Evaluation and Prediction of Prevention and Control Effects of the COVID-19 Epidemic Based on the SEIR Model

CHEN Xingzhi; TIAN Baodan; WANG Daiwen; HUANG Feixiang; FU Lingyan; XU Haoying

doi:10.21656/1000-0887.410139

Volume 42 Issue 2

Feb. 2021

Turn off MathJax

Article Contents

Article Navigation > Applied Mathematics and Mechanics > 2021 > 42(2): 199-211

CHEN Xingzhi, TIAN Baodan, WANG Daiwen, HUANG Feixiang, FU Lingyan, XU Haoying. Evaluation and Prediction of Prevention and Control Effects of the COVID-19 Epidemic Based on the SEIR Model[J]. Applied Mathematics and Mechanics, 2021, 42(2): 199-211. doi: 10.21656/1000-0887.410139

Citation:

PDF( 4660 KB)

Evaluation and Prediction of Prevention and Control Effects of the COVID-19 Epidemic Based on the SEIR Model

doi: 10.21656/1000-0887.410139

School of Science, Southwest University of Science and Technology, Mianyang, Sichuan 621010, P.R.China

Received Date: 2020-05-14
Rev Recd Date: 2020-12-31
Publish Date: 2021-02-01

Abstract

Abstract

Based on the analysis of the spread of the COVID-19 epidemic in China, a SEIR epidemic model was established with the diagnosed population divided into 2 categories: the admitted population and the non-admitted population. Through theoretical analysis, the basic reproduction number, the disease-free equilibrium of the model and its stability were derived. Further, several numerical simulations and comparative analysis were conducted on the development trend of the epidemic situation in Wuhan before and after the city closure, as well as the influences of some important parameters in the model on the number of diagnosed cases. Finally, according to the results of above theoretical analysis and numerical simulations, some control strategies previously adopted were analyzed and evaluated, and predictions were made for the development of the epidemic.
- COVID-19,
- basic reproduction number,
- disease-free equilibrium,
- stability,
- epidemic assessment

FullText(HTML)

References(20)

References

[1]	周娟, 李丹, 龙云铸. 新型冠状病毒(2019- n CoV)相关研究进展[J]. 中国感染控制杂志, 2020,19(3): 288-292.(ZHOU Juan, LI Dan, LONG Yunzhu. Advances in related research on novel coronavirus (2019- n CoV) [J]. Chinese Journal of Infection Control,2020,19(3): 288-292.(in Chinese))
[2]	秦红亚, 刘瑞娟, 苗健龙, 等. 2019新型冠状病毒肺炎研究进展[J]. 临床肺科杂志, 2020,25(3): 440-444.(QIN Hongya, LIU Ruijuan, MIAO Jianlong, et al. Research progress of new coronavirus pneumonia in 2019[J]. Journal of Clinical Pulmonary Medicine,2020,25(3): 440-444.(in Chinese))
[3]	汤芳, 王晓芹, 栾进, 等. 新型冠状病毒肺炎的流行病学研究进展[J]. 武警医学, 2020,31(3): 272-276.(TANG Fang, WANG Xiaoqin, LUAN Jin, et al. Epidemiological research progress of new coronavirus pneumonia[J]. Medical Journal of the Chinese People’s Armed Police Forces,2020,31(3): 272-276.(in Chinese))
[4]	DAI C, JING Y, WANG K. Evaluation of prevention and control interventions and its impact on the epidemic of coronavirus disease 2019 in Chongqing and Guizhou provinces[J]. Mathematical Biosciences and Engineering,2020,17(4): 2781-2791.
[5]	杨雨琦, 孙琦, 王悦欣, 等. 重庆市新型冠状病毒肺炎（NCP）疫情分析与趋势预测[J]. 重庆师范大学学报(自然科学版), 2020,37(1): 135-140.(YANG Yuqi, SUN Qi, WANG Yuexin, et al. Epidemic situation analysis and trend forecast of new coronavirus pneumonia (NCP) in Chongqing[J]. Journal of Chongqing Normal University (Natural Science),2020,37(1): 135-140.(in Chinese))
[6]	耿辉, 徐安定, 王晓艳, 等. 基于SEIR模型分析相关干预措施在新型冠状病毒肺炎疫情中的作用[J]. 暨南大学学报(自然科学与医学版), 2020,41(2): 175-180.(GENG Hui, XU Anding, WANG Xiaoyan, et al. Analysis of the role of current prevention and control measures in the epidemic of corona virus disease 2019 based on SEIR model [J]. Journal of Jinan University (Natural Science & Medicine Edition),2020,41(2): 175-180.(in Chinese))
[7]	WU J T, LEUNG K, LEUNG G M. Nowcasting and forecasting the potential domestic and international spread of the 2019- n CoV outbreak originating in Wuhan, China: a modelling study[J]. The Lancet,2020,395(10225): 689-697.
[8]	张云俊, 张原, 尤翀, 等. 新型冠状病毒肺炎(COVID-19)传染病传播动力学模型的综述[J]. 中华医学科研管理杂志, 2020,33: E014. DOI: 10.3760/cma.j.cn113565-20200214-00007.(ZHANG Yunjun, ZHANG Yuan, YOU Chong, et al. Review on the study of spreading of the COVID-19 based on dynamic models [J]. Chinese Journal of Medical Research Management,2020,33: E014. DOI: 10.3760/cma.j.cn113565-20200214-00007.(in Chinese))
[9]	曹盛力, 冯沛华, 时朋朋. 修正SEIR传染病动力学模型应用于湖北省2019冠状病毒病(COVID-19)疫情预测和评估[J]. 浙江大学学报(医学版), 2020,49(2): 178-184.(CAO Shengli, FENG Peihua, SHI Pengpeng. Study on the epidemic development of COVID-19 in Hubei province by a modified SEIR model[J]. Journal of Zhejiang University (Medical Science),2020,49(2): 178-184.(in Chinese))
[10]	赵序茅, 李欣海, 聂常虹. 基于大数据回溯新冠肺炎的扩散趋势及中国对疫情的控制研究[J]. 中国科学院院刊, 2020,35(3): 248-255.(ZHAO Xumao, LI Xinhai, NIE Changhong. Backtracking transmission of COVID-19 in China based on big data source, and effect of strict pandemic control policy[J]. Bulletin of the Chinese Academy of Sciences,2020,35(3): 248-255.(in Chinese))
[11]	梁桂珍. 一类潜伏期和染病期均传染的SEIQR流行病模型的稳定性[J]. 西南师范大学学报(自然科学版), 2020,45(3): 1-9.(LIANG Guizhen. Stability of a SEIQR epidemic model with infectious incubation period and infectious period[J]. Journal of Southwest Normal University (Natural Science Edition),2020,45(3): 1-9.(in Chinese))
[12]	BRAUER F, NOHEL J A. The Qualitative Theory of Ordinary Differential Equations: an Introduction [M]. Courier Corporation, 1989.
[13]	谢英超, 程燕, 贺天宇. 一类具有非线性发生率的时滞传染病模型的全局稳定性[J]. 应用数学和力学, 2015,36(10): 1107-1116.(XIE Yingchao, CHENG Yan, HE Tianyu. Global stability of a class of delayed epidemic models with nonlinear incidence rates[J]. Applied Mathematics and Mechanics,2015,36(10): 1107-1116.(in Chinese))
[14]	赵英英, 胡华. 带有标准发生率和信息干预的随机时滞SIRS传染病模型的动力学行为[J]. 应用数学和力学, 2019,40(12): 1373-1388.(ZHAO Yingying, HU Hua. Dynamic behaviors of stochastically delayed SIRS epidemic models with standard incidence rates under information intervention[J].Applied Mathematics and Mechanics,2019,40(12): 1373-1388.(in Chinese))
[15]	湖北省卫生健康委员会. 湖北省新型冠状病毒肺炎疫情情况[EB/OL]. [2020-05-14]. http://wjw.hubei.gov.cn/bmdt/ztzl/fkxxgzbdgrfyyq/xxfb/202003/t20200328_2195436.shtml.(Health Commission of Hubei Province. Epidemic situation of new coronavirus pneumonia in Hubei province[EB/OL]. [2020-05-14]. http://wjw.hubei.gov.cn/bmdt/ztzl/fkxxgzbdgrfyyq/xxfb/202003/t20200328_2195436.shtml.(in Chinese))
[16]	中华人民共和国国家卫生健康委员会. 截止2020年3月27日24时新型冠状病毒肺炎疫情情况 [EB/OL]. [2020-05-14]. http://www.nhc.gov.cn/xcs/yqtb/202003/bf66696029ba420098164607240074f8.shtml.(National Health Commission of the People’s Republic of China. The new coronavirus pneumonia epidemic situation as of 24:00 on March 27, 2020[N]. [2020-05-14]. http://www.nhc.gov.cn/xcs/yqtb/202003/bf66696029ba420098164607240074f8.shtml.(in Chinese))
[17]	陈凯, 苏彬, 杨易, 等. 新型冠状病毒肺炎病原学及临床特点研究进展[J]. 武警医学, 2020,31(3): 269-271.(CHEN Kai, SU Bin, YANG Yi, et al. Research progress on etiology and clinical characteristics of new coronavirus pneumonia[J]. Medical Journal of the Chinese People’s Armed Police Forces,2020,31(3): 269-271.(in Chinese))
[18]	GUAN W, NI Z, HU Y, et al. Clinical characteristics of coronavirus disease 2019 in China[J]. New England Journal of Medicine,2020,382(18): 1708-1720.
[19]	BACKER J A, KLINKENBERG D, WALLINGA J. Incubation period of 2019 novel coronavirus (2019- n CoV) infections among travellers from Wuhan, China, 20-28 January 2020[J]. Eurosurveillance,2020,25(5): 2000062.
[20]	中华人民共和国国家统计局. 中华人民共和国2019年国民经济和社会发展统计公报[M]. 北京: 中国统计出版社, 2019: 2-8.(National Bureau of Statistics of the People’s Republic of China. Statistical Communiqué on the National Economic and Social Development of the People’s Republic of China in 2019 [M]. Beijing: China Statistical Press, 2019: 2-8.(in Chinese))