Research on the Modeling of New Coronary Disease Based on Awareness and Communication of Multilayer Network

The COVID-19 pandemic has been a global health crisis for several years, and understanding its transmission and behavioral dynamics is crucial for controlling its spread. In this paper, we propose a multi-layer composite network-based model that combines disease transmission and consciousness to simulate COVID-19. The model is an extension of the UAU-SIER model that takes into account the topology of physical contacts between groups of people and the influence of awareness on disease transmission. We develop a state transition equation using the Micro Markov Chain Method (MMCA) and derive the transmission threshold under the epidemic model. We also compare the performance of different models in the upper network layer that represents information exchange between conscious and unconscious states. Our results contribute to COVID-19 research by providing more effective models for epidemiological studies.