Forecasting the increase in new cases during the current pandemic has largely been the domain of compartment-style or time-series models. In this paper we propose a third approach that constructs forecasts by using the past history of countries that have had similar epidemiological experiences to Ontario to create a view of the future. The approach can be likened to projecting hurricane paths using the historical record of storms passing through a common geographical area. The forecast is then simply constructed by following the historical storms from that point forward, with the ensemble creating a cone of possible futures.

Bio: Taha Jaffer is currently focusing on AI applied to managing structural interest rate risk at Scotiabank. He has been the head of Wholesale Banking and Treasury AI and was responsible for large-scale AI initiatives in Global Treasury, Global Banking & Markets, and Commercial Banking. Before Scotiabank, Taha was a Special Executive Advisor in AI at TD, a principal at the Carlyle Group, and has held positions in multiple asset management firms with a focus on alternative investments. Taha holds a PhD in Electrical and Computer Engineering, a Masters in Biomedical Engineering, and a Masters in Mathematical Finance, all from the University of Toronto.