Assessing the Tendency of 2019-nCoV (COVID-19) Outbreak in China

Since December 8, 2019, the spread of COVID-19 is increasing every day. It is particularly important to predict the trend of the epidemic for the timely adjustment of the economy and industries. We proposed a Flow-SEHIR model in this paper, based on which we further analyzed the trends of 2019-nCoV (COVID-19) in China. The results show that the basic reproductive numbers R0 of COVID-19 is 3.56 (95% CI: 2.31 – 4.81). The number of daily confirmed new cases reaches the inflection point on Feb. 6 – 10 outside Hubei. For the maximum of infected cases number, the predicted peak value in China except Hubei was estimated to be 13806 (95% CI: 11926 15845). The peak arrival time is on March 3 9. The temporal number of patients in most areas of China outside Hubei will peak from March 12 to March 15. The peak values of more than 73.5% provinces or regions in China will be controlled within 1000. According to Flow-SEHIR model and estimations from the data of evacuation of nationals from Wuhan, the peak cumulative number of patients in Hubei was estimated to be 403481 (95% CI: 143284 – 1166936).

[1]  L. Yang,et al.  Preliminary estimation of the basic reproduction number of novel coronavirus (2019-nCoV) in China, from 2019 to 2020: A data-driven analysis in the early phase of the outbreak , 2020, International Journal of Infectious Diseases.

[2]  I B Schwartz,et al.  Seasonality and period-doubling bifurcations in an epidemic model. , 1984, Journal of theoretical biology.

[3]  Liancheng Wang,et al.  Global Dynamics of an SEIR Epidemic Model with Vertical Transmission , 2001, SIAM J. Appl. Math..

[4]  D. Cummings,et al.  Novel coronavirus 2019-nCoV: early estimation of epidemiological parameters and epidemic predictions , 2020, medRxiv.

[5]  Hualiang Lin,et al.  Population movement, city closure and spatial transmission of the 2019-nCoV infection in China , 2020, medRxiv.

[6]  J. Wallinga,et al.  The incubation period of 2019-nCoV infections among travellers from Wuhan, China , 2020, medRxiv.

[7]  Qianyun Liu,et al.  Emerging coronaviruses: Genome structure, replication, and pathogenesis , 2020, Journal of medical virology.

[8]  G. Leung,et al.  Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modelling study , 2020, The Lancet.

[9]  Michael Y. Li,et al.  Global stability for the SEIR model in epidemiology. , 1995, Mathematical biosciences.

[10]  G. Chowell,et al.  SARS outbreaks in Ontario, Hong Kong and Singapore: the role of diagnosis and isolation as a control mechanism , 2003, Journal of Theoretical Biology.

[11]  M. Kraemer,et al.  Pneumonia of unknown aetiology in Wuhan, China: potential for international spread via commercial air travel , 2020, Journal of travel medicine.

[12]  Rui Xia,et al.  Effects of closing and reopening live poultry markets on the epidemic of human infection with avian influenza A virus , 2015, Journal of biomedical research.

[13]  Qiushi Lin,et al.  Estimating the daily trend in the size of the COVID-19 infected population in Wuhan , 2020, Infectious Diseases of Poverty.

[14]  Maogui Hu Visualizing the largest annual human migration during the Spring Festival travel season in China , 2019, Environment and Planning A: Economy and Space.

[15]  Jianhong Wu,et al.  Estimation of the Transmission Risk of the 2019-nCoV and Its Implication for Public Health Interventions , 2020, Journal of clinical medicine.

[16]  Zhicheng Liu,et al.  Estimating the Efficacy of Traffic Blockage and Quarantine for the Epidemic Caused by 2019-nCoV (COVID-19) , 2020, medRxiv.

[17]  Gerardo Chowell,et al.  Forecasting Epidemics Through Nonparametric Estimation of Time-Dependent Transmission Rates Using the SEIR Model , 2017, Bulletin of Mathematical Biology.

[18]  Jonathan H. Epstein,et al.  Bats Are Natural Reservoirs of SARS-Like Coronaviruses , 2005, Science.