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Evolutionary vaccination dynamics with internal support mechanisms

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  • Tang, Guo-Mei
  • Cai, Chao-Ran
  • Wu, Zhi-Xi

Abstract

This paper reports internal support mechanisms (i.e., without external intervention) to enhance the vaccine coverage in the evolutionary vaccination dynamics. We present two internal support mechanisms, one is global support mechanism in which each individual pays a support cost to build up a public fund and then the public fund is divided by all vaccinated individuals, while another is local support mechanism in which each individual pays a support cost and then this support cost will be divided by its immediate vaccinated neighbors. By means of extensive computer simulations, we show that, in the same strength of support cost, the heterogeneous (local) support mechanism can encourage more people to take vaccination than the homogeneous (global) support mechanism. And then, we study the most general case that includes supporters and troublemakers together, where supporters (troublemakers) mean that the individuals join (do not join) the internal support mechanism, in the population. We surprisingly find that, in scale-free networks, the voluntary vaccination dynamics with the local support mechanism will not degrade into the original voluntary vaccination dynamics, and the vaccination level can still be effectively improved. In view of most social networks are of scale-free degree distribution, we study further in empirical networks and find that the vaccination level can still be improved in the absence of external intervention.

Suggested Citation

  • Tang, Guo-Mei & Cai, Chao-Ran & Wu, Zhi-Xi, 2017. "Evolutionary vaccination dynamics with internal support mechanisms," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 135-143.
    • Handle: RePEc:eee:phsmap:v:473:y:2017:i:c:p:135-143
    DOI: 10.1016/j.physa.2017.01.046
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    References listed on IDEAS

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    1. Daniel M Cornforth & Timothy C Reluga & Eunha Shim & Chris T Bauch & Alison P Galvani & Lauren Ancel Meyers, 2011. "Erratic Flu Vaccination Emerges from Short-Sighted Behavior in Contact Networks," PLOS Computational Biology, Public Library of Science, vol. 7(1), pages 1-10, January.
    2. Cai, Chao-Ran & Wu, Zhi-Xi & Guan, Jian-Yue, 2014. "Effect of vaccination strategies on the dynamic behavior of epidemic spreading and vaccine coverage," Chaos, Solitons & Fractals, Elsevier, vol. 62, pages 36-43.
    3. Fukuda, Eriko & Kokubo, Satoshi & Tanimoto, Jun & Wang, Zhen & Hagishima, Aya & Ikegaya, Naoki, 2014. "Risk assessment for infectious disease and its impact on voluntary vaccination behavior in social networks," Chaos, Solitons & Fractals, Elsevier, vol. 68(C), pages 1-9.
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    Cited by:

    1. Cui, Guang-Hai & Wang, Zhen & Li, Jun-Li & Jin, Xing & Zhang, Zhi-Wang, 2021. "Influence of precaution and dynamic post-indemnity based insurance policy on controlling the propagation of epidemic security risks in networks," Applied Mathematics and Computation, Elsevier, vol. 392(C).
    2. 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.
    3. Ding, Hong & Xu, Jia-Hao & Wang, Zhen & Ren, Yi-Zhi & Cui, Guang-Hai, 2018. "Subsidy strategy based on history information can stimulate voluntary vaccination behaviors on seasonal diseases," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 390-399.
    4. Wang, Xinhe & Lu, Junwei & Wang, Zhen & Li, Yuxia, 2020. "Dynamics of discrete epidemic models on heterogeneous networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).

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