A co-evolutionary model of information, behavior, and epidemics in multiplex networks: Incorporating subjective and objective factors

IF 3.5 2区 数学 Q1 MATHEMATICS, APPLIED
Yue Yu , Liang'an Huo
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引用次数: 0

Abstract

The dissemination of information and the adoption of immunization behaviors are vital for preventing infection during epidemics. Positive and negative information have different influences on the decision to accept immunization behaviors, and individuals make decisions about whether to accept immunization based on both subjective cognizance and objective environmental factors. A three-layer propagation model is proposed to explore the co-evolutionary dynamics of competitive information, immunization behavior, and epidemics in multiplex networks. We consider the competitive transmission of positive and negative information under the effect of individual cognitive preference and the effect of the subjective cognizance and objective environmental factors. For the objective environmental factors, the Prospect Theory is introduced to describe the risk-related costs. Furthermore, we investigate the local group immunity phenomenon. Utilizing the MMCA (microscopic Markov chain approach) for theoretical analysis, our findings indicate that the dynamics of epidemic transmission can indeed undergo multi-stage phase transitions when there exists a competing propagation of positive and negative information. Improving individual cognitive preference for positive information is essential for making the right judgments when engaging in the immunization game process and reducing the epidemic transmission scale. In addition, individuals are encouraged to reduce the free-rider strategy and adopt immunization behavior timely during epidemic transmission, as this contributes to overall emergency management.
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来源期刊
CiteScore
7.90
自引率
10.00%
发文量
755
审稿时长
36 days
期刊介绍: Applied Mathematics and Computation addresses work at the interface between applied mathematics, numerical computation, and applications of systems – oriented ideas to the physical, biological, social, and behavioral sciences, and emphasizes papers of a computational nature focusing on new algorithms, their analysis and numerical results. In addition to presenting research papers, Applied Mathematics and Computation publishes review articles and single–topics issues.
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