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Epidemic Trend and Transmission Risk of SARS-CoV-2 after Government Intervention in the Mainland of China: A Mathematical Model Study

31 Pages Posted: 20 Feb 2020

See all articles by Jian Zu

Jian Zu

Xi'an Jiaotong University (XJTU) - School of Mathematics and Statistics

Miaolei Li

Xi'an Jiaotong University (XJTU) - School of Mathematics and Statistics

Zongfang Li

Xi'an Jiaotong University (XJTU) - Key Laboratory of Environment and Genes Related to Diseases

Mingwang Shen

Xi'an Jiaotong University (XJTU) - School of Public Health

Yanni Xiao

Xi'an Jiaotong University (XJTU) - School of Mathematics and Statistics

Fanpu Ji

Xi'an Jiaotong University (XJTU) - Department of Infectious Diseases; Xi'an Jiaotong University (XJTU) - National Local Joint Engineering Research Center for Precision Surgery & Regenerative Medicine

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Abstract

Background: The outbreak of SARS-CoV-2 had seriously endangered the lives and health of Chinese people and brought heavy economic burden to China. We predicted the epidemic trend of COVID-19 and estimated the effectiveness of several prevention and control strategies.

Methods: According to the epidemic status of COVID-19, we constructed an SEIPQR transmission model. Based on the reported data from Jan 23 to Feb 13, we estimated model parameters and initial values. Then we predicted the epidemic trend and transmission risk of COVID-19. Using sensitivity analysis method, we estimated the impact of several intervention strategies.

Findings: The finally cumulative number of confirmed cases in the mainland of China will be 91,661 (95%CI, 91,492-91,829). Up-to March 15, the case-fatality rate will up-to 6.10% (95%CI, 5.88-6.32%). On Feb 26, the existing confirmed cases would reach its peak, with 64,128 cases (95%CI, 63,040-65,216). On Jan 23, the effective reproduction number was 2.564 (95%CI, 2.502-2.631), and had dropped below 1.0 since Feb 6. Due to government intervention, both of the total number of confirmed cases and deaths would reduce by 99.99%. If the isolation is relaxed from Feb 27, there might be a second peak of infection, with more than 457,900 cases. However, relax the isolation after Mar 2 will avoid a second peak. The total number of confirmed cases and deaths would increase by 7.08% and 9.90% by one-day delayed diagnosis in unquarantined infected patients after January 23. Moreover, if the coverage of tracing close contacts was increased to 100%, the cumulative number of confirmed cases would decrease by 81.67%.

Interpretation: The series of quarantine measures adopted by the Chinese government since January 23 were necessary and effective. Postponing the relaxation of isolation, early detection and isolation of patients, widely tracing of close contacts and strict monitoring of infected persons could effectively reduce the scale of infection and mortality.

Funding Statement: The study was supported by grants from the National Natural Science Foundation of China (11971375, 11571272, 11631012 and 11201368), grant from the National Science and Technology Major Project of China (2018ZX10721202), grant from the Natural Science Foundation of Shaanxi Province (2019JM-273), and grant from the China Postdoctoral Science Foundation (2014M560755), Fundamental Research Funds for the Central Universities (No.xzy012019107).

Declaration of Interests: The authors declared that they do not have anything to disclose regarding conflict of interest with respect to this manuscript.

Keywords: SARS-CoV-2; Transmission dynamics; Prevalence; Effective reproduction number; Intervention strategy

Suggested Citation

Zu, Jian and Li, Miaolei and Li, Zongfang and Shen, Mingwang and Xiao, Yanni and Ji, Fanpu, Epidemic Trend and Transmission Risk of SARS-CoV-2 after Government Intervention in the Mainland of China: A Mathematical Model Study (2/16/2020). Available at SSRN: https://ssrn.com/abstract=3539669 or http://dx.doi.org/10.2139/ssrn.3539669

Jian Zu

Xi'an Jiaotong University (XJTU) - School of Mathematics and Statistics ( email )

China

Miaolei Li

Xi'an Jiaotong University (XJTU) - School of Mathematics and Statistics

China

Zongfang Li

Xi'an Jiaotong University (XJTU) - Key Laboratory of Environment and Genes Related to Diseases

China

Mingwang Shen

Xi'an Jiaotong University (XJTU) - School of Public Health

China

Yanni Xiao

Xi'an Jiaotong University (XJTU) - School of Mathematics and Statistics

China

Fanpu Ji (Contact Author)

Xi'an Jiaotong University (XJTU) - Department of Infectious Diseases

Xi'an
China

Xi'an Jiaotong University (XJTU) - National Local Joint Engineering Research Center for Precision Surgery & Regenerative Medicine ( email )

Xi'an
China

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