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Improving the representativeness of UK’s national COVID-19 Infection Survey through spatio-temporal regression and post-stratification

Author

Listed:
  • Koen B. Pouwels

    (University of Oxford
    The National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance at the University of Oxford)

  • David W. Eyre

    (The National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance at the University of Oxford
    University of Oxford
    Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital
    University of Oxford)

  • Thomas House

    (University of Manchester
    Sci-Tech)

  • Ben Aspey

    (Office for National Statistics)

  • Philippa C. Matthews

    (The Francis Crick Institute
    University of Oxford
    University College London)

  • Nicole Stoesser

    (The National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance at the University of Oxford
    Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital
    University of Oxford
    University of Oxford)

  • John N. Newton

    (University of Exeter)

  • Ian Diamond

    (Office for National Statistics)

  • Ruth Studley

    (Office for National Statistics)

  • Nick G. H. Taylor

    (Office for National Statistics)

  • John I. Bell

    (University of Oxford)

  • Jeremy Farrar

    (Wellcome Trust)

  • Jaison Kolenchery

    (Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital
    University of Oxford)

  • Brian D. Marsden

    (University of Oxford
    University of Oxford)

  • Sarah Hoosdally

    (University of Oxford)

  • E. Yvonne Jones

    (University of Oxford)

  • David I. Stuart

    (University of Oxford)

  • Derrick W. Crook

    (The National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance at the University of Oxford
    Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital
    University of Oxford
    University of Oxford)

  • Tim E. A. Peto

    (The National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance at the University of Oxford
    Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital
    University of Oxford
    University of Oxford)

  • A. Sarah Walker

    (The National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance at the University of Oxford
    University of Oxford
    UCL)

Abstract

Population-representative estimates of SARS-CoV-2 infection prevalence and antibody levels in specific geographic areas at different time points are needed to optimise policy responses. However, even population-wide surveys are potentially impacted by biases arising from differences in participation rates across key groups. Here, we used spatio-temporal regression and post-stratification models to UK’s national COVID-19 Infection Survey (CIS) to obtain representative estimates of PCR positivity (6,496,052 tests) and antibody prevalence (1,941,333 tests) for different regions, ages and ethnicities (7-December-2020 to 4-May-2022). Not accounting for vaccination status through post-stratification led to small underestimation of PCR positivity, but more substantial overestimations of antibody levels in the population (up to 21 percentage points), particularly in groups with low vaccine uptake in the general population. There was marked variation in the relative contribution of different areas and age-groups to each wave. Future analyses of infectious disease surveys should take into account major drivers of outcomes of interest that may also influence participation, with vaccination being an important factor to consider.

Suggested Citation

  • Koen B. Pouwels & David W. Eyre & Thomas House & Ben Aspey & Philippa C. Matthews & Nicole Stoesser & John N. Newton & Ian Diamond & Ruth Studley & Nick G. H. Taylor & John I. Bell & Jeremy Farrar & J, 2024. "Improving the representativeness of UK’s national COVID-19 Infection Survey through spatio-temporal regression and post-stratification," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-49201-4
    DOI: 10.1038/s41467-024-49201-4
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    References listed on IDEAS

    as
    1. Mario Morvan & Anna Lo Jacomo & Celia Souque & Matthew J. Wade & Till Hoffmann & Koen Pouwels & Chris Lilley & Andrew C. Singer & Jonathan Porter & Nicholas P. Evens & David I. Walker & Joshua T. Bunc, 2022. "An analysis of 45 large-scale wastewater sites in England to estimate SARS-CoV-2 community prevalence," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    2. Riva, Mylene & Curtis, Sarah & Gauvin, Lise & Fagg, James, 2009. "Unravelling the extent of inequalities in health across urban and rural areas: Evidence from a national sample in England," Social Science & Medicine, Elsevier, vol. 68(4), pages 654-663, February.
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