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Initiation of injectable therapies in type 2 diabetes (T2D) is often delayed, however the reasons why are not fully understood.A mixed methods study performed in sequential phases. Phase 1: focus groups with people with T2D (injectable naïve [n = 12] and experienced [n = 5]) and healthcare professionals (HCPs; nurses [n = 5] and general practitioners (GPs) [n = 7]) to understand their perceptions of factors affecting initiation of injectables. Phase 2: video-captured GP consultations (n = 18) with actor-portrayed patient scenarios requiring T2D treatment escalation to observe the initiation in the clinical setting. Phase 3: HCP surveys (n = 87) to explore external validity of the themes identified in a larger sample.Focus groups identified patients' barriers to initiation; fear, lack of knowledge and misconceptions about diabetes and treatment aims, concerns regarding lifestyle restrictions and social stigma, and feelings of failure. Facilitators included education, good communication, clinician support and competence. HCP barriers included concerns about weight gain and hypoglycaemia, and limited consultation time. In simulated consultations, GPs performed high-quality consultations and recognised the need for injectable initiation in 9/12 consultations where this was the expert recommended option but did not provide support for initiation themselves. Survey results demonstrated HCPs believe injectable initiation should be performed in primary care, although many practitioners reported inability to do so or difficulty in maintaining skills.People with T2D have varied concerns and educational needs regarding injectables. GPs recognise the need to initiate injectables but lack practical skills and time to address patient concerns and provide education. Primary care nurses also report difficulties in maintaining these skills. Primary care HCPs initiating injectables require additional training to provide practical demonstrations, patient education and how to identify and address concerns. These skills should be concentrated in the hands of a small number of primary care providers to ensure they can maintain their skills.

Background We investigated differences in risk of stroke, with all-cause mortality as a competing risk, in people newly diagnosed with atrial fibrillation (AF) who were commenced on either direct oral anticoagulants (DOACs) or warfarin treatment. Methods and results We conducted a retrospective cohort study of the Oxford Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) database (a network of 500 English general practices). We compared long term exposure to DOAC (n = 5,168) and warfarin (n = 7,451) in new cases of AF not previously treated with oral anticoagulants. Analyses included: survival analysis, estimating cause specific hazard ratios (CSHR), Fine-Gray analysis for factors affecting cumulative incidence of events occurring over time and a cumulative risk regression with time varying effects.We found no difference in CSHR between stroke 1.08 (0.72–1.63, p = 0.69) and all-cause mortality 0.93 (0.81–1.08, p = 0.37), or between the anticoagulant groups. Fine-Gray analysis produced similar results 1.07 (0.71–1.6 p = 0.75) for stroke and 0.93 (0.8–1.07, p = 0.3) mortality. The cumulative risk of mortality with DOAC was significantly elevated in early follow-up (67 days), with cumulative risk decreasing until 1,537 days and all-cause mortality risk significantly decreased coefficient estimate:: -0.23 (-0.38–0.01, p = 0.001); which persisted over seven years of follow-up. Conclusions In this large, contemporary, real world primary care study with longer follow-up, we found no overall difference in the hazard of stroke between warfarin and DOAC treatment for AF. However, there was a significant time-varying effect between anti-coagulant regimen on all-cause mortality, with DOACs showing better survival. This is a key methodological observation for future follow-up studies, and reassuring for patients and health care professionals for longer duration of therapy

BackgroundThe Platform Randomised trial of INterventions against COVID-19 In older peoPLE (PRINCIPLE) has provided in-pandemic evidence that azithromycin and doxycycline were not beneficial in the early primary care management of coronavirus 2019 disease (COVID-19).AimTo explore the extent of in-pandemic azithromycin and doxycycline use, and the scope for trial findings impacting on practice.Design & settingCrude rates of prescribing and respiratory tract infections (RTI) in 2020 were compared with 2019, using the Oxford Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC).MethodNegative binomial models were used to compare azithromycin and doxycycline prescribing, lower respiratory tract infections (LRTI), upper respiratory tract infections (URTI), and influenza-like illness (ILI) in 2020 with 2019; reporting incident rate ratios (IRR) between years, and 95% confidence intervals (95% CI).ResultsAzithromycin prescriptions increased 7% in 2020 compared with 2019, whereas doxycycline decreased by 7%. Concurrently, LRTI and URTI incidence fell by over half (58.3% and 54.4%, respectively) while ILI rose slightly (6.4%). The overall percentage of RTI-prescribed azithromycin rose from 0.51% in 2019 to 0.72% in 2020 (risk difference 0.214%; 95% CI = 0.211 to 0.217); doxycycline rose from 11.86% in 2019 to 15.79% in 2020 (risk difference 3.93%; 95% CI = 3.73 to 4.14). The adjusted IRR showed azithromycin prescribing was 22% higher in 2020 (IRR = 1.22; 95% CI = 1.19 to 1.26; PPConclusionPRINCIPLE demonstrates scope for improved antimicrobial stewardship during a pandemic.

Background In the 2016/2017 influenza season, England was in its fourth season of the roll-out of a live-attenuated influenza vaccine (LAIV) targeted at healthy children aged two to less than 17 years. For the first time, all healthy children aged 2 to 8 years were offered LAIV at national level in 2016/2017. Since the commencement of the programme in 2013/2014, a series of geographically discrete pilot areas have been in place where quadrivalent LAIV was also offered to all school age children. In 2016/2017, these were children aged 8 to 11 years, other than those targeted by the national programme. Methods We evaluated the overall and indirect impact of vaccinating primary school age children, on the population of England, by measuring vaccine uptake levels and comparing cumulative disease incidence through various influenza surveillance schemes, in targeted and non-targeted age groups in pilot and non-pilot areas in 2016/2017. Results Our findings indicate that cumulative primary care influenza-like consultations, primary and secondary care swab positivity, influenza confirmed hospitalisations and emergency department attendances in pilot areas were overall lower than those observed in non-pilot areas; however, significant differences were not always observed in both targeted and non-targeted age groups. Excess mortality was higher in pilot areas compared with non-pilot areas. Conclusions These results are similar to earlier seasons of the programme indicating the importance and continuing support of vaccinating all primary school children with LAIV to reduce influenza related illness across the population, although further work is needed to understand the differences in excess mortality.

Background A multi-tiered surveillance system based on influenza surveillance was adopted in the United Kingdom in the early stages of the coronavirus disease (COVID-19) epidemic to monitor different stages of the disease. Mandatory social and physical distancing measures (SPDM) were introduced on 23 March 2020 to attempt to limit transmission. Aim To describe the impact of SPDM on COVID-19 activity as detected through the different surveillance systems. Methods Data from national population surveys, web-based indicators, syndromic surveillance, sentinel swabbing, respiratory outbreaks, secondary care admissions and mortality indicators from the start of the epidemic to week 18 2020 were used to identify the timing of peaks in surveillance indicators relative to the introduction of SPDM. This timing was compared with median time from symptom onset to different stages of illness and levels of care or interactions with healthcare services. Results The impact of SPDM was detected within 1 week through population surveys, web search indicators and sentinel swabbing reported by onset date. There were detectable impacts on syndromic surveillance indicators for difficulty breathing, influenza-like illness and COVID-19 coding at 2, 7 and 12 days respectively, hospitalisations and critical care admissions (both 12 days), laboratory positivity (14 days), deaths (17 days) and nursing home outbreaks (4 weeks). Conclusion The impact of SPDM on COVID-19 activity was detectable within 1 week through community surveillance indicators, highlighting their importance in early detection of changes in activity. Community swabbing surveillance may be increasingly important as a specific indicator, should circulation of seasonal respiratory viruses increase.

Objectives To mitigate risk of mortality from coronavirus 2019 infection (COVID-19), the UK government recommended ‘shielding’ of vulnerable people through self-isolation for 12 weeks. Methods A retrospective cohort study using a nationally representative English primary care database comparing people aged >= 40 years who were recorded as being advised to shield using a fixed ratio of 1:1, matching to people with the same diagnoses not advised to shield (n = 77,360 per group). Time-to-death was compared using Cox regression, reporting the hazard ratio (HR) of mortality between groups. A sensitivity analysis compared exact matched cohorts (n = 24,752 shielded, n = 61,566 exact matches). Results We found a time-varying HR of mortality between groups. In the first 21 days, the mortality risk in people shielding was half those not (HR = 0.50, 95%CI:0.41–0.59. p

Objectives To monitor changes in seroprevalence of SARS-CoV-2 antibodies in populations over time and between different demographic groups. Methods A subset of practices in the Oxford-Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) sentinel network provided serum samples, collected when volunteer patients had routine blood tests. We tested these samples for SARS-CoV-2 antibodies using Abbott (Chicago, USA), Roche (Basel, Switzerland) and/or Euroimmun (Luebeck, Germany) assays, and linked the results to the patients’ primary care computerised medical records. We report seropositivity by region and age group, and additionally examined the effects of gender, ethnicity, deprivation, rurality, shielding recommendation and smoking status. Results We estimated seropositivity from patients aged 18-100 years old, which ranged from 4.1% (95% CI 3.1–5.3%) to 8.9% (95% CI 7.8–10.2%) across the different assays and time periods. We found higher Euroimmun seropositivity in younger age groups, people of Black and Asian ethnicity (compared to white), major conurbations, and non-smokers. We did not observe any significant effect by region, gender, deprivation, or shielding recommendation. Conclusions Our results suggest that prior to the vaccination programme, most of the population remained unexposed to SARS-CoV-2.

BackgroundThe Platform Randomised trial of INterventions against COVID-19 In older peoPLE (PRINCIPLE) trial has provided in-pandemic evidence of what does not work in the early primary care management of coronavirus-2019 disease (COVID-19). PRINCIPLE’s first finding was that azithromycin and doxycycline were not effective.AimTo explore the extent to which azithromycin and doxycycline were being used in-pandemic, and the scope for trial findings impacting on practice.Design and SettingWe compared crude rates of prescribing and respiratory tract infections (RTI) in 2020, the pandemic year, with 2019, using the Oxford-Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC).MethodsWe used a negative binomial model including age-band, gender, socioeconomic status, and NHS region to compare azithromycin and doxycycline lower respiratory tract infections (LRTI), upper respiratory tract infections (URTI), and influenza-like-illness (ILI) in 2020 with 2019; reporting incident rate ratios (IRR) between years and 95% confidence intervals (95%CI).ResultsAzithromycin prescriptions increased 7% in 2020 compared to 2019, whereas doxycycline decreased by 7%. Concurrently, LRTI and URTI incidence fell by over half (58.3% and 54.4% respectively) while ILI rose slightly (6.4%). The overall percentage of RTI prescribed azithromycin rose by 42.1% between 2019 and 2020, doxycycline increased by 33%.Our adjusted IRR showed azithromycin prescribing was 22% higher in 2020 (IRR=1.22, 95%CI:1.19-1.26, pConclusionPRINCIPLE trial flags scope for improvement in antimicrobial stewardship.

Background: The cell-based quadrivalent influenza vaccine (QIVc) is now offered as an alternative to egg-based quadrivalent (QIVe) and adjuvanted trivalent (aTIV) influenza vaccines in the UK. While post-licensure studies show non-inferiority of cell-based vaccines, it is not known how its safety profile compares to other types of vaccines in real-world use. Methods: We conducted a retrospective cohort study using computerised medical records from the Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) sentinel network database. We used a self-controlled case series design and calculated the relative incidence (RI) of adverse events of interest (AEIs) over different risk periods. We then compared the RIs of AEIs within seven days of vaccination overall and between QIVc and QIVe in the 18-64 years age group, and between QIVc and aTIV in the ≥65 years age group. Findings: The majority of AEIs occurred within seven days of vaccination, and a seasonal effect was observed. Using QIVc as the reference group, QIVe showed similar incidence of AEIs whereas live attenuated influenza vaccine (LAIV) and aTIV had lower incidence of AEIs. In the stratified analyses, QIVe and aTIV were associated with a 16% lower incidence of AEIs in the seven days post-vaccination in both the 18-64 years and ≥65 years age groups. Interpretation: Routine sentinel network data allow comparisons of safety profiles of equally suitable seasonal influenza vaccines. The higher incidence of AEIs associated with QIVc suggest monitoring of several seasons would allow robust comparisons to be made.

Background Atrial fibrillation (AF) is one of the commonest arrhythmias observed in general practice. The thromboembolic complications of AF include transient ischemic attack, stroke, and pulmonary embolism. Early recognition of AF can lead to early intervention with managing the risks of these complications. Objective The primary aim of this study is to investigate if patients are managed in general practice according to current national guidelines. In addition, the study will evaluate the impact of direct oral anticoagulant use with respect to AF complications in a real-world dataset. The secondary aims of the study are to develop a dashboard that will allow monitoring the management of AF in general practice and evaluate the usability of the dashboard. Methods The study was conducted in 2 phases. The initial phase was a quantitative analysis of routinely collected primary care data from the Oxford Royal College of General Practitioners Research and Surveillance Center (RCGP RSC) sentinel network database. AF cases from 2009 to 2019 were identified. The study investigated the impact of the use of anticoagulants on complications of AF over this time period. We used this dataset to examine how AF was managed in primary care during the last decade. The second phase involved development of an online dashboard for monitoring management of AF in general practice. We conducted a usability evaluation for the dashboard to identify usability issues and performed enhancements to improve usability. Results We received funding for both phases in January 2019 and received approval from the RCGP RSC research committee in March 2019. We completed data extraction for phase 1 in May 2019 and completed analysis in December 2019. We completed building the AF dashboard in May 2019. We started recruiting participants for phase 1 in May 2019 and concluded data collection in July 2019. We completed data analysis for phase 2 in October 2019. The results are expected to be published in the second half of 2020. As of October 2020, the publications reporting the results are under review. Conclusions Results of this study will provide an insight into the current trends in management of AF using real-world data from the Oxford RCGP RSC database. We anticipate that the outcomes of this study will be used to guide the development and implementation of an audit-based intervention tool to assist practitioners in identifying and managing AF in primary care. International Registered Report Identifier (IRRID) RR1-10.2196/21259

Background Creating an ontology for COVID-19 surveillance should help ensure transparency and consistency. Ontologies formalize conceptualizations at either the domain or application level. Application ontologies cross domains and are specified through testable use cases. Our use case was an extension of the role of the Oxford Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) to monitor the current pandemic and become an in-pandemic research platform. Objective This study aimed to develop an application ontology for COVID-19 that can be deployed across the various use-case domains of the RCGP RSC research and surveillance activities. Methods We described our domain-specific use case. The actor was the RCGP RSC sentinel network, the system was the course of the COVID-19 pandemic, and the outcomes were the spread and effect of mitigation measures. We used our established 3-step method to develop the ontology, separating ontological concept development from code mapping and data extract validation. We developed a coding system–independent COVID-19 case identification algorithm. As there were no gold-standard pandemic surveillance ontologies, we conducted a rapid Delphi consensus exercise through the International Medical Informatics Association Primary Health Care Informatics working group and extended networks. Results Our use-case domains included primary care, public health, virology, clinical research, and clinical informatics. Our ontology supported (1) case identification, microbiological sampling, and health outcomes at an individual practice and at the national level; (2) feedback through a dashboard; (3) a national observatory; (4) regular updates for Public Health England; and (5) transformation of a sentinel network into a trial platform. We have identified a total of 19,115 people with a definite COVID-19 status, 5226 probable cases, and 74,293 people with possible COVID-19, within the RCGP RSC network (N=5,370,225). Conclusions The underpinning structure of our ontological approach has coped with multiple clinical coding challenges. At a time when there is uncertainty about international comparisons, clarity about the basis on which case definitions and outcomes are made from routine data is essential.

BACKGROUND The Oxford–Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) and Public Health England (PHE) are commencing their 54th season of collaboration at a time when SARS-CoV-2 infections are likely to be cocirculating with the usual winter infections. OBJECTIVE The aim of this study is to conduct surveillance of influenza and other monitored respiratory conditions and to report on vaccine uptake and effectiveness using nationally representative surveillance data extracted from primary care computerized medical records systems. We also aim to have general practices collect virology and serology specimens and to participate in trials and other interventional research. METHODS The RCGP RSC network comprises over 1700 general practices in England and Wales. We will extract pseudonymized data twice weekly and are migrating to a system of daily extracts. First, we will collect pseudonymized, routine, coded clinical data for the surveillance of monitored and unexpected conditions; data on vaccine exposure and adverse events of interest; and data on approved research study outcomes. Second, we will provide dashboards to give general practices feedback about levels of care and data quality, as compared to other network practices. We will focus on collecting data on influenza-like illness, upper and lower respiratory tract infections, and suspected COVID-19. Third, approximately 300 practices will participate in the 2020-2021 virology and serology surveillance; this will include responsive surveillance and long-term follow-up of previous SARS-CoV-2 infections. Fourth, member practices will be able to recruit volunteer patients to trials, including early interventions to improve COVID-19 outcomes and point-of-care testing. Lastly, the legal basis for our surveillance with PHE is Regulation 3 of the Health Service (Control of Patient Information) Regulations 2002; other studies require appropriate ethical approval. RESULTS The RCGP RSC network has tripled in size; there were previously 100 virology practices and 500 practices overall in the network and we now have 322 and 1724, respectively. The Oxford–RCGP Clinical Informatics Digital Hub (ORCHID) secure networks enable the daily analysis of the extended network; currently, 1076 practices are uploaded. We are implementing a central swab distribution system for patients self-swabbing at home in addition to in-practice sampling. We have converted all our primary care coding to Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) coding. Throughout spring and summer 2020, the network has continued to collect specimens in preparation for the winter or for any second wave of COVID-19 cases. We have collected 5404 swabs and detected 623 cases of COVID-19 through extended virological sampling, and 19,341 samples have been collected for serology. This shows our preparedness for the winter season. CONCLUSIONS The COVID-19 pandemic has been associated with a groundswell of general practices joining our network. It has also created a permissive environment in which we have developed the capacity and capability of the national primary care surveillance systems and our unique public health institute, the RCGP and University of Oxford collaboration.

BackgroundMolecular point-of-care testing (POCT) for influenza in primary care could influence clinical care and patient outcomes.AimTo assess the feasibility of incorporating influenza POCT into general practice in England.Design and settingA mixed-methods study conducted in six general practices that had not previously participated in respiratory virology sampling, which are part of the Royal College of General Practitioners Research and Surveillance Centre English sentinel surveillance network, from February 2019 to May 2019.MethodA sociotechnical perspective was adopted using the Public Health England POCT implementation toolkit and business process modelling notation to inform qualitative analysis. Quantitative data were collected about the number of samples taken, their representativeness, and the virology results obtained, comparing them with the rest of the sentinel system over the same weeks.ResultsA total of 312 POCTs were performed; 276 were used for quantitative analysis, of which 60 were positive for influenza and 216 were negative. The average swabbing rate was 0.4 per 1000 population and swab positivity was between 16.7% (n = 14/84) and 41.4% (n = 12/29). Given a positive influenza POCT result, the odds ratio of receiving an antiviral was 14.1 (95% confidence intervals [CI] = 2.9 to 70.0, PP = 0.01), compared with patients with a negative result. Qualitative analysis showed that it was feasible for practices to implement POCT, but there is considerable variation in the processes used.ConclusionTesting for influenza using POCT is feasible in primary care and may improve antimicrobial use. However, further evidence from randomised trials of influenza POCT in general practice is needed.

BACKGROUND Creating an ontology for COVID-19 surveillance should help ensure transparency and consistency. Ontologies formalize conceptualizations at either the domain or application level. Application ontologies cross domains and are specified through testable use cases. Our use case was an extension of the role of the Oxford Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) to monitor the current pandemic and become an in-pandemic research platform. OBJECTIVE This study aimed to develop an application ontology for COVID-19 that can be deployed across the various use-case domains of the RCGP RSC research and surveillance activities. METHODS We described our domain-specific use case. The actor was the RCGP RSC sentinel network, the system was the course of the COVID-19 pandemic, and the outcomes were the spread and effect of mitigation measures. We used our established 3-step method to develop the ontology, separating ontological concept development from code mapping and data extract validation. We developed a coding system–independent COVID-19 case identification algorithm. As there were no gold-standard pandemic surveillance ontologies, we conducted a rapid Delphi consensus exercise through the International Medical Informatics Association Primary Health Care Informatics working group and extended networks. RESULTS Our use-case domains included primary care, public health, virology, clinical research, and clinical informatics. Our ontology supported (1) case identification, microbiological sampling, and health outcomes at an individual practice and at the national level; (2) feedback through a dashboard; (3) a national observatory; (4) regular updates for Public Health England; and (5) transformation of a sentinel network into a trial platform. We have identified a total of 19,115 people with a definite COVID-19 status, 5226 probable cases, and 74,293 people with possible COVID-19, within the RCGP RSC network (N=5,370,225). CONCLUSIONS The underpinning structure of our ontological approach has coped with multiple clinical coding challenges. At a time when there is uncertainty about international comparisons, clarity about the basis on which case definitions and outcomes are made from routine data is essential.

BACKGROUND Atrial fibrillation (AF) is one of the commonest arrhythmias observed in general practice. The thromboembolic complications of AF include transient ischemic attack, stroke, and pulmonary embolism. Early recognition of AF can lead to early intervention with managing the risks of these complications. OBJECTIVE The primary aim of this study is to investigate if patients are managed in general practice according to current national guidelines. In addition, the study will evaluate the impact of direct oral anticoagulant use with respect to AF complications in a real-world dataset. The secondary aims of the study are to develop a dashboard that will allow monitoring the management of AF in general practice and evaluate the usability of the dashboard. METHODS The study was conducted in 2 phases. The initial phase was a quantitative analysis of routinely collected primary care data from the Oxford Royal College of General Practitioners Research and Surveillance Center (RCGP RSC) sentinel network database. AF cases from 2009 to 2019 were identified. The study investigated the impact of the use of anticoagulants on complications of AF over this time period. We used this dataset to examine how AF was managed in primary care during the last decade. The second phase involved development of an online dashboard for monitoring management of AF in general practice. We conducted a usability evaluation for the dashboard to identify usability issues and performed enhancements to improve usability. RESULTS We received funding for both phases in January 2019 and received approval from the RCGP RSC research committee in March 2019. We completed data extraction for phase 1 in May 2019 and completed analysis in December 2019. We completed building the AF dashboard in May 2019. We started recruiting participants for phase 1 in May 2019 and concluded data collection in July 2019. We completed data analysis for phase 2 in October 2019. The results are expected to be published in the second half of 2020. As of October 2020, the publications reporting the results are under review. CONCLUSIONS Results of this study will provide an insight into the current trends in management of AF using real-world data from the Oxford RCGP RSC database. We anticipate that the outcomes of this study will be used to guide the development and implementation of an audit-based intervention tool to assist practitioners in identifying and managing AF in primary care. INTERNATIONAL REGISTERED REPORT RR1-10.2196/21259

BACKGROUND Routinely recorded primary care data have been used for many years by sentinel networks for surveillance. More recently, real world data have been used for a wider range of research projects to support rapid, inexpensive clinical trials. Because the partial national lockdown in the United Kingdom due to the coronavirus disease (COVID-19) pandemic has resulted in decreasing community disease incidence, much larger numbers of general practices are needed to deliver effective COVID-19 surveillance and contribute to in-pandemic clinical trials. OBJECTIVE The aim of this protocol is to describe the rapid design and development of the Oxford Royal College of General Practitioners Clinical Informatics Digital Hub (ORCHID) and its first two platforms. The Surveillance Platform will provide extended primary care surveillance, while the Trials Platform is a streamlined clinical trials platform that will be integrated into routine primary care practice. METHODS We will apply the FAIR (Findable, Accessible, Interoperable, and Reusable) metadata principles to a new, integrated digital health hub that will extract routinely collected general practice electronic health data for use in clinical trials and provide enhanced communicable disease surveillance. The hub will be findable through membership in Health Data Research UK and European metadata repositories. Accessibility through an online application system will provide access to study-ready data sets or developed custom data sets. Interoperability will be facilitated by fixed linkage to other key sources such as Hospital Episodes Statistics and the Office of National Statistics using pseudonymized data. All semantic descriptors (ie, ontologies) and code used for analysis will be made available to accelerate analyses. We will also make data available using common data models, starting with the US Food and Drug Administration Sentinel and Observational Medical Outcomes Partnership approaches, to facilitate international studies. The Surveillance Platform will provide access to data for health protection and promotion work as authorized through agreements between Oxford, the Royal College of General Practitioners, and Public Health England. All studies using the Trials Platform will go through appropriate ethical and other regulatory approval processes. RESULTS The hub will be a bottom-up, professionally led network that will provide benefits for member practices, our health service, and the population served. Data will only be used for SQUIRE (surveillance, quality improvement, research, and education) purposes. We have already received positive responses from practices, and the number of practices in the network has doubled to over 1150 since February 2020. COVID-19 surveillance has resulted in tripling of the number of virology sites to 293 (target 300), which has aided the collection of the largest ever weekly total of surveillance swabs in the United Kingdom as well as over 3000 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) serology samples. Practices are recruiting to the PRINCIPLE (Platform Randomised trial of INterventions against COVID-19 In older PeopLE) trial, and these participants will be followed up through ORCHID. These initial outputs demonstrate the feasibility of ORCHID to provide an extended national digital health hub. CONCLUSIONS ORCHID will provide equitable and innovative use of big data through a professionally led national primary care network and the application of FAIR principles. The secure data hub will host routinely collected general practice data linked to other key health care repositories for clinical trials and support enhanced in situ surveillance without always requiring large volume data extracts. ORCHID will support rapid data extraction, analysis, and dissemination with the aim of improving future research and development in general practice to positively impact patient care. INTERNATIONAL REGISTERED REPORT DERR1-10.2196/19773

Background The Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) and Public Health England (PHE) have successfully worked together on the surveillance of influenza and other infectious diseases for over 50 years, including three previous pandemics. With the emergence of the international outbreak of the coronavirus infection (COVID-19), a UK national approach to containment has been established to test people suspected of exposure to COVID-19. At the same time and separately, the RCGP RSC’s surveillance has been extended to monitor the temporal and geographical distribution of COVID-19 infection in the community as well as assess the effectiveness of the containment strategy. Objectives The aims of this study are to surveil COVID-19 in both asymptomatic populations and ambulatory cases with respiratory infections, ascertain both the rate and pattern of COVID-19 spread, and assess the effectiveness of the containment policy. Methods The RCGP RSC, a network of over 500 general practices in England, extract pseudonymized data weekly. This extended surveillance comprises of five components: (1) Recording in medical records of anyone suspected to have or who has been exposed to COVID-19. Computerized medical records suppliers have within a week of request created new codes to support this. (2) Extension of current virological surveillance and testing people with influenza-like illness or lower respiratory tract infections (LRTI)—with the caveat that people suspected to have or who have been exposed to COVID-19 should be referred to the national containment pathway and not seen in primary care. (3) Serology sample collection across all age groups. This will be an extra blood sample taken from people who are attending their general practice for a scheduled blood test. The 100 general practices currently undertaking annual influenza virology surveillance will be involved in the extended virological and serological surveillance. (4) Collecting convalescent serum samples. (5) Data curation. We have the opportunity to escalate the data extraction to twice weekly if needed. Swabs and sera will be analyzed in PHE reference laboratories. Results General practice clinical system providers have introduced an emergency new set of clinical codes to support COVID-19 surveillance. Additionally, practices participating in current virology surveillance are now taking samples for COVID-19 surveillance from low-risk patients presenting with LRTIs. Within the first 2 weeks of setup of this surveillance, we have identified 3 cases: 1 through the new coding system, the other 2 through the extended virology sampling. Conclusions We have rapidly converted the established national RCGP RSC influenza surveillance system into one that can test the effectiveness of the COVID-19 containment policy. The extended surveillance has already seen the use of new codes with 3 cases reported. Rapid sharing of this protocol should enable scientific critique and shared learning. International Registered Report Identifier (IRRID) DERR1-10.2196/18606

BACKGROUND The Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) and Public Health England (PHE) have successfully worked together on the surveillance of influenza and other infectious diseases for over 50 years, including three previous pandemics. With the emergence of the international outbreak of the coronavirus infection (COVID-19), a UK national approach to containment has been established to test people suspected of exposure to COVID-19. At the same time and separately, the RCGP RSC’s surveillance has been extended to monitor the temporal and geographical distribution of COVID-19 infection in the community as well as assess the effectiveness of the containment strategy. OBJECTIVE The aim of this study is the surveillance of COVID-19 in both asymptomatic populations and ambulatory cases with respiratory infections to ascertain both the rate and pattern of COVID-19 spread and to assess the effectiveness of the containment policy. METHODS The RCGP RSC, a network of over 500 general practices in England, extract pseudonymized data weekly. This extended surveillance comprises of five components: (1) Recording in medical records of anyone suspected to have or who has been exposed to COVID-19. Computerized medical records suppliers have within a week of request created new codes to support this. (2) Extension of current virological surveillance and testing people with influenza-like illness or lower respiratory tract infections (LRTI)—with the caveat that people suspected to have or who have been exposed to COVID-19 should be referred to the national containment pathway and not seen in primary care. (3) Serology sample collection across all age groups. This will be an extra blood sample taken from people who are attending their general practice for a scheduled blood test. The 100 general practices currently undertaking annual influenza virology surveillance will be involved in the extended virological and serological surveillance. (4) Collecting convalescent serum samples. (5) Data curation. We have the opportunity to escalate the data extraction to twice weekly if needed. Swabs and sera will be analyzed in PHE reference laboratories. RESULTS General practice clinical system providers have introduced an emergency new set of clinical codes to support COVID-19 surveillance. Additionally, practices participating in current virology surveillance are now taking samples for COVID-19 surveillance from low-risk patients presenting with LRTIs. Within the first 2 weeks of setup of this surveillance, we have identified 3 cases: 1 through the new coding system, the other 2 through the extended virology sampling. CONCLUSIONS We have rapidly converted the established national RCGP RSC influenza surveillance system into one that can test the effectiveness of the COVID-19 containment policy. The extended surveillance has already seen the use of new codes with 3 cases reported. Rapid sharing of this protocol should enable scientific critique and shared learning. INTERNATIONAL REGISTERED REPORT DERR1-10.2196/18606

Background: Mandatory social and physical distancing measures (SPDM) were introduced in the UK on the 23rd March 2020. A multi-tiered surveillance system based on influenza surveillance, was adopted from the early stages of the COVID-19 Epidemic to monitor different stages of disease. We describe how the impact SPDM was detected through each surveillance system and how these systems may be applied to detect increases in COVID-19 activity as SPDM are eased. Methods: Data from national population surveys, web-based indicators, syndromic surveillance, sentinel swabbing, respiratory outbreaks, secondary care admissions, and mortality indicators from the start of the epidemic to Week 20 2020 were used to identify timing of peaks in the indicator relative to the introduction of SPDM. This was compared to median time from symptom onset to different stages of illness or interactions with healthcare services. Results: The impact of SPDM was detected within 1 week through population symptom surveys, web search indicators and through GP sentinel swabbing reported by onset date. There were detectable impacts on syndromic surveillance indicators for difficulty breathing, influenza-like illness and COVID-19 coding at 2, 7 and 12 days respectively. This was followed by hospitalisations and critical care admissions (both 12 days), laboratory positivity (14 days), deaths (17 days) and care home outbreaks (4 weeks). Interpretation: There was a clear impact of SPDM on COVID-19 activity which was detectable within 1 week through community indicators highlighting their importance in early detection of changes in activity. Community swabbing surveillance will be increasingly important as a specific indicator when circulation of seasonal respiratory viruses increases. Funding Statement: There was no specific funding for this report. Declaration of Interests: None declared. Ethics Approval Statement: The surveillance collections included here are approved as Health Protection, under Regulation 3 of The Health Service (Control of Patient Information) Regulations 2002.

Background: There was excess mortality from the first wave of coronavirus 2019 infection (COVID-19), which mainly affected older people. To mitigate risk, the UK government recommended ‘shielding’ of vulnerable people through self-isolation for 12 weeks. We investigated the impact of primary care-reinforced shielding advice on all-cause mortality. Methods: We conducted a retrospective cohort study using a nationally representative English primary care database. We compare people aged >=40years who were recorded as being advised to shield using a fixed ratio of 1:1, matching (a mixture of exact and propensity score matching) to people with the same diagnoses not advised to shield (n=77,360 per group). Time-to-death was compared using Cox regression, reporting the hazard ratio (HR) of mortality between groups. A sensitivity analysis compared exact matched cohorts (n=24,752 shielded, n=61,566 exact matches). Findings: Over the follow-up period, we found a time-varying HR of mortality between groups. In the first 21 days, the mortality risk in people shielding was half those not (HR=0.50, 95%CI:0.41-0.59. p

BACKGROUND Monitoring the effectiveness of the influenza vaccination programme within the UK is necessary in order to assess its clinical impact. Data are collected from general practice sentinel network computerised medical record (CMR) systems on patients from whom virology specimens have been taken for influenza. The data collected includes demographics, comorbidities, vaccine exposure and if patients have had a virology specimen taken. Unfortunately not all virology specimens collected can be used in the vaccine effectiveness (VE) studies conducted. OBJECTIVE To describe the proportion, reasons and any trends in virology specimen data collected but not used in influenza VE analyses, with the goal of defining strategies to reduce collection of specimens ineligible for use in VE studies. METHODS We examined UK influenza VE studies from the past 10 years and identified incidences where data were labelled unusable. We categorised reasons for not using data as: (1) Vaccination history: Missing or Uncertain categories (including patient not registered with the practice at the start of the season); (2) Swab timing: Not recorded; More than 7 days (historically over 29 days) after symptom onset or within 14 days of vaccination; (3) Laboratory: Not sufficient data for processing (e.g. no age), CT values; (4) Flu or vaccination type of no interest (including pandemic years). The proportion, reasons and trends for data loss were identified through descriptive statistics and graphical representations. We included an analysis of where other data had been available at the point of analysis but not used. RESULTS Over 30% (13292/41337) of virology specimen data was not used across all seasons. Data loss gradually began to decrease from 2014/15 onwards. Data loss were highest for flu or vaccination type of no interest and swab timing. Retrospective and prospective actions were identified to reduce data loss in future. Around 60% of samples could have been included if identifiable data were better shared between records. CONCLUSIONS The reasons for excluding samples and missing data varied, particularly prior to 2014; consistent categorisation was in place from 2014 onwards. Leaving aside the different issues around pandemic years, many of the virology swabs not included were due to suboptimal case selection by practices, but over half (58%) could have been included if identifiable data were better shared between data sources. CLINICALTRIAL N/A

BackgroundRapidly undertaken age-stratified serology studies can produce valuable data about a new emerging infection including background population immunity and seroincidence during an influenza pandemic. Traditionally seroepidemiology studies have used surplus laboratory sera with little or no clinical information or have been expensive detailed population based studies. We propose collecting population based sera from the Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC), a sentinel network with extensive clinical data.AimTo pilot a mechanism to undertake population based surveys that collect serological specimens and associated patient data to measure seropositivity and seroincidence due to seasonal influenza, and create a population based serology bank.Methods and analysisSetting and Participants: We will recruit 6 RCGP RSC practices already taking nasopharyngeal virology swabs. Patients who attend a scheduled blood test will be consented to donate additional blood samples. Approximately 100–150 blood samples will be collected from each of the following age bands – 18– 29, 30– 39, 40– 49, 50– 59, 60– 69 and 70+ years.MethodsWe will send the samples to the Public Health England (PHE) Seroepidemiology Unit for processing and storage. These samples will be tested for influenza antibodies, using haemagglutination inhibition assays. Serology results will be pseudonymised, sent to the RCGP RSC and combined using existing processes at the RCGP RSC secure hub. The influenza seroprevalence results from the RCGP cohort will be compared against those from the annual PHE influenza residual serosurvey.Ethics and disseminationEthical approval was granted by the Proportionate Review Sub- Committee of the London – Camden & Kings Cross on 6 February 2018. This study received approval from Health Research Authority on 7 February 2018. On completion the results will be made available via peer-reviewed journals.

About the Authors: Simon de Lusignan Roles Conceptualization, Funding acquisition, Methodology, Project administration, Resources, Supervision, Writing – review & editing * E-mail: simon delusignan@phc ox ac uk Affiliation: Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom ORCID logo https://orcid org/0000-0002-8553-2641 Uy Hoang Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Writing – original draft, Writing – review & editing Affiliation: Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom Harshana Liyanage Roles Data curation, Investigation, Project administration, Writing – review & editing Affiliation: Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom Manasa Tripathy Roles Project administration, Writing – review & editing Affiliation: Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom Julian Sherlock Roles Data curation, Investigation, Software, Validation Affiliation: Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom Mark Joy Roles Methodology, Writing – review & editing Affiliation: Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom Filipa Ferreira Roles Project administration, Supervision, Writing – review & editing Affiliation: Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom ORCID logo https://orcid org/0000-0002-7717-8486 Javier Diez-Domingo Roles Resources, Writing – review & editing Affiliation: Vaccine Research Department, FISABIO-Public Health, Valencia, Spain Tristan Clark Roles Conceptualization, Project administration, Writing – review & editing Affiliation: Academic Unit of Clinical and Experimental Sciences, University of Southampton, Southampton, United Kingdom Introduction Influenza is a major cause of clinical and public health burden [1] The vaccine requires reformulating annually to match with the characteristics of the circulating influenza viruses which undergo frequent genetic and antigenic changes [6] [ ]influenza vaccine effectiveness (IVE) is assessed annually and observed IVE varies year-to-year [5, 7] Study practices provided POCT machines performed more tests than other virology sampling practices when their practice population size and respiratory virus infection rates were taken into account The following set of covariates were collected from the routine data extracted from the electronic health record and used for confounder adjustment of IVE with backward stepwise elimination to find the best model fit [22] * Age * Sex * Ethnicity, reported in five categories, white, Asian, black, other, or mixed, and maximised using an ontology [23] * Socio-economic status, measured using the index of multiple deprivation (IMD) [24]