Human prophylaxis-driven cooperative spreading between information and epidemics in duplex networks

困境 流行病模型 计算机科学 风险分析(工程) 业务 医学 环境卫生 人口 数学 几何学
作者
Congying Liu,Xiaoqun Wu,Xiaoyang Liu,Ling Lei,Junchan Zhao
出处
期刊:Chaos [American Institute of Physics]
卷期号:35 (3)
标识
DOI:10.1063/5.0254726
摘要

Human behaviors play a crucial role in the intertwined dynamics of information diffusion and epidemic spreading. In turn, the spread of information and epidemics also affects individual behavioral changes. Understanding how information and epidemics propagate when individuals make coordinated decisions is essential to designing practicable control policies. To delve into this, we modify the unaware–aware–unaware susceptible-infected-susceptible (UAU-SIS) model by a two-strategy game-theory dilemma and explore how individual protective behaviors drive the interaction between information diffusion and epidemic spreading. Our theoretical analysis reveals that at the onset of an epidemic, individuals will not take any preventive measures, with the epidemic threshold being determined primarily by the topological structure of the epidemic layer. Extensive simulations help us explore the emergence of protective behaviors. A key finding is the existence of a crucial protection threshold, beyond which aware individuals begin to adopt preventive measures. Furthermore, our findings suggest that the high recovery rate or cost associated with contracting the disease, coupled with the poor failure rate of preventive measures or the low forgotten rate, leads to a significant number of aware individuals participating in self-protection, curbing the spread of epidemics. Moreover, even though individual protective decisions evolve in the information layer, the topology of the epidemic layer profoundly impacts both information diffusion and epidemic spreading. This work offers a new insight into the intertwined processes between information diffusion and epidemic spreading driven by human behaviors, which could help decision-makers gain some viable approaches to intervening in diseases.
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