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Investigation of vaccination game approach in spreading covid-19 epidemic model with considering the birth and death rates

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  • Vivekanandhan, Gayathri
  • Nourian Zavareh, Mahdi
  • Natiq, Hayder
  • Nazarimehr, Fahimeh
  • Rajagopal, Karthikeyan
  • Svetec, Milan

Abstract

In this study, an epidemic model for spreading COVID-19 is presented. This model considers the birth and death rates in the dynamics of spreading COVID-19. The birth and death rates are assumed to be the same, so the population remains constant. The dynamics of the model are explained in two phases. The first is the epidemic phase, which spreads during a season based on the proposed SIR/V model and reaches a stable state at the end of the season. The other one is the “vaccination campaign”, which takes place between two seasons based on the rules of the vaccination game. In this stage, each individual in the population decides whether to be vaccinated or not. Investigating the dynamics of the studied model during a single epidemic season without consideration of the vaccination game shows waves in the model as experimental knowledge. In addition, the impact of the parameters is studied via the rules of the vaccination game using three update strategies. The result shows that the pandemic speeding can be changed by varying parameters such as efficiency and cost of vaccination, defense against contagious, and birth and death rates. The final epidemic size decreases when the vaccination coverage increases and the average social payoff is modified.

Suggested Citation

  • Vivekanandhan, Gayathri & Nourian Zavareh, Mahdi & Natiq, Hayder & Nazarimehr, Fahimeh & Rajagopal, Karthikeyan & Svetec, Milan, 2022. "Investigation of vaccination game approach in spreading covid-19 epidemic model with considering the birth and death rates," Chaos, Solitons & Fractals, Elsevier, vol. 163(C).
    • Handle: RePEc:eee:chsofr:v:163:y:2022:i:c:s0960077922007573
    DOI: 10.1016/j.chaos.2022.112565
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    References listed on IDEAS

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    2. Cui, Guang-Hai & Li, Jun-Li & Dong, Kun-Xiang & Jin, Xing & Yang, Hong-Yong & Wang, Zhen, 2024. "Influence of subsidy policies against insurances on controlling the propagation of epidemic security risks in networks," Applied Mathematics and Computation, Elsevier, vol. 476(C).

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