 25% during the pandemic. In addition, 20%, 10% and 5% fewer people received BMI, HbA1c and liver function tests respectively before they were diagnosed with pancreatic cancer. There was no impact of the pandemic on the number of people making contact with primary care, but the number of contacts increased on average by 1 to 2 per person amongst those who made contact. Abdominal scans decreased by 7% and reporting of jaundice decreased by 20%, but recovered within six months into the pandemic. Emergency department visits, hospital admissions and deaths were not affected. Conclusions The pandemic affected healthcare in England across the pancreatic cancer pathway. Positive lessons could be learnt from services that recovered quickly. The reductions in healthcare experienced by people with cancer have the potential to lead to worse outcomes. Current efforts should focus on addressing the unmet needs of people with cancer.

Eleven key measures for monitoring general practice clinical activity during COVID-19 using federated analytics on 48 million adults' primary care records through OpenSAFELY (preprint)

Background The COVID-19 pandemic has had a significant impact on delivery of NHS care. We have developed the OpenSAFELY Service Restoration Observatory (SRO) to describe this impact on primary care activity and monitor its recovery. Objectives To develop key measures of primary care activity and describe the trends in these measures throughout the COVID-19 pandemic. Methods With the approval of NHS England we developed an open source software framework for data management and analysis to describe trends and variation in clinical activity across primary care electronic health record (EHR) data on 48 million adults. We developed SNOMED-CT codelists for key measures of primary care clinical activity selected by a expert clinical advisory group and conducted a population cohort-based study to describe trends and variation in these measures January 2019-December 2021, and pragmatically classified their level of recovery one year into the pandemic using the percentage change in the median practice level rate. Results We produced 11 measures reflective of clinical activity in general practice. A substantial drop in activity was observed in all measures at the outset of the COVID-19 pandemic. By April 2021, the median rate had recovered to within 15% of the median rate in April 2019 in six measures. The remaining measures showed a sustained drop, ranging from a 18.5% reduction in medication reviews to a 42.0% reduction in blood pressure monitoring. Three measures continued to show a sustained drop by December 2021. Conclusions The COVID-19 pandemic was associated with a substantial change in primary care activity across the measures we developed, with recovery in most measures. We delivered an open source software framework to describe trends and variation in clinical activity across an unprecedented scale of primary care data. We will continue to expand the set of key measures to be routinely monitored using our publicly available NHS OpenSAFELY SRO dashboards with near real-time data.

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.

OpenSAFELY: Representativeness of Electronic Health Record platform OpenSAFELY-TPP data compared to the population of England. (preprint)

BackgroundSince its inception in March 2020, data from the OpenSAFELY-TPP electronic health record platform has been used for more than 50 studies relating to the global COVID-19 emergency. OpenSAFELY-TPP data is derived from practices in England using SystmOne software, and has been used for the majority of these studies. We set out to investigate the representativeness of OpenSAFELY-TPP data by comparing it to national population estimates. MethodsWith the approval of NHS England, we describe the age, sex, Index of Multiple Deprivation and ethnicity of the OpenSAFELY-TPP population compared to national estimates from the Office for National Statistics. The five leading causes of death occurring between the 1st January 2020 and the 31st December 2020 were also compared to deaths registered in England during the same period. ResultsDespite regional variations, TPP is largely representative of the general population of England in terms of IMD (all within 1.1 percentage points), age, sex (within 0.1 percentage points), ethnicity and causes of death. The proportion of the five leading causes of death is broadly similar to those reported by ONS (all within 1 percentage point). ConclusionsData made available via OpenSAFELY-TPP is broadly representative of the English population. SummaryUsers of OpenSAFELY must consider the issues of representativeness, generalisability and external validity associated with using TPP data for health research. Although the coverage of TPP practices varies regionally across England, TPP registered patients are generally representative of the English population as a whole in terms of key demographic characteristics. Key messagesO_LIThere is regional variability across England in terms of key population characteristics C_LIO_LIUsers of OpenSAFELY should carefully consider the issues of representativeness, generalisability and external validity associated with using TPP data for health research. C_LIO_LITPP registered patients are a representative sub-sample of the English population as a whole in terms of age, sex, IMD and ethnicity. C_LIO_LIThe proportions of the five leading causes of death in TPP in 2020 are broadly similar to those reported by ONS. C_LI

Effectiveness of BNT162b2 booster doses in England: an observational study in OpenSAFELY-TPP (preprint)

Background The UK COVID-19 vaccination programme delivered its first "booster" doses in September 2021, initially in groups at high risk of severe disease then across the adult population. The BNT162b2 Pfizer-BioNTech vaccine was used initially, with Moderna mRNA-1273 subsequently also used. Methods We used the OpenSAFELY-TPP database, covering 40% of English primary care practices and linked to national coronavirus surveillance, hospital episodes, and death registry data, to estimate the effectiveness of boosting with BNT162b2 compared with no boosting in eligible adults who had received two primary course vaccine doses between 16 September and 16 December 2021 when the Delta variant of SARS-CoV-2 was dominant. Follow up was for up to 10 weeks. Each booster recipient was matched with an unboosted control on factors relating to booster priority status and prior immunisation. Additional factors were adjusted for in Cox models estimating hazard ratios (HRs). Outcomes were positive SARS-CoV-2 test, COVID-19 hospitalisation, COVID-19 death and non-COVID-9 death. Booster vaccine effectiveness was defined as 1-HR. Results Among 4,352,417 BNT162b2 booster recipients matched with unboosted controls, estimated effectiveness of a booster dose compared with two doses only was 50.7% (95% CI 50.1-51.3) for positive SARS-CoV-2 test, 80.1% (78.3-81.8) for COVID-19 hospitalisation, 88.5% (85.0-91.1) for COVID-19 death, and 80.3% (79.0-81.5) for non-COVID-19 death. Estimated effectiveness was similar among those who had received a BNT162b2 or ChAdOx1-S two-dose primary vaccination course, but effectiveness against severe COVID-19 was slightly lower in those classified as clinically extremely vulnerable (76.3% (73.1-79.1) for COVID-19 hospitalisation, and 85.1% (79.6-89.1) for COVID-19 death). Estimated effectiveness against each outcome was lower in those aged 18-65 years than in those aged 65 and over. Conclusion Our findings are consistent with strong protection of BNT162b2 boosting against positive SARS-CoV-2 test, COVID-19 hospitalisation, and COVID-19 death.

OpenSAFELY NHS Service Restoration Observatory 2: changes in primary care activity across six clinical areas during the COVID-19 pandemic (preprint)

Background The COVID-19 pandemic has disrupted healthcare activity across a broad range of clinical services. The NHS stopped non-urgent work in March 2020, later recommending services be restored to near-normal levels before winter where possible. Aims Using routinely collected data, our aim was to describe changes in the volume and variation of coded clinical activity in general practice in: (i) cardiovascular disease, (ii) diabetes, (iii) mental health, (iv) female and reproductive health, (v) screening, and (vi) processes related to medication. Design and setting With the approval of NHS England, we conducted a cohort study of 23.8 million patient records in general practice, in-situ using OpenSAFELY. Methods We selected common primary care activity using CTV3 codes and keyword searches from January 2019 - December 2020, presenting median and deciles of code usage across practices per month. Results We identified substantial and widespread changes in clinical activity in primary care since the onset of the COVID-19 pandemic, with generally good recovery by December 2020. A few exceptions showed poor recovery and warrant further investigation, such as mental health, e.g. "Depression interim review" (median across practices in December 2020 -41.6% compared to December 2019). Conclusions Granular NHS GP data at population-scale can be used to monitor disruptions to healthcare services and guide the development of mitigation strategies. The authors are now developing real-time monitoring dashboards for key measures identified here as well as further studies, using primary care data to monitor and mitigate the indirect health impacts of Covid-19 on the NHS.

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.

Changes in English medication safety indicators throughout the COVID-19 pandemic: a federated analysis of 57 million patients' primary care records in situ using OpenSAFELY (preprint)

Objective: To describe the impact of the COVID-19 pandemic on safe prescribing, using the PINCER prescribing indicators; to implement complex prescribing indicators at national scale using GP data. Design: Population based cohort study, with the approval of NHS England using the OpenSAFELY platform. Setting: Electronic health record data from 56.8 million NHS patients' general practice records. Participants: All NHS patients registered at a GP practice using TPP or EMIS computer systems and recorded as at risk of at least one potentially hazardous PINCER indicator between September 2019 and September 2021. Main outcome measure: Monthly trends and between-practice variation for compliance with 13 PINCER measures between September 2019 and September 2021. Results: The indicators were successfully implemented across GP data in OpenSAFELY. Hazardous prescribing remained largely unchanged during the COVID-19 pandemic, with only small reductions in achievement of the PINCER indicators. There were transient delays in blood test monitoring for some medications, particularly ACE inhibitors. All indicators exhibited substantial recovery by September 2021. We identified 1,813,058 patients at risk of at least one hazardous prescribing event. Conclusion: Good performance was maintained during the COVID-19 pandemic across a diverse range of widely evaluated measures of safe prescribing.

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).

Waning effectiveness of BNT162b2 and ChAdOx1 COVID-19 vaccines over six months since second dose: a cohort study using linked electronic health records (preprint)

Summary Background The rate at which COVID-19 vaccine effectiveness wanes over time is crucial for vaccination policies, but is incompletely understood with conflicting results from different studies. Methods This cohort study, using the OpenSAFELY-TPP database and approved by NHS England, included individuals without prior SARS-CoV-2 infection assigned to vaccines priority groups 2-12 defined by the UK Joint Committee on Vaccination and Immunisation. We compared individuals who had received two doses of BNT162b2 or ChAdOx1 with unvaccinated individuals during six 4-week comparison periods, separately for subgroups aged 65+ years; 16-64 years and clinically vulnerable; 40-64 years and 18-39 years. We used Cox regression, stratified by first dose eligibility and geographical region and controlled for calendar time, to estimate adjusted hazard ratios (aHRs) comparing vaccinated with unvaccinated individuals, and quantified waning vaccine effectiveness as ratios of aHRs per-4-week period. The outcomes were COVID-19 hospitalisation, COVID-19 death, positive SARS-CoV-2 test, and non-COVID-19 death. Findings The BNT162b2, ChAdOx1 and unvaccinated groups comprised 1,773,970, 2,961,011 and 2,433,988 individuals, respectively. Waning of vaccine effectiveness was similar across outcomes and vaccine brands: e.g. in the 65+ years subgroup ratios of aHRs versus unvaccinated for COVID-19 hospitalisation, COVID-19 death and positive SARS-CoV-2 test ranged from 1.23 (95% CI 1.15-1.32) to 1.27 (1.20-1.34) for BNT162b2 and 1.16 (0.98-1.37) to 1.20 (1.14-1.27) for ChAdOx1. Despite waning, rates of COVID-19 hospitalisation and COVID-19 death were substantially lower among vaccinated individuals compared to unvaccinated individuals up to 26 weeks after second dose, with estimated aHRs <0.20 (>80% vaccine effectiveness) for BNT162b2, and <0.26 (>74%) for ChAdOx1. By weeks 23-26, rates of SARS-CoV-2 infection in fully vaccinated individuals were similar to or higher than those in unvaccinated individuals: aHRs ranged from 0.85 (0.78-0.92) to 1.53 (1.07-2.18) for BNT162b2, and 1.21 (1.13-1.30) to 1.99 (1.94-2.05) for ChAdOx1. Interpretation The rate at which estimated vaccine effectiveness waned was strikingly consistent for COVID-19 hospitalisation, COVID-19 death and positive SARS-CoV-2 test, and similar across subgroups defined by age and clinical vulnerability. If sustained to outcomes of infection with the Omicron variant and to booster vaccination, these findings will facilitate scheduling of booster vaccination doses.

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.