Global dynamics of a SUIR model with predicting COVID-19

Wang, Jingyuan; Lin, Xin; Liu, Yuxi; Qilegeri,; Lin, Hui; Wu, Manqing

Since December 2019, A novel coronavirus (2019-nCoV) has been breaking out in China, which can cause respiratory diseases and severe pneumonia. Epidemic models relying on the incidence rate of new cases for forecasting epidemic outbreaks have received increasing attention. However, many prior works in this area mostly focus on the application of the traditional SIR model and disregard the transmission characteristics of 2019-nCoV, exceptionally the infectious of undiagnosed cases. Here, we propose a SUIR model based on the classical SIR model object to supervise the effective prediction, prevention, and control of infectious diseases. SUIR model adds a unique $U$ (Undiagnosed) state of the epidemic and divides the population into four states: S (Susceptible), U (Undiagnosed), I (Infectious and Uninfectious), and R (Recovered). This approach enables us to predict the incidence of 2019-nCoV effectively and the clear advantage of the model accuracy more reliable than the traditional SIR model.