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Dynamical behaviors and social efficiency deficit analysis of an epidemic model with three combined strategies

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  • Mahato, Kiriti Bhusan
  • Khatun, Mst Sebi
  • Ariful Kabir, K.M.
  • Das, Pritha

Abstract

In this article, we develop an SuSaVITR epidemic model that incorporates three unique behavior dynamics based on the evolutionary game theory (EGT). This study includes some of the most effective strategies for controlling the COVID-19 epidemic such as awareness, vaccination, and treatment, all of which depend on changes in human behavior influenced by risk perception and careful evaluation of costs. Each intervention in the behavioral model is represented by a dynamic equation that balances the associated costs against the risk of infection. In the non-behavioral model, we use the normalized forward sensitivity index method for local sensitivity analysis of the basic reproduction number (R0), while the LHS-PRCC method is employed for global sensitivity analysis of the infected compartment to identify the most influential parameters affecting disease dynamics. The simultaneous application of three strategies incorporating EGT with the minimum possible cost for each intervention proves to be the most effective approach for reducing the maximum number of infections compared to the application of single or double strategies. Simultaneously, the numerical results show that when awareness effect, vaccine efficacy and treatment recovery rates are high, they can significantly reduce the community’s risk of infection. Also, the average social payoff has been evaluated at both Nash equilibrium and social optimum to emphasize the increased social benefits that emerge when the costs of awareness, vaccination and treatment are minimized. Finally, the social efficiency deficit has been discussed to identify the situations that lead to dilemmas related to the epidemic model.

Suggested Citation

  • Mahato, Kiriti Bhusan & Khatun, Mst Sebi & Ariful Kabir, K.M. & Das, Pritha, 2025. "Dynamical behaviors and social efficiency deficit analysis of an epidemic model with three combined strategies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 659(C).
  • Handle: RePEc:eee:phsmap:v:659:y:2025:i:c:s0378437124008252
    DOI: 10.1016/j.physa.2024.130315
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    References listed on IDEAS

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    1. Chris T Bauch & Samit Bhattacharyya, 2012. "Evolutionary Game Theory and Social Learning Can Determine How Vaccine Scares Unfold," PLOS Computational Biology, Public Library of Science, vol. 8(4), pages 1-12, April.
    2. Khan, Md. Mamun-Ur-Rashid & Arefin, Md. Rajib & Tanimoto, Jun, 2022. "Investigating the trade-off between self-quarantine and forced quarantine provisions to control an epidemic: An evolutionary approach," Applied Mathematics and Computation, Elsevier, vol. 432(C).
    3. Khatun, Mst Sebi & Das, Samhita & Das, Pritha, 2023. "Dynamics and control of an SITR COVID-19 model with awareness and hospital bed dependency," Chaos, Solitons & Fractals, Elsevier, vol. 175(P1).
    4. Ullah, Mohammad Sharif & Higazy, M. & Kabir, K.M. Ariful, 2022. "Dynamic analysis of mean-field and fractional-order epidemic vaccination strategies by evolutionary game approach," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).
    5. Khatun, Mst Sebi & Mahato, Kiriti Bhusan & Das, Pritha, 2024. "Dynamics of an SuSaV IR epidemic model with stochastic optimal control and awareness programs," Chaos, Solitons & Fractals, Elsevier, vol. 183(C).
    6. Nishimura, Itsuki & Arefin, Md. Rajib & Tatsukawa, Yuichi & Utsumi, Shinobu & Hossain, Md. Anowar & Tanimoto, Jun, 2023. "Social dilemma analysis on vaccination game accounting for the effect of immunity waning," Chaos, Solitons & Fractals, Elsevier, vol. 171(C).
    7. Tori, Risa & Tanimoto, Jun, 2022. "A study on prosocial behavior of wearing a mask and self-quarantining to prevent the spread of diseases underpinned by evolutionary game theory," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
    8. Basnarkov, Lasko, 2021. "SEAIR Epidemic spreading model of COVID-19," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
    9. Yuan, Yiran & Li, Ning, 2022. "Optimal control and cost-effectiveness analysis for a COVID-19 model with individual protection awareness," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    10. Yadav, Pramod Kumar & Goel, Palak, 2023. "Treatment seeking dilemma for tuberculosis as timed strategic prisoner’s dilemma game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 632(P1).
    11. Turkyilmazoglu, Mustafa, 2022. "An extended epidemic model with vaccination: Weak-immune SIRVI," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 598(C).
    12. Liu, Qun & Jiang, Daqing & Hayat, Tasawar & Alsaedi, Ahmed, 2018. "Stationary distribution of a stochastic delayed SVEIR epidemic model with vaccination and saturation incidence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 849-863.
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