An Evolutionary Game-Theoretic Approach to Assessing Single-Season Vaccination Strategies in a Two-Strain Epidemic Model

Md. Jaman Mia and K. M. Ariful Kabir

Complexity, 2026, vol. 2026, 1-35

Abstract: This study investigates the impact of single-dose vaccination strategies on the transmission dynamics of double-strain infectious diseases within a single epidemic season, in which the original and mutant strains cocirculate in a population. To capture the interaction between epidemiological processes and adaptive human behavior, we develop a coupled evolutionary–epidemiological framework in which vaccination uptake evolves dynamically according to replicator dynamics driven by state-dependent payoffs. The model incorporates key factors, including vaccination costs, vaccine efficacy, infection risk, and policy-driven incentives, enabling individuals to update their decisions in response to real-time epidemic conditions continuously. A mathematical analysis yields explicit expressions for the basic reproduction numbers of both strains and establishes conditions for their coexistence. The results show that vaccine efficacy, particularly against mutant strains, plays a critical role in suppressing infection peaks and preventing strain dominance. Furthermore, reduced vaccination costs and increased public awareness significantly enhance vaccination uptake, thereby lowering overall disease burden. Numerical simulations confirm that high vaccine effectiveness, combined with affordable costs and targeted awareness campaigns, substantially reduces outbreak risks, whereas behavioral hesitancy can sustain transmission through insufficient vaccination coverage. Sensitivity analysis further identifies transmission rates, recovery rates, and vaccination-related parameters as key determinants of epidemic outcomes. Overall, these findings highlight the importance of integrating behavioral responses into epidemic models and provide insights for designing adaptive and cost-effective vaccination strategies in the presence of competing pathogen strains.

Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:hin:complx:5051384

DOI: 10.1155/cplx/5051384

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