Simulation analysis of epidemic trend for Covid-19 based on SEIRS model

Ge, J.; Zhang, L.; Chen, Z.; Chen, G.; Peng, J.

The current novel coronavirus disease 2019 (COVID-19) outbreak in global has provided an opportunity to understand the spread of this pandemic linked to healthcare settings. It is very important to predict the trend of epidemic situation for timely response. In this paper, we proposed a Susceptible-Exposed-Infectious-Recovered-Susceptible (SEIRS) model to simulate and forecast the trend of COVID-19 epidemic in China. The simulation results provide a good fit to the actual number and peak time of confirmed epidemic in Hubei province, and the simulation results also show that the epidemic of Hubei province would decline in early June. However, there are some differences between the simulation results and the real situation of other regions in China, because this model does not consider human intervention strategy. In a word, our SEIRS dynamic model is effective in simulating and predicting the COVID-19 epidemic in Hubei province, China, it has meaningful reference for the prevention and control of the pandemic situation which is raging all over the world. ©2020 IEEE