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Studying the social determinants of COVID‐19 in a data vacuum
Author(s) -
Choi Kate H.,
Denice Patrick,
Haan Michael,
Zajacova Anna
Publication year - 2021
Publication title -
canadian review of sociology/revue canadienne de sociologie
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.414
H-Index - 35
eISSN - 1755-618X
pISSN - 1755-6171
DOI - 10.1111/cars.12336
Subject(s) - covid-19 , census , pandemic , geography , demography , race (biology) , american community survey , medicine , population , sociology , outbreak , disease , virology , infectious disease (medical specialty) , gender studies , pathology
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.