Dynamical behaviors for vaccination can suppress infectious disease – A game theoretical approach

K. M.Ariful Kabir, Jun Tanimoto

研究成果: Contribution to journalArticle

16 引用 (Scopus)


To avoid the infection, the epidemic outburst plays a significant role that encourages people to take vaccination and induce behavioral changes. The interplay between disease incidence, vaccine uptake and the behavior of individuals are taking place on the local time scale. Here, we analyze the individual's behavior in disease-vaccination interaction model based on the evolutionary game approach that captures the idea of vaccination decisions on disease prevalence that also include social learning. The effect of herd immunity is partly important when the individuals are deciding whether to take the vaccine or not. The possibility that an individual taking a vaccination or becoming infected depends upon how many other people are vaccinated. To apprehend this interplay, four strategy updating rules: individual based risk assessment (IB-RA), society based risk assessment (SB-RA), direct commitment (DC) and modified replicator dynamics (MRD) are contemplated for game theoretical approach by how one individual can learn from society or neighbors. The theory and findings of this paper provide a new perspective for vaccination taking policy in daily basis that provision of prompt learning with the collective information reliefs to reduce infection, which gives a new ‘vaccination game’ from other previous models.

ジャーナルChaos, solitons and fractals
出版物ステータス出版済み - 6 2019

All Science Journal Classification (ASJC) codes

  • Statistical and Nonlinear Physics
  • Mathematics(all)
  • Physics and Astronomy(all)
  • Applied Mathematics

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