M onkeypox is a reemerging zoonosis caused by Monkeypox virus (MPXV), a member of the genus Orthopoxvirus. MPXV is related to Variola virus, the causative agent of smallpox. Although infections with these 2 viruses share many clinical features, monkeypox is generally less severe than smallpox (1). Among unvaccinated persons, the monkeypox case-fatality rate can be up to 10%, although casefatality rates are lower for infection with the West African than the Central African clade of MPXV (2). In recent years, the number of cases and geographic spread of monkeypox have been increasing, possibly because of waning immunity to smallpox (3-5). Before 2018, the only human cases of monkeypox outside Africa occurred in the United States in 2003; that outbreak was associated with rodents imported from Ghana, and human-to-human transmission did not occur (6). In September 2018, Public Health England (PHE) was notified of 2 unrelated cases of monkeypox affecting travelers who had recently returned from Nigeria (7). We describe transmission of monkeypox virus from the second of these cases to a healthcare worker (HCW) and the public health measures implemented to prevent further cases. The Cases On September 6, 2018, a man with a maculopapular rash, fever, lymphadenopathy, and a 1-week history of feeling generally unwell (patient 2) sought care at a hospital in England (7). He was admitted to a singleoccupancy room in the acute medical unit. The staff attending the patient wore standard personal protective equipment (PPE), consisting of disposable aprons and gloves. Because a travel-associated infection was considered possible, patient 2 was transferred to an isolation room on September 7, 2018. Three days later, a clinical diagnosis of suspected monkeypox was made, and infection prevention and control precautions for a high-consequence infectious disease (HCID) were implemented (e.g., enhanced PPE consisting of disposable gown, disposable gloves, filtering facepiece 3 respirator, and face shield or goggles). The patient was transferred to an Airborne HCID Treatment Centre, and monkeypox was confirmed by laboratory testing at PHE (7). Although the risk to the public was considered to be very low, a precautionary approach was adopted. Possible hospital and community contacts of patient 2 were identified and assessed for risk (Table).

Background: Long COVID describes new or persistent symptoms at least four weeks after onset of acute COVID-19. Clinical codes to describe this were recently created. Aim: To describe the use of long COVID codes, and variation of use by general practice, demographics and over time. Design and Setting: Population-based cohort study in English primary care records. Method: Working on behalf of NHS England, we used OpenSAFELY data encompassing 96% of the English population between 2020-02-01 and 2021-04-25. We measured the proportion of people with a recorded code for long COVID, overall and by demographic factors, electronic health record software system (EMIS or TPP), and week. Results: Long COVID was recorded for 23,273 people. Coding was unevenly distributed amongst practices, with 26.7% of practices having never used the codes. Regional variation, ranged 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). Coding was higher amongst women (52.1, 95% CI 51.3-52.9) than men (28.1, 95% CI 27.5-28.7), and higher amongst EMIS practices (53.7, 95% CI 52.9-54.4) than TPP practices (20.9, 95% CI 20.3-21.4). Conclusion: Long 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.

BackgroundOn 8 December 2020 NHS England administered the first COVID-19 vaccination.AimTo describe trends and variation in vaccine coverage in different clinical and demographic groups in the first 100 days of the vaccine rollout.Design and settingWith the approval of NHS England, a cohort study was conducted of 57.9 million patient records in general practice in England, in situ and within the infrastructure of the electronic health record software vendors EMIS and TPP using OpenSAFELY.MethodVaccine coverage across various subgroups of Joint Committee on Vaccination and Immunisation (JCVI) priority cohorts is described.ResultsA total of 20 852 692 patients (36.0%) received a vaccine between 8 December 2020 and 17 March 2021. Of patients aged ≥80 years not in a care home (JCVI group 2) 94.7% received a vaccine, but with substantial variation by ethnicity (White 96.2%, Black 68.3%) and deprivation (least deprived 96.6%, most deprived 90.7%). Patients with pre-existing medical conditions were more likely to be vaccinated with two exceptions: severe mental illness (89.5%) and learning disability (91.4%). There were 275 205 vaccine recipients who were identified as care home residents (JCVI group 1; 91.2% coverage). By 17 March, 1 257 914 (6.0%) recipients had a second dose.ConclusionThe NHS rapidly delivered mass vaccination. In this study a data-monitoring framework was deployed using publicly auditable methods and a secure in situ processing model, using linked but pseudonymised patient-level NHS data for 57.9 million patients. Targeted activity may be needed to address lower vaccination coverage observed among certain key groups.

BackgroundOn December 8th 2020, NHS England administered the first COVID-19 vaccination as part of an ambitious vaccination programme during a global health emergency.AimsTo develop a framework for detailed near-real-time monitoring of COVID-19 vaccine roll-out; to describe trends and variation in coverage by geographic area, and between key clinical and demographic patient groups.MethodsWorking on behalf of NHS England we used routine clinical data from 23.4 million patients to conduct a retrospective cohort study of comprehensive electronic health record data in NHS England, using the OpenSAFELY-TPP platform which covers approximately 40% of the general population in England with weekly data updates. We developed algorithms to identify key demographic and clinical sub-groups within this population and generated descriptive statistics on proportion of eligible patients receiving the vaccine among key Joint Committee on Vaccination and Immunisation (JCVI) target groups.ResultsBetween December 8th and January 13th 961,580 people out of 23.4m in our dataset received a COVID-19 vaccine. Of 1,160,062 patients aged 80 or over and not living in a care home (currently targeted by JCVI) 476,375 had been vaccinated in total (41.1%). We observed a substantial divergence in vaccination by ethnicity within this group (White 42.5% vaccinated, Black 20.5%) and across rankings of deprivation (least deprived 44.7%, most deprived 37.9%). Patients with pre-existing medical conditions were equally likely, or more likely, to have received a vaccine across most co-morbidity groups with two exceptions: severe mental illness (30.3% vaccinated) and learning disability (28.1%). We identify substantial variation in vaccination among the over-80s between Sustainability and Transformation Partnerships (STPs; Range 12%-74%); lower vaccination rates among ethnic minority and deprived groups was observed in most but not all STPs. In the 70-79 age cohort 74,108 people (3.6%) had been vaccinated. 378,921 vaccine recipients under 70 and not identifiably resident in a care home were presumed to be health or social care workers; 32,174 recipients were identified as older aged care home residents (33.2% coverage). Of all those vaccinated, 169,472 had received a second dose (17.6%).ConclusionsThe NHS in England has rapidly delivered mass vaccination. We were able to deploy a data monitoring framework across small clinical subgroups using linked patient-level NHS data on 23.4 million people with very short delays from vaccine administration to completed analysis. Targeted activity may be needed to address lower vaccination rates observed among certain key groups: ethnic minorities, people living in areas of higher deprivation, and those with severe mental illness or learning disabilities. However we note that this data is only from the first preliminary weeks of the vaccination programme. Variation in vaccination coverage between groups and regions will have many complex drivers, the figures presented in this manuscript require thoughtful interpretation to support a rapidly evolving NHS vaccination campaign; we are sharing local level data with national and regional NHS teams on request.

ObjectiveTo 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.DesignPopulation based cohort study, with the approval of NHS England using the OpenSAFELY platform.SettingElectronic health record data from 56.8 million NHS patients’ general practice records.ParticipantsAll 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 measureMonthly trends and between-practice variation for compliance with 13 PINCER measures between September 2019 and September 2021.ResultsThe 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.ConclusionGood performance was maintained during the COVID-19 pandemic across a diverse range of widely evaluated measures of safe prescribing.Summary boxWHAT IS ALREADY KNOWN ON THIS TOPICPrimary care services were substantially disrupted by the COVID-19 pandemic.Disruption to safe prescribing during the pandemic has not previously been evaluated.PINCER is a nationally adopted programme of activities that aims to identify and correct hazardous prescribing in GP practices, by conducting manual audit on subgroups of practices.WHAT THIS STUDY ADDSFor the first time, we were able to successfully generate data on PINCER indicators for almost the whole population of England, in a single analysis.Our study is the most comprehensive assessment of medication safety during the COVID-19 pandemic in England, covering 95% of the population using well-validated measures.Good performance was maintained across many PINCER indicators throughout the pandemic.Delays in delivering some medication-related blood test monitoring were evident though considerable recovery was made by the end of the study period.

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.

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Background Long 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. Methods Working 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. Results Long 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). Conclusions Long 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.