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Statistical Estimate of Epidemic Trend, Suggestions and Lessons for Public Safety from the 2019 Novel Coronavirus (COVID-19)

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Document pages: 26 pages

Abstract: Background: The central Chinese city of Wuhan has reported the first case of unexplained pneumonia on early of December 2019, then recorded outbreak of atypical pneumonia caused by the 2019 novel coronavirus (COVID-19) since December 31, 2019. Cases have been exported to other Chinese cities, as well as internationally, threatening to public health and safety. Here, we provide an estimate of epidemic trend in Hubei and all of the China on the basis of the fitted models of confirmed cases and learn lessons for the prevention and control measures to the future similar outbreak, accounting for the prevention interventions of enterprises, governments and people, as well as social economy and public safety. Methods: We used the data from January 23, 2020 to February 10, 2020 published by the National Health Commission, Health Commission of Hubei Province and Chinese Center for Disease Control and Prevention, which includes the raw Outbreak data of China and Hubei Province. The raw Outbreak data of other Provinces of China has been taken from Kaggle. We tried to build 10000 functions on the basis of coupled the exponential, natural logarithm, and Sin functions, and fit the statistical models between time and the daily confirmed case. We selected the top 5 fitted models of Hubei Province and national condition with Rs greater than 0.95 to predict the trend development and last time of the epidemics. We presented some suggestions and measures for control the epidemic and learned lessons from COVID-19 on 7 aspects, including doctor and researcher, Hospitals, County City centers for disease control and prevention (CDC), Provincial CDC, China CDC, Education for all (EFA), and Government. Findings: We presented a statistical forecast on the development trend of COVID-19 epidemic through the data as of February 10, 2020. The results show that China has well partially controlled the spread of the epidemic. The number of daily confirmed cases has continued to decline since February 4. February is a critical period for epidemic prevention and control. It is expected that on February 27, 2020, the daily diagnosis will be significantly reduced; by the end of March, the estimated number of confirmed cases would be less than 100 per day, with about 75,000 cases confirmed in Hubei province and 90,000 nationwide. Based on the challenges and problems encountered in the prevention and control of the epidemic in Wuhan and the whole country, suggestions are given from seven levels, including doctors, hospitals, government, etc., and lessons are learned from COVID-19. If the recommendations and lessons learned can be implemented, it is expected to effectively prevent and control the spread of similar outbreaks in the future, and ensure the safety and health of the public. Interpretation: The rapid and intensive measures taken by the Chinese government brought Wuhan epidemic under preliminary control. Some factories have resumed work since February 11, 2020, which exist the potential to cause the epidemic to increase again nationwide. In particular, because of the Spring Festival, more than 100 million migrant workers have to rework and 200 million school students at all levels might open the spring semesters. Consequently, its impact on the coronavirus epidemic block should be stressed. The publicity and supervision department should strengthen these two special groups’ epidemic learning and education, monitor their itinerary through a big data platform, and control their health and travel status in real time. It is recommended that migrant workers should not resume their work earlier than Feb. 27, 2020 and the school semester should also postpone to Apr. 1, 2020 at the earliest since large population density of students and their concentrated living and learning place.Funding Statement: Key Projects of National Natural Science Foundation of China (51534008).Declaration of Interests: The authors declare no competing interests.Ethics Approval Statement: Data are available on various websites and have been made publicly available.

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