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Understanding the Challenges and Uncertainties of Seroprevalence Studies for SARS-CoV-2

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  • David McConnell

    (National Centre for Pharmacoeconomics, St James’s Hospital, D08 HD53 Dublin, Ireland
    Department of Pharmacology and Therapeutics, Trinity College Dublin, D08 HD53 Dublin, Ireland)

  • Conor Hickey

    (National Centre for Pharmacoeconomics, St James’s Hospital, D08 HD53 Dublin, Ireland
    Department of Pharmacology and Therapeutics, Trinity College Dublin, D08 HD53 Dublin, Ireland)

  • Norma Bargary

    (Health Research Institute and MACSI, University of Limerick, V94 T9PX Limerick, Ireland)

  • Lea Trela-Larsen

    (National Centre for Pharmacoeconomics, St James’s Hospital, D08 HD53 Dublin, Ireland
    Department of Pharmacology and Therapeutics, Trinity College Dublin, D08 HD53 Dublin, Ireland)

  • Cathal Walsh

    (National Centre for Pharmacoeconomics, St James’s Hospital, D08 HD53 Dublin, Ireland
    Health Research Institute and MACSI, University of Limerick, V94 T9PX Limerick, Ireland)

  • Michael Barry

    (National Centre for Pharmacoeconomics, St James’s Hospital, D08 HD53 Dublin, Ireland
    Department of Pharmacology and Therapeutics, Trinity College Dublin, D08 HD53 Dublin, Ireland)

  • Roisin Adams

    (National Centre for Pharmacoeconomics, St James’s Hospital, D08 HD53 Dublin, Ireland
    Department of Pharmacology and Therapeutics, Trinity College Dublin, D08 HD53 Dublin, Ireland)

Abstract

SARS-CoV-2 continues to widely circulate in populations globally. Underdetection is acknowledged and is problematic when attempting to capture the true prevalence. Seroprevalence studies, where blood samples from a population sample are tested for SARS-CoV-2 antibodies that react to the SARS-CoV-2 virus, are a common method for estimating the proportion of people previously infected with the virus in a given population. However, obtaining reliable estimates from seroprevalence studies is challenging for a number of reasons, and the uncertainty in the results is often overlooked by scientists, policy makers, and the media. This paper reviews the methodological issues that arise in designing these studies, and the main sources of uncertainty that affect the results. We discuss the choice of study population, recruitment of subjects, uncertainty surrounding the accuracy of antibody tests, and the relationship between antibodies and infection over time. Understanding these issues can help the reader to interpret and critically evaluate the results of seroprevalence studies.

Suggested Citation

  • David McConnell & Conor Hickey & Norma Bargary & Lea Trela-Larsen & Cathal Walsh & Michael Barry & Roisin Adams, 2021. "Understanding the Challenges and Uncertainties of Seroprevalence Studies for SARS-CoV-2," IJERPH, MDPI, vol. 18(9), pages 1-19, April.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:9:p:4640-:d:544414
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    References listed on IDEAS

    as
    1. Andrew Gelman & Bob Carpenter, 2020. "Bayesian analysis of tests with unknown specificity and sensitivity," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(5), pages 1269-1283, November.
    2. Geneletti, Sara & Mason, Alexina & Best, Nicky, 2011. "Adjusting for selection effects in epidemiologic studies: why sensitivity analysis is the only “solution”," LSE Research Online Documents on Economics 31520, London School of Economics and Political Science, LSE Library.
    3. Niels Keiding & Thomas A. Louis, 2016. "Perils and potentials of self-selected entry to epidemiological studies and surveys," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 179(2), pages 319-376, February.
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    1. Stefania Paduano & Pasquale Galante & Nausicaa Berselli & Luca Ugolotti & Alberto Modenese & Alessandro Poggi & Marcella Malavolti & Sara Turchi & Isabella Marchesi & Roberto Vivoli & Paola Perlini & , 2022. "Seroprevalence Survey of Anti-SARS-CoV-2 Antibodies in a Population of Emilia-Romagna Region, Northern Italy," IJERPH, MDPI, vol. 19(13), pages 1-11, June.

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