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

Whitaker, Heather; Tsang, Ruby S M; Byford, Rachel; Aspden, Carole; Button, Elizabeth; Pillai, Praveen Sebastian; Jamie, Gavin; Kar, Debasish; Williams, John; Sinnathamby, Mary; Marsden, Gemma; Elson, William H.; Leston, Meredith; Anand, Sneha; Okusi, Cecilia; Fan, Xuejuan; Linley, Ezra; Rowe, Cathy; D’Arcangelo, Silvia; Otter, Ashley; Ellis, Joanna; Hobbs, FD Richard; Tzortziou-Brown, Victoria; Zambon, Maria; Ramsay, Mary; Brown, Kevin E.; Amirthalingam, Gayatri; Andrews, Nick; Lusignan, Simon de

doi:10.1016/j.jinf.2023.08.005

Cited by 7 publications

(2 citation statements)

References 28 publications

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“…We do not have sufficient coverage of all high-risk settings and do not collect data from hospitals where nosocomial infection is common. We can readily identify community-recorded vulnerable populations, and we term these “risk groups” [ 60 ]. We do not directly measure whether health care systems are overwhelmed, but we do record community rates of illnesses compared with other years [ 61 ].…”

Section: Resultsmentioning

confidence: 99%

“…In Domain III ( informing about health interventions ), we are able to infer the impact of interventions, such as lockdowns and shielding, during the COVID-19 pandemic, and we can see from our data the impact of school closures [ 62 , 63 ]. We are strong in measuring vaccine uptake and effectiveness, and our data have been used for vaccine adverse events [ 60 , 64 ]. We only have limited abilities to assess the effectiveness of some antivirals and other therapeutics owing to their central administration, and our capabilities are greater where these are recorded in the GP CMR.…”

Section: Resultsmentioning

confidence: 99%

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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

Gu,

Watson,

Agrawal

et al. 2024

JMIR Public Health Surveill

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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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Section: Resultsmentioning

confidence: 99%