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Using traveller-derived cases in Henan Province to quantify the spread of COVID-19 in Wuhan, China.
Song, Haitao; Li, Feng; Jia, Zhongwei; Jin, Zhen; Liu, Shengqiang.
  • Song H; Complex Systems Research Center, Shanxi University, Taiyuan, 030006 China.
  • Li F; Shanxi Key Laboratory of Mathematical Techniques and Big Data Analysis on Disease Control and Prevention, Shanxi University, Taiyuan, 030006 China.
  • Jia Z; Data Science and Technology, North University of China, Taiyuan, 030051 China.
  • Jin Z; College of Arts and Sciences, Shanxi Agricultural University, Taigu, 030801 China.
  • Liu S; National Institute of Drug Dependence, Peking University, Beijing, 100191 China.
Nonlinear Dyn ; 101(3): 1821-1831, 2020.
Article in English | MEDLINE | ID: covidwho-692680
ABSTRACT
Wuhan shutdown was implemented on January 23 and the first level response to public health emergencies (FLRPHE) was launched over the country, and then China got the outbreak of COVID-19 under control. A mathematical model is established to study the transmission of COVID-19 in Wuhan. This research investigates the spread of COVID-19 in Wuhan and assesses the effectiveness of control measures including the Wuhan city travel ban and FLRPHE. Based on the dynamical analysis and data fitting, the transmission of COVID-19 in Wuhan is estimated and the effects of control measures including Wuhan city travel ban and FLRPHE are investigated. According to the assumptions, the basic reproduction number for COVID-19 estimated that for Wuhan equal to 7.53 and there are 4.718 × 10 4 infectious people in Wuhan as of January 23. The interventions including the Wuhan city travel ban and FLRPHE reduce the size of peak and the cumulative number of confirmed cases of COVID-19 in Wuhan by 99%. The extraordinary efforts implemented by China effectively contain the transmission of COVID-19 and protect public health in China.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study Language: English Journal: Nonlinear Dyn Year: 2020 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study Language: English Journal: Nonlinear Dyn Year: 2020 Document Type: Article