Two-Stage Game Theoretic Framework for Evaluating COVID-19 Risk and Allocating Medical Resources

Cheng-Kuang Wu ()
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Cheng-Kuang Wu: Zhejiang Industry & Trade Vocational College, School of Artificial Intelligence

A chapter in Proceedings of the 11th Annual Meeting of Risk Analysis Council of China Association for Disaster Prevention (RAC 2024), 2025, pp 181-187 from Springer

Abstract: Abstract This study presents a framework for decision-makers that integrates two game theory models aimed at determining the allocation of medical resources across all impacted districts in response to an elevated threat advisory level. The interactions among a cluster of coronavirus cases and the district response agent for the impacted area are conceptualized as a non-cooperative game, subsequently leading to the derivation of a risk value (RV) for COVID-19 for each district utilizing the mixed Nash equilibrium method. The risk value denotes the hazard, vulnerability, and consequences associated with the coronavirus outbreak in the afflicted district. Subsequently, this study employs the risk values from all districts to compute a Shapley value for each district. We equitably allocate medical resources across all districts according to their anticipated marginal contribution. The experimental findings demonstrate that the administrator can utilize this framework to quantitatively assess the COVID-19 risk value in each district, and that the proposed Shapley value method is viable for resource mobilization planning and enhancing relief efforts against COVID-19.

Keywords: COVID-19; Medical Resource Allocation; Nash Equilibrium; Risk Value; Shapley Value (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:spr:advbcp:978-94-6463-946-9_23

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DOI: 10.2991/978-94-6463-946-9_23

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