Evidence map›Paper›PMID 35945541›Full record

ArticleBMC public health2022

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

Katrina A S Davis, Ewan Carr, Daniel Leightley, Valentina Vitiello, Gabriella Bergin-Cartwright, Grace Lavelle, Alice Wickersham, Michael H Malim, Carolin Oetzmann, Catherine Polling and 3 more

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In one paragraph

Article in BMC public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Katrina A S DavisKing's College London Institute of Psychiatry Psychology and Neuroscience, London, UK. katrina.davis@kcl.ac.uk.
Ewan CarrKing's College London Institute of Psychiatry Psychology and Neuroscience, London, UK.
Daniel LeightleyKing's College London Institute of Psychiatry Psychology and Neuroscience, London, UK.
Valentina VitielloSchool of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London, London, UK.
Gabriella Bergin-CartwrightKing's College London Institute of Psychiatry Psychology and Neuroscience, London, UK.
Grace LavelleKing's College London Institute of Psychiatry Psychology and Neuroscience, London, UK.
Alice WickershamKing's College London Institute of Psychiatry Psychology and Neuroscience, London, UK.
Michael H MalimFaculty of Life Sciences and Medicine, King's College London School of Immunology & Microbial Sciences, London, UK.
Carolin OetzmannKing's College London Institute of Psychiatry Psychology and Neuroscience, London, UK.
Catherine PollingKing's College London Institute of Psychiatry Psychology and Neuroscience, London, UK.
Sharon A M StevelinkKing's College London Institute of Psychiatry Psychology and Neuroscience, London, UK.
Reza Razavi *School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London, London, UK.
Matthew Hotopf *King's College London Institute of Psychiatry Psychology and Neuroscience, London, UK.

Funding

Department of HealthWellcome Trust
6 · The paper itself

Abstract

backgroundResearchers 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.

methodsWe 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.

resultsCore 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%).

conclusionsOur 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.

Indexed as

COVID-19HumansSARS-CoV-2StudentsUnited KingdomUniversitiesClassificationCohort studiesCOVID-19COVID-19 serological testingPublic health

Identifiers

PMID35945541
PMCPMC9363143

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.