Assessment and Prediction of COVID-19 Based on SEIR Model with Undiscovered People

In this paper the concept of 'undiscovered people' is introduced into traditional SEIR model for the research of COVID-19. The model fitting with result analysis is performed by utilizing COVID-19 data from 25 January 2020 to 22 February 2020. And then the fitted model is used to simulate the evolution after February 22, 2020. The results show that the introduction of 'undiscovered people' has a significant improvement in fitting and prediction performance, reducing the fitting error by 50% to 70%. The fitting coefficient shows that the virus-laden population accounted for 30% and 5% of exposed people, respectively, in the early and late stages of epidemic. The diagnosed probability of virus-laden population has increased from 7% to 40%, which shows that nucleic acid detection technology is becoming matured. Initial number of undiscovered people is about 70 000, and under effective national control, it is currently controlled at about 2 500. It is predicted that the "inflection point" will be mid-March, then residents can return to normal life at the end of April, and the cumulative diagnosis is about 100 000 finally. © 2020, Editorial Board of Journal of the University of Electronic Science and Technology of China. All right reserved.