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Risk of SARS-CoV-2 Among Ontario Healthcare Workers: A Comparison of Test-negative and Cohort Study Designs in a
Louis Everest1, Paul A Demers, Brendan T Smith
1From the Occupational Cancer Research Centre, Ontario Health, Toronto, Ontario, Canada (L.E., P.A.D., M.A.H., C.S., T.L.K., J.S.); Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada (P.A.D., B.T.S., J.K., V.H.A., M.A.H., T.L.K., J.S.); Health Promotion, Chronic Disease and Injury Prevention, Public Health Ontario, Toronto, Ontario, Canada (B.T.S.); Environmental and Occupational Health, Public Health Ontario, Toronto, Ontario, Canada (J.K.); Department of Medicine, University of Toronto, Toronto, Ontario, Canada (J.K.); and School of Occupational and Public Health, Toronto Metropolitan University, Toronto, Ontario, Canada (M.A.H.).
Objective:
Differential reason-for-testing may bias test-negative estimates. This study aimed to estimate healthcare worker SARS-CoV-2 risk, with adjustment for healthcare-seeking behavior and unmeasured reason-for-testing.
Methods:
A total of 1.2-million workers in Ontario, Canada, were followed for SARS-CoV-2 polymerase chain reaction tests from February 2020 to December 2021. Hazard ratios (HRs) were used to estimate SARS-CoV-2 risk in healthcare workers versus non-healthcare workers based on the overall and test-negative subcohort. Unmeasured reason-for-testing was examined through probabilistic bias analyses.
Results:
In the test-negative subcohort, healthcare and non-healthcare workers had a similar risk of SARS-CoV-2. However, healthcare workers had an increased risk in the symptomatic-adjusted (HR: 1.15, 95% confidence interval: 1.03-1.40) and asymptomatic-adjusted (HR: 2.83, 95% confidence interval: 1.08-9.07) models.
Conclusions:
Future test-negative studies should account for potential bias from varying symptomatic and asymptomatic testing groups and may consider using probabilistic bias analysis methods when reason-for-testing data is missing.
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