Spatial and Temporal Hotspot Analysis of COVID-19 in Toronto

Abstract

ABSTRACT The COVID-19 pandemic in Toronto, Canada was unequal for its 2.7 million residents. As a dynamic pandemic, COVID-19 trends might have also varied over space and time. We conducted a spatiotemporal hotspot analysis of COVID-19 over the first four major waves of COVID-19 using three different applications of Moran’s I to highlight the variable experience of COVID-19 infections in Toronto, while describing the potential impact of socioeconomic and sociodemographic factors on increased risk of COVID-19 exposure and infection. Results highlight potential clustering of COVID-19 case rate hot spots in areas with higher concentrations of immigrant and low-income residents and cold spots in areas with more affluent and non-immigrant residents during the first three waves. By the fourth wave, case rate clustering patterns were more dynamic. In all, a better understanding of the unequal COVID-19 pandemic experience in Toronto needs to also consider the dynamic nature of the pandemic. HIGHLIGHTS - The COVID-19 pandemic was spatially and temporarily dynamic in the City of Toronto. - At first, hotspots were concentrated in areas with more marginalized residents. - Later, COVID-19 spatial trends diverged from initially identified patterns. - East Asian enclaves in the city disproportionally had lower COVID-19 case counts. - COVID-19 studies need to consider the dynamic nature of the pandemic.

Locations

• medRxiv (Cold Spring Harbor Laboratory) - View - PDF