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Modelling the Situation of COVID-19 and Effects of Different Containment Strategies in China with Dynamic Differential Equations and Parameters Estimation

36 Pages Posted: 18 Mar 2020

See all articles by Xiuli Liu

Xiuli Liu

Chinese Academy of Sciences (CAS) - Academy of Mathematics and Systems Science

Geoffrey J.D. Hewings

University of Illinois at Urbana-Champaign - Regional Economics, Application Labratory, REAL

Minghui Qin

Chinese Academy of Sciences (CAS) - Academy of Mathematics and Systems Science

Xin Xiang

Chinese Academy of Sciences (CAS) - Academy of Mathematics and Systems Science

Shan Zheng

Chinese Academy of Sciences (CAS) - Academy of Mathematics and Systems Science

Xuefeng Li

Chinese Academy of Sciences (CAS) - Academy of Mathematics and Systems Science

Shouyang Wang

Chinese Academy of Sciences (CAS) - Academy of Mathematics and Systems Science

More...

Abstract

Background: An ongoing outbreak of a novel coronavirus (COVID-19) pneumonia has spread to many parts of the world generating concerns about the possibility of an extensive pandemic. However, due to the limited emerging understanding of the new virus and its transmission mechanisms, the results are largely inconsistent across studies.

Methods: This paper proposed a quarantined-susceptible-exposed-infectious-resistant (QSEIR) model which considers the unprecedented strict quarantined measures in almost the whole China to resist the epidemic. We estimated model parameters from published information with statistical method and stochastic simulation, we found the parameters that achieved the best simulation test result. The next stage involved quantitative predictions of future epidemic developments based on different containment strategies with QSEIR model, focused on the sensitivity of the outcomes to different parameter choices in mainland China.

Findings: The main results are as follows. If the strict quarantined measures are being retained, the peak value of confirmed cases would be in the range of [52438, 64090] and the peak date would be expected in the range February 7 to February 19, 2020. During March 18-30, 2020, the epidemic would be totally controlled. The end date would be in the period from August 20 to September 1, 2020. With 80% probability, our prediction on the peak date was 4 days ahead of the real date, the prediction error of the peak value is 0.43%, both estimates are much closer to the observed values compared with published studies. The sensitive analysis indicated that the quarantine measures (or with vaccination) is the most effective containment strategy to control the epidemic, followed by measures to increase the cured rate (like finding special medicine). The long-term simulation result and sensitive analysis in mainland China showed that the QSEIR model is stable and can be empirically validated. It is suggested that the QSEIR model can be applied to predict the development trend of epidemic in other regions or countries in the world. In mainland China, the quarantine measures can't be relaxed before the end of March, 2020. China can fully resume production with the appropriate anti-measures beginning in early April, 2020. The significance of this study for other countries now facing the epidemic outbreaks is that they should act more decisively and take in time quarantine measures though it may have negative short-term public and economic consequences.

Interpretation: Parameter estimation is the most important part in the kind of SEIR model (Cao et al., 2020b). The paper illustrated the method to generate the parameter estimations. Given the data limitations, there were 20% errors in the simulation tests. With the improvement of data quality and more data, variable parameters can be estimated and the forecasting accuracy of the model can be enhanced.

Funding Statement: The 2019 Chinese Government Scholarship and National Natural Science Foundation of China under Grants No. 71874184 and No. 71988101.

Declaration of Interests: The authors declare no competing interests.

Ethics Approval Statement: Missing.

Keywords: dynamically modeling; parameters estimation; sensitive analysis; effects of different containment strategies; novel coronavirus (COVID-19)

Suggested Citation

Liu, Xiuli and Hewings, Geoffrey J.D. and Qin, Minghui and Xiang, Xin and Zheng, Shan and Li, Xuefeng and Wang, Shouyang, Modelling the Situation of COVID-19 and Effects of Different Containment Strategies in China with Dynamic Differential Equations and Parameters Estimation (3/8/2020). Available at SSRN: https://ssrn.com/abstract=3551359 or http://dx.doi.org/10.2139/ssrn.3551359

Xiuli Liu (Contact Author)

Chinese Academy of Sciences (CAS) - Academy of Mathematics and Systems Science ( email )

Beijing
China

Geoffrey J.D. Hewings

University of Illinois at Urbana-Champaign - Regional Economics, Application Labratory, REAL

United States

Minghui Qin

Chinese Academy of Sciences (CAS) - Academy of Mathematics and Systems Science

Beijing
China

Xin Xiang

Chinese Academy of Sciences (CAS) - Academy of Mathematics and Systems Science

Beijing
China

Shan Zheng

Chinese Academy of Sciences (CAS) - Academy of Mathematics and Systems Science

Beijing
China

Xuefeng Li

Chinese Academy of Sciences (CAS) - Academy of Mathematics and Systems Science

Beijing
China

Shouyang Wang

Chinese Academy of Sciences (CAS) - Academy of Mathematics and Systems Science

Beijing
China

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