A Statistical Learning Tool as Decision Support to Control the Spreading of COVID-19 and its Resurgence [Funder: Carleton University COVID-19 Rapid Research Response Grants]

We propose to develop a novel statistical learning tool as decision support to mitigate the effects of the COVID-19 pandemic and its resurgence. The main objective is to develop a new model based on the recent progress in network science and machine learning. This new model will allow us to adequately analyze the data stream related to COVID-19 and thus to precisely understand the evolution of the situation and the degree of the threat on our province (and across Canada and beyond). Compared to other available models, our approach is expected to be robust and dynamic, and parameters can be easily updated through learning processes according to decision mitigation measures. Such a tool is needed in both the short and long terms to inform effective and objective policies and strategies to be adopted in order to minimize morbidity and mortality, and societal and economic disruption at the same time.