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; Shubin Si

doi:10.1016/j.chaos.2023.113294

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

Chaos Solitons Fractals. 2023 Apr:169:113294. doi: 10.1016/j.chaos.2023.113294. Epub 2023 Mar 2.

Authors

Xueyu Meng^{1

2

3}, Jianhong Lin^{3

4}, Yufei Fan^{1

2}, Fujuan Gao³, Enrico Maria Fenoaltea³, Zhiqiang Cai^{1

2}, Shubin Si^{1

2}

Affiliations

¹ Department of Industrial Engineering, School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an 710072, China.
² Ministry of Industry and Information Technology Key Laboratory of Industrial Engineering and Intelligent Manufacturing, Northwestern Polytechnical University, Xi'an 710072, China.
³ Department of Physics, University of Fribourg, Fribourg 1700, Switzerland.
⁴ Department of Management, Technology and Economics, ETH Zürich, Scheuchzerstrasse 7, CH-8092 Zürich, Switzerland.

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: COVID-19; Compartment model; Epidemic spreading; Evolutionary game theory; Vaccination behavior.