Coupled disease-vaccination behavior dynamic analysis and its application in COVID-19 pandemic

Xueyu Meng, Jianhong Lin, Yufei Fan, Fujuan Gao, Enrico Maria Fenoaltea, Zhiqiang Cai and Shubin Si

Chaos, Solitons & Fractals, 2023, vol. 169, issue C

Abstract: Predicting the evolutionary dynamics of the COVID-19 pandemic is a complex challenge. The complexity increases when the vaccination process dynamic is also considered. In addition, when applying a voluntary vaccination policy, the simultaneous behavioral evolution of individuals who decide whether and when to vaccinate must be included. In this paper, a coupled disease-vaccination behavior dynamic model is introduced to study the coevolution of individual vaccination strategies and infection spreading. We study disease transmission by a mean-field compartment model and introduce a non-linear infection rate that takes into account the simultaneity of interactions. Besides, the evolutionary game theory is used to investigate the contemporary evolution of vaccination strategies. Our findings suggest that sharing information with the entire population about the negative and positive consequences of infection and vaccination is beneficial as it boosts behaviors that can reduce the final epidemic size. Finally, we validate our transmission mechanism on real data from the COVID-19 pandemic in France.

Keywords: Epidemic spreading; Vaccination behavior; Compartment model; Evolutionary game theory; COVID-19 (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:169:y:2023:i:c:s0960077923001959

DOI: 10.1016/j.chaos.2023.113294

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