Studying the social determinants of COVID-19 in a data vacuum

Race-based and other demographic information on COVID-19 patients is not being collected consistently across provinces in Canada. Therefore, whether the burden of COVID-19 is falling disproportionately on the shoulders of particular demographic groups is relatively unknown. In this article, we first provide an overview of the available geographic and demographic data related to COVID-19. We then make creative use of these existing data to fill the vacuum and identify key demographic risk factors for COVID-19 across Canada's health regions. Drawing on COVID-19 counts and tabular census data, we examine the association between communities' demographic composition and the number of COVID-19 infections. COVID-19 infections are higher in communities with larger shares of Black and low-income residents. Our approach offers a way for researchers and policymakers to use existing data to identify communities nationwide that are vulnerable to the pandemic in the absence of more detailed demographic and more granular geographic data.

Automated summary

This article highlights the inconsistent collection of race-based and demographic information on COVID-19 patients across provinces in Canada, leading to a relative lack of understanding on whether the burden of COVID-19 is falling disproportionately on specific demographic groups. By creatively utilizing existing data, the study reveals that communities with higher proportions of Black and low-income residents tend to have higher rates of COVID-19 infections. This approach provides a way for researchers and policymakers to identify vulnerable communities nationwide using available data in the absence of more detailed demographic and geographic information.