TY - JOUR
T1 - Coupled disease-vaccination behavior dynamic analysis and its application in COVID-19 pandemic
AU - Meng, Xueyu
AU - Lin, Jianhong
AU - Fan, Yufei
AU - Gao, Fujuan
AU - Fenoaltea, Enrico Maria
AU - Cai, Zhiqiang
AU - Si, Shubin
N1 - Publisher Copyright:
© 2023 Elsevier Ltd
PY - 2023/4
Y1 - 2023/4
N2 - 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.
AB - 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.
KW - COVID-19
KW - Compartment model
KW - Epidemic spreading
KW - Evolutionary game theory
KW - Vaccination behavior
UR - http://www.scopus.com/inward/record.url?scp=85149443004&partnerID=8YFLogxK
U2 - 10.1016/j.chaos.2023.113294
DO - 10.1016/j.chaos.2023.113294
M3 - 文章
AN - SCOPUS:85149443004
SN - 0960-0779
VL - 169
JO - Chaos, Solitons and Fractals
JF - Chaos, Solitons and Fractals
M1 - 113294
ER -