Forecasting Covid-19 Epidemic in Canada with Spatial-Temporal Models That Exploit Population Behaviour on Twitter
The Covid-19 pandemic is creating unprecedented damages to the public health and world economy. Being able to accurately forecast the spread of Covid-19 is critical for the federal and provincial governments of Canada to devise policies and measures maximally protecting the lives of Canadians and rapidly reviving the Canadian economy. In this project, we aim at developing accurate AI-enabled predictive models for the forecast and projection of Covid-19 epidemic in Canada by exploiting the population behaviour revealed on Twitter and the spatial correlation of the viral spread across Canada. Modern machine learning and text mining techniques will be combined with epidemiological modelling in this research. The outcome of this project is a validated suite of models, algorithms and web application that is able to forecast the daily number of new cases of Covid-19 across Canada at an accuracy significantly higher than all known models and algorithms developed to date.
This research will have profound health and socio-economical impact. For example, the Canadian governments at various levels may proactively devise policies and measures to fight Covid-19; healthcare systems in all provinces may better plan and prepare medical resources for treating Covid-19 patients; business of all sizes may exploit the epidemic projections to design more resilient business strategies and managerial solutions.
