Transmission Process Prediction of Novel Coronavirus Based on System Dynamics

Authors

Xuepeng Lu, School of Information, Beijing Wuzi University, Beijing 101149, China;
Shang Jiao, School of Information, Beijing Wuzi University, Beijing 101149, China;
Junhui Zhao, School of Information, Beijing Wuzi University, Beijing 101149, China;
Lulu Lü, School of Information, Beijing Wuzi University, Beijing 101149, China;
Zhou Li, School of Information, Beijing Wuzi University, Beijing 101149, China;

Abstract

Abstract: The transmission characteristics of novel coronavirus is considered and a new SE4IR2 model based on the principle of system dynamics is proposed. The US epidemic data from June to November is used to set the isolation rate and other parameters, and the SE4IR2 model is used to fit, analyze and predict the development of the epidemic trend in the next stage. The empirical part uses the data from June to November in the United States to achieve the parameters of the SE4IR2 model, obtains the parameter values in December and January through the time series prediction model, and compares the predicted number of deaths and the people cured with those of the WTO published in December and January. The error in December is 0.75% and - 0.86%, and the error in January is 2.78% and 3.57%. Based on the results of the empirical analysis, considering the constraints between the various parameters, the corresponding recommendations for epidemic prevention and control are given. The results show that the SE4IR2 model has better simulation accuracy and is more suitable for simulating the spread of COVID-19.

Recommended Citation

Lu, Xuepeng; Jiao, Shang; Zhao, Junhui; Lü, Lulu; and Li, Zhou (2021) "Transmission Process Prediction of Novel Coronavirus Based on System Dynamics," Journal of System Simulation: Vol. 33: Iss. 7, Article 23.
DOI: 10.16182/j.issn1004731x.joss.20-1019
Available at: https://dc-china-simulation.researchcommons.org/journal/vol33/iss7/23

First Page

1713

Revised Date

2021-02-24

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.20-1019

Last Page

1721

CLC

TP391.9

Recommended Citation

Lu Xuepeng, Shang Jiao, Zhao Junhui, Lü Lulu, Zhou Li. Transmission Process Prediction of Novel Coronavirus Based on System Dynamics[J]. Journal of System Simulation, 2021, 33(7): 1713-1721.

DOI

10.16182/j.issn1004731x.joss.20-1019