Harnessing the Power of Data Analytics against COVID-19: Developing Decision Support Tools for Policymakers

COVID-19大流行给全球政策制定者带来了前所未有的挑战。大多数国家已采取严格行动控制其传播，包括旅行限制、家庭隔离、集中隔离和接触者追踪。与此同时，已经进行了大量投资，以迅速提高医疗保健系统的容量和能力，以满足激增的需求。然而，所有公共干预都有社会和经济代价，其中包括经济长期关闭造成的重大经济损失，以及严重孤立战略即将产生的负面社会、心理甚至健康影响。决策者需要可靠的工具，以便在正确的时间做出正确的决定。

The COVID-19 pandemic is posing unprecedented challenges for policymakers around the globe. Most countries have taken severe action to contain its spread, including travel restriction, home quarantine, centralized quarantine, and contact tracing. Concurrently, substantial investments have been made to quickly improve the capacity and capability of healthcare systems to meet the surge in demand. Nevertheless, all public interventions have societal and economic costs, which include the substantial economic losses resulting from a prolonged shut-shown of the economy and the impending negative social, psychological and even health impacts of severe isolation strategies. Policymakers need reliable tools to make the right decision at the right time. This research aims to devise new decision support tools to guide COVID-19 response strategies. In particular, it will focus on decisions related to the levels and timings of population quarantine and requirements of the health system. Classical infectious disease modeling techniques will be combined with operations research and data analytics methods to address the several layers of complexity surrounding this decision problem. The proposed tools can help policymakers in Canada to answer urgent questions like which population segments must be quarantined and for how long, when can some activity be restored and what type of activities to be opened, when can students return to their schools, what is the required health care resources, both personnel and equipment, to meet the projected demand, and what is the total cost of these policies, both human and economic.