Study on the interaction between information dissemination and infectious disease dissemination under government prevention and management

In recent years, public health emergencies have occurred frequently around the world, and infectious diseases are one of the most destructive and influential events. The coupling effect between infectious disease transmission and information dissemination has been a research hotspot that scholars have focused on in recent years. Analyzing how to effectively prevent the impact of information dissemination on the process of infectious disease transmission from the perspective of government prevention and control has important theoretical significance. Firstly, this paper investigates the COVID-19 epidemic and establishes a coupled multi-channel network UFAT-SEIR transmission model under government prevention and management based on the characteristics of infectious disease transmission and information transmission. Considering the individual's ability to recognize information, the interaction between false information and real information, and the impact of group polarization, the step function is used to explore the results of the user's information decision-making process. Secondly, the microscopic Markov chain approach (MMCA) is constructed to derive the transmission threshold of infectious diseases related to the information transmission layer. Finally, simulation is performed based on the impact of government prevention and management actions on parameters. The research findings can provide relevant strategies and suggestions for the government to prevent and control the spread of infectious diseases.