Dynamic Resource Management in Response to Pandemics

Business-as-usual medical and public health practices cannot cope with the large shocks of a pandemic. Coordinated and well-timed response mechanisms are required. In this proposal, we aim to build a data analytic framework to optimize resource management for testing, prevention, and care, both prior to a potential spread, as well as during a rapidly developing outbreak. The proposed research builds upon our current work to help the State of Illinois to mitigate the ongoing COVID-19 outbreak. Key outcomes of our research include: 1) risk-aware dynamic equipment and workforce allocation mechanism implemented on the C3.ai platform, 2) comparison of federalized resource allocation to that where states compete with one another for resources via game theory, 3) flexible capacity provisioning in medical supply chains and dynamic inventory management for perishable goods such as N95 masks. While part of our research will directly help combat the current crisis, the rest will forge operational resilience and enhance the readiness to fight a potential future outbreak. The team is multidisciplinary and combines expertise in optimization and control, healthcare management, operations research, data analytics and game theory.