Are at-risk sociodemographic attributes stable across COVID-19 transmission waves?

Keywords: COVID-19, Health Geography, Medical Geography
Session Type: Virtual Paper Abstract
Day: Sunday
Session Start / End Time: 2/27/2022 03:40 PM (Eastern Time (US & Canada)) - 2/27/2022 05:00 PM (Eastern Time (US & Canada))
Room: Virtual 31

Abstract

Research in Canada has demonstrated that regions with higher shares of black-Canadians, foreign-born individuals, and low-income individuals have increased COVID-19 infection counts. These studies, however, have been performed either in one specific urban area or at a high spatial resolution, which may yield results with a higher error rate or results that do not clearly distinguish spatial patterns for urban, suburban, and rural populations. There is a literature gap for identifying spatial regions which are consistently vulnerable to COVID-19 over time at smaller spatial resolutions. This paper will account for both urban and rural at-risk populations and the patterns of COVID-19 over time at the FSA level in Ontario, Canada. COVID-19 case data comes from validated COVID-19 case reports from the Ontario Ministry of Health Public Health Case and Contact Management Solution (CCM), a centralized information system used by Ontario’s Public Health Units for the reporting and surveillance of infectious disease, including COVID-19. This data was then aggregated to the FSA level of spatial resolution. Epi-week is the temporal unit used to define the time exposure variable, waves, with the first epi-week for COVID-19 beginning on January 1, 2020. There are five COVID-19 waves in Ontario, which are defined as one crest on a weekly time series graph. Using bivariate analyses and regression models, this paper will establish if social vulnerability predictors for COVID-19 in Ontario change over time. Time-varying beta estimates will be used to establish if COVID-19 case predictors vary over time and space (urban and rural settings).