Spatiotemporal clusters and the socioeconomic determinants of COVID-19 in Toronto neighbourhoods, Canada. (November 2022)

• Record Type: Journal Article
• Authors: Nazia, Nushrat; Law, Jane; Butt, Zahid Ahmad
• Is Part Of: Spatial and spatio-temporal epidemiology. Volume 43(2022)
• Publication Date: 2022-11
• Subjects: Space-time clusters -- Spatial regression -- Multiscale geographically weighted regression (mgwr) -- COVID-19 -- Clustering analysis; Epidemiology -- Statistical methods -- Periodicals; Epidemiology -- Periodicals; 614.4072
• DOI: 10.1016/j.sste.2022.100534
• Languages: English
• ISSNs: 1877-5845

Abstract

Highlights: Space-time clusters were observed between October 2020 and January 2021 (high-risk periods). Lower level of education and higher concentration of immigrants in the neighbourhoodswere associated with higher incidences of COVID-19. The geographically weighted regression model identified several locally varyingsocioeconomic drivers of the COVID-19 incidences. Early localization of clusters may help in planning for a locally adaptable protection measures to limit the spread of COVID-19. Abstract: The aim of this study is to identify spatiotemporal clusters and the socioeconomic drivers of COVID-19 in Toronto. Geographical, epidemiological, and socioeconomic data from the 140 neighbourhoods in Toronto were used in this study. We used local and global Moran's I, and space-time scan statistic to identify spatial and spatiotemporal clusters of COVID-19. We also used global (spatial regression models), and local geographically weighted regression (GWR) and Multiscale Geographically weighted regression (MGWR) models to identify the globally and locally varying socioeconomic drivers of COVID-19. The global regression model identified a lower percentage of educated people and a higher percentage of immigrants in the neighbourhoods as significant predictors of COVID-19. MGWR shows the best fit model to explain the variables affecting COVID-19. The findings imply that a single intervention package for the entire area would not be an effective strategy for controlling COVID-19; a locally adaptable intervention package would be beneficial.