Increasing evidence suggests that human movement, including international travel and mass forced population displacement, acts as a catalyst for global antimicrobial resistance (AMR) transmission. Immigration increases the likelihood of antibiotic-resistant bacterial strains being imported into developed countries, particularly from several developing countries with high antimicrobial resistance. On the other hand, self-medication, easy access to over-the-counter drugs, promiscuous use, and lax oversight all contribute to an increase in antibiotic use in most lower-middle- and middle-income countries. It leads to antimicrobial resistance and an increased health burden, particularly in high-income countries. Third-party funding agencies are working to reduce the global antimicrobial resistance burden. Understanding the complex system of antibiotic overuse, third-party funding, and cross-border transmission of antimicrobial-resistant strains is a critical task for public health policymakers. In this study, a modeling framework is developed using a combination of epidemiological and game theory methods. This framework aims to describe the phenomenon of migration between countries, specifically focusing on the movement between developing and developed nations. Additionally, the framework incorporates the analysis of self-medication behavior within the developing population. Simulations of the model are conducted, followed by a sensitivity analysis, in order to investigate the influence of various parameters on the optimal funding amount. Our findings indicate that the total cost due to treatment of infection and funding is a convex function of the amount of third-party assistance. This means that there is an optimal level of funding in place to keep the total cost of antimicrobial resistance as low as possible. The sensitivity analyses in relation to various epidemiological and behavioral parameters indicate that the optimal fund is highly dependent on the other parameters of the system. Third-party assistance may be required, as predicted, to reduce the amount of self-medication, but it is only beneficial up to a certain point. These findings result in useful policy recommendations as well as intriguing new research directions.
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