Tavis Buckland

The emergence of SARS-CoV-2 in late 2019 posed a significant risk to global public health. In attempting to mitigate this risk, public health officials were presented with the considerable challenge of developing successful surveillance strategies to monitor disease spread. The primary objective of this study is to evaluate the efficacy of recurrent daily spatio-temporal cluster detection towards the discovery and prioritization of emerging space-time clusters of SARS-CoV-2 in the City of Toronto, Canada. Second, to this objective, we sought to evaluate if the geographic distribution of these clusters could be predicted by sociodemographic characteristics in developing a logistic regression model. Between June 21^st and August 16^th, 2021, eleven significant space-time clusters were identified and communicated to Toronto’s public health agency for close examination. The results of statistical modelling suggest an association exists between the prevalence of sales, service, and health care sector employment, educational attainment, and marital status with significant clusters of COVID-19.