Utilizing Strategies of Masks and Retroactive Treatment for Epidemic Disease Control on Behavioral Dynamics

Without a vaccination solution, implementing intermediary defense measures such as mask wearing becomes imperative to curtail disease transmission, hinging on individuals’ choices to wear masks. Conversely, postinfection treatment serves as a last-resort avenue for disease reduction. This model proposes an innovative epidemic modeling approach to address these dual aspects, integrating mask-wearing behavior and treatment decisions as strategic choices grounded in game theory principles. The primary objective of this model is to delve into the intricate interplay between individual behaviors and their implications for disease propagation, particularly in the absence of vaccination. By factoring in rational decisions made by agents within a dynamic epidemic context, the model seeks to unravel the intricate connections between adopting masks and seeking treatments and their subsequent impact on disease control. By incorporating mask adoption and treatment seeking as dynamic variables, this model sheds light on the efficacy of preventive measures and treatment protocols in managing epidemic outbreaks. The model investigates the transition rates from susceptibility to mask adoption and infection to treatment seeking through a comprehensive evolutionary game theory lens. The inherent strategies related to mask wearing and treatment are depicted using an extensive evolutionary game theory framework among societal individuals, presented through an illustrative phase diagram. In-depth numerical simulations indicate that the efficacy of masks and treatment could implicitly reduce community infection risks, particularly when these solutions are reliable and cost-effective. This entails exploring how the evolution and coexistence of mask wearing and treatment strategies interact, using metrics such as the social dilemma’s impact and the count of individuals benefiting from these approaches.