lancet-header
Preprints with The Lancet is part of SSRN´s First Look, a place where journals and other research experts identify content of interest prior to publication. These preprint papers are not peer-reviewed. Authors have either opted in at submission to The Lancet family of journals to post their preprints on Preprints with The Lancet, or submitted directly via SSRN. The usual SSRN checks and a Lancet-specific check for appropriateness and transparency have been applied. These papers should not be used for clinical decision making or reporting of research to a lay audience without indicating that this is preliminary research that has not been peer-reviewed. For more information see the Comment published in The Lancet, or visit The Lancet´s FAQ page, and for any feedback please contact preprints@lancet.com

Mathematical Models for Devising the Optimal SARS-CoV-2 Eradication in China, South Korea, Iran, and Italy

19 Pages Posted: 1 Apr 2020

See all articles by Shuo Jiang

Shuo Jiang

Fudan University - Shanghai Public Health Clinical Center

Qiuyue Li

Fudan University - Shanghai Public Health Clinical Center

Chaoqun Li

Fudan University - Shanghai Public Health Clinical Center

Xiaomeng He

Fudan University - Shanghai Public Health Clinical Center

Tao Wang

Wuhan Academy of Social Sciences

Hua Li

Shanghai Jiao Tong University (SJTU) - State Key Laboratory of Oncogenes and Related Genes

Christopher Corpe

University of London - Diabetes and Nutritional Sciences

Xiaoyan Zhang

Fudan University - Shanghai Public Health Clinical Center

Jianqing Xu

Fudan University - Shanghai Public Health Clinical Center

Jin Wang

Fudan University - Shanghai Public Health Clinical Center

More...

Abstract

Background: Coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), spreads rapidly and has attracted worldwide attention.

Methods: To improve forecast accuracy and investigate the spread of SARS-CoV-2, we constructed four mathematical models to investigate the numerical spread of SARS-CoV-2 and eradication pathways.

Findings: Using the SEIR model, and including measures, such as city closure and holiday extension policy taken by the Chinese government which effectively reduced the β value, we estimated that the β value and basic transmission R0 of SARS-CoV-2 was 0 · 476 / 6·66 in Wuhan, 0·359 / 5·03 in Korea, 0·400 / 5·60 in Italy, and 0·638 / 8·93 in Iran. Considering medicine and vaccines, an advanced model demonstrated that the emergence of vaccines can greatly alleviate the spread of the virus. Our model predicted that 100,000 people would become infected assuming the isolation rate alpha is 0·30 in Wuhan, which was consistent with the reported number of infected people.

Interpretation: Our mathematical models propose that SARS-CoV-2 eradication depends on systematic thinking, effective hospital isolation, and SARS-CoV-2 medicine and vaccination, and some measures including city closure and holiday policy should be taken for SARS-CoV-2 eradication.

Funding Statement: G The work is supported partially by a grant (2018ZX10302103-003) from the National Special Research Program of China for Important Infectious Diseases, and a grant from the National Natural Science Foundation of China (81672383).

Declaration of Interests: The authors declare no competing financial interests.

Keywords: COVID-19, SARS-CoV-2, Mathematical models, R0, Hospital isolation

Suggested Citation

Jiang, Shuo and Li, Qiuyue and Li, Chaoqun and He, Xiaomeng and Wang, Tao and Li, Hua and Corpe, Christopher and Zhang, Xiaoyan and Xu, Jianqing and Wang, Jin, Mathematical Models for Devising the Optimal SARS-CoV-2 Eradication in China, South Korea, Iran, and Italy (3/19/2020). Available at SSRN: https://ssrn.com/abstract=3559541 or http://dx.doi.org/10.2139/ssrn.3559541

Shuo Jiang

Fudan University - Shanghai Public Health Clinical Center

Shanghai
China

Qiuyue Li

Fudan University - Shanghai Public Health Clinical Center

Shanghai
China

Chaoqun Li

Fudan University - Shanghai Public Health Clinical Center

Shanghai
China

Xiaomeng He

Fudan University - Shanghai Public Health Clinical Center

Shanghai
China

Tao Wang

Wuhan Academy of Social Sciences

China

Hua Li

Shanghai Jiao Tong University (SJTU) - State Key Laboratory of Oncogenes and Related Genes

China

Christopher Corpe

University of London - Diabetes and Nutritional Sciences

United Kingdom

Xiaoyan Zhang

Fudan University - Shanghai Public Health Clinical Center

Shanghai
China

Jianqing Xu

Fudan University - Shanghai Public Health Clinical Center

Shanghai
China

Jin Wang (Contact Author)

Fudan University - Shanghai Public Health Clinical Center ( email )

Shanghai
China

Click here to go to TheLancet.com

Paper statistics

Abstract Views
580
Downloads
99