BACKGROUND: Optimizing the public with a diagnosis, we used separate ana-density (adjusted odds ratio [OR] 1.86, health response to reduce the burden of lytic designs to compare predictors of 95% confidence interval [CI] 1.75-1.98), COVID-19 necessitates characterizing people testing positive versus negative; highest proportion of essential workers population-level heterogeneity of risks symptomatic people testing positive (adjusted OR 1.58, 95% CI 1.48-1.69), for the disease. However, heterogeneity versus testing negative; and people lowest educational attainment in SARS-CoV-2 testing may introduce testing positive versus people not test-(adjusted OR 1.33, 95% CI 1.26-1.41) biased estimates depending on analytic ing positive (i.e., testing negative or not and highest proportion of recent immidesign. We aimed to explore the poten-being tested). Our analyses included grants (adjusted OR 1.10, 95% CI 1.05tial for collider bias in a large study of tests conducted between Mar. 1 and 1.15) were consistently related to disease determinants, and evaluate June 20, 2020. increased odds of SARS-CoV-2 diagnosis individual, environmental and social regardless of analytic design. determinants associated with SARS-RESULTS: Of 14 695 579 people, we CoV-2 testing and diagnosis among resifound that 758 691 were tested for INTERPRETATION: Where testing is limdents of Ontario, Canada. SARS-CoV-2, of whom 25 030 (3.3%) had ited, our results suggest that risk factors a positive test result. The further the may be better estimated using population METHODS: We explored the potential odds of testing from the null, the more comparators rather than test-negative for collider bias and characterized indi-variability we generally observed in the comparators. Optimizing COVID-19 vidual, environmental and social deter-odds of diagnosis across analytic responses necessitates investment in minants of being tested and testing design, particularly among individual and sufficient coverage of structural positive for SARS-CoV-2 infection using factors. We found that there was less interventions tailored to heterogeneity in cross-sectional analyses among variability in testing by social determi-social determinants of risk, including 14.7 million community-dwelling peo-nants across analytic designs. Residing household crowding, occupation and ple in Ontario, Canada. Among those in areas with the highest household structural racism.
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