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Oliveira JF, Vasconcelos AO, Alencar AL, Cunha MCSL, Marcilio I, Barral-Netto M, P Ramos PI. Balancing Human Mobility and Health Care Coverage in Sentinel Surveillance of Brazilian Indigenous Areas: Mathematical Optimization Approach. JMIR Public Health Surveill 2025; 11:e69048. [PMID: 40168644 PMCID: PMC12034576 DOI: 10.2196/69048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2024] [Revised: 02/18/2025] [Accepted: 02/19/2025] [Indexed: 04/03/2025] Open
Abstract
Background Optimizing sentinel surveillance site allocation for early pathogen detection remains a challenge, particularly in ensuring coverage of vulnerable and underserved populations. Objective This study evaluates the current respiratory pathogen surveillance network in Brazil and proposes an optimized sentinel site distribution that balances Indigenous population coverage and national human mobility patterns. Methods We compiled Indigenous Special Health District (Portuguese: Distrito Sanitário Especial Indígena [DSEI]) locations from the Brazilian Ministry of Health and estimated national mobility routes by using the Ford-Fulkerson algorithm, incorporating air, road, and water transportation data. To optimize sentinel site selection, we implemented a linear optimization algorithm that maximizes (1) Indigenous region representation and (2) human mobility coverage. We validated our approach by comparing results with Brazil's current influenza sentinel network and analyzing the health attraction index from the Brazilian Institute of Geography and Statistics to assess the feasibility and potential benefits of our optimized surveillance network. Results The current Brazilian network includes 199 municipalities, representing 3.6% (199/5570) of the country's cities. The optimized sentinel site design, while keeping the same number of municipalities, ensures 100% coverage of all 34 DSEI regions while rearranging 108 (54.3%) of the 199 cities from the existing flu sentinel system. This would result in a more representative sentinel network, addressing gaps in 9 of 34 previously uncovered DSEI regions, which span 750,515 km² and have a population of 1.11 million. Mobility coverage would improve by 16.8 percentage points, from 52.4% (4,598,416 paths out of 8,780,046 total paths) to 69.2% (6,078,747 paths out of 8,780,046 total paths). Additionally, all newly selected cities serve as hubs for medium- or high-complexity health care, ensuring feasibility for pathogen surveillance. Conclusions The proposed framework optimizes sentinel site allocation to enhance disease surveillance and early detection. By maximizing DSEI coverage and integrating human mobility patterns, this approach provides a more effective and equitable surveillance network, which would particularly benefit underserved Indigenous regions.
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Affiliation(s)
- Juliane Fonseca Oliveira
- Center for Data and Knowledge Integration for Health, Gonçalo Moniz Institute, Fundação Oswaldo Cruz, Parque Tecnológico da Edf. Tecnocentro, R. Mundo, 121 - sala 315 - Trobogy, Salvador, 41745-715, Brazil, 55 71 3176 2357
| | - Adriano O Vasconcelos
- Luiz Coimbra Institute of Graduate and Engineering Research, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
| | - Andrêza L Alencar
- Department of Computer Science, Federal Rural University of Pernambuco, Recife, Brazil
| | - Maria Célia S L Cunha
- Luiz Coimbra Institute of Graduate and Engineering Research, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
| | - Izabel Marcilio
- Center for Data and Knowledge Integration for Health, Gonçalo Moniz Institute, Fundação Oswaldo Cruz, Parque Tecnológico da Edf. Tecnocentro, R. Mundo, 121 - sala 315 - Trobogy, Salvador, 41745-715, Brazil, 55 71 3176 2357
- Bahiana School of Medicine and Public Health (EBMSP), Salvador, Brazil
| | - Manoel Barral-Netto
- Center for Data and Knowledge Integration for Health, Gonçalo Moniz Institute, Fundação Oswaldo Cruz, Parque Tecnológico da Edf. Tecnocentro, R. Mundo, 121 - sala 315 - Trobogy, Salvador, 41745-715, Brazil, 55 71 3176 2357
- Medicine and Precision Public Health Laboratory, Gonçalo Moniz Institute, Fundação Oswaldo Cruz, Salvador, Brazil
| | - Pablo Ivan P Ramos
- Center for Data and Knowledge Integration for Health, Gonçalo Moniz Institute, Fundação Oswaldo Cruz, Parque Tecnológico da Edf. Tecnocentro, R. Mundo, 121 - sala 315 - Trobogy, Salvador, 41745-715, Brazil, 55 71 3176 2357
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Bednarska NG, Smith S, Bardsley M, Loveridge P, Byford R, Elson WH, Hughes HE, de Lusignan S, Todkill D, Elliot AJ. Trends in general practitioner consultations for hand foot and mouth disease in England between 2017 and 2022. Epidemiol Infect 2025; 153:e22. [PMID: 39801026 PMCID: PMC11795447 DOI: 10.1017/s095026882400181x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2024] [Revised: 11/28/2024] [Accepted: 12/05/2024] [Indexed: 01/31/2025] Open
Abstract
Hand, foot and mouth disease (HFMD) is a contagious communicable disease, with a high incidence in children aged under 10 years. It is a mainly self-limiting disease but can also cause serious neurological or cardiopulmonary complications in some cases, which can lead to death. Little is known about the burden of HMFD on primary care health care services in the UK. The aim of this work was to describe trends in general practitioner (GP) consultations for HFMD in England from January 2017 to December 2022 using a syndromic surveillance network of GPs. Daily GP consultations for HFMD in England were extracted from 1 January 2017 to 31 December 2022. Mean weekly consultation rates per 100,000 population and 95% confidence intervals (CI) were calculated. Consultation rates and rate ratios (RR) were calculated by age group and sex. During the study period, the mean weekly consultation rate for HFMD (per 100,000 registered GP patients) was 1.53 (range of 0.27 to 2.47). In England, children aged 1-4 years old accounted for the largest affected population followed by children <1 years old. We observed a seasonal pattern of HFMD incidence during the non-COVID years, with a seasonal peak of mean weekly rates between months of September and December. HFMD is typically diagnosed clinically rather than through laboratory sampling. Therefore, the ability to look at the daily HFMD consultation rates provides an excellent epidemiological overview on disease trends. The use of a novel GP-in-hours surveillance system allowed a unique epidemiological insight into the recent trends of general practitioner consultations for HFMD. We demonstrate a male predominance of cases, the impact of the non-pharmaceutical interventions during the COVID-19 pandemic, and a change in the week in which the peak number of cases happens post-pandemic.
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Affiliation(s)
- Natalia G. Bednarska
- Real-time Syndromic Surveillance Team, Field Services, UK Health Security Agency, Birmingham, UK
| | - Sue Smith
- Real-time Syndromic Surveillance Team, Field Services, UK Health Security Agency, Birmingham, UK
| | - Megan Bardsley
- Real-time Syndromic Surveillance Team, Field Services, UK Health Security Agency, Birmingham, UK
| | - Paul Loveridge
- Real-time Syndromic Surveillance Team, Field Services, UK Health Security Agency, Birmingham, UK
| | - Rachel Byford
- Nuffield Department of Primary Care Health Sciences, University of Oxford, OxfordUK
| | - William H Elson
- Nuffield Department of Primary Care Health Sciences, University of Oxford, OxfordUK
| | - Helen E. Hughes
- Real-time Syndromic Surveillance Team, Field Services, UK Health Security Agency, Birmingham, UK
| | - Simon de Lusignan
- Nuffield Department of Primary Care Health Sciences, University of Oxford, OxfordUK
- Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC), RCGP, London, UK
| | - Daniel Todkill
- Real-time Syndromic Surveillance Team, Field Services, UK Health Security Agency, Birmingham, UK
| | - Alex J. Elliot
- Real-time Syndromic Surveillance Team, Field Services, UK Health Security Agency, Birmingham, UK
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Hoang U, Delanerolle G, Fan X, Aspden C, Byford R, Ashraf M, Haag M, Elson W, Leston M, Anand S, Ferreira F, Joy M, Hobbs R, de Lusignan S. A Profile of Influenza Vaccine Coverage for 2019-2020: Database Study of the English Primary Care Sentinel Cohort. JMIR Public Health Surveill 2024; 10:e39297. [PMID: 38787605 PMCID: PMC11161707 DOI: 10.2196/39297] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Revised: 12/06/2023] [Accepted: 02/17/2024] [Indexed: 05/25/2024] Open
Abstract
BACKGROUND Innovation in seasonal influenza vaccine development has resulted in a wider range of formulations becoming available. Understanding vaccine coverage across populations including the timing of administration is important when evaluating vaccine benefits and risks. OBJECTIVE This study aims to report the representativeness, uptake of influenza vaccines, different formulations of influenza vaccines, and timing of administration within the English Primary Care Sentinel Cohort (PCSC). METHODS We used the PCSC of the Oxford-Royal College of General Practitioners Research and Surveillance Centre. We included patients of all ages registered with PCSC member general practices, reporting influenza vaccine coverage between September 1, 2019, and January 29, 2020. We identified influenza vaccination recipients and characterized them by age, clinical risk groups, and vaccine type. We reported the date of influenza vaccination within the PCSC by International Standard Organization (ISO) week. The representativeness of the PCSC population was compared with population data provided by the Office for National Statistics. PCSC influenza vaccine coverage was compared with published UK Health Security Agency's national data. We used paired t tests to compare populations, reported with 95% CI. RESULTS The PCSC comprised 7,010,627 people from 693 general practices. The study population included a greater proportion of people aged 18-49 years (2,982,390/7,010,627, 42.5%; 95% CI 42.5%-42.6%) compared with the Office for National Statistics 2019 midyear population estimates (23,219,730/56,286,961, 41.3%; 95% CI 4.12%-41.3%; P<.001). People who are more deprived were underrepresented and those in the least deprived quintile were overrepresented. Within the study population, 24.7% (1,731,062/7,010,627; 95% CI 24.7%-24.7%) of people of all ages received an influenza vaccine compared with 24.2% (14,468,665/59,764,928; 95% CI 24.2%-24.2%; P<.001) in national data. The highest coverage was in people aged ≥65 years (913,695/1,264,700, 72.3%; 95% CI 72.2%-72.3%). The proportion of people in risk groups who received an influenza vaccine was also higher; for example, 69.8% (284,280/407,228; 95% CI 69.7%-70%) of people with diabetes in the PCSC received an influenza vaccine compared with 61.2% (983,727/1,607,996; 95% CI 61.1%-61.3%; P<.001) in national data. In the PCSC, vaccine type and brand information were available for 71.8% (358,365/498,923; 95% CI 71.7%-72%) of people aged 16-64 years and 81.9% (748,312/913,695; 95% CI 81.8%-82%) of people aged ≥65 years, compared with 23.6% (696,880/2,900,000) and 17.8% (1,385,888/7,700,000), respectively, of the same age groups in national data. Vaccination commenced during ISO week 35, continued until ISO week 3, and peaked during ISO week 41. The in-week peak in vaccination administration was on Saturdays. CONCLUSIONS The PCSC's sociodemographic profile was similar to the national population and captured more data about risk groups, vaccine brands, and batches. This may reflect higher data quality. Its capabilities included reporting precise dates of administration. The PCSC is suitable for undertaking studies of influenza vaccine coverage.
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Affiliation(s)
- Uy Hoang
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Gayathri Delanerolle
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Xuejuan Fan
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Carole Aspden
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Rachel Byford
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | | | | | - William Elson
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Meredith Leston
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Sneha Anand
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Filipa Ferreira
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Mark Joy
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Richard Hobbs
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Simon de Lusignan
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
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Gu X, Watson C, Agrawal U, Whitaker H, Elson WH, Anand S, Borrow R, Buckingham A, Button E, Curtis L, Dunn D, Elliot AJ, Ferreira F, Goudie R, Hoang U, Hoschler K, Jamie G, Kar D, Kele B, Leston M, Linley E, Macartney J, Marsden GL, Okusi C, Parvizi O, Quinot C, Sebastianpillai P, Sexton V, Smith G, Suli T, Thomas NPB, Thompson C, Todkill D, Wimalaratna R, Inada-Kim M, Andrews N, Tzortziou-Brown V, Byford R, Zambon M, Lopez-Bernal J, de Lusignan S. Postpandemic Sentinel Surveillance of Respiratory Diseases in the Context of the World Health Organization Mosaic Framework: Protocol for a Development and Evaluation Study Involving the English Primary Care Network 2023-2024. JMIR Public Health Surveill 2024; 10:e52047. [PMID: 38569175 PMCID: PMC11024753 DOI: 10.2196/52047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Revised: 01/02/2024] [Accepted: 01/17/2024] [Indexed: 04/05/2024] Open
Abstract
BACKGROUND Prepandemic sentinel surveillance focused on improved management of winter pressures, with influenza-like illness (ILI) being the key clinical indicator. The World Health Organization (WHO) global standards for influenza surveillance include monitoring acute respiratory infection (ARI) and ILI. The WHO's mosaic framework recommends that the surveillance strategies of countries include the virological monitoring of respiratory viruses with pandemic potential such as influenza. The Oxford-Royal College of General Practitioner Research and Surveillance Centre (RSC) in collaboration with the UK Health Security Agency (UKHSA) has provided sentinel surveillance since 1967, including virology since 1993. OBJECTIVE We aim to describe the RSC's plans for sentinel surveillance in the 2023-2024 season and evaluate these plans against the WHO mosaic framework. METHODS Our approach, which includes patient and public involvement, contributes to surveillance objectives across all 3 domains of the mosaic framework. We will generate an ARI phenotype to enable reporting of this indicator in addition to ILI. These data will support UKHSA's sentinel surveillance, including vaccine effectiveness and burden of disease studies. The panel of virology tests analyzed in UKHSA's reference laboratory will remain unchanged, with additional plans for point-of-care testing, pneumococcus testing, and asymptomatic screening. Our sampling framework for serological surveillance will provide greater representativeness and more samples from younger people. We will create a biomedical resource that enables linkage between clinical data held in the RSC and virology data, including sequencing data, held by the UKHSA. We describe the governance framework for the RSC. RESULTS We are co-designing our communication about data sharing and sampling, contextualized by the mosaic framework, with national and general practice patient and public involvement groups. We present our ARI digital phenotype and the key data RSC network members are requested to include in computerized medical records. We will share data with the UKHSA to report vaccine effectiveness for COVID-19 and influenza, assess the disease burden of respiratory syncytial virus, and perform syndromic surveillance. Virological surveillance will include COVID-19, influenza, respiratory syncytial virus, and other common respiratory viruses. We plan to pilot point-of-care testing for group A streptococcus, urine tests for pneumococcus, and asymptomatic testing. We will integrate test requests and results with the laboratory-computerized medical record system. A biomedical resource will enable research linking clinical data to virology data. The legal basis for the RSC's pseudonymized data extract is The Health Service (Control of Patient Information) Regulations 2002, and all nonsurveillance uses require research ethics approval. CONCLUSIONS The RSC extended its surveillance activities to meet more but not all of the mosaic framework's objectives. We have introduced an ARI indicator. We seek to expand our surveillance scope and could do more around transmissibility and the benefits and risks of nonvaccine therapies.
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Affiliation(s)
- Xinchun Gu
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Conall Watson
- Immunisation and Vaccine-Preventable Diseases Division, UK Health Security Agency, London, United Kingdom
| | - Utkarsh Agrawal
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Heather Whitaker
- Statistics, Modelling and Economics Department, UK Health Security Agency, London, United Kingdom
| | - William H Elson
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Sneha Anand
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Ray Borrow
- Vaccine Evaluation Unit, UK Health Security Agency, Manchester, United Kingdom
| | | | - Elizabeth Button
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Lottie Curtis
- Royal College of General Practitioners, London, United Kingdom
| | - Dominic Dunn
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Alex J Elliot
- Real-time Syndromic Surveillance Team, UK Health Security Agency, Birmingham, United Kingdom
| | - Filipa Ferreira
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Rosalind Goudie
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Uy Hoang
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Katja Hoschler
- Respiratory Virus Unit, UK Health Security Agency, London, United Kingdom
| | - Gavin Jamie
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Debasish Kar
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Beatrix Kele
- Respiratory Virus Unit, UK Health Security Agency, London, United Kingdom
| | - Meredith Leston
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Ezra Linley
- Vaccine Evaluation Unit, UK Health Security Agency, Manchester, United Kingdom
| | - Jack Macartney
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Gemma L Marsden
- Royal College of General Practitioners, London, United Kingdom
| | - Cecilia Okusi
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Omid Parvizi
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
- Respiratory Virus Unit, UK Health Security Agency, London, United Kingdom
| | - Catherine Quinot
- Immunisation and Vaccine-Preventable Diseases Division, UK Health Security Agency, London, United Kingdom
| | | | - Vanashree Sexton
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Gillian Smith
- Real-time Syndromic Surveillance Team, UK Health Security Agency, Birmingham, United Kingdom
| | - Timea Suli
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | | | - Catherine Thompson
- Respiratory Virus Unit, UK Health Security Agency, London, United Kingdom
| | - Daniel Todkill
- Real-time Syndromic Surveillance Team, UK Health Security Agency, Birmingham, United Kingdom
| | - Rashmi Wimalaratna
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | | | - Nick Andrews
- Immunisation and Vaccine-Preventable Diseases Division, UK Health Security Agency, London, United Kingdom
| | | | - Rachel Byford
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Maria Zambon
- Virus Reference Department, UK Health Security Agency, London, United Kingdom
| | - Jamie Lopez-Bernal
- Immunisation and Vaccine-Preventable Diseases Division, UK Health Security Agency, London, United Kingdom
| | - Simon de Lusignan
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
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Talts T, Mosscrop LG, Williams D, Tregoning JS, Paulo W, Kohli A, Williams TC, Hoschler K, Ellis J, de Lusignan S, Zambon M. Robust and sensitive amplicon-based whole-genome sequencing assay of respiratory syncytial virus subtype A and B. Microbiol Spectr 2024; 12:e0306723. [PMID: 38411056 PMCID: PMC10986592 DOI: 10.1128/spectrum.03067-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Accepted: 02/06/2024] [Indexed: 02/28/2024] Open
Abstract
Prevention of respiratory syncytial virus (RSV) infection is now a global health priority, with a long-acting monoclonal antibody and two RSV vaccines recently licenced for clinical use. Most licenced and candidate interventions target the RSV fusion (RSV-F) protein. New interventions may be associated with the spread of mutations, reducing susceptibility to antibody neutralization in RSV-F. There is a need for ongoing longitudinal global surveillance of circulating RSV strains. To achieve this large-scale genomic surveillance, a reliable, high-throughput RSV sequencing assay is required. Here we report an improved high-throughput RSV whole-genome sequencing (WGS) assay performed directly on clinical samples without additional enrichment, using a 4-primer-pool, short-amplicon PCR-tiling approach that is suitable for short-read sequencing platforms. Using upper respiratory tract (URT) RSV-positive clinical samples obtained from a sentinel network of primary care providers and from hospital patients (29.7% and 70.2%, respectively; n = 1,037), collected over the period 2019 to 2023, this assay had a threshold of approximately 4 × 103 to 8 × 103 copies/mL (RSV-B and RSV-A sub-types, respectively) as the lowest amount of virus needed in the sample to achieve >96% of whole-genome coverage at a high-quality level. Using a Ct value of 31 as an empirical cut-off, the overall assay success rate of obtaining >90% genome coverage at a read depth minimum of 20 was 96.83% for clinical specimens successfully sequenced from a total of 1,071. The RSV WGS approach described in this study has increased sensitivity compared to previous approaches and can be applied to clinical specimens without the requirement for enrichment. The updated approach produces sequences of high quality consistently and cost-effectively, suitable for implementation to underpin national programs for the surveillance of RSV genomic variation. IMPORTANCE In this paper, we report an improved high-throughput respiratory syncytial virus (RSV) whole-genome sequencing (WGS) assay performed directly on clinical samples, using a 4-primer-pool, short-amplicon PCR-tiling approach that is suitable for short-read sequencing platforms. The RSV WGS approach described in this study has increased sensitivity compared to previous approaches and can be applied to clinical specimens without the requirement for enrichment. The updated approach produces sequences of high quality consistently and cost-effectively, suitable for implementation to underpin national and global programs for the surveillance of RSV genomic variation. The quality of sequence produced is essential for preparedness for new interventions in monitoring antigenic escape, where a single point mutation might lead to a reduction in antibody binding effectiveness and neutralizing activity, or indeed in the monitoring of retaining susceptibility to neutralization by existing and new interventions.
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Affiliation(s)
- Tiina Talts
- UK Health Security Agency, London, United Kingdom
| | | | | | | | | | | | | | | | - Joanna Ellis
- UK Health Security Agency, London, United Kingdom
| | | | - Maria Zambon
- UK Health Security Agency, London, United Kingdom
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6
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Tsang RSM, Agrawal U, Joy M, Byford R, Robertson C, Anand SN, Hinton W, Mayor N, Kar D, Williams J, Victor W, Akbari A, Bradley DT, Murphy S, O’Reilly D, Owen RK, Chuter A, Beggs J, Howsam G, Sheikh A, Richard Hobbs FD, de Lusignan S. Adverse events after first and second doses of COVID-19 vaccination in England: a national vaccine surveillance platform self-controlled case series study. J R Soc Med 2024; 117:134-148. [PMID: 37921538 PMCID: PMC11100448 DOI: 10.1177/01410768231205430] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 09/17/2023] [Indexed: 11/04/2023] Open
Abstract
OBJECTIVES To estimate the incidence of adverse events of interest (AEIs) after receiving their first and second doses of coronavirus disease 2019 (COVID-19) vaccinations, and to report the safety profile differences between the different COVID-19 vaccines. DESIGN We used a self-controlled case series design to estimate the relative incidence (RI) of AEIs reported to the Oxford-Royal College of General Practitioners national sentinel network. We compared the AEIs that occurred seven days before and after receiving the COVID-19 vaccinations to background levels between 1 October 2020 and 12 September 2021. SETTING England, UK. PARTICIPANTS Individuals experiencing AEIs after receiving first and second doses of COVID-19 vaccines. MAIN OUTCOME MEASURES AEIs determined based on events reported in clinical trials and in primary care during post-license surveillance. RESULTS A total of 7,952,861 individuals were vaccinated with COVID-19 vaccines within the study period. Among them, 781,200 individuals (9.82%) presented to general practice with 1,482,273 AEIs. Within the first seven days post-vaccination, 4.85% of all the AEIs were reported. There was a 3-7% decrease in the overall RI of AEIs in the seven days after receiving both doses of Pfizer-BioNTech BNT162b2 (RI = 0.93; 95% CI: 0.91-0.94) and 0.96; 95% CI: 0.94-0.98), respectively) and Oxford-AstraZeneca ChAdOx1 (RI = 0.97; 95% CI: 0.95-0.98) for both doses), but a 20% increase after receiving the first dose of Moderna mRNA-1273 (RI = 1.20; 95% CI: 1.00-1.44)). CONCLUSIONS COVID-19 vaccines are associated with a small decrease in the incidence of medically attended AEIs. Sentinel networks could routinely report common AEI rates, which could contribute to reporting vaccine safety.
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Affiliation(s)
- Ruby SM Tsang
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK
| | - Utkarsh Agrawal
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK
| | - Mark Joy
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK
| | - Rachel Byford
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK
| | - Chris Robertson
- Department of Mathematics and Statistics, University of Strathclyde, Glasgow, G1 1XH, UK
- Public Health Scotland, Glasgow, G2 6QE, UK
| | - Sneha N Anand
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK
| | - William Hinton
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK
| | - Nikhil Mayor
- Royal Surrey NHS Foundation Trust, Guildford, GU2 7XX, UK
| | - Debasish Kar
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK
| | - John Williams
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK
| | - William Victor
- Royal College of General Practitioners, London, NW1 2FB, UK
| | - Ashley Akbari
- Population Data Science, Swansea University Medical School, Swansea University, Swansea, SA2 8QA, UK
| | - Declan T Bradley
- Centre for Public Health, Queen’s University Belfast, Belfast, BT12 6BA, UK
- Public Health Agency, Belfast, BT2 8BS, UK
| | - Siobhan Murphy
- Centre for Public Health, Queen’s University Belfast, Belfast, BT12 6BA, UK
| | - Dermot O’Reilly
- Centre for Public Health, Queen’s University Belfast, Belfast, BT12 6BA, UK
| | - Rhiannon K Owen
- Population Data Science, Swansea University Medical School, Swansea University, Swansea, SA2 8QA, UK
| | - Antony Chuter
- BREATHE – The Health Data Research Hub for Respiratory Health, Edinburgh, EH16 4SS, UK
| | - Jillian Beggs
- BREATHE – The Health Data Research Hub for Respiratory Health, Edinburgh, EH16 4SS, UK
| | - Gary Howsam
- Royal College of General Practitioners, London, NW1 2FB, UK
| | - Aziz Sheikh
- Usher Institute, University of Edinburgh, Edinburgh, EH16 4SS, UK
| | - FD Richard Hobbs
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK
| | - Simon de Lusignan
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK
- Department of Mathematics and Statistics, University of Strathclyde, Glasgow, G1 1XH, UK
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Vusirikala A, Tonge S, Bell A, Linley E, Borrow R, O'Boyle S, de Lusignan S, Charlett A, Balasegaram S, Amirthalingam G. Reassurance of population immunity to diphtheria in England: Results from a 2021 national serosurvey. Vaccine 2023; 41:6878-6883. [PMID: 37821313 DOI: 10.1016/j.vaccine.2023.10.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 09/04/2023] [Accepted: 10/02/2023] [Indexed: 10/13/2023]
Abstract
BACKGROUND Diphtheria is rare in England because of an effective national immunisation schedule that includes 5 doses of a diphtheria-containing vaccine at 2, 3, 4 months, preschool and adolescent boosters. However, in recent years there has been a notable increase in cases due to Corynebacterium ulcerans among older adults and evidence of endemic transmission of C. diphtheriae (normally associated with travel to endemic countries). We aimed to update 2009 estimates of diphtheria immunity considering the evolving epidemiology. METHODS Residual sera collected from diagnostic laboratories and general practitioners in England in 2021 were randomly selected and tested for diphtheria antibody, to estimate proportions protected per age group. Diphtheria antibody levels were defined as susceptible (<0.01 IU/mL), basic protection (0.01-0.099 IU/mL) and full protection (≥0.1 IU/mL). Immunity estimates were standardised to the England population and compared to 2009. RESULTS Based on 3,745 residual sera tested, 89% (95%CI: 87%-90%) of the 2021 England population had at least basic diphtheria protection (vs. 90% [88%-92%] in 2009) and 50% (48%-52%) full protection (vs. 41% [38%-44%]). Higher antibody levels were observed in those aged 1 and under, 10-11, 12-15, 25-34 and 35-44 years compared to 2009. The largest proportion susceptible were observed in those aged 70+, 26% (21%-31%) vs 12% (7%-18%) in 2009. CONCLUSIONS Basic diphtheria protection is comparable between 2021 and 2009. The increase in immunity in working age adults is likely due to the school leaver booster introduced in 1994. The current vaccination schedule is maintaining sufficient population immunity. However, we recommend clinicians remain vigilant to severe diphtheria outcomes in older adults, because of their observed susceptibility.
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Affiliation(s)
- Amoolya Vusirikala
- UK Health Security Agency, 61 Colindale Avenue, London NW9 5EQ, UK; UK Field Epidemiology Training Programme, UK Health Security Agency, London, UK.
| | - Simon Tonge
- Vaccine Evaluation Unit, UK Health Security Agency, Manchester Medical Microbiology Partnership, Manchester Royal Infirmary, Oxford Road, Manchester M13 9WL, UK
| | - Abigail Bell
- Vaccine Evaluation Unit, UK Health Security Agency, Manchester Medical Microbiology Partnership, Manchester Royal Infirmary, Oxford Road, Manchester M13 9WL, UK
| | - Ezra Linley
- Vaccine Evaluation Unit, UK Health Security Agency, Manchester Medical Microbiology Partnership, Manchester Royal Infirmary, Oxford Road, Manchester M13 9WL, UK
| | - Ray Borrow
- Vaccine Evaluation Unit, UK Health Security Agency, Manchester Medical Microbiology Partnership, Manchester Royal Infirmary, Oxford Road, Manchester M13 9WL, UK
| | - Shennae O'Boyle
- UK Health Security Agency, 61 Colindale Avenue, London NW9 5EQ, UK
| | - Simon de Lusignan
- Royal College of General Practitioners Research and Surveillance Centre, Euston Square, London NW1 2FB, UK; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford OX2 6GG, UK
| | - Andre Charlett
- UK Health Security Agency, 61 Colindale Avenue, London NW9 5EQ, UK
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Whitaker HJ, Tsang RSM, Byford R, Aspden C, Button E, Sebastian Pillai P, Jamie G, Kar D, Williams J, Sinnathamby M, Marsden G, Elson WH, Leston M, Anand S, Okusi C, Fan X, Linley E, Rowe C, DArcangelo S, Otter AD, Ellis J, Hobbs FDR, Tzortziou-Brown V, Zambon M, Ramsay M, Brown KE, Amirthalingam G, Andrews NJ, de Lusignan S, Lopez Bernal J. COVID-19 vaccine effectiveness against hospitalisation and death of people in clinical risk groups during the Delta variant period: English primary care network cohort study. J Infect 2023; 87:315-327. [PMID: 37579793 DOI: 10.1016/j.jinf.2023.08.005] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 08/07/2023] [Accepted: 08/09/2023] [Indexed: 08/16/2023]
Abstract
BACKGROUND COVID-19 vaccines have been shown to be highly effective against hospitalisation and death following COVID-19 infection. COVID-19 vaccine effectiveness estimates against severe endpoints among individuals with clinical conditions that place them at increased risk of critical disease are limited. METHODS We used English primary care medical record data from the Oxford-Royal College of General Practitioners Research and Surveillance Centre sentinel network (N > 18 million). Data were linked to the National Immunisation Management Service database, Second Generation Surveillance System for virology test data, Hospital Episode Statistics, and death registry data. We estimated adjusted vaccine effectiveness (aVE) against COVID-19 infection followed by hospitalisation and death among individuals in specific clinical risk groups using a cohort design during the delta-dominant period. We also report mortality statistics and results from our antibody surveillance in this population. FINDINGS aVE against severe endpoints was high, 14-69d following a third dose aVE was 96.4% (95.1%-97.4%) and 97.9% (97.2%-98.4%) for clinically vulnerable people given a Vaxzevria and Comirnaty primary course respectively. Lower aVE was observed in the immunosuppressed group: 88.6% (79.1%-93.8%) and 91.9% (85.9%-95.4%) for Vaxzevria and Comirnaty respectively. Antibody levels were significantly lower among the immunosuppressed group than those not in this risk group across all vaccination types and doses. The standardised case fatality rate within 28 days of a positive test was 3.9/1000 in people not in risk groups, compared to 12.8/1000 in clinical risk groups. Waning aVE with time since 2nd dose was also demonstrated, for example, Comirnaty aVE against hospitalisation reduced from 96.0% (95.1-96.7%) 14-69days post-dose 2-82.9% (81.4-84.2%) 182days+ post-dose 2. INTERPRETATION In all clinical risk groups high levels of vaccine effectiveness against severe endpoints were seen. Reduced vaccine effectiveness was noted among the immunosuppressed group.
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Affiliation(s)
- Heather J Whitaker
- Statistics, Modelling and Economics Department, UK Health Security Agency, 61 Colindale Avenue, London NW9 5EQ, UK
| | - Ruby S M Tsang
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford OX2 6GG, UK
| | - Rachel Byford
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford OX2 6GG, UK
| | - Carole Aspden
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford OX2 6GG, UK
| | - Elizabeth Button
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford OX2 6GG, UK
| | | | - Gavin Jamie
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford OX2 6GG, UK
| | - Debasish Kar
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford OX2 6GG, UK
| | - John Williams
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford OX2 6GG, UK
| | - Mary Sinnathamby
- Immunisation and Vaccine Preventable Diseases Division, UK Health Security Agency, 61 Colindale Avenue, London NW9 5EQ, UK
| | - Gemma Marsden
- Royal College of General Practitioners Research and Surveillance Centre, Euston Square, London NW1 2FB, UK
| | - William H Elson
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford OX2 6GG, UK
| | - Meredith Leston
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford OX2 6GG, UK
| | - Sneha Anand
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford OX2 6GG, UK
| | - Cecilia Okusi
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford OX2 6GG, UK
| | - Xuejuan Fan
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford OX2 6GG, UK
| | - Ezra Linley
- Vaccine Evaluation Unit, UK Health Security Agency, Manchester M13 9WL, UK
| | - Cathy Rowe
- Diagnostics and Genomics, UK Health Security Agency, Porton Down, Salisbury SP4 0JG, UK
| | - Silvia DArcangelo
- Diagnostics and Genomics, UK Health Security Agency, Porton Down, Salisbury SP4 0JG, UK
| | - Ashley D Otter
- Diagnostics and Genomics, UK Health Security Agency, Porton Down, Salisbury SP4 0JG, UK
| | - Joanna Ellis
- Immunisation and Vaccine Preventable Diseases Division, UK Health Security Agency, 61 Colindale Avenue, London NW9 5EQ, UK; Virus Reference Laboratory, UK Health Security Agency, 61 Colindale Avenue, London NW9 5EQ, UK
| | - F D Richard Hobbs
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford OX2 6GG, UK
| | - Victoria Tzortziou-Brown
- Royal College of General Practitioners Research and Surveillance Centre, Euston Square, London NW1 2FB, UK
| | - Maria Zambon
- Virus Reference Laboratory, UK Health Security Agency, 61 Colindale Avenue, London NW9 5EQ, UK
| | - Mary Ramsay
- Immunisation and Vaccine Preventable Diseases Division, UK Health Security Agency, 61 Colindale Avenue, London NW9 5EQ, UK
| | - Kevin E Brown
- Immunisation and Vaccine Preventable Diseases Division, UK Health Security Agency, 61 Colindale Avenue, London NW9 5EQ, UK
| | - Gayatri Amirthalingam
- Immunisation and Vaccine Preventable Diseases Division, UK Health Security Agency, 61 Colindale Avenue, London NW9 5EQ, UK
| | - Nick J Andrews
- Statistics, Modelling and Economics Department, UK Health Security Agency, 61 Colindale Avenue, London NW9 5EQ, UK; Immunisation and Vaccine Preventable Diseases Division, UK Health Security Agency, 61 Colindale Avenue, London NW9 5EQ, UK
| | - Simon de Lusignan
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford OX2 6GG, UK; Royal College of General Practitioners Research and Surveillance Centre, Euston Square, London NW1 2FB, UK
| | - Jamie Lopez Bernal
- Immunisation and Vaccine Preventable Diseases Division, UK Health Security Agency, 61 Colindale Avenue, London NW9 5EQ, UK.
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Joy M, Agrawal U, Fan X, Robertson C, Anand SN, Ordonez-Mena J, Byford R, Goudie R, Jamie G, Kar D, Williams J, Marsden GL, Tzortziou-Brown V, Sheikh SA, Hobbs FR, de Lusignan S. Thrombocytopenic, thromboembolic and haemorrhagic events following second dose with BNT162b2 and ChAdOx1: self-controlled case series analysis of the English national sentinel cohort. THE LANCET REGIONAL HEALTH. EUROPE 2023; 32:100681. [PMID: 37671127 PMCID: PMC10477035 DOI: 10.1016/j.lanepe.2023.100681] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Revised: 06/26/2023] [Accepted: 06/27/2023] [Indexed: 09/07/2023]
Abstract
Background Thrombosis associated with thrombocytopenia was a matter of concern post first and second doses of BNT162b2 and ChAdOx1 COVID-19 vaccines. Therefore, it is important to investigate the risk of thrombocytopenic, thromboembolic and haemorrhagic events following a second dose of BNT162b2 and ChAdOx1 COVID-19 vaccines. Methods We conducted a large-scale self-controlled case series analysis, using routine primary care data linked to hospital data, among 12.3 million individuals (16 years old and above) in England. We used the nationally representative Oxford-Royal College of General Practitioners (RCGP) sentinel network database with baseline and risk periods between 8th December 2020 and 11th June 2022. We included individuals who received two vaccine (primary) doses of the BNT162b2 mRNA (Pfizer-BioNTech) and two vaccine doses of ChAdOx1 nCoV-19 (Oxford-AstraZeneca) vaccines in our analyses. We carried out a self-controlled case series (SCCS) analysis for each outcome using a conditional Poisson regression model with an offset for the length of risk period. We reported the incidence rate ratios (IRRs) and 95% confidence intervals (CI) of thrombocytopenic, thromboembolic (including arterial and venous events) and haemorrhagic events, in the period of 0-27 days after receiving a second dose of BNT162b2 or ChAdOx1 vaccines compared to the baseline period (14 or more days prior to first dose, 28 or more days after the second dose and the time between 28 or more days after the first and 14 or more days prior to the second dose). We adjusted for a range of potential confounders, including age, sex, comorbidities and deprivation. Findings Between December 8, 2020 and February 11, 2022, 6,306,306 individuals were vaccinated with two doses of BNT162b2 and 6,046,785 individuals were vaccinated with two doses of ChAdOx1. Compared to the baseline, our analysis show no increased risk of venous thromboembolic events (VTE) for both BNT162b2 (IRR 0.71, 95% CI: 0.65-0.770) and ChAdOx1 (IRR 0.91, 95% CI: 0.84-0.98); and similarly there was no increased risk for cerebral venous sinus thrombosis (CVST) for both BNT162b2 (IRR 0.87, 95% CI: 0.41-1.85) and ChAdOx1 (IRR 1.73, 95% CI: 0.82-3.68). We additionally report no difference in IRR for pulmonary embolus, and deep vein thrombosis, thrombocytopenia, including idiopathic thrombocytopenic purpura (ITP), and haemorrhagic events post second dose for both BNT162b2. Interpretation Reassuringly, we found no associations between increased risk of thrombocytopenic, thromboembolic and haemorrhagic events post vaccination with second dose for either of these vaccines. Funding Data and Connectivity: COVID-19 Vaccines Pharmacovigilance study.
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Affiliation(s)
- Mark Joy
- Nuffield Department of Primary Care Health Sciences, University of Oxford, UK
| | - Utkarsh Agrawal
- Nuffield Department of Primary Care Health Sciences, University of Oxford, UK
| | - Xuejuan Fan
- Nuffield Department of Primary Care Health Sciences, University of Oxford, UK
| | - Chris Robertson
- Department of Mathematics and Statistics, University of Strathclyde, Glasgow, UK
- Public Health Scotland, Glasgow, UK
| | - Sneha N. Anand
- Nuffield Department of Primary Care Health Sciences, University of Oxford, UK
| | - Jose Ordonez-Mena
- Nuffield Department of Primary Care Health Sciences, University of Oxford, UK
| | - Rachel Byford
- Nuffield Department of Primary Care Health Sciences, University of Oxford, UK
| | - Rosalind Goudie
- Nuffield Department of Primary Care Health Sciences, University of Oxford, UK
| | - Gavin Jamie
- Nuffield Department of Primary Care Health Sciences, University of Oxford, UK
| | - Debasish Kar
- Nuffield Department of Primary Care Health Sciences, University of Oxford, UK
| | - John Williams
- Nuffield Department of Primary Care Health Sciences, University of Oxford, UK
| | | | | | | | - F.D. Richard Hobbs
- Nuffield Department of Primary Care Health Sciences, University of Oxford, UK
| | - Simon de Lusignan
- Nuffield Department of Primary Care Health Sciences, University of Oxford, UK
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10
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Hoang U, Williams A, Smylie J, Aspden C, Button E, Macartney J, Okusi C, Byford R, Ferreira F, Leston M, Xie CX, Joy M, Marsden G, Clark T, de Lusignan S. The Impact of Point-of-Care Testing for Influenza on Antimicrobial Stewardship (PIAMS) in UK Primary Care: Protocol for a Mixed Methods Study. JMIR Res Protoc 2023; 12:e46938. [PMID: 37327029 DOI: 10.2196/46938] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 05/12/2023] [Accepted: 05/23/2023] [Indexed: 06/17/2023] Open
Abstract
BACKGROUND Molecular point-of-care testing (POCT) used in primary care can inform whether a patient presenting with an acute respiratory infection has influenza. A confirmed clinical diagnosis, particularly early in the disease, could inform better antimicrobial stewardship. Social distancing and lockdowns during the COVID-19 pandemic have disturbed previous patterns of influenza infections in 2021. However, data from samples taken in the last quarter of 2022 suggest that influenza represents 36% of sentinel network positive virology, compared with 24% for respiratory syncytial virus. Problems with integration into the clinical workflow is a known barrier to incorporating technology into routine care. OBJECTIVE This study aims to report the impact of POCT for influenza on antimicrobial prescribing in primary care. We will additionally describe severe outcomes of infection (hospitalization and mortality) and how POCT is integrated into primary care workflows. METHODS The impact of POCT for influenza on antimicrobial stewardship (PIAMS) in UK primary care is an observational study being conducted between December 2022 and May 2023 and involving 10 practices that contribute data to the English sentinel network. Up to 1000 people who present to participating practices with respiratory symptoms will be swabbed and tested with a rapid molecular POCT analyzer in the practice. Antimicrobial prescribing and other study outcomes will be collected by linking information from the POCT analyzer with data from the patient's computerized medical record. We will collect data on how POCT is incorporated into practice using data flow diagrams, unified modeling language use case diagrams, and Business Process Modeling Notation. RESULTS We will present the crude and adjusted odds of antimicrobial prescribing (all antibiotics and antivirals) given a POCT diagnosis of influenza, stratifying by whether individuals have a respiratory or other relevant diagnosis (eg, bronchiectasis). We will also present the rates of hospital referrals and deaths related to influenza infection in PIAMS study practices compared with a set of matched practices in the sentinel network and the rest of the network. We will describe any difference in implementation models in terms of staff involved and workflow. CONCLUSIONS This study will generate data on the impact of POCT testing for influenza in primary care as well as help to inform about the feasibility of incorporating POCT into primary care workflows. It will inform the design of future larger studies about the effectiveness and cost-effectiveness of POCT to improve antimicrobial stewardship and any impact on severe outcomes. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) DERR1-10.2196/46938.
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Affiliation(s)
- Uy Hoang
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Alice Williams
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Jessica Smylie
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Carole Aspden
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Elizabeth Button
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Jack Macartney
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Cecilia Okusi
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Rachel Byford
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Filipa Ferreira
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Meredith Leston
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Charis Xuan Xie
- Wolfson Institute of Population Health, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| | - Mark Joy
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Gemma Marsden
- Royal College of General Practitioners, London, United Kingdom
| | - Tristan Clark
- School of Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, United Kingdom
- University Hospital Southampton, National Health Service Foundation Trust, Southampton, United Kingdom
| | - Simon de Lusignan
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
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11
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Tsang RSM, Joy M, Byford R, Robertson C, Anand SN, Hinton W, Mayor N, Kar D, Williams J, Victor W, Akbari A, Bradley DT, Murphy S, O’Reilly D, Owen RK, Chuter A, Beggs J, Howsam G, Sheikh A, Hobbs FDR, de Lusignan S. Adverse events following first and second dose COVID-19 vaccination in England, October 2020 to September 2021: a national vaccine surveillance platform self-controlled case series study. Euro Surveill 2023; 28:2200195. [PMID: 36695484 PMCID: PMC9853944 DOI: 10.2807/1560-7917.es.2023.28.3.2200195] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Abstract
BackgroundPost-authorisation vaccine safety surveillance is well established for reporting common adverse events of interest (AEIs) following influenza vaccines, but not for COVID-19 vaccines.AimTo estimate the incidence of AEIs presenting to primary care following COVID-19 vaccination in England, and report safety profile differences between vaccine brands.MethodsWe used a self-controlled case series design to estimate relative incidence (RI) of AEIs reported to the national sentinel network, the Oxford-Royal College of General Practitioners Clinical Informatics Digital Hub. We compared AEIs (overall and by clinical category) 7 days pre- and post-vaccination to background levels between 1 October 2020 and 12 September 2021.ResultsWithin 7,952,861 records, 781,200 individuals (9.82%) presented to general practice with 1,482,273 AEIs, 4.85% within 7 days post-vaccination. Overall, medically attended AEIs decreased post-vaccination against background levels. There was a 3-7% decrease in incidence within 7 days after both doses of Comirnaty (RI: 0.93; 95% CI: 0.91-0.94 and RI: 0.96; 95% CI: 0.94-0.98, respectively) and Vaxzevria (RI: 0.97; 95% CI: 0.95-0.98). A 20% increase was observed after one dose of Spikevax (RI: 1.20; 95% CI: 1.00-1.44). Fewer AEIs were reported as age increased. Types of AEIs, e.g. increased neurological and psychiatric conditions, varied between brands following two doses of Comirnaty (RI: 1.41; 95% CI: 1.28-1.56) and Vaxzevria (RI: 1.07; 95% CI: 0.97-1.78).ConclusionCOVID-19 vaccines are associated with a small decrease in medically attended AEI incidence. Sentinel networks could routinely report common AEI rates, contributing to reporting vaccine safety.
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Affiliation(s)
- Ruby SM Tsang
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Mark Joy
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Rachel Byford
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Chris Robertson
- Department of Mathematics and Statistics, University of Strathclyde, Glasgow, United Kingdom,Public Health Scotland, Glasgow, United Kingdom
| | - Sneha N Anand
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - William Hinton
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Nikhil Mayor
- Chelsea and Westminster Hospital NHS Foundation Trust, London, United Kingdom
| | - Debasish Kar
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - John Williams
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - William Victor
- Royal College of General Practitioners, London, United Kingdom
| | - Ashley Akbari
- Population Data Science, Swansea University Medical School, Swansea University, United Kingdom
| | - Declan T Bradley
- Centre for Public Health, Queen’s University Belfast, Belfast, United Kingdom,Public Health Agency, Belfast, United Kingdom
| | - Siobhan Murphy
- Centre for Public Health, Queen’s University Belfast, Belfast, United Kingdom
| | - Dermot O’Reilly
- Centre for Public Health, Queen’s University Belfast, Belfast, United Kingdom
| | - Rhiannon K Owen
- Population Data Science, Swansea University Medical School, Swansea University, United Kingdom
| | - Antony Chuter
- BREATHE – The Health Data Research Hub for Respiratory Health, Edinburgh, United Kingdom
| | - Jillian Beggs
- BREATHE – The Health Data Research Hub for Respiratory Health, Edinburgh, United Kingdom
| | - Gary Howsam
- Royal College of General Practitioners, London, United Kingdom
| | - Aziz Sheikh
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - FD Richard Hobbs
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Simon de Lusignan
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom,Royal College of General Practitioners, London, United Kingdom
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12
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Hoang U, Button E, Armstrong M, Okusi C, Ellis J, Zambon M, Anand S, Delanerolle G, Hobbs FDR, van Summeren J, Paget J, de Lusignan S. Assessing the Clinical and Socioeconomic Burden of Respiratory Syncytial Virus in Children Aged Under 5 Years in Primary Care: Protocol for a Prospective Cohort Study in England and Report on the Adaptations of the Study to the COVID-19 Pandemic. JMIR Res Protoc 2022; 11:e38026. [PMID: 35960819 PMCID: PMC9415952 DOI: 10.2196/38026] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Revised: 07/21/2022] [Accepted: 08/10/2022] [Indexed: 11/13/2022] Open
Abstract
Background Respiratory syncytial virus (RSV) commonly causes lower respiratory tract infections and hospitalization in children. In 2019-2020, the Europe-wide RSV ComNet standardized study protocol was developed to measure the clinical and socioeconomic disease burden of RSV infections among children aged <5 years in primary care. RSV has a recognized seasonality in England. Objective We aimed to describe (1) the adaptations of the RSV ComNet standardized study protocol for England and (2) the challenges of conducting the study during the COVID-19 pandemic. Methods This study was conducted by the Oxford-Royal College of General Practitioners Research and Surveillance Centre—the English national primary care sentinel network. We invited all (N=248) general practices within the network that undertook virology sampling to participate in the study by recruiting eligible patients (registered population: n=3,056,583). Children aged <5 years with the following case definition of RSV infection were included in the study: those consulting a health care practitioner in primary care with symptoms meeting the World Health Organization’s definition of acute respiratory illness or influenza-like illness who have laboratory-confirmed RSV infection. The parents/guardians of these cases were asked to complete 2 previously validated questionnaires (14 and 30 days postsampling). A sample size of at least 100 RSV-positive cases is required to estimate the percentage of children that consult in primary care who need hospitalization. Assuming a swab positivity rate of 20% in children aged <5 years, we estimated that 500 swabs are required. We adapted our method for the pandemic by extending sampling planned for winter 2020-2021 to a rolling data collection, allowing verbal consent and introducing home swabbing because of increased web-based consultations during the COVID-19 pandemic. Results The preliminary results of the data collection between International Organization for Standardization (ISO) weeks 1-41 in 2021 are described. There was no RSV detected in the winter of 2020-2021 through the study. The first positive RSV swab collected through the sentinel network in England was collected in ISO week 17 and then every week since ISO week 25. In total, 16 (N=248, 6.5%) of the virology-sampling practices volunteered to participate; these were high-sampling practices collecting the majority of eligible swabs across the sentinel network—200 (43.8%) out of 457 swabs, of which 54 (N=200, 27%) were positive for RSV. Conclusions Measures to control the COVID-19 pandemic meant there was no circulating RSV last winter; however, RSV has circulated out of season, as detected by the sentinel network. The sentinel network practices have collected 40% (200/500) of the required samples, and 27% (54/200) were RSV positive. We have demonstrated the feasibility of implementing a European-standardized RSV disease burden study protocol in England during a pandemic, and we now need to recruit to this adapted protocol. International Registered Report Identifier (IRRID) DERR1-10.2196/38026
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Affiliation(s)
- Uy Hoang
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Elizabeth Button
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | | | - Cecilia Okusi
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Joanna Ellis
- Reference Microbiology Services, United Kingdom Health Security Agency, London, United Kingdom
| | - Maria Zambon
- Reference Microbiology Services, United Kingdom Health Security Agency, London, United Kingdom
| | - Sneha Anand
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Gayathri Delanerolle
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - F D Richard Hobbs
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | | | - John Paget
- Netherlands Institute for Health Services Research, Utrecht, Netherlands
| | - Simon de Lusignan
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
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Delanerolle G, Williams R, Stipancic A, Byford R, Forbes A, Tsang RSM, Anand SN, Bradley D, Murphy S, Akbari A, Bedston S, Lyons RA, Owen R, Torabi F, Beggs J, Chuter A, Balharry D, Joy M, Sheikh A, Hobbs FDR, de Lusignan S. Methodological Issues in Using a Common Data Model of COVID-19 Vaccine Uptake and Important Adverse Events of Interest: Feasibility Study of Data and Connectivity COVID-19 Vaccines Pharmacovigilance in the United Kingdom. JMIR Form Res 2022; 6:e37821. [PMID: 35786634 PMCID: PMC9400842 DOI: 10.2196/37821] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Revised: 05/16/2022] [Accepted: 05/17/2022] [Indexed: 01/13/2023] Open
Abstract
BACKGROUND The Data and Connectivity COVID-19 Vaccines Pharmacovigilance (DaC-VaP) UK-wide collaboration was created to monitor vaccine uptake and effectiveness and provide pharmacovigilance using routine clinical and administrative data. To monitor these, pooled analyses may be needed. However, variation in terminologies present a barrier as England uses the Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT), while the rest of the United Kingdom uses the Read v2 terminology in primary care. The availability of data sources is not uniform across the United Kingdom. OBJECTIVE This study aims to use the concept mappings in the Observational Medical Outcomes Partnership (OMOP) common data model (CDM) to identify common concepts recorded and to report these in a repeated cross-sectional study. We planned to do this for vaccine coverage and 2 adverse events of interest (AEIs), cerebral venous sinus thrombosis (CVST) and anaphylaxis. We identified concept mappings to SNOMED CT, Read v2, the World Health Organization's International Classification of Disease Tenth Revision (ICD-10) terminology, and the UK Dictionary of Medicines and Devices (dm+d). METHODS Exposures and outcomes of interest to DaC-VaP for pharmacovigilance studies were selected. Mappings of these variables to different terminologies used across the United Kingdom's devolved nations' health services were identified from the Observational Health Data Sciences and Informatics (OHDSI) Automated Terminology Harmonization, Extraction, and Normalization for Analytics (ATHENA) online browser. Lead analysts from each nation then confirmed or added to the mappings identified. These mappings were then used to report AEIs in a common format. We reported rates for windows of 0-2 and 3-28 days postvaccine every 28 days. RESULTS We listed the mappings between Read v2, SNOMED CT, ICD-10, and dm+d. For vaccine exposure, we found clear mapping from OMOP to our clinical terminologies, though dm+d had codes not listed by OMOP at the time of searching. We found a list of CVST and anaphylaxis codes. For CVST, we had to use a broader cerebral venous thrombosis conceptual approach to include Read v2. We identified 56 SNOMED CT codes, of which we selected 47 (84%), and 15 Read v2 codes. For anaphylaxis, our refined search identified 60 SNOMED CT codes and 9 Read v2 codes, of which we selected 10 (17%) and 4 (44%), respectively, to include in our repeated cross-sectional studies. CONCLUSIONS This approach enables the use of mappings to different terminologies within the OMOP CDM without the need to catalogue an entire database. However, Read v2 has less granular concepts than some terminologies, such as SNOMED CT. Additionally, the OMOP CDM cannot compensate for limitations in the clinical coding system. Neither Read v2 nor ICD-10 is sufficiently granular to enable CVST to be specifically flagged. Hence, any pooled analysis will have to be at the less specific level of cerebrovascular venous thrombosis. Overall, the mappings within this CDM are useful, and our method could be used for rapid collaborations where there are only a limited number of concepts to pool.
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Affiliation(s)
- Gayathri Delanerolle
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Robert Williams
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Ana Stipancic
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
- Royal College of General Practitioners, London, United Kingdom
| | - Rachel Byford
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Anna Forbes
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Ruby S M Tsang
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Sneha N Anand
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Declan Bradley
- Centre for Public Health, Queen's University Belfast, Belfast, United Kingdom
- Public Health Agency, Belfast, United Kingdom
| | - Siobhán Murphy
- Centre for Public Health, Queen's University Belfast, Belfast, United Kingdom
| | - Ashley Akbari
- Population Data Science, Swansea University, Swansea, United Kingdom
| | - Stuart Bedston
- Population Data Science, Swansea University, Swansea, United Kingdom
| | - Ronan A Lyons
- Population Data Science, Swansea University, Swansea, United Kingdom
| | - Rhiannon Owen
- Population Data Science, Swansea University, Swansea, United Kingdom
| | - Fatemeh Torabi
- Population Data Science, Swansea University, Swansea, United Kingdom
| | - Jillian Beggs
- Usher Institute, University of Edinburgh, Edingburgh, United Kingdom
| | - Antony Chuter
- Usher Institute, University of Edinburgh, Edingburgh, United Kingdom
| | | | - Mark Joy
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Aziz Sheikh
- Usher Institute, University of Edinburgh, Edingburgh, United Kingdom
| | - F D Richard Hobbs
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Simon de Lusignan
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
- Royal College of General Practitioners, London, United Kingdom
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Sociodemographic disparities in COVID-19 seroprevalence across England in the Oxford RCGP primary care sentinel network. J Infect 2022; 84:814-824. [PMID: 35405169 PMCID: PMC8993757 DOI: 10.1016/j.jinf.2022.04.016] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2021] [Revised: 04/01/2022] [Accepted: 04/04/2022] [Indexed: 01/11/2023]
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.
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Whitaker HJ, Tsang RSM, Byford R, Andrews NJ, Sherlock J, Sebastian Pillai P, Williams J, Button E, Campbell H, Sinnathamby M, Victor W, Anand S, Linley E, Hewson J, DArchangelo S, Otter AD, Ellis J, Hobbs RFD, Howsam G, Zambon M, Ramsay M, Brown KE, de Lusignan S, Amirthalingam G, Lopez Bernal J. Pfizer-BioNTech and Oxford AstraZeneca COVID-19 vaccine effectiveness and immune response amongst individuals in clinical risk groups. J Infect 2022; 84:675-683. [PMID: 34990709 PMCID: PMC8720678 DOI: 10.1016/j.jinf.2021.12.044] [Citation(s) in RCA: 73] [Impact Index Per Article: 24.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Accepted: 12/29/2021] [Indexed: 01/30/2023]
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.
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Affiliation(s)
- Heather J Whitaker
- Statistics, Modelling and Economics Department, UK Health Security Agency (formerly Public Health England), 61 Colindale Avenue, London NW9 5EQ, UK
| | - Ruby S M Tsang
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford OX2 6GG, UK
| | - Rachel Byford
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford OX2 6GG, UK
| | - Nick J Andrews
- Statistics, Modelling and Economics Department, UK Health Security Agency (formerly Public Health England), 61 Colindale Avenue, London NW9 5EQ, UK; Immunisation and Vaccine Preventable Diseases Division, UK Health Security Agency (formerly Public Health England), 61 Colindale Avenue, London NW9 5EQ, UK
| | - Julian Sherlock
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford OX2 6GG, UK
| | - Praveen Sebastian Pillai
- Virus Reference Laboratory, UK Health Security Agency (formerly Public Health England), 61 Colindale Avenue, London NW9 5EQ, UK
| | - John Williams
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford OX2 6GG, UK
| | - Elizabeth Button
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford OX2 6GG, UK
| | - Helen Campbell
- Immunisation and Vaccine Preventable Diseases Division, UK Health Security Agency (formerly Public Health England), 61 Colindale Avenue, London NW9 5EQ, UK
| | - Mary Sinnathamby
- Immunisation and Vaccine Preventable Diseases Division, UK Health Security Agency (formerly Public Health England), 61 Colindale Avenue, London NW9 5EQ, UK
| | - William Victor
- Royal College of General Practitioners Research and Surveillance Centre, Euston Square, London, NW1 2FB, UK
| | - Sneha Anand
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford OX2 6GG, UK
| | - Ezra Linley
- Vaccine Evaluation Unit, UK Health Security Agency (formerly Public Health England)), Manchester M13 9WL, UK
| | - Jacqueline Hewson
- Diagnostics and Genomics, UK Health Security Agency (formerly Public Health England), Porton Down, Salisbury SP4 0JG, UK
| | - Silvia DArchangelo
- Diagnostics and Genomics, UK Health Security Agency (formerly Public Health England), Porton Down, Salisbury SP4 0JG, UK
| | - Ashley D Otter
- Diagnostics and Genomics, UK Health Security Agency (formerly Public Health England), Porton Down, Salisbury SP4 0JG, UK
| | - Joanna Ellis
- Immunisation and Vaccine Preventable Diseases Division, UK Health Security Agency (formerly Public Health England), 61 Colindale Avenue, London NW9 5EQ, UK; Virus Reference Laboratory, UK Health Security Agency (formerly Public Health England), 61 Colindale Avenue, London NW9 5EQ, UK
| | - Richard F D Hobbs
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford OX2 6GG, UK
| | - Gary Howsam
- Royal College of General Practitioners Research and Surveillance Centre, Euston Square, London, NW1 2FB, UK
| | - Maria Zambon
- Virus Reference Laboratory, UK Health Security Agency (formerly Public Health England), 61 Colindale Avenue, London NW9 5EQ, UK
| | - Mary Ramsay
- Immunisation and Vaccine Preventable Diseases Division, UK Health Security Agency (formerly Public Health England), 61 Colindale Avenue, London NW9 5EQ, UK
| | - Kevin E Brown
- Immunisation and Vaccine Preventable Diseases Division, UK Health Security Agency (formerly Public Health England), 61 Colindale Avenue, London NW9 5EQ, UK
| | - Simon de Lusignan
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford OX2 6GG, UK; Royal College of General Practitioners Research and Surveillance Centre, Euston Square, London, NW1 2FB, UK
| | - Gayatri Amirthalingam
- Immunisation and Vaccine Preventable Diseases Division, UK Health Security Agency (formerly Public Health England), 61 Colindale Avenue, London NW9 5EQ, UK
| | - Jamie Lopez Bernal
- Immunisation and Vaccine Preventable Diseases Division, UK Health Security Agency (formerly Public Health England), 61 Colindale Avenue, London NW9 5EQ, UK.
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Consultations for clinical features of possible cancer and associated urgent referrals before and during the COVID-19 pandemic: an observational cohort study from English primary care. Br J Cancer 2021; 126:948-956. [PMID: 34934176 PMCID: PMC8691390 DOI: 10.1038/s41416-021-01666-6] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Revised: 11/15/2021] [Accepted: 12/02/2021] [Indexed: 02/07/2023] Open
Abstract
Background It remains unclear to what extent reductions in urgent referrals for suspected cancer during the COVID-19 pandemic were the result of fewer patients attending primary care compared to GPs referring fewer patients. Methods Cohort study including electronic health records data from 8,192,069 patients from 663 English practices. Weekly consultation rates, cumulative consultations and referrals were calculated for 28 clinical features from the NICE suspected cancer guidelines. Clinical feature consultation rate ratios (CRR) and urgent referral rate ratios (RRR) compared time periods in 2020 with 2019. Findings Consultations for cancer clinical features decreased by 24.19% (95% CI: 24.04–24.34%) between 2019 and 2020, particularly in the 6–12 weeks following the first national lockdown. Urgent referrals for clinical features decreased by 10.47% (95% CI: 9.82–11.12%) between 2019 and 2020. Overall, once patients consulted with primary care, GPs urgently referred a similar or greater proportion of patients compared to previous years. Conclusion Due to the significant fall in patients consulting with clinical features of cancer there was a lower than expected number of urgent referrals in 2020. Sustained efforts should be made throughout the pandemic to encourage the public to consult their GP with cancer clinical features.
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PRINCIPLE trial demonstrates scope for in-pandemic improvement in primary care antibiotic stewardship: a retrospective sentinel network cohort study. BJGP Open 2021; 5:BJGPO.2021.0087. [PMID: 34312163 PMCID: PMC8596310 DOI: 10.3399/bjgpo.2021.0087] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Accepted: 06/09/2021] [Indexed: 10/31/2022] Open
Abstract
BACKGROUND The 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 COVID-19. AIM To explore the extent of azithromycin and doxycycline in-pandemic use, and the scope for trial findings impacting on practice. DESIGN & SETTING Crude 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). METHOD A negative binomial model was used 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). RESULTS Azithromycin 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 of 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, P<0.0001), for every unit rise in confirmed COVID-19 there was an associated 3% rise in prescription (IRR = 1.03, 95% CI = 1.02 to 1.03, P<0.0001); whereas these measures were static for doxycycline. CONCLUSION PRINCIPLE demonstrates scope for improved antimicrobial stewardship during a pandemic.
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18
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Espinosa-Gonzalez AB, Neves AL, Fiorentino F, Prociuk D, Husain L, Ramtale SC, Mi E, Mi E, Macartney J, Anand SN, Sherlock J, Saravanakumar K, Mayer E, de Lusignan S, Greenhalgh T, Delaney BC. Predicting Risk of Hospital Admission in Patients With Suspected COVID-19 in a Community Setting: Protocol for Development and Validation of a Multivariate Risk Prediction Tool. JMIR Res Protoc 2021; 10:e29072. [PMID: 33939619 PMCID: PMC8153031 DOI: 10.2196/29072] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Revised: 04/01/2021] [Accepted: 04/01/2021] [Indexed: 01/30/2023] Open
Abstract
Background During the pandemic, remote consultations have become the norm for assessing patients with signs and symptoms of COVID-19 to decrease the risk of transmission. This has intensified the clinical uncertainty already experienced by primary care clinicians when assessing patients with suspected COVID-19 and has prompted the use of risk prediction scores, such as the National Early Warning Score (NEWS2), to assess severity and guide treatment. However, the risk prediction tools available have not been validated in a community setting and are not designed to capture the idiosyncrasies of COVID-19 infection. Objective The objective of this study is to produce a multivariate risk prediction tool, RECAP-V1 (Remote COVID-19 Assessment in Primary Care), to support primary care clinicians in the identification of those patients with COVID-19 that are at higher risk of deterioration and facilitate the early escalation of their treatment with the aim of improving patient outcomes. Methods The study follows a prospective cohort observational design, whereby patients presenting in primary care with signs and symptoms suggestive of COVID-19 will be followed and their data linked to hospital outcomes (hospital admission and death). Data collection will be carried out by primary care clinicians in four arms: North West London Clinical Commissioning Groups (NWL CCGs), Oxford-Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC), Covid Clinical Assessment Service (CCAS), and South East London CCGs (Doctaly platform). The study involves the use of an electronic template that incorporates a list of items (known as RECAP-V0) thought to be associated with disease outcome according to previous qualitative work. Data collected will be linked to patient outcomes in highly secure environments. We will then use multivariate logistic regression analyses for model development and validation. Results Recruitment of participants started in October 2020. Initially, only the NWL CCGs and RCGP RSC arms were active. As of March 24, 2021, we have recruited a combined sample of 3827 participants in these two arms. CCAS and Doctaly joined the study in February 2021, with CCAS starting the recruitment process on March 15, 2021. The first part of the analysis (RECAP-V1 model development) is planned to start in April 2021 using the first half of the NWL CCGs and RCGP RSC combined data set. Posteriorly, the model will be validated with the rest of the NWL CCGs and RCGP RSC data as well as the CCAS and Doctaly data sets. The study was approved by the Research Ethics Committee on May 27, 2020 (Integrated Research Application System number: 283024, Research Ethics Committee reference number: 20/NW/0266) and badged as National Institute of Health Research Urgent Public Health Study on October 14, 2020. Conclusions We believe the validated RECAP-V1 early warning score will be a valuable tool for the assessment of severity in patients with suspected COVID-19 in the community, either in face-to-face or remote consultations, and will facilitate the timely escalation of treatment with the potential to improve patient outcomes. Trial Registration ISRCTN registry ISRCTN13953727; https://www.isrctn.com/ISRCTN13953727 International Registered Report Identifier (IRRID) DERR1-10.2196/29072
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Affiliation(s)
| | - Ana Luisa Neves
- Patient Safety Translational Research Centre, Institute of Global Health Innovation, Imperial College London, London, United Kingdom.,Center for Health Technology and Services Research / Department of Community Medicine, Health Information and Decision (CINTESIS/MEDCIDS), Faculty of Medicine, University of Porto, Porto, Portugal
| | - Francesca Fiorentino
- Department of Surgery and Cancer, Imperial College London, London, United Kingdom
| | - Denys Prociuk
- Department of Surgery and Cancer, Imperial College London, London, United Kingdom
| | - Laiba Husain
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | | | - Emma Mi
- Department of Surgery and Cancer, Imperial College London, London, United Kingdom
| | - Ella Mi
- Department of Surgery and Cancer, Imperial College London, London, United Kingdom
| | - Jack Macartney
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Sneha N Anand
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Julian Sherlock
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Kavitha Saravanakumar
- Whole Systems Integrated Care, North West London Clinical Commissioning Group, London, United Kingdom
| | - Erik Mayer
- Department of Surgery and Cancer, Imperial College London, London, United Kingdom
| | - Simon de Lusignan
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Trisha Greenhalgh
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Brendan C Delaney
- Department of Surgery and Cancer, Imperial College London, London, United Kingdom
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19
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Bernal JL, Sinnathamby MA, Elgohari S, Zhao H, Obi C, Coughlan L, Lampos V, Simmons R, Tessier E, Campbell H, McDonald S, Ellis J, Hughes H, Smith G, Joy M, Tripathy M, Byford R, Ferreira F, de Lusignan S, Zambon M, Dabrera G, Brown K, Saliba V, Andrews N, Amirthalingam G, Mandal S, Edelstein M, Elliot AJ, Ramsay M. The impact of social and physical distancing measures on COVID-19 activity in England: findings from a multi-tiered surveillance system. Euro Surveill 2021; 26:2001062. [PMID: 33739255 PMCID: PMC7976385 DOI: 10.2807/1560-7917.es.2021.26.11.2001062] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2020] [Accepted: 10/21/2020] [Indexed: 01/22/2023] Open
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.
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Affiliation(s)
- Jamie Lopez Bernal
- Public Health England COVID-19 Surveillance Cell, London, United Kingdom
| | - Mary A Sinnathamby
- Public Health England COVID-19 Surveillance Cell, London, United Kingdom
| | - Suzanne Elgohari
- Public Health England COVID-19 Surveillance Cell, London, United Kingdom
| | - Hongxin Zhao
- Public Health England COVID-19 Surveillance Cell, London, United Kingdom
| | - Chinelo Obi
- Public Health England COVID-19 Surveillance Cell, London, United Kingdom
| | - Laura Coughlan
- Public Health England COVID-19 Surveillance Cell, London, United Kingdom
| | - Vasileios Lampos
- Department of Computer Science, University College London, London, United Kingdom
| | - Ruth Simmons
- Public Health England COVID-19 Surveillance Cell, London, United Kingdom
| | - Elise Tessier
- Public Health England COVID-19 Surveillance Cell, London, United Kingdom
| | - Helen Campbell
- Public Health England COVID-19 Surveillance Cell, London, United Kingdom
| | - Suzanna McDonald
- Public Health England COVID-19 Surveillance Cell, London, United Kingdom
| | - Joanna Ellis
- Public Health England COVID-19 Virology Cell, London, United Kingdom
| | - Helen Hughes
- Public Health England COVID-19 Surveillance Cell, London, United Kingdom
| | - Gillian Smith
- Public Health England COVID-19 Surveillance Cell, London, United Kingdom
| | - Mark Joy
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
- Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC), London, United Kingdom
| | - Manasa Tripathy
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
- Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC), London, United Kingdom
| | - Rachel Byford
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
- Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC), London, United Kingdom
| | - Filipa Ferreira
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
- Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC), London, United Kingdom
| | - Simon de Lusignan
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
- Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC), London, United Kingdom
| | - Maria Zambon
- Public Health England COVID-19 Virology Cell, London, United Kingdom
| | - Gavin Dabrera
- Public Health England COVID-19 Epidemiology Cell, London, United Kingdom
| | - Kevin Brown
- Public Health England COVID-19 Surveillance Cell, London, United Kingdom
- Public Health England COVID-19 Virology Cell, London, United Kingdom
| | - Vanessa Saliba
- Public Health England COVID-19 Surveillance Cell, London, United Kingdom
| | - Nick Andrews
- Public Health England COVID-19 Surveillance Cell, London, United Kingdom
| | | | - Sema Mandal
- Public Health England COVID-19 Surveillance Cell, London, United Kingdom
| | - Michael Edelstein
- Public Health England COVID-19 Surveillance Cell, London, United Kingdom
| | - Alex J Elliot
- Public Health England COVID-19 Surveillance Cell, London, United Kingdom
| | - Mary Ramsay
- Public Health England COVID-19 Surveillance Cell, London, United Kingdom
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