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Historical payoff can not overcome the vaccination dilemma on Barabási–Albert scale-free networks

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  • Wang, Qingqing
  • Du, Chunpeng
  • Geng, Yini
  • Shi, Lei

Abstract

Past experiences have an important impact on people's behavioral decisions. In this paper, we propose an epidemiological model to study the impact of historical payoff on the vaccination behavior on scale-free network. The individual's fitness is not affected by historical payoff when an individual's payoff is higher than his neighbor's average payoff. On the contrary, individual's fitness depends on a certain extent on the previous round of his own payoff. Through numerical simulation, our results show that the historical payoff has negative effect on the vaccination behavior on scale-free network. We will explain these results in terms of network heterogeneity in this article. Finally, we verify the robustness of the model in different networks.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:chsofr:v:130:y:2020:i:c:s0960077919303996
    DOI: 10.1016/j.chaos.2019.109453
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    Cited by:

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    2. Chang, Sheryl L. & Piraveenan, Mahendra & Prokopenko, Mikhail, 2020. "Impact of network assortativity on epidemic and vaccination behaviour," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
    3. Kabir, K.M. Ariful, 2021. "How evolutionary game could solve the human vaccine dilemma," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).

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