Impact of environmental factors on the coevolution of information–emotions–epidemic dynamics in activity-driven multiplex networks

• Published in: Chinese physics B Vol. 33; no. 12; pp. 128903 - 615
• Main Authors: Huo, Liang’an, Liu, Bingjie, Zhao, Xiaomin
• Format: Journal Article
• Language: English
• Published: Chinese Physical Society and IOP Publishing Ltd 01.12.2024
• Subjects: activity-driven multiplex networks; emotional transmission; environmental factors; epidemic spreading; information diffusion; epidemic spreading; activity-driven multiplex networks; emotional transmission; environmental factors; information diffusion
• ISSN: 1674-1056; 2058-3834
• DOI: 10.1088/1674-1056/ad7df5

During public health emergencies, the diffusion of negative information can exacerbate the transmission of adverse emotions, such as fear and anxiety. These emotions can adversely affect immune function and, consequently, influence the spread of the epidemic. In this study, we established a coupled model incorporating environmental factors to explore the coevolution dynamic process of information–emotions–epidemic dynamics in activity-driven multiplex networks. In this model, environmental factors refer to the external conditions or pressures that affect the spread of information, emotions, and epidemics. These factors include media coverage, public opinion, and the prevalence of diseases in the neighborhood. These layers are dynamically cross-coupled, where the environmental factors in the information layer are influenced by the emotional layer; the higher the levels of anxious states among neighboring individuals, the greater the likelihood of information diffusion. Although environmental factors in the emotional layer are influenced by both the information and epidemic layers, they come from the factors of global information and the proportion of local infections among surrounding neighbors. Subsequently, we utilized the microscopic Markov chain approach to describe the dynamic processes, thereby obtaining the epidemic threshold. Finally, conclusions are drawn through numerical modeling and analysis. The conclusions suggest that when negative information increases, the probability of the transmission of anxious states across the population increases. The transmission of anxious states increases the final size of the disease and decreases its outbreak threshold. Reducing the impact of environmental factors at both the informational and emotional levels is beneficial for controlling the scale of the spread of the epidemic. Our findings can provide a reference for improving public health awareness and behavioral decision-making, mitigating the adverse impacts of anxious states, and ultimately controlling the spread of epidemics.