Abstract：Novel coronavirus is a new type of virus, and its transmission characteristics are different from previous virus. Infected people not only have an incubation period, but also a large number of asymptomatic infections. Based on the classic model SEIR, this study redefines the latent state as close contact state, introduces an asymptomatic state of infection, and the influence of time on the state transition parameters in the model is considered, proposed a new transmission model which includes five types of states: susceptible state, close contact state, asymptomatic infection state, infected state, and removed state. The model uses the actual epidemic data of Hubei Province to conduct experiments, and uses RMSE and MAPE as evaluation indicators to compare the experimental results. The results show that the fitting accuracy of the SCUIR model has been significantly improved. Compared with the traditional model, the fitting error is reduced by 8.3%~47.6%, and hidden data that is difficult to count in the epidemic can be calculated, which further characterizes the mechanism of epidemic transmission.
李冯, 宾晟, 孙更新. 基于时变参数的SCUIR传播模型的构建与研究[J]. 复杂系统与复杂性科学, 2022, 19(2): 80-86.
LI Feng, BIN Sheng, SUN Gengxin. Based on Time-varying Parameters. Complex Systems and Complexity Science, 2022, 19(2): 80-86.
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