| Abstract: | Amid the ongoing pandemic, nations are facing two conflicting objectives: mitigating COVID-19 infections and fatalities, and reopening communities. While politics has clashed with public health science, yielding mixed messaging, the deeper issue is recognizing that engineering may hold the solution to balancing these objectives. Transmission via asymptomatic and pre-symptomatic cases is a new challenge that has worked against existing public health protocols, and, yet, U.S. pandemic decision-makers demonstrate reluctance to change course. This project will employ the C3 AI COVID-19 Data Lake to benchmark and inform engineering-based intervention strategies using multi-objective optimization and agent-based modeling. |