Research of COVID-19 epidemic Model based on SEIR Model
DOI: 10.23977/medsc.2021.020101 | Downloads: 10 | Views: 1672
Author(s)
Wenhui Zhu 1, Xiyi Wang 2, Congcong Li 1
Affiliation(s)
1 School of Economics and Management, Anhui Agricultural University, Hefei, Anhui, 230036, China
2 School of Science, Anhui Agricultural University, Hefei, Anhui, 230036, China
Corresponding Author
Wenhui ZhuABSTRACT
This article mainly studies the infectious disease model of COVID-19. Based on the SEIR model, the epidemic prevention and control are divided into two stages according to my country's national conditions. The subjects of the study are normal people, lurking people, confirmed people, cured people, and dead people. Establish differential equation models and solve parameters for analysis and prediction. At the same time, the basic infection number is defined to compare the size of the basic infection number in the two cases of China's unmanned intervention and related prevention and control measures, and draw the conclusion that China's epidemic prevention and control policy is obviously effective.
KEYWORDS
COVID-19, SEIR, matlab fitting, epidemic modelCITE THIS PAPER
Wenhui Zhu, Xiyi Wang, Congcong Li. Research of COVID-19 epidemic Model based on SEIR Model. MEDS Clinical Medicine (2021) 2: 1-5. DOI: http://dx.doi.org/10.23977/medsc.2021.020101.
REFERENCES
[1] Cao Shengli, Feng Peihua, Shi Peng. The modified SEIR epidemic dynamics model was applied to predict and evaluate the epidemic situation of 2019 coronavirus disease (COVID-19) in Hubei Province [J]. Journal of Zhejiang University (Medical Edition), 2020, 49 (02): 178-184.
[2] Yang Guang, Zhang Qingling. Threshold analysis of applying control to the mathematical model of infectious disease (Kermack-Mckendrick model) [J]. Journal of Biomathematics, 2004 (02): 180, 184.
[3] Sun Mingjing. Study on time-delay SEIR Model with birth rate and Mortality rate [D]. Dalian University of Technology, 2005.
[4] Chen Liujuan. Global stability of a SEIR epidemic model with nonmonotone infection rate [J]. Journal of Biomathematics, 2009. 24 (04): 591-598.
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