A multi-information epidemic spreading model on a two-layer network

During the epidemic outbreak, a substantial volume of information circulated among the public concerning the disease. To account for both local and global information, as well as individual differences, we developed a multi-information epidemic spreading model on a two-layer network. We employed the microscopic Markov chain approximation (MMCA) method to establish the dynamic equation and spreading threshold for the proposed model. Our research has revealed the following: (i) Disseminating positive information and increasing media coverage can effectively hinder the spread of epidemics. (ii) Under certain conditions, negative information can also hinder epidemic spreading. (iii) Both local and global information can enhance individuals' self-protection awareness, leading to inhibition of epidemic spread. (iv) Increasing an individual's awareness of the epidemic's severity and improving their response to infected neighbors can help prevent an outbreak of the disease.