SEIR-Based COVID-19 Transmission Model and Inflection Point Prediction Analysis

Abstract

The COVID-19 has severely affected the country, and people's social and economic lives have been greatly disrupted. Based on the complex network theory, a SEIR dynamic model of the COVID-19 epidemic with a latency period is established in this paper. By setting three scenarios of different incubation periods of the virus, based on national and partial epidemic data, the model parameters are simulated and analyzed for different scenarios. The inflection points of the three cases are predicted, and the results showed that the model analysis is basically consistent with the true performance of the epidemic development. Finally, the paper concludes with specific countermeasures and suggestions for strengthening the prevention and control of the epidemic.