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1.
SSRN; 2022.
Preprint in English | SSRN | ID: ppcovidwho-334531

ABSTRACT

Background: Two doses of COVID-19 vaccine offer greater protection than one dose. There are known disparities in COVID-19 outcomes and vaccine uptake. However, it is not known whether non-uptake of the second dose in people who have already received their first dose is predicted by differences in demographic characteristics and disease risk. Methods: We conducted a retrospective cohort study using computerised medical record data from the nationally representative Oxford-Royal College of General Practitioners primary care sentinel cohort (N=7,952,861). Among adults who received at least one dose of Oxford-AstraZeneca ChAdOx1, mRNA Pfizer-BioNTech BNT162b2 or Moderna mRNA-1273 vaccines, we used univariable and multivariable logistic regressions to estimate the odds ratios (ORs) and adjusted ORs (aORs), and their 95% confidence intervals (95% CI), of second dose uptake. Findings: In adults vaccinated with one dose (n=2,802,314), younger age, ethnic minorities, rurality (aOR=0.93 (95% CI 0.91-0.94)), East of England and the South West, current (0.59 (0.58-0.60)) and ex-smokers (0.93 (0.91-0.94)), severe mental illness (0.58 (0.56-0.60)) among other comorbidities, COVID-19 (0.57 (0.55-0.58)) or adverse events after their first dose, were associated with lower second dose uptake. Male sex (1.02 (1.00-1.03)), increasing socioeconomic status, asthma (1.04 (1.02-1.07)), and first dose mRNA vaccine (1.28 (1.27-1.30)) were associated with higher likelihood of second dose uptake. Interpretation: Several demographic and risk groups at higher risk of adverse COVID-19 outcomes are less likely to receive second COVID-19 vaccination. Initiatives to increase vaccine uptake targeting people in sociodemographic groups and with comorbidities where interventions might have the greatest impact are needed.

2.
J Infect ; 2022 Jan 03.
Article in English | MEDLINE | ID: covidwho-1788130

ABSTRACT

Background COVID-19 vaccines approved in the UK are highly effective in general population cohorts, however, data on effectiveness amongst individuals with clinical conditions that place them at increased risk of severe disease are limited. Methods We used GP electronic health record data, sentinel virology swabbing and antibody testing within a cohort of 712 general practices across England to estimate vaccine antibody response and vaccine effectiveness against medically attended COVID-19 amongst individuals in clinical risk groups using cohort and test-negative case control designs. Findings There was no reduction in S-antibody positivity in most clinical risk groups, however reduced S-antibody positivity and response was significant in the immunosuppressed group. Reduced vaccine effectiveness against clinical disease was also noted in the immunosuppressed group; after a second dose, effectiveness was moderate (Pfizer: 59.6%, 95%CI 18.0-80.1%; AstraZeneca 60.0%, 95%CI -63.6-90.2%). Interpretation In most clinical risk groups, immune response to primary vaccination was maintained and high levels of vaccine effectiveness were seen. Reduced antibody response and vaccine effectiveness were seen after 1 dose of vaccine amongst a broad immunosuppressed group, and second dose vaccine effectiveness was moderate. These findings support maximising coverage in immunosuppressed individuals and the policy of prioritisation of this group for third doses.

3.
J Infect ; 2022 Apr 08.
Article in English | MEDLINE | ID: covidwho-1778314

ABSTRACT

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.

4.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-324925

ABSTRACT

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<0.0001). Over the remaining nine weeks, mortality risk was 54% higher in the shielded group (HR=1.54, 95%CI:1.41-1.70, p<0.0001). Beyond the shielding period, mortality risk was over two-and-a-half times higher in the shielded group (HR=2.61, 95%CI:2.38-2.87, p<0.0001).Interpretation: General practitioner-reinforced advice to shield halved the risk of mortality for 21 days compared to those who were not. Mortality risk became higher across the remainder of the shielding period, rising to two-and-a-half times greater post-shielding. Shielding may be beneficial in the next wave of COVID-19.Funding Statement: NIHR School of Primary Care, Public Health EnglandDeclaration of Interests: SdeL is the director of RCGP RSC. He has unrelated projects funded by GSK, Seqirus and has been a member of Global Advisory Boards for Seqirus and Sanofi. FDRH reports personal fees from Novartis and Boehringer Ingelheim and grants from Pfizer. All other authors declare no competing interests.Ethics Approval Statement: The RCGP RSC’s work concerning SARS-CoV-2 has been approved by Public Health England’s Caldicott Guardian Committee as fitting under Regulation 3 of the Health Service Control Patient Information Regulations 2002. The study was approved by RCGP.

5.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-293893

ABSTRACT

Background: There are few epidemiological studies of community cases in the current coronavirus-2019 (COVID-19) pandemic. We report on the first 500 COVID-19 cases identified through United Kingdom primary care surveillance and describe risk factors for testing COVID-19 positive. <br><br>Methods: The Oxford-Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC), is a nationally representative primary care sentinel network sharing pseudonymised data, including virological test data for COVID-19. We used multivariable logistic regression models with multiple imputation to identify risk factors for positive COVID-19 tests within this surveillance programme. <br><br>Findings: We identified 3,802 COVID-19 results between 28/01/20 and 04/04/2020, 587 were positive. Greater odds of testing COVID-19 positive included: working-age people (40-64years) and older age, (≥75 years) versus 0-17 year olds (adjusted odds ratio [aOR] 5.26, 95%CI:3.26-8.49 and 5.17,95%CI:2.99-8.92, respectively);male gender (aOR 1.56, 95%CI:1.28-1.90);black and mixed ethnicity compared with white (aOR 4.55, 95%CI:2.55-8.10 and 1.84 95%CO:1.1-3.14, respectively));urban compared with rural areas (aOR 4.58, 95%CI:3.57-5.88);people with chronic kidney disease (CKD) (aOR 1.88, 95%CI:1.29-2.75) and increasing body mass index (aOR 1.02, 95%CI:1.00-1.03). People in the least deprived deprivation quintile had lower odds of a positive test (aOR 0.49 95%CI:0.36-0.65) as did current smokers (aOR 0.53, 95%CI:0.38-0.74). <br><br>Interpretation: A positive COVID-19 test result in primary care was associated with similar risk factors for severe outcomes seen in hospital settings, with the exception of smoking. We provide early evidence of potential sociodemographic factors associated with a positive test, including ethnicity, deprivation, population density, and CKD. <br><br>Funding Statement: Public Health England provides the core funding for RCGP RSC, no specific funding was provided for this analysis.<br><br>Declaration of Interests: The authors have no competing interests. SdeL is the Director of the Oxford RCGP RSC, RB, JS, FF, EK and GH are part funded by PHE;and CO and AC by a Wellcome Biomedical resources grant (212763/Z/18/Z). JD is funded by Wellcome Trust (216421/Z/19/Z).<br><br>Ethics Approval Statement: This study was approved by the RCGP RSC study approval committee and was classified as a study of “usual practice”. Therefore, no further ethical approval was required.

6.
J Infect ; 83(2): 228-236, 2021 08.
Article in English | MEDLINE | ID: covidwho-1230619

ABSTRACT

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 < 0.0001). Over the remaining nine weeks, mortality risk was 54% higher in the shielded group (HR=1.54, 95%CI:1.41-1.70, p < 0.0001). Beyond the shielding period, mortality risk was over two-and-a-half times higher in the shielded group (HR=2.61, 95%CI:2.38-2.87, p < 0.0001). CONCLUSIONS: Shielding halved the risk of mortality for 21 days. Mortality risk became higher across the remainder of the shielding period, rising to two-and-a-half times greater post-shielding. Shielding may be beneficial in the next wave of COVID-19.


Subject(s)
COVID-19 , Cohort Studies , Humans , Primary Health Care , Retrospective Studies , SARS-CoV-2
7.
Euro Surveill ; 26(11)2021 03.
Article in English | MEDLINE | ID: covidwho-1181332

ABSTRACT

BackgroundA 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.AimTo describe the impact of SPDM on COVID-19 activity as detected through the different surveillance systems.MethodsData 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.ResultsThe 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).ConclusionThe 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.


Subject(s)
COVID-19/prevention & control , Epidemiological Monitoring , Physical Distancing , COVID-19/epidemiology , Humans , United Kingdom/epidemiology
8.
JMIR Public Health Surveill ; 7(2): e24341, 2021 02 19.
Article in English | MEDLINE | ID: covidwho-1090464

ABSTRACT

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.


Subject(s)
Clinical Protocols , Influenza, Human/prevention & control , Respiratory Tract Infections/prevention & control , Vaccines/therapeutic use , COVID-19/drug therapy , COVID-19/prevention & control , Female , Humans , Influenza, Human/drug therapy , Male , Middle Aged , Population Surveillance/methods , Public Health , Respiratory Tract Infections/drug therapy , Respiratory Tract Infections/virology , United Kingdom
9.
Diagn Progn Res ; 5(1): 4, 2021 Feb 08.
Article in English | MEDLINE | ID: covidwho-1069608

ABSTRACT

BACKGROUND: The aim of RApid community Point-of-care Testing fOR COVID-19 (RAPTOR-C19) is to assess the diagnostic accuracy of multiple current and emerging point-of-care tests (POCTs) for active and past SARS-CoV2 infection in the community setting. RAPTOR-C19 will provide the community testbed to the COVID-19 National DiagnOstic Research and Evaluation Platform (CONDOR). METHODS: RAPTOR-C19 incorporates a series of prospective observational parallel diagnostic accuracy studies of SARS-CoV2 POCTs against laboratory and composite reference standards in patients with suspected current or past SARS-CoV2 infection attending community settings. Adults and children with suspected current SARS-CoV2 infection who are having an oropharyngeal/nasopharyngeal (OP/NP) swab for laboratory SARS-CoV2 reverse transcriptase Digital/Real-Time Polymerase Chain Reaction (d/rRT-PCR) as part of clinical care or community-based testing will be invited to participate. Adults (≥ 16 years) with suspected past symptomatic infection will also be recruited. Asymptomatic individuals will not be eligible. At the baseline visit, all participants will be asked to submit samples for at least one candidate point-of-care test (POCT) being evaluated (index test/s) as well as an OP/NP swab for laboratory SARS-CoV2 RT-PCR performed by Public Health England (PHE) (reference standard for current infection). Adults will also be asked for a blood sample for laboratory SARS-CoV-2 antibody testing by PHE (reference standard for past infection), where feasible adults will be invited to attend a second visit at 28 days for repeat antibody testing. Additional study data (e.g. demographics, symptoms, observations, household contacts) will be captured electronically. Sensitivity, specificity, positive, and negative predictive values for each POCT will be calculated with exact 95% confidence intervals when compared to the reference standard. POCTs will also be compared to composite reference standards constructed using paired antibody test results, patient reported outcomes, linked electronic health records for outcomes related to COVID-19 such as hospitalisation or death, and other test results. DISCUSSION: High-performing POCTs for community use could be transformational. Real-time results could lead to personal and public health impacts such as reducing onward household transmission of SARS-CoV2 infection, improving surveillance of health and social care staff, contributing to accurate prevalence estimates, and understanding of SARS-CoV2 transmission dynamics in the population. In contrast, poorly performing POCTs could have negative effects, so it is necessary to undertake community-based diagnostic accuracy evaluations before rolling these out. TRIAL REGISTRATION: ISRCTN, ISRCTN14226970.

10.
Br J Cancer ; 124(7): 1231-1236, 2021 03.
Article in English | MEDLINE | ID: covidwho-1065853

ABSTRACT

BACKGROUND: The faecal immunochemical test (FIT) was introduced to triage patients with low-risk symptoms of possible colorectal cancer in English primary care in 2017, underpinned by little primary care evidence. METHODS: All healthcare providers in the South West of England (population 4 million) participated in this evaluation. 3890 patients aged ≥50 years presenting in primary care with low-risk symptoms of colorectal cancer had a FIT from 01/06/2018 to 31/12/2018. A threshold of 10 µg Hb/g faeces defined a positive test. RESULTS: Six hundred and eighteen (15.9%) patients tested positive; 458 (74.1%) had an urgent referral to specialist lower gastrointestinal (GI) services within three months. Forty-three were diagnosed with colorectal cancer within 12 months. 3272 tested negative; 324 (9.9%) had an urgent referral within three months. Eight were diagnosed with colorectal cancer within 12 months. Positive predictive value was 7.0% (95% CI 5.1-9.3%). Negative predictive value was 99.8% (CI 99.5-99.9%). Sensitivity was 84.3% (CI 71.4-93.0%), specificity 85.0% (CI 83.8-86.1%). The area under the ROC curve was 0.92 (CI 0.86-0.96). A threshold of 37 µg Hb/g faeces would identify patients with an individual 3% risk of cancer. CONCLUSIONS: FIT performs exceptionally well to triage patients with low-risk symptoms of colorectal cancer in primary care; a higher threshold may be appropriate in the wake of the COVID-19 crisis.


Subject(s)
Colorectal Neoplasms/diagnosis , Feces/chemistry , Occult Blood , Primary Health Care , Anemia, Iron-Deficiency/complications , Colorectal Neoplasms/complications , Colorectal Neoplasms/physiopathology , England , Female , Hemoglobins/analysis , Humans , Male , Middle Aged , Risk Factors , Sensitivity and Specificity , Weight Loss
12.
JMIR Public Health Surveill ; 6(4): e21434, 2020 11 17.
Article in English | MEDLINE | ID: covidwho-976102

ABSTRACT

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.


Subject(s)
Biological Ontologies , COVID-19/epidemiology , Primary Health Care/methods , Sentinel Surveillance , Humans , Pandemics
13.
Br J Gen Pract ; 70(701): e890-e898, 2020 12.
Article in English | MEDLINE | ID: covidwho-881363

ABSTRACT

BACKGROUND: The SARS-CoV-2 pandemic has passed its first peak in Europe. AIM: To describe the mortality in England and its association with SARS-CoV-2 status and other demographic and risk factors. DESIGN AND SETTING: Cross-sectional analyses of people with known SARS-CoV-2 status in the Oxford RCGP Research and Surveillance Centre (RSC) sentinel network. METHOD: Pseudonymised, coded clinical data were uploaded from volunteer general practice members of this nationally representative network (n = 4 413 734). All-cause mortality was compared with national rates for 2019, using a relative survival model, reporting relative hazard ratios (RHR), and 95% confidence intervals (CI). A multivariable adjusted odds ratios (OR) analysis was conducted for those with known SARS-CoV-2 status (n = 56 628, 1.3%) including multiple imputation and inverse probability analysis, and a complete cases sensitivity analysis. RESULTS: Mortality peaked in week 16. People living in households of ≥9 had a fivefold increase in relative mortality (RHR = 5.1, 95% CI = 4.87 to 5.31, P<0.0001). The ORs of mortality were 8.9 (95% CI = 6.7 to 11.8, P<0.0001) and 9.7 (95% CI = 7.1 to 13.2, P<0.0001) for virologically and clinically diagnosed cases respectively, using people with negative tests as reference. The adjusted mortality for the virologically confirmed group was 18.1% (95% CI = 17.6 to 18.7). Male sex, population density, black ethnicity (compared to white), and people with long-term conditions, including learning disability (OR = 1.96, 95% CI = 1.22 to 3.18, P = 0.0056) had higher odds of mortality. CONCLUSION: The first SARS-CoV-2 peak in England has been associated with excess mortality. Planning for subsequent peaks needs to better manage risk in males, those of black ethnicity, older people, people with learning disabilities, and people who live in multi-occupancy dwellings.


Subject(s)
COVID-19 , Noncommunicable Diseases/epidemiology , SARS-CoV-2/isolation & purification , Age Factors , COVID-19/diagnosis , COVID-19/epidemiology , Electronic Health Records/statistics & numerical data , England/epidemiology , Family Characteristics , Female , Humans , Male , Middle Aged , Mortality , Risk Assessment/methods , Risk Factors , Sentinel Surveillance , Sex Factors
15.
JMIR Public Health Surveill ; 6(3): e19773, 2020 07 02.
Article in English | MEDLINE | ID: covidwho-791866

ABSTRACT

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 IDENTIFIER (IRRID): DERR1-10.2196/19773.


Subject(s)
Clinical Trials as Topic , Coronavirus Infections/epidemiology , General Practice/organization & administration , Medical Records Systems, Computerized , Pneumonia, Viral/epidemiology , Public Health Surveillance , COVID-19 , Humans , Pandemics , Primary Health Care/organization & administration , Societies, Medical , United Kingdom/epidemiology
16.
J Infect ; 81(5): 785-792, 2020 11.
Article in English | MEDLINE | ID: covidwho-728713

ABSTRACT

OBJECTIVES: Few studies report contributors to the excess mortality in England during the first wave of coronavirus disease 2019 (COVID-19) infection. We report the absolute excess risk (AER) of mortality and excess mortality rate (EMR) from a nationally representative COVID-19 sentinel surveillance network including known COVID-19 risk factors in people aged 45 years and above. METHODS: Pseudonymised, coded clinical data were uploaded from contributing primary care providers (N = 1,970,314, ≥45years). We calculated the AER in mortality by comparing mortality for weeks 2 to 20 this year with mortality data from the Office for National Statistics (ONS) from 2018 for the same weeks. We conducted univariate and multivariate analysis including preselected variables. We report AER and EMR, with 95% confidence intervals (95% CI). RESULTS: The AER of mortality was 197.8/10,000 person years (95%CI:194.30-201.40). The EMR for male gender, compared with female, was 1.4 (95%CI:1.35-1.44, p<0.00); for our oldest age band (≥75 years) 10.09 (95%CI:9.46-10.75, p<0.00) compared to 45-64 year olds; Black ethnicity's EMR was 1.17 (95%CI: 1.03-1.33, p<0.02), reference white; and for dwellings with ≥9 occupants 8.01 (95%CI: 9.46-10.75, p<0.00). Presence of all included comorbidities significantly increased EMR. Ranked from lowest to highest these were: hypertension, chronic kidney disease, chronic respiratory and heart disease, and cancer or immunocompromised. CONCLUSIONS: The absolute excess mortality was approximately 2 deaths per 100 person years in the first wave of COVID-19. More personalised shielding advice for any second wave should include ethnicity, comorbidity and household size as predictors of risk.


Subject(s)
Betacoronavirus , Coronavirus Infections/epidemiology , Coronavirus Infections/mortality , Pneumonia, Viral/epidemiology , Pneumonia, Viral/mortality , Age Factors , Aged , COVID-19 , Comorbidity , Coronavirus Infections/ethnology , Coronavirus Infections/virology , Cross-Sectional Studies , England/epidemiology , Family Characteristics , Female , Humans , Male , Middle Aged , Pandemics , Pneumonia, Viral/ethnology , Pneumonia, Viral/virology , Risk Factors , SARS-CoV-2 , Sentinel Surveillance , Sex Factors
17.
Lancet Infect Dis ; 20(9): 1034-1042, 2020 09.
Article in English | MEDLINE | ID: covidwho-276807

ABSTRACT

BACKGROUND: There are few primary care studies of the COVID-19 pandemic. We aimed to identify demographic and clinical risk factors for testing positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) within the Oxford Royal College of General Practitioners (RCGP) Research and Surveillance Centre primary care network. METHODS: We analysed routinely collected, pseudonymised data for patients in the RCGP Research and Surveillance Centre primary care sentinel network who were tested for SARS-CoV-2 between Jan 28 and April 4, 2020. We used multivariable logistic regression models with multiple imputation to identify risk factors for positive SARS-CoV-2 tests within this surveillance network. FINDINGS: We identified 3802 SARS-CoV-2 test results, of which 587 were positive. In multivariable analysis, male sex was independently associated with testing positive for SARS-CoV-2 (296 [18·4%] of 1612 men vs 291 [13·3%] of 2190 women; adjusted odds ratio [OR] 1·55, 95% CI 1·27-1·89). Adults were at increased risk of testing positive for SARS-CoV-2 compared with children, and people aged 40-64 years were at greatest risk in the multivariable model (243 [18·5%] of 1316 adults aged 40-64 years vs 23 [4·6%] of 499 children; adjusted OR 5·36, 95% CI 3·28-8·76). Compared with white people, the adjusted odds of a positive test were greater in black people (388 [15·5%] of 2497 white people vs 36 [62·1%] of 58 black people; adjusted OR 4·75, 95% CI 2·65-8·51). People living in urban areas versus rural areas (476 [26·2%] of 1816 in urban areas vs 111 [5·6%] of 1986 in rural areas; adjusted OR 4·59, 95% CI 3·57-5·90) and in more deprived areas (197 [29·5%] of 668 in most deprived vs 143 [7·7%] of 1855 in least deprived; adjusted OR 2·03, 95% CI 1·51-2·71) were more likely to test positive. People with chronic kidney disease were more likely to test positive in the adjusted analysis (68 [32·9%] of 207 with chronic kidney disease vs 519 [14·4%] of 3595 without; adjusted OR 1·91, 95% CI 1·31-2·78), but there was no significant association with other chronic conditions in that analysis. We found increased odds of a positive test among people who are obese (142 [20·9%] of 680 people with obesity vs 171 [13·2%] of 1296 normal-weight people; adjusted OR 1·41, 95% CI 1·04-1·91). Notably, active smoking was linked with decreased odds of a positive test result (47 [11·4%] of 413 active smokers vs 201 [17·9%] of 1125 non-smokers; adjusted OR 0·49, 95% CI 0·34-0·71). INTERPRETATION: A positive SARS-CoV-2 test result in this primary care cohort was associated with similar risk factors as observed for severe outcomes of COVID-19 in hospital settings, except for smoking. We provide evidence of potential sociodemographic factors associated with a positive test, including deprivation, population density, ethnicity, and chronic kidney disease. FUNDING: Wellcome Trust.


Subject(s)
Betacoronavirus , Coronavirus Infections/epidemiology , Pneumonia, Viral/epidemiology , Adolescent , Adult , Age Factors , Aged , Betacoronavirus/genetics , Betacoronavirus/isolation & purification , COVID-19 , Child , Child, Preschool , Coronavirus Infections/complications , Coronavirus Infections/ethnology , Coronavirus Infections/etiology , Cross-Sectional Studies , England/epidemiology , Female , Humans , Infant , Male , Middle Aged , Multivariate Analysis , Obesity/complications , Pandemics , Pneumonia, Viral/complications , Pneumonia, Viral/ethnology , Pneumonia, Viral/etiology , Poverty Areas , Real-Time Polymerase Chain Reaction , Renal Insufficiency, Chronic/complications , Risk Factors , Rural Population , SARS-CoV-2 , Sex Factors , Smoking , Urban Population , Young Adult
18.
JMIR Public Health Surveill ; 6(2): e18606, 2020 04 02.
Article in English | MEDLINE | ID: covidwho-31012

ABSTRACT

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.


Subject(s)
Coronavirus Infections/epidemiology , Coronavirus , Disease Notification/methods , Medical Records Systems, Computerized , Pandemics/prevention & control , Pneumonia, Viral/epidemiology , Public Health Surveillance/methods , Betacoronavirus , COVID-19 , Disease Outbreaks , England/epidemiology , Female , Humans , Male , Public Health , SARS-CoV-2 , Sentinel Surveillance
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