基于多层网络的传染病与负面情绪耦合传播模型 ̇

To reveal the co-evolutionary relationship between disease transmission intensity and emotional diffusion rate, based on a two-layer complex network structure, this study integrated the classical Susceptible-Exposed-Infected-Recovered (SEIR) epidemic model with a five-state emotional dynamics framework (S-E-I-G-R) to construct a coupled dynamics model (SEIR-SE IGR). Theoretical derivation and simulation validation were conducted using the microscopic Markov chain approach and Monte Carlo simulation. The findings reveal that although reducing the disease infection probability can mitigate the scale of emotional propagation, its inhibitory effect on the peak of emotional propagation remains limited. In contrast, shortening the disease incubation period and improving the recovery rate significantly regulate the spread of negative emotions, exhibiting a two-stage propagation pattern characterized by emotional metabolic hysteresis and the density threshold effect of emotional guides. Furthermore, enhancing individuals compliance with epidemic preventive measures can effectively delay the spread and reduce the scale of negative emotions through three pathways; blocking transmission chains, reinforcing social norms, and correcting cognitive biases.