True prevalence of long-COVID in a nationwide, population cohort study

Claire E. Hastie, David J. Lowe, Andrew McAuley, Nicholas L. Mills, Andrew J. Winter, Corri Black, Janet T. Scott, Catherine A. O’Donnell, David N. Blane, Susan Browne, Tracy R. Ibbotson and Jill P. Pell ()
Additional contact information
Claire E. Hastie: University of Glasgow
David J. Lowe: University of Glasgow
Andrew McAuley: Public Health Scotland, Meridian Court
Nicholas L. Mills: University of Edinburgh
Andrew J. Winter: Sandyford Sexual Health Services, NHS Greater Glasgow and Clyde
Corri Black: University of Aberdeen
Janet T. Scott: University of Glasgow
Catherine A. O’Donnell: University of Glasgow
David N. Blane: University of Glasgow
Susan Browne: University of Glasgow
Tracy R. Ibbotson: University of Glasgow
Jill P. Pell: University of Glasgow

Nature Communications, 2023, vol. 14, issue 1, 1-6

Abstract: Abstract Long-COVID prevalence estimates vary widely and should take account of symptoms that would have occurred anyway. Here we determine the prevalence of symptoms attributable to SARS-CoV-2 infection, taking account of background rates and confounding, in a nationwide population cohort study of 198,096 Scottish adults. 98,666 (49.8%) had symptomatic laboratory-confirmed SARS-CoV-2 infections and 99,430 (50.2%) were age-, sex-, and socioeconomically-matched and never-infected. While 41,775 (64.5%) reported at least one symptom 6 months following SARS-CoV-2 infection, this was also true of 34,600 (50.8%) of those never-infected. The crude prevalence of one or more symptom attributable to SARS-CoV-2 infection was 13.8% (13.2%,14.3%), 12.8% (11.9%,13.6%), and 16.3% (14.4%,18.2%) at 6, 12, and 18 months respectively. Following adjustment for potential confounders, these figures were 6.6% (6.3%, 6.9%), 6.5% (6.0%, 6.9%) and 10.4% (9.1%, 11.6%) respectively. Long-COVID is characterised by a wide range of symptoms that, apart from altered taste and smell, are non-specific. Care should be taken in attributing symptoms to previous SARS-CoV-2 infection.

Date: 2023
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DOI: 10.1038/s41467-023-43661-w

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