Abstract
Background
The coronavirus disease 2019 (COVID-19) is rapidly spreading in China and more than 30 countries over last two months. COVID-19 has multiple characteristics distinct from other infectious diseases, including high infectivity during incubation, time delay between real dynamics and daily observed number of confirmed cases, and the intervention effects of implemented quarantine and control measures.
Methods
We develop a Susceptible, Un-quanrantined infected, Quarantined infected, Confirmed infected (SUQC) model to characterize the dynamics of COVID-19 and explicitly parameterize the intervention effects of control measures, which is more suitable for analysis than other existing epidemic models.
Results
The SUQC model is applied to the daily released data of the confirmed infections to analyze the outbreak of COVID-19 in Wuhan, Hubei (excluding Wuhan), China (excluding Hubei) and four first-tier cities of China. We found that, before January 30, 2020, all these regions except Bei**g had a reproductive number R > 1, and after January 30, all regions had a reproductive number R < 1, indicating that the quarantine and control measures are effective in preventing the spread of COVID-19. The confirmation rate of Wuhan estimated by our model is 0.0643, substantially lower than that of Hubei excluding Wuhan (0.1914), and that of China excluding Hubei (0.2189), but it jumps to 0.3229 after February 12 when clinical evidence was adopted in new diagnosis guidelines. The number of unquarantined infected cases in Wuhan on February 12, 2020 is estimated to be 3,509 and declines to 334 on February 21, 2020. After fitting the model with data as of February 21, 2020, we predict that the end time of COVID-19 in Wuhan and Hubei is around late March, around mid March for China excluding Hubei, and before early March 2020 for the four tier-one cities. A total of 80,511 individuals are estimated to be infected in China, among which 49,510 are from Wuhan, 17,679 from Hubei (excluding Wuhan), and the rest 13,322 from other regions of China (excluding Hubei). Note that the estimates are from a deterministic ODE model and should be interpreted with some uncertainty.
Conclusions
We suggest that rigorous quarantine and control measures should be kept before early March in Bei**g, Shanghai, Guangzhou and Shenzhen, and before late March in Hubei. The model can also be useful to predict the trend of epidemic and provide quantitative guide for other countries at high risk of outbreak, such as South Korea, Japan, Italy and Iran.
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Acknowledgements
We are grateful to Drs. Yongbiao Xue and Li** Wang for motivating this project, to Dr. Hongyu Zhao and the anonymous reviewers for their valuable comments. This project was supported by the National Natural Science Foundation of China (Nos. 31571370, 91631106 and 91731302), the “Strategic Priority Research Program” of the Chinese Academy of Sciences (No. XDB13000000), the National Key R&D Program of China (No. 2018YFC1406902), and the One Hundred Talents Program of the Chinese Academy of Sciences.
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The authors Shilei Zhao and Hua Chen declare that they have no conflict of interests.
All procedures performed in studies were in accordance with the ethical standards of the institution or practice at which the studies were conducted, and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
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Author summary: The coronavirus disease 2019 (COVID-19) is rapidly spreading in China and more than 30 countries over last two months. COVID-19 has multiple characteristics distinct from other infectious diseases, including high infectivity during incubation, time delay between real dynamics and daily numbers of confirmed cases, and the intervention effects of quarantine and control measures.We developed a SUQC model to characterize the dynamics of COVID-19. SUQC is applied to the daily released data of China to predict the trend of epidemic. SUQC can also provide quantitative guidance for other countries in a high risk of outbreak, such as South Korea, Japan and Iran.
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Zhao, S., Chen, H. Modeling the epidemic dynamics and control of COVID-19 outbreak in China. Quant Biol 8, 11–19 (2020). https://doi.org/10.1007/s40484-020-0199-0
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DOI: https://doi.org/10.1007/s40484-020-0199-0