Forecasting Covid-19 Epidemic in Canada with Spatial-Temporal Models That Exploit Population Behaviour on Twitter

新型冠状病毒疫情正在对公共卫生和世界经济造成前所未有的损害。能够准确预测COVID-19的传播对加拿大联邦和省政府制定政策和措施以最大限度地保护加拿大人的生命和迅速振兴加拿大经济至关重要。在这个项目中，我们的目标是通过利用Twitter上揭示的人口行为和加拿大各地病毒传播的空间相关性，开发准确的人工智能预测模型，用于预测和预测加拿大的Covid-19疫情。在这项研究中，现代机器学习和文本挖掘技术将与流行病学建模相结合。该项目的成果是一套经过验证的模型、算法和网络应用程序，能够预测加拿大各地每日新冠肺炎病例的数量，其准确性远远高于迄今为止开发的所有已知模型和算法。 这项研究将产生深远的健康和社会经济影响。例如，加拿大各级政府可积极制定政策及措施以对抗新型冠状病毒;各省的医疗系统可更好地规划及准备医疗资源以治疗新型冠状病毒患者;各种规模的企业可利用疫情预测来设计更具弹性的业务策略及管理解决方案。

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.