Game Theory-Based Decision Making for the Allocation of Scarce Medical Resources in the COVID-19 Situation

COVID-19, being declared a pandemic, has affected human lives, economics, healthcare, and education in multiple geographic locations worldwide. The outbreak of this pandemic has demonstrated the necessity of efficient decision making to handle supply chain disruptions, especially for medical resources. The work in this article focuses on creating a decision support system (DSS) for the hierarchical allocation of critical medical resources among different geographical locations. The methodology adopted in this article relies on the concept of noncooperative games and designs a single-stage, multiplayer game to allocate medical resources among the affected locations while considering them as the self-interested players of the game. All the players or the affected locations involved in the game are imposed by different penalties derived from a nonmonetary cost function. The solution of the resource allocation game is given by one of the Nash equilibria of the game chosen by using different selection methods. This article proves analytically that the proposed game-theoretic model always admits pure strategy Nash equilibria (PSNE). Realistic case studies are demonstrated to validate the results given in this article.