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Current trends and future prediction of novel coronavirus disease (COVID-19) epidemic in China: a dynamical modeling analysis

1 College of Medical Engineering and Technology, Xinjiang Medical University, Urumqi 830011, China
2 Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
3 School of Mathematics and Statistics, Huaiyin Normal University, Huaian, 223300, China
4 Central Laboratory of Xinjiang Medical University, Urumqi, 830011, China
5 College of Public Health, Xinjiang Medical University, Urumqi, 830011, China
6 Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China

These authors contributed equally.

Special Issues: Modeling the Biological, Epidemiological, Immunological, Molecular, Virological Aspects of COVID-19

The novel coronavirus disease 2019 (COVID-19) infection broke out in December 2019 in Wuhan, and rapidly overspread 31 provinces in mainland China on 31 January 2020. In the face of the increasing number of daily confirmed infected cases, it has become a common concern and worthy of pondering when the infection will appear the turning points, what is the final size and when the infection would be ultimately controlled. Based on the current control measures, we proposed a dynamical transmission model with contact trace and quarantine and predicted the peak time and final size for daily confirmed infected cases by employing Markov Chain Monte Carlo algorithm. We estimate the basic reproductive number of COVID-19 is 5.78 (95%CI: 5.71–5.89). Under the current intervention before 31 January, the number of daily confirmed infected cases is expected to peak on around 11 February 2020 with the size of 4066 (95%CI: 3898–4472). The infection of COVID-19 might be controlled approximately after 18 May 2020. Reducing contact and increasing trace about the risk population are likely to be the present effective measures.
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Keywords novel coronavirus; dynamical model; Markov Chain Monte Carlo; peak time; basic reproduction number

Citation: Kai Wang, Zhenzhen Lu, Xiaomeng Wang, Hui Li, Huling Li, Dandan Lin, Yongli Cai, Xing Feng, Yateng Song, Zhiwei Feng, Weidong Ji, Xiaoyan Wang, Yi Yin, Lei Wang, Zhihang Peng. Current trends and future prediction of novel coronavirus disease (COVID-19) epidemic in China: a dynamical modeling analysis. Mathematical Biosciences and Engineering, 2020, 17(4): 3052-3061. doi: 10.3934/mbe.2020173

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