Emotion-based epidemic dynamics coupling information with diseases in multiplex networks.

The process of information diffusion can cause changes in the emotions of individuals, which in turn can have an impact on the process of disease spreading. This paper describes a coupled information-disease spreading model based on multiplex networks, taking into account individual emotions, which can be used to investigate the interaction between positive and negative information diffusion, emotion accumulation, and disease spreading. In our model, emotions act as a mediator of the interaction between information diffusion and disease spreading, with individuals reacting emotionally based on the information they receive, and emotions in turn influencing disease infection and recovery through accumulation. In addition, to measure the impact of emotions, we introduce two indicators: the emotion threshold and the immune impact factor. The Micro-Markov chain approach is used for the theoretical analysis to derive the dynamic evolution process of the model and to calculate the prevalence threshold. We validate the theoretical analysis through extensive numerical simulations. The results show that individual emotions can have an impact on the disease spreading process. Specifically, positive emotions can effectively inhibit the spread of disease, slow down the rate of an outbreak, and reduce outbreak size in a population, while negative emotions can greatly facilitate the spread of disease, accelerate the rate of disease prevalence, and increase outbreak size. [ABSTRACT FROM AUTHOR]