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Vaccination strategies and virulent mutation spread: A game theory study

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  • Han, Dun
  • Wang, Xiao

Abstract

The frequent mutations of viruses often result in enhanced infectivity and pathogenicity, presenting substantial challenges to human populations worldwide. This study employs the SVIPIMR model, grounded in the principles of evolutionary game theory, to thoroughly investigate the dynamics of infectious diseases under a single-dose vaccination strategy. The model’s dynamics are divided into two main stages. Initially, during the epidemic phase, the model propagates within a season and ultimately stabilizes at a steady state. The basic reproduction number R0 produced at this stage is influenced by the basic reproduction numbers of two strains, R01 and R02. Our findings affirm that the persistence of the disease is guaranteed if both these numbers surpass one. Furthermore, it is observed that the strain with a higher basic reproduction number will invariably overshadow the other. In the following phase, the model assesses the impact of voluntary vaccination strategies and viral mutation rates on the spread of the disease, using two distinct strategy-updating rules derived from evolutionary game theory. Interestingly, our study reveals that a large-scale vaccination campaign at the epidemic’s onset can significantly increase the prevalence of the original strain. Additionally, despite the original strain’s higher transmission rate, the mutated strain comes to dominate the transmission process as the mutation rate progressively escalates. In summary, our research elucidates the dynamics of infectious diseases and highlights the potential effectiveness of augmenting vaccination rates and enhancing vaccine efficacy against mutated strains. These strategies could prove instrumental in curbing the spread of mutated strains, reducing the overall epidemic size, and improving the societal health impact.

Suggested Citation

  • Han, Dun & Wang, Xiao, 2023. "Vaccination strategies and virulent mutation spread: A game theory study," Chaos, Solitons & Fractals, Elsevier, vol. 176(C).
  • Handle: RePEc:eee:chsofr:v:176:y:2023:i:c:s096007792301007x
    DOI: 10.1016/j.chaos.2023.114106
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    References listed on IDEAS

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