## 2 Literature Review
Susceptible and infected individuals adopt different behavioral strategies based on their perceptions of disease prevalence and burden, and their susceptibility to isolation measures, and evolve their strategies using social learning algorithms. The study concludes that incentives for altruistic behaviors, such as voluntary self-isolation by infected individuals, are necessary to reduce the social burden of pandemics. This study also did not take into account the impact of pharmaceuticals. Our study also focuses on people's behavior. Then, we review the literature that combines infectious disease and inventory management models. [PERSON] et al. [23] proposed a unique time-varying forecasting model for the dynamic demand for medical resources based on the SEIR model. The entire medical resource allocation process is structured as a multi-stage integer programming problem. At each stage, a cost minimization subproblem is solved subject to the time-varying demand. The corresponding optimal allocation results are then used as inputs to a process that controls the spread of influenza and determines the demand for the next stage. This study demonstrates that the subproblem may help decision-makers prepare for a pandemic, including how to dynamically allocate limited resources. Since this study is about influenza, we propose a model that takes into account the characteristics of COVID-19. We also focus on the influence of human behavior. [PERSON] et al. [24] proposed a dynamic logistics model for healthcare resource allocation that can be used to control epidemic spread. The model combines a predictive mechanism constructed for the demand for medicines during the course of epidemic spread with a logistics planning system to meet the predicted demand and minimize the total cost. The study did not consider characteristics of COVID-19, such as viral mutations, or human behavior. [PERSON] et al. [25] addressed a novel dual-purpose vehicle routing problem for distributing vaccines among different regions to control the spread of infectious diseases. The model developed aims to minimize the social costs incurred by considering different priority groups under the SIR epidemic model and the cost of vehicles used simultaneously. Viral mutations were not taken into account in this study, nor did it take into account the effects of actions taken by individuals. [PERSON] et al. [26] proposed a generic framework for pharmaceutical inventory management, consisting of hospital, forecasting, and inventory management modules. The disease spread forecasting model is shown to be superior to naive policies in terms of mitigating infections and saving inventory. The authors then analyzed the quantification of the impact of important factors such as the selection of appropriate ordering policies,safety stockpiles, and epidemic declaration thresholds on epidemic dynamics. The study did not consider virus mutations or human behavior. [PERSON] et al. [27] examined various inventory policies such as reorder points, recurring orders, and just-in-time to minimize inventory management costs for medical supplies. They used an infectious disease model to determine the dynamics of COVID-19 and the percentage of infected patients admitted to the hospital. Based on this information, various situations are created that take into account lockdown, social awareness, etc., and appropriate inventory policies are proposed to reduce inventory management costs. Viral mutations were not considered in this study. Our study also uses evolutionary games to represent human behavior. A large number of literature surveys were conducted, indicating that studies have been conducted from a variety of perspectives. Among the reviewed studies, the study on infectious disease models was very helpful in developing a method to represent human behavior in the models. The study on pharmaceutical inventory management was very helpful in developing the infectious disease model into an inventory management method.