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Realistic decision-making process with memory and adaptability in evolutionary vaccination game

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  • Wang, Jianwei
  • He, Jialu
  • Yu, Fengyuan
  • Guo, Yuxin
  • Li, Meiyu
  • Chen, Wei

Abstract

Of particular importance for controlling infectious diseases by voluntary vaccination is how to understand individuals’ strategic vaccination behavior in social networks. Previous studies have always assumed an imitating and learning process by the Fermi’s rule, however, individuals’ stochastic behavior of whether to vaccinate is influenced by their intentions instead of simply imitating others. In this paper, a new strategy updating rule is proposed, demonstrating a more realistic vaccination decision-making process with memory effect and adaptability. Individuals determine whether vaccination is significant by comparing the vaccination cost and the average cost of their unvaccinated neighbors, and accordingly change their intentions to vaccinate in the next season, during which the memory effect and adaptability are taken into account. We find that the new updating rule has an extraordinary impact on the vaccination behavior of individuals, and, as a result, on the final epidemic size. It is especially noteworthy that, comparing with the traditional model, the vaccination coverage is improved and the infection size is reduced. Our results highlight that it is necessary to consider memory effect and adaptability in controlling the infectious spreading.

Suggested Citation

  • Wang, Jianwei & He, Jialu & Yu, Fengyuan & Guo, Yuxin & Li, Meiyu & Chen, Wei, 2020. "Realistic decision-making process with memory and adaptability in evolutionary vaccination game," Chaos, Solitons & Fractals, Elsevier, vol. 132(C).
    • Handle: RePEc:eee:chsofr:v:132:y:2020:i:c:s0960077919305399
    DOI: 10.1016/j.chaos.2019.109582
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    References listed on IDEAS

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    Cited by:

    1. Ge, Jingwen & Wang, Wendi, 2022. "Vaccination games in prevention of infectious diseases with application to COVID-19," Chaos, Solitons & Fractals, Elsevier, vol. 161(C).
    2. Wang, Jianwei & Chen, Wei & Yu, Fengyuan & He, Jialu & Xu, Wenshu, 2022. "Wealth-based rule favors cooperation in costly public goods games when individual selection is inevitable," Applied Mathematics and Computation, Elsevier, vol. 414(C).
    3. Meng, Xueyu & Cai, Zhiqiang & Si, Shubin & Duan, Dongli, 2021. "Analysis of epidemic vaccination strategies on heterogeneous networks: Based on SEIRV model and evolutionary game," Applied Mathematics and Computation, Elsevier, vol. 403(C).
    4. He, Jialu & Wang, Jianwei & Yu, Fengyuan & Chen, Wei & Xu, Wenshu, 2022. "The persistence and transition of multiple public goods games resolves the social dilemma," Applied Mathematics and Computation, Elsevier, vol. 418(C).
    5. Wang, Jianwei & Xu, Wenshu & Chen, Wei & Yu, Fengyuan & He, Jialu, 2021. "Information sharing can suppress the spread of epidemics: Voluntary vaccination game on two-layer networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 583(C).
    6. Chen, Wei & Wang, Jianwei & Yu, Fengyuan & He, Jialu & Xu, Wenshu & Wang, Rong, 2021. "Effects of emotion on the evolution of cooperation in a spatial prisoner’s dilemma game," Applied Mathematics and Computation, Elsevier, vol. 411(C).
    7. Wang, Jianwei & Xu, Wenshu & Chen, Wei & Yu, Fengyuan & He, Jialu, 2021. "Inter-group selection of strategy promotes cooperation in public goods game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 583(C).
    8. Wang, Jianwei & He, Jialu & Yu, Fengyuan, 2021. "Heterogeneity of reputation increment driven by individual influence promotes cooperation in spatial social dilemma," Chaos, Solitons & Fractals, Elsevier, vol. 146(C).

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