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Cited by 118COVID-19 epidemiological studiesSARS-CoV-2 detection and testingCOVID-19 Clinical Research Studies

Individual and social determinants of SARS-CoV-2 testing and positivity in Ontario, Canada: a population-wide study

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Sundaram, Maria E., Calzavara, Andrew, Mishra, Sharmistha, Kustra, Rafal, Chan, Adrienne K., Hamilton, Mackenzie A., Djebli, Mohamed, Rosella, Laura C. +5 more·2021·Canadian Medical Association Journal
DOI 10.1503/cmaj.202608PMC PMC8177943

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Abstract

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

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  • By using individual-level vaccination and death data among the total population vs. those diagnosed, our study limited potential ecological fallacy and collider bias.

    “By using individual-level vaccination and death data among the total population vs. those diagnosed, our study limited potential ecological fallacy and collider bias”

    From Social inequalities in COVID-19 death by area-level income in 11.2 million people in Ontario, Canada: patterns over time and the mediating role of vaccination. (2026) · cites this paper as [35]

    The Methods (Statistical analysis; page unavailable) compare positive cases with the broader population, and the Interpretation says this design appeared to mitigate some collider bias. The paper does not address ecological fallacy or establish that the citing study’s individual-level vaccination and death data limited either bias. (LLM, conf=0.84)

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Cited by

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Authors
Sundaram, M. E., Calzavara, A., Mishra, S., Kustra, R., Chan, A. K., Hamilton, M. A., Djebli, M., Rosella, L. C., Watson, T., Chen, H., Chen, B., Baral, S. D., & Kwong, J. C.
Affiliations
St. Michael's Hospital (CA)
Corresponding author
Kwong, Jeffrey C.
ORCID
Venue
Canadian Medical Association Journal
Publisher
CMA Impact Inc.
Published
2021-04-27
Volume
193
Issue
20
Pages
E723-E734
ISSN
  • 0820-3946 (ISSN-L)
  • 1488-2329
DOI
10.1503/cmaj.202608
PMC
PMC8177943
OpenAlex
W3158770594
Cited by
118
References
5
Citations by year
2026: 7 · 2025: 11 · 2024: 18 · 2023: 17 · 2022: 31 · 2021: 33 · 2020: 1
FWCI
9.76
Type
journal article
Language
en
Open access
Licence
cc-by-nc-nd
Locations
  • Canadian Medical Association Journal (publishedVersion, cc-by-nc-nd)
  • medRxiv (acceptedVersion)
  • PubMed Central (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
Funders
  • Cancer Care Ontario
  • Ontario Ministry of Health and Long-Term Care
  • University of Toronto
  • Canadian Institutes of Health Research (COVID-19)
  • Department of Family and Community Medicine, University of Toronto
Topics
  • Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
  • Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 detection and testing
  • Health Sciences › Medicine › Infectious Diseases › COVID-19 Clinical Research Studies
Keywords
COVID-19 testing, COVID-19 diagnosis, social determinants of health, collider bias, test-negative design, household density, essential workers, educational attainment, new immigrants, risk heterogeneity, Ontario residents, structural interventions
MeSH terms
COVID-19, SARS-CoV-2, COVID-19 Testing, Adolescent, Adult, Cross-Sectional Studies, Female, Humans, Male, Middle Aged, Ontario, Population Surveillance, RNA, Viral, Young Adult, Pandemics, Social Determinants of Health

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