Prediction of the Initial Development Trend of COVID-19 with Dynamic Infectious Models

ABSTRACT

In the field of public health, using mathematical models to analyze the spread of infectious diseases is an excellent method. The purpose of this paper is to use the improved SEIR model to study the transmission trend in the early stage of the Covid-19. Under using the real-time data and related parameters, in order to better simulate the actual situation of disease transmission, this paper adds more detailed conditions on the basis of the classical model. The results show that the two improved models can predict the actual propagation trend more accurately than the classical model. The improvement of the SEIR is not only conducive to the progress of mathematical model field, but also can provide better suggestions for government agencies to control Covid-19. © 2020 IEEE.