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

By Katrina A S Davis, Ewan Carr, Daniel Leightley, Valentina Vitiello, Gabriella Bergin Cartwright, Grace Lavelle, Alice Wickersham, Michael Malim, Carolin Oetzmann, Catherine Polling, Sharon Stevelink, Reza Razavi, Matthew Hotopf, KCL-CHECK research team

Posted 07 Dec 2020
medRxiv DOI: 10.1101/2020.12.07.20245183

Background Definitive diagnosis of COVID-19 requires resources frequently restricted to the severely ill. Cohort studies must rely on surrogate indicators to define cases of COVID-19 in the community. We describe the prevalence and overlap of potential indicators including self-reported symptoms, suspicion, and routine test results, plus home antibody testing. Methods An occupational cohort of 2807 staff and postgraduate students at a large London university. Repeated surveys covering March to June 2020. Antibody test results from 'lateral flow' IgG/IgM cassettes in June 2020. Results 1882 participants had valid antibody test results, and 124 (7%) were positive. Core symptoms of COVID-19 were common (770 participants positive, 41%), although fewer met criteria on a symptom algorithm (n=297, 16%). Suspicion of COVID-19 (n=509, 27%) was much higher than positive external tests (n=39, 2%). Positive antibody tests were rare in people who had no suspicion (n=4, 1%) or no core symptoms (n=10, 2%). In those who reported external antibody tests, 15% were positive on the study antibody test, compared with 24% on earlier external antibody tests. Discussion Our results demonstrate the agreement between different COVID indicators. Antibody testing using lateral flow devices at home can detect asymptomatic cases and provide greater certainty to self-report; but due to weak and waning antibody responses to mild infection, may under-ascertain. Multiple indicators used in combination can provide a more complete story than one used alone. Cohort studies need to consider how they deal with different, sometimes conflicting, indicators of COVID-19 illness to understand its long-term outcomes.

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