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Rational behavior is a ‘double-edged sword’ when considering voluntary vaccination

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  • Zhang, Haifeng
  • Fu, Feng
  • Zhang, Wenyao
  • Wang, Binghong

Abstract

Of particular importance for public health is how to understand strategic vaccination behavior in social networks. Social learning is a central aspect of human behavior, and it thus shapes vaccination individuals’ decision-making. Here, we study two simple models to address the impact of the more rational decision-making of individuals on voluntary vaccination. In the first model, individuals are endowed with memory capacity for their past experiences of dealing with vaccination. In addition to their current payoffs, they also take account of the historical payoffs that are discounted by a memory-decaying factor. They use such overall payoffs (weighing the current payoffs and historical payoffs) to reassess their vaccination strategies. Those who have higher overall payoffs are more likely imitated by their social neighbors. In the second model, individuals do not blindly learn the strategies of neighbors; they also combine the fraction of infection in the past epidemic season. If the fraction of infection surpasses the perceived risk threshold, individuals will increase the probability of taking vaccination. Otherwise, they will decrease the probability of taking vaccination. Then we use evolutionary game theory to study the vaccination behavior of people during an epidemiological process. To do this, we propose a two-stage model: individuals make vaccination decisions during a yearly vaccination campaign, followed by an epidemic season. This forms a feedback loop between the vaccination decisions of individuals and their health outcomes, and thus payoffs. We find that the two more rational decision-making models have nontrivial impacts on the vaccination behavior of individuals, and, as a result, on the final fraction of infection. Our results highlight that, from an individual’s viewpoint, the decisions are optimal and more rational. However, from the social viewpoint, the strategies of individuals can give rise to distinct outcomes. Namely, the rational behavior of individuals plays a ‘double-edged-sword’ role on the social effects.

Suggested Citation

  • Zhang, Haifeng & Fu, Feng & Zhang, Wenyao & Wang, Binghong, 2012. "Rational behavior is a ‘double-edged sword’ when considering voluntary vaccination," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(20), pages 4807-4815.
    • Handle: RePEc:eee:phsmap:v:391:y:2012:i:20:p:4807-4815
    DOI: 10.1016/j.physa.2012.05.009
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    Citations

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    Cited by:

    1. Sheryl Le Chang & Mahendra Piraveenan & Mikhail Prokopenko, 2019. "The Effects of Imitation Dynamics on Vaccination Behaviours in SIR-Network Model," IJERPH, MDPI, vol. 16(14), pages 1-31, July.
    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. 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).
    4. Lin, Ying-Ting & Han, Xiao-Pu & Wang, Bing-Hong, 2014. "Dynamics of human innovative behaviors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 394(C), pages 74-81.
    5. 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.
    6. Alam, Muntasir & Kuga, Kazuki & Tanimoto, Jun, 2019. "Three-strategy and four-strategy model of vaccination game introducing an intermediate protecting measure," Applied Mathematics and Computation, Elsevier, vol. 346(C), pages 408-422.
    7. 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.
    8. Wang, Qingqing & Du, Chunpeng & Geng, Yini & Shi, Lei, 2020. "Historical payoff can not overcome the vaccination dilemma on Barabási–Albert scale-free networks," Chaos, Solitons & Fractals, Elsevier, vol. 130(C).
    9. Dong, Chao & Yin, Qiuju & Liu, Wenyang & Yan, Zhijun & Shi, Tianyu, 2015. "Can rewiring strategy control the epidemic spreading?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 169-177.
    10. 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.
    11. 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.
    12. Ichinose, Genki & Kurisaku, Takehiro, 2017. "Positive and negative effects of social impact on evolutionary vaccination game in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 84-90.
    13. 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.
    14. Shi, Benyun & Liu, Guangliang & Qiu, Hongjun & Wang, Zhen & Ren, Yizhi & Chen, Dan, 2019. "Exploring voluntary vaccination with bounded rationality through reinforcement learning," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 171-182.
    15. 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.

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