Indicators of recent COVID-19 infection status: findings from a large occupational cohort of staff and postgraduate research students from a UK university.

COVID-19 COVID-19 serological testing Classification Cohort studies Public health

Journal

BMC public health
ISSN: 1471-2458
Titre abrégé: BMC Public Health
Pays: England
ID NLM: 100968562

Informations de publication

Date de publication:
09 08 2022
Historique:
received: 12 03 2021
accepted: 22 07 2022
entrez: 9 8 2022
pubmed: 10 8 2022
medline: 12 8 2022
Statut: epublish

Résumé

Researchers conducting cohort studies may wish to investigate the effect of episodes of COVID-19 illness on participants. A definitive diagnosis of COVID-19 is not always available, so studies have to rely on proxy indicators. This paper seeks to contribute evidence that may assist the use and interpretation of these COVID-indicators. We described five potential COVID-indicators: self-reported core symptoms, a symptom algorithm; self-reported suspicion of COVID-19; self-reported external results; and home antibody testing based on a 'lateral flow' antibody (IgG/IgM) test cassette. Included were staff and postgraduate research students at a large London university who volunteered for the study and were living in the UK in June 2020. Excluded were those who did not return a valid antibody test result. We provide descriptive statistics of prevalence and overlap of the five indicators. Core symptoms were the most common COVID-indicator (770/1882 participants positive, 41%), followed by suspicion of COVID-19 (n = 509/1882, 27%), a positive symptom algorithm (n = 298/1882, 16%), study antibody lateral flow positive (n = 124/1882, 7%) and a positive external test result (n = 39/1882, 2%), thus a 20-fold difference between least and most common. Meeting any one indicator increased the likelihood of all others, with concordance between 65 and 94%. Report of a low suspicion of having had COVID-19 predicted a negative antibody test in 98%, but positive suspicion predicted a positive antibody test in only 20%. Those who reported previous external antibody tests were more likely to have received a positive result from the external test (24%) than the study test (15%). Our results support the use of proxy indicators of past COVID-19, with the caveat that none is perfect. Differences from previous antibody studies, most significantly in lower proportions of participants positive for antibodies, may be partly due to a decline in antibody detection over time. Subsequent to our study, vaccination may have further complicated the interpretation of COVID-indicators, only strengthening the need to critically evaluate what criteria should be used to define COVID-19 cases when designing studies and interpreting study results.

Sections du résumé

BACKGROUND
Researchers conducting cohort studies may wish to investigate the effect of episodes of COVID-19 illness on participants. A definitive diagnosis of COVID-19 is not always available, so studies have to rely on proxy indicators. This paper seeks to contribute evidence that may assist the use and interpretation of these COVID-indicators.
METHODS
We described five potential COVID-indicators: self-reported core symptoms, a symptom algorithm; self-reported suspicion of COVID-19; self-reported external results; and home antibody testing based on a 'lateral flow' antibody (IgG/IgM) test cassette. Included were staff and postgraduate research students at a large London university who volunteered for the study and were living in the UK in June 2020. Excluded were those who did not return a valid antibody test result. We provide descriptive statistics of prevalence and overlap of the five indicators.
RESULTS
Core symptoms were the most common COVID-indicator (770/1882 participants positive, 41%), followed by suspicion of COVID-19 (n = 509/1882, 27%), a positive symptom algorithm (n = 298/1882, 16%), study antibody lateral flow positive (n = 124/1882, 7%) and a positive external test result (n = 39/1882, 2%), thus a 20-fold difference between least and most common. Meeting any one indicator increased the likelihood of all others, with concordance between 65 and 94%. Report of a low suspicion of having had COVID-19 predicted a negative antibody test in 98%, but positive suspicion predicted a positive antibody test in only 20%. Those who reported previous external antibody tests were more likely to have received a positive result from the external test (24%) than the study test (15%).
CONCLUSIONS
Our results support the use of proxy indicators of past COVID-19, with the caveat that none is perfect. Differences from previous antibody studies, most significantly in lower proportions of participants positive for antibodies, may be partly due to a decline in antibody detection over time. Subsequent to our study, vaccination may have further complicated the interpretation of COVID-indicators, only strengthening the need to critically evaluate what criteria should be used to define COVID-19 cases when designing studies and interpreting study results.

Identifiants

pubmed: 35945541
doi: 10.1186/s12889-022-13889-0
pii: 10.1186/s12889-022-13889-0
pmc: PMC9363143
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1514

Subventions

Organisme : Wellcome Trust
Pays : United Kingdom
Organisme : Department of Health
Pays : United Kingdom

Informations de copyright

© 2022. The Author(s).

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Auteurs

Katrina A S Davis (KAS)

King's College London Institute of Psychiatry Psychology and Neuroscience, London, UK. katrina.davis@kcl.ac.uk.
South London and Maudsley NHS Foundation Trust, London, UK. katrina.davis@kcl.ac.uk.

Ewan Carr (E)

King's College London Institute of Psychiatry Psychology and Neuroscience, London, UK.

Daniel Leightley (D)

King's College London Institute of Psychiatry Psychology and Neuroscience, London, UK.

Valentina Vitiello (V)

School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London, London, UK.

Gabriella Bergin-Cartwright (G)

King's College London Institute of Psychiatry Psychology and Neuroscience, London, UK.
South London and Maudsley NHS Foundation Trust, London, UK.

Grace Lavelle (G)

King's College London Institute of Psychiatry Psychology and Neuroscience, London, UK.

Alice Wickersham (A)

King's College London Institute of Psychiatry Psychology and Neuroscience, London, UK.
South London and Maudsley NHS Foundation Trust, London, UK.

Michael H Malim (MH)

Faculty of Life Sciences and Medicine, King's College London School of Immunology & Microbial Sciences, London, UK.

Carolin Oetzmann (C)

King's College London Institute of Psychiatry Psychology and Neuroscience, London, UK.

Catherine Polling (C)

King's College London Institute of Psychiatry Psychology and Neuroscience, London, UK.
South London and Maudsley NHS Foundation Trust, London, UK.

Sharon A M Stevelink (SAM)

King's College London Institute of Psychiatry Psychology and Neuroscience, London, UK.

Reza Razavi (R)

School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London, London, UK.

Matthew Hotopf (M)

King's College London Institute of Psychiatry Psychology and Neuroscience, London, UK.
South London and Maudsley NHS Foundation Trust, London, UK.

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Classifications MeSH