Analysis of 2019-nCoV epidemic situation based on modified SEIR model and DSGE algorithm

Abstract

In order to analyze the spread of novel coronavirus pneumonia., a prediction model based on the modified SEIR infectious disease transmission kinetic model for the number of confirmed and fatal cases of novel coronavirus pneumonia was constructed to predict the outbreak of the epidemic in China. Differential equations were constructed to take into account the spread of the epidemic and the assignment of each parameter in the model to obtain the prediction results for China. The prediction of the epidemic in the United States was divided into two cases with and without a home order. In order to analyze the impact of 2019-nCoV epidemic on economic development, the fiscal revenue of Hubei Province from January to July in 2020 is analyzed, and the change of GDP and tertiary industry output value in Hubei Province is predicted by combining grey prediction model with time series. In this paper, DSGE algorithm is used to study the changes of labor supply, output, investment and capital under different costs during the epidemic period. The results were analyzed with respect to the major epidemic prevention measures taken by the Chinese Ministry of Health (MOH). Finally, the reliability of the model was analyzed.