Abstract

ObjectiveThe COVID-19 pandemic highlighted and exacerbated health inequities worldwide. While several studies have examined the impact of individual social factors on COVID infection, our objective was to examine how interactions of social factors were associated with the risk of testing positive for SARS-CoV-2 during the first two years of the pandemic. Study design and settingWe conducted an observational cohort study using linked health administrative data for Ontarians tested for SARS-CoV-2 between January 1st, 2020, and December 31st, 2021. We constructed multivariable models to examine the association between SARS-CoV-2 positivity and key variables including immigration status (immigrants vs. other Ontarians), and neighbourhood variables for household size, income, essential worker status, and visible minority status. We report main and interaction effects using odds ratios and predicted probabilities, with age and sex controlled in all models. ResultsOf 6,575,523 Ontarians in the cohort, 88.5 % tested negative, and 11.5 % tested positive for SARS-CoV-2. In all models, immigrants and those living in neighbourhoods with large average household sizes had greater odds of testing positive for SARS-CoV-2. The strength of these associations increased with increasing levels of neighbourhood marginalization for income, essential worker proportion and visible minority proportion. We observed little change in the probability of testing positive across neighbourhood income quintiles among other Ontarians who live in neighbourhoods with smaller households, but a large change in probability among other Ontarians who live in neighbourhoods with larger households. ConclusionOur study found that SARS-CoV-2 positivity was greater among people with certain combinations of social factors, but in all cases the probability of testing positive was consistently greater for immigrants than for other Ontarians. Examining interactions of social factors can provide a more nuanced and more comprehensive understanding of health inequity than examining factors separately.

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