A multi objective framework with an interactive dashboard for cost optimal infectious disease management

During an infectious disease outbreak, policymakers face the critical challenge of balancing the healthcare burden with the socioeconomic consequences of social distancing. To facilitate this complex decision-making process, we developed an integrated framework that combines multi-objective optimization, economic evaluation, and an interactive dashboard. This dashboard allows stakeholders to input dynamic cost parameters and immediately derive cost-optimal intervention strategies. We validated this framework using data from the early COVID-19 outbreak in South Korea. Our results demonstrate that cost-optimal solutions remained remarkably consistent across a wide range of costs per infection (from 4,410 USD to 361,000 USD), exhibiting similar transmission reduction patterns. This suggests that the cost-optimal policy is relatively insensitive to variations in the estimated cost per infection, providing a robust basis for intervention planning. By synthesizing rapid optimization with rigorous economic evaluation, our framework offers a scalable tool for timely, evidence-based decision-making during the urgent situation of a pandemic.