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