The high infectivity and insidiousness of COVID-19 have enabled the virus to spread rapidly around the world, threatening human life, health and social order, and being infectious in crowded places such as subway stations. Based on the analysis of COVID-19 transmission, this paper divides the population into three categories: susceptible category, discovered disease category and immune category consisting of cure and death, and proposes two models: crowd contact network and contact

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... SIR model to simulate the transmission process of SIR; then absorbs the idea of synchronous update of cellular automaton model, and finally establishes a contact network-based SIR model whose members are affected by all passengers at the same time simulation model. For this model, we fit the data of Beijing, analyze and predict the peak of the latest round of epidemic development (the peak of the number of patients, the peak of the transmission rate), and the length of the latest round of epidemic development cycle, etc, and propose some policy recommendations accordingly.