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Persistent COVID-19 symptoms in a community study of 606,434 people in England

Author

Listed:
  • Matthew Whitaker

    (Imperial College London
    Imperial College London)

  • Joshua Elliott

    (Imperial College Healthcare NHS Trust
    Imperial College London)

  • Marc Chadeau-Hyam

    (Imperial College London
    Imperial College London)

  • Steven Riley

    (Imperial College London
    Imperial College London
    Imperial College London)

  • Ara Darzi

    (Imperial College Healthcare NHS Trust
    Institute of Global Health Innovation at Imperial College London)

  • Graham Cooke

    (Imperial College Healthcare NHS Trust
    Imperial College London
    National Institute for Health Research Imperial Biomedical Research Centre)

  • Helen Ward

    (Imperial College Healthcare NHS Trust
    Imperial College London
    National Institute for Health Research Imperial Biomedical Research Centre)

  • Paul Elliott

    (Imperial College London
    Imperial College London
    Imperial College Healthcare NHS Trust
    National Institute for Health Research Imperial Biomedical Research Centre)

Abstract

Long COVID remains a broadly defined syndrome, with estimates of prevalence and duration varying widely. We use data from rounds 3–5 of the REACT-2 study (n = 508,707; September 2020 – February 2021), a representative community survey of adults in England, and replication data from round 6 (n = 97,717; May 2021) to estimate the prevalence and identify predictors of persistent symptoms lasting 12 weeks or more; and unsupervised learning to cluster individuals by reported symptoms. At 12 weeks in rounds 3–5, 37.7% experienced at least one symptom, falling to 21.6% in round 6. Female sex, increasing age, obesity, smoking, vaping, hospitalisation with COVID-19, deprivation, and being a healthcare worker are associated with higher probability of persistent symptoms in rounds 3–5, and Asian ethnicity with lower probability. Clustering analysis identifies a subset of participants with predominantly respiratory symptoms. Managing the long-term sequelae of COVID-19 will remain a major challenge for affected individuals and their families and for health services.

Suggested Citation

  • Matthew Whitaker & Joshua Elliott & Marc Chadeau-Hyam & Steven Riley & Ara Darzi & Graham Cooke & Helen Ward & Paul Elliott, 2022. "Persistent COVID-19 symptoms in a community study of 606,434 people in England," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-29521-z
    DOI: 10.1038/s41467-022-29521-z
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    References listed on IDEAS

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    2. Bethan Davies & Brandon L. Parkes & James Bennett & Daniela Fecht & Marta Blangiardo & Majid Ezzati & Paul Elliott, 2021. "Community factors and excess mortality in first wave of the COVID-19 pandemic in England," Nature Communications, Nature, vol. 12(1), pages 1-9, December.
    3. Hennig, Christian, 2007. "Cluster-wise assessment of cluster stability," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 258-271, September.
    4. Linzer, Drew A. & Lewis, Jeffrey B., 2011. "poLCA: An R Package for Polytomous Variable Latent Class Analysis," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 42(i10).
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    Cited by:

    1. Fischer, Kai & Reade, J. James & Schmal, W. Benedikt, 2022. "What cannot be cured must be endured: The long-lasting effect of a COVID-19 infection on workplace productivity," Labour Economics, Elsevier, vol. 79(C).
    2. Anna Irene Vedel Sørensen & Lampros Spiliopoulos & Peter Bager & Nete Munk Nielsen & Jørgen Vinsløv Hansen & Anders Koch & Inger Kristine Meder & Steen Ethelberg & Anders Hviid, 2022. "A nationwide questionnaire study of post-acute symptoms and health problems after SARS-CoV-2 infection in Denmark," Nature Communications, Nature, vol. 13(1), pages 1-8, December.

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