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The Transmission Dynamics of SARS-COV-2 in China: Modeling Study and the Impact of Public Health Interventions

39 Pages Posted: 17 Mar 2020

See all articles by Wenbao Wang

Wenbao Wang

Yango University - Department of Engineering Managment

Yiqin Chen

Fujian Medical University - Fujian Province Key Laboratory of Environment and Health

Qi Wang

Fujian Medical University - Fujian Province Key Laboratory of Environment and Health

Ping Cai

Fujian Medical University - Department of Health Inspection and Quarantine

Ye He

Fujian Medical University - Department of Health Inspection and Quarantine

Shanwen Hu

Fujian Medical University - Department of Health Inspection and Quarantine

Yan Wu

Fujian Medical University - Department of Health Inspection and Quarantine

Wang Wenxiang

Fujian Medical University - Fujian Province Key Laboratory of Environment and Health

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Abstract

Background: COVID-19 is breaking out and has become a global pandemic. However, at present, the transmission dynamics remain unclear. We aimed to establish a SEIRD mathematical model based on the existing data to fit the transmission curve and evaluate the effects of the existing public health interventions.

Methods: First, the incidence of COVID-19 in the eight provinces to which the highest number of people moved from Wuhan between Jan 14 and Jan 23 was used to estimate the number of infected people in the incubation period in Wuhan city; and then the reproductive number (R0) was calculated by the SEIRD model and differential equations. In addition, the parameters of the SEIRD model were estimated to simulate the transmission trend. Furthermore, the fit of the model was verified. Finally, the infection curve and daily transmission replication curve were constructed, and the trend of cumulative confirmed cases was used to evaluate the effects of the public health interventions.

Findings: In the SEIRD model established in the present study, we estimated that R0 is 3.38 (95% CI, 3.25–3.48). The SEIRD curve model had a good fit when the parameters were set as follows: from Jan 24 to Jan 29, R = 2.37, TE = 6, TI = 3.5, and k = 0 . 0306; from Jan 30 to Feb 4, R = 1.78, TE = 6, TI = 3.5, and k = 0.0306; from Feb 5 to Feb 11, R = 0.83, TE = 6, TI = 3.5, and k = 0.0306, and from Feb 12 to Mar 5, R = 0.5, TE = 6, TI = 3.5, and k = 0.0306. The SEIRD curve from Feb 12 to Mar 5 (including the cumulative number of cases curve, the number of new cases curve, and the cumulative number of deaths curve) show a small difference between the simulated number of cases and the actual number; the correlation index (H2) is 0.934, and the reproductive number (R) has been reduced from 3.38 to 0.5 under the current public health interventions. According to the prediction SEIRD curves of three different states (A, B, and C), the final cumulative number of cases in China is about 70,000–100,000. Finally, the actual growth curve of new cases, the virus infection curve, and the daily transmission replication curve indicate that the public health interventions are effective.

Interpretation: According to the SEIRD model curve we established, the transmission dynamics of SARS-COV-2 far exceed those of SARS in 2003, and the estimated final number of cases in China lies between 70,000 and 100,000. The current public health interventions are effective and should be maintained or strengthened until COVID-19 is no longer considered a global threat.

Funding Statement: Natural Science Foundation of Fujian Province (2019J01312) in China.

Declaration of Interests: None of the authors have any conflicts of interest.

Keywords: COVID-19; SARS-COV-2; SEIRD; Wuhan; Public health interventions; Transmission dynamics

Suggested Citation

Wang, Wenbao and Chen, Yiqin and Wang, Qi and Cai, Ping and He, Ye and Hu, Shanwen and Wu, Yan and Wenxiang, Wang, The Transmission Dynamics of SARS-COV-2 in China: Modeling Study and the Impact of Public Health Interventions (3/7/2020). Available at SSRN: https://ssrn.com/abstract=3551319 or http://dx.doi.org/10.2139/ssrn.3551319

Wenbao Wang

Yango University - Department of Engineering Managment

Fujian
China

Yiqin Chen

Fujian Medical University - Fujian Province Key Laboratory of Environment and Health

Fuzhou
China

Qi Wang

Fujian Medical University - Fujian Province Key Laboratory of Environment and Health

Fuzhou
China

Ping Cai

Fujian Medical University - Department of Health Inspection and Quarantine

Fuzhou
China

Ye He

Fujian Medical University - Department of Health Inspection and Quarantine

Fuzhou
China

Shanwen Hu

Fujian Medical University - Department of Health Inspection and Quarantine

Fuzhou
China

Yan Wu

Fujian Medical University - Department of Health Inspection and Quarantine

Fuzhou
China

Wang Wenxiang (Contact Author)

Fujian Medical University - Fujian Province Key Laboratory of Environment and Health ( email )

Fuzhou
China

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