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Investigating the trade-off between self-quarantine and forced quarantine provisions to control an epidemic: An evolutionary approach

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  • Khan, Md. Mamun-Ur-Rashid
  • Arefin, Md. Rajib
  • Tanimoto, Jun

Abstract

During a pandemic event like the present COVID-19, self-quarantine, mask-wearing, hygiene maintenance, isolation, forced quarantine, and social distancing are the most effective nonpharmaceutical measures to control the epidemic when the vaccination and proper treatments are absent. In this study, we proposed an epidemiological model based on the SEIR dynamics along with the two interventions defined as self-quarantine and forced quarantine by human behavior dynamics. We consider a disease spreading through a population where some people can choose the self-quarantine option of paying some costs and be safer than the remaining ones. The remaining ones act normally and send to forced quarantine by the government if they get infected and symptomatic. The government pays the forced quarantine costs for individuals, and the government has a budget limit to treat the infected ones. Each intervention derived from the so-called behavior model has a dynamical equation that accounts for a proper balance between the costs for each case, the total budget, and the risk of infection. We show that the infection peak cannot be reduced if the authority does not enforce a proactive (quantified by a higher sensitivity parameter) intervention. While comparing the impact of both self- and forced quarantine provisions, our results demonstrate that the latter is more influential to reduce the disease prevalence and the social efficiency deficit (a gap between social optimum payoff and equilibrium payoff).

Suggested Citation

  • 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).
  • Handle: RePEc:eee:apmaco:v:432:y:2022:i:c:s0096300322004398
    DOI: 10.1016/j.amc.2022.127365
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    References listed on IDEAS

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    1. Nenchev, Vladislav, 2020. "Optimal quarantine control of an infectious outbreak," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
    2. Amaral, Marco A. & Oliveira, Marcelo M. de & Javarone, Marco A., 2021. "An epidemiological model with voluntary quarantine strategies governed by evolutionary game dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 143(C).
    3. Li, Hui-Jia & Xu, Wenzhe & Song, Shenpeng & Wang, Wen-Xuan & Perc, Matjaž, 2021. "The dynamics of epidemic spreading on signed networks," Chaos, Solitons & Fractals, Elsevier, vol. 151(C).
    4. Dror Meidan & Nava Schulmann & Reuven Cohen & Simcha Haber & Eyal Yaniv & Ronit Sarid & Baruch Barzel, 2021. "Alternating quarantine for sustainable epidemic mitigation," Nature Communications, Nature, vol. 12(1), pages 1-12, December.
    5. 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).
    6. 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.
    7. Babaei, A. & Ahmadi, M. & Jafari, H. & Liya, A., 2021. "A mathematical model to examine the effect of quarantine on the spread of coronavirus," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
    8. Deka, Aniruddha & Bhattacharyya, Samit, 2022. "The effect of human vaccination behaviour on strain competition in an infectious disease: An imitation dynamic approach," Theoretical Population Biology, Elsevier, vol. 143(C), pages 62-76.
    9. Kabir, KM Ariful & Chowdhury, Atiqur & Tanimoto, Jun, 2021. "An evolutionary game modeling to assess the effect of border enforcement measures and socio-economic cost: Export-importation epidemic dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 146(C).
    10. Kabir, K.M. Ariful & Kuga, Kazuki & Tanimoto, Jun, 2019. "Analysis of SIR epidemic model with information spreading of awareness," Chaos, Solitons & Fractals, Elsevier, vol. 119(C), pages 118-125.
    11. Stipic, Dorian & Bradac, Mislav & Lipic, Tomislav & Podobnik, Boris, 2021. "Effects of quarantine disobedience and mobility restrictions on COVID-19 pandemic waves in dynamical networks," Chaos, Solitons & Fractals, Elsevier, vol. 150(C).
    12. Alberto Aleta & David Martín-Corral & Ana Pastore y Piontti & Marco Ajelli & Maria Litvinova & Matteo Chinazzi & Natalie E. Dean & M. Elizabeth Halloran & Ira M. Longini Jr & Stefano Merler & Alex Pen, 2020. "Modelling the impact of testing, contact tracing and household quarantine on second waves of COVID-19," Nature Human Behaviour, Nature, vol. 4(9), pages 964-971, September.
    13. Miyaji, Kohei & Tanimoto, Jun, 2021. "A co-evolutionary model combined mixed-strategy and network adaptation by severing disassortative neighbors promotes cooperation in prisoner’s dilemma games," Chaos, Solitons & Fractals, Elsevier, vol. 143(C).
    14. Ahsan Habib, Md. & Tanaka, Masaki & Tanimoto, Jun, 2020. "How does conformity promote the enhancement of cooperation in the network reciprocity in spatial prisoner's dilemma games?," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
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