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An evolutionary vaccination game in the modified activity driven network by considering the closeness

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  • Han, Dun
  • Sun, Mei

Abstract

In this paper, we explore an evolutionary vaccination game in the modified activity driven network by considering the closeness. We set a closeness parameter p which is used to describe the way of connection between two individuals. The simulation results show that the closeness p may have an active role in weakening both the spreading of epidemic and the vaccination. Besides, when vaccination is not allowed, the final recovered density increases with the value of the ratio of the infection rate to the recovery rate λ/μ. However, when vaccination is allowed the final density of recovered individual first increases and then decreases with the value of λ/μ. Two variables are designed to identify the relation between the individuals’ activities and their states. The results draw that both recovered and vaccinated frequency increase with the increase of the individuals’ activities. Meanwhile, the immune fee has less impact on the individuals’ vaccination than the closeness. While the λ/μ is in a certain range, with the increase of the value of λ/μ, the recovered frequency of the whole crowds reduces. Our results, therefore, reveal the fact that the best of intentions may lead to backfire.

Suggested Citation

  • Han, Dun & Sun, Mei, 2016. "An evolutionary vaccination game in the modified activity driven network by considering the closeness," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 49-57.
    • Handle: RePEc:eee:phsmap:v:443:y:2016:i:c:p:49-57
    DOI: 10.1016/j.physa.2015.09.073
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    References listed on IDEAS

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    1. Han, Dun & Sun, Mei & Li, Dandan, 2015. "Epidemic process on activity-driven modular networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 432(C), pages 354-362.
    2. Li, Dandan & Ma, Jing & Tian, Zihao & Zhu, Hengmin, 2015. "An evolutionary game for the diffusion of rumor in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 433(C), pages 51-58.
    3. Han, Dun & Sun, Mei & Li, Dandan, 2015. "The virus variation model by considering the degree-dependent spreading rate," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 433(C), pages 42-50.
    4. Timothy C Reluga, 2010. "Game Theory of Social Distancing in Response to an Epidemic," PLOS Computational Biology, Public Library of Science, vol. 6(5), pages 1-9, May.
    5. Han, Dun & Sun, Mei, 2014. "Can memory and conformism resolve the vaccination dilemma?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 95-104.
    6. Schimit, P.H.T. & Monteiro, L.H.A., 2011. "A vaccination game based on public health actions and personal decisions," Ecological Modelling, Elsevier, vol. 222(9), pages 1651-1655.
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    Cited by:

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    3. 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).
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    6. Li, Qiu & Li, MingChu & Lv, Lin & Guo, Cheng & Lu, Kun, 2017. "A new prediction model of infectious diseases with vaccination strategies based on evolutionary game theory," Chaos, Solitons & Fractals, Elsevier, vol. 104(C), pages 51-60.
    7. Iwamura, Yoshiro & Tanimoto, Jun, 2018. "Realistic decision-making processes in a vaccination game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 494(C), pages 236-241.
    8. Yan, Shiqing, 2017. "The evolution of human mobility based on the public goods game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 478(C), pages 69-76.
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    10. Han, Dun & Shao, Qi & Li, Dandan & Sun, Mei, 2020. "How the individuals’ risk aversion affect the epidemic spreading," Applied Mathematics and Computation, Elsevier, vol. 369(C).
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