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Title: COVID-19 Modelling and Forecasting in the US and Canada: A statistician’s pro(retro)spective
Abstract: Since the COVID pandemic came to North America in March 2020, researchers and research groups have pivoted or sprung up to aid and nudge policy decision making. For the last year-plus, I’ve worked regularly with two of these – the BC COVID Modelling Group and Carnegie Mellon University’s Delphi Research Group – groups that share a number of similarities but which could not be more different. In this talk, I’ll give an overview of the structure, goals, and accomplishments of these groups and highlight many of the difficulties faced, especially when it comes to data. I’ll also describe the statistical tools used for forecasting and modeling, efforts made to evaluate models and develop better forecasters, and some major lessons learned. I’ll conclude by describing some of the many open projects that need statistical input going forward.