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Exploring epidemic voluntary vaccinating behavior based on information-driven decisions and benefit-cost analysis

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  • Zuo, Chao
  • Ling, Yuting
  • Zhu, Fenping
  • Ma, Xinyu
  • Xiang, Guochun

Abstract

A complex dynamic interplay exists between epidemic transmission and vaccination, which is significantly influenced by human behavioral responses. We construct a research framework combining both the function modeling of the cumulative global COVID-19 information and limited individuals’ information processing capacity employing the Gompertz model for growing processes. Meanwhile, we built a function representing the decision to get vaccinated following benefit-cost analysis considered the choices made by people in each scenario have an influence from altruism, free-riding and immunity escaping capacity. Through the mean-field calculation analysis and using a fourth-order Runge-Kutta method with constant step size, we obtain plots from numerical simulations.

Suggested Citation

  • Zuo, Chao & Ling, Yuting & Zhu, Fenping & Ma, Xinyu & Xiang, Guochun, 2023. "Exploring epidemic voluntary vaccinating behavior based on information-driven decisions and benefit-cost analysis," Applied Mathematics and Computation, Elsevier, vol. 447(C).
    • Handle: RePEc:eee:apmaco:v:447:y:2023:i:c:s0096300323000747
    DOI: 10.1016/j.amc.2023.127905
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    References listed on IDEAS

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    1. Wang, Xueli & Zhang, Suxia, 2024. "Coupling media coverage and susceptibility for modeling epidemic dynamics: An application to COVID-19," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 217(C), pages 374-394.

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