期刊
CHAOS SOLITONS & FRACTALS
卷 169, 期 -, 页码 -出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.chaos.2023.113294
关键词
Epidemic spreading; Vaccination behavior; Compartment model; Evolutionary game theory; COVID-19
In this study, a coupled disease-vaccination behavior dynamic model is introduced to investigate the coevolution of individual vaccination strategies and infection spreading. The study finds that sharing information about the consequences of infection and vaccination with the entire population is beneficial in reducing the final epidemic size.
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.
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