{"ID":2872009,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2509.09087","arxiv_id":"2509.09087","title":"Cost-Effective Strategies for Infectious Diseases: A Multi-Objective Framework with an Interactive Dashboard","abstract":"During an infectious disease outbreak, policymakers must balance medical costs with social and economic burdens and seek interventions that minimize both. To support this decision-making process, we developed a framework that integrates multi-objective optimization, cost-benefit analysis, and an interactive dashboard. This platform enables users to input cost parameters and immediately obtain a cost-optimal intervention strategy. We applied this framework to the early outbreak of COVID-19 in South Korea. The results showed that cost-optimal solutions for costs per infection ranging from 4,410 USD to 361,000 USD exhibited a similar pattern. This indicates that once the cost per infection is specified, our approach generates the corresponding cost-optimal solution without additional calculations. Our framework supports decision-making by accounting for trade-offs between policy and infection costs. It delivers rapid optimization and cost-benefit analysis results, enabling timely and informed decision-making during the critical phases of a pandemic.","short_abstract":"During an infectious disease outbreak, policymakers must balance medical costs with social and economic burdens and seek interventions that minimize both. To support this decision-making process, we developed a framework that integrates multi-objective optimization, cost-benefit analysis, and an interactive dashboard....","url_abs":"https://arxiv.org/abs/2509.09087","url_pdf":"https://arxiv.org/pdf/2509.09087v2","authors":"[\"Jongmin Lee\",\"Renier Mendoza\",\"Victoria May P. Mendoza\",\"Eunok Jung\"]","published":"2025-09-11T01:40:33Z","proceeding":"math.OC","tasks":"[\"math.OC\"]","methods":"[]","has_code":false}