Learning Fair Policies for Infectious Diseases Mitigation using Path Integral Control

• URL: http://arxiv.org/abs/2502.09831v1
• Date: Fri, 14 Feb 2025 00:08:06 GMT
• Title: Learning Fair Policies for Infectious Diseases Mitigation using Path Integral Control
• Authors: Zhuangzhuang Jia, Hyuk Park, Gökçe Dayanıklı, Grani A. Hanasusanto,
• Abstract summary: Infectious diseases pose major public health challenges to society. We propose a framework for sequential decision-making under uncertainty to design fairness-aware disease mitigation policies.
• Score: 0.4583163610461423
• License:
• Abstract: Infectious diseases pose major public health challenges to society, highlighting the importance of designing effective policies to reduce economic loss and mortality. In this paper, we propose a framework for sequential decision-making under uncertainty to design fairness-aware disease mitigation policies that incorporate various measures of unfairness. Specifically, our approach learns equitable vaccination and lockdown strategies based on a stochastic multi-group SIR model. To address the challenges of solving the resulting sequential decision-making problem, we adopt the path integral control algorithm as an efficient solution scheme. Through a case study, we demonstrate that our approach effectively improves fairness compared to conventional methods and provides valuable insights for policymakers.

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