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An Updated Trend Analysis Representing the Outbreak of Novel Coronavirus (2019-nCoV) in 16 Cities of Hubei Province, China Using Logistic S-Curve Model

17 Pages Posted: 17 Mar 2020

See all articles by Muhammad Fawad

Muhammad Fawad

Zhengzhou University - Henan Academy of Big Data

Sumaira Mubarik

Wuhan University - Department of Epidemiology and Biostatistics

Saima Shakil Malik

University of Gujrat - Department of Zoology

Yangyang Hao

Zhengzhou University - School of Mathematics and Statistics

Chuanhua Yu

Wuhan University - Department of Epidemiology and Biostatistics

Jingli Ren

Zhengzhou University - Henan Academy of Big Data

More...

Abstract

Background: A novel Coronavirus (2019-nCoV) infected pneumonia outbreak in Hubei province, China, in December 2019. The number of infected cases has increased rapidly throughout the world, particularly in Hubei province China. Precise estimates of its current and future trends are highly required for future policy implications.

Methods: We retrieved data from the Heath Commission of Hubei Province, China. Logistic-S curve model was used to estimate the current and future trends of 2019-nCoV infected cases among 16 cities of Hubei province, China from Jan-11 to Feb-24, 2020.

Findings: Out of 64287 confirmed 2019-nCoV infected cases in Hubei province, higher percentage of cases (76.54%) was from Wuhan and Xiaogan (62.91%) during the study period. The highest death percentage was observed in Wuhan (4.26%), Qianjiang (4.12%) and Jingmen (4.02%). The more significant cure percentage was found in Enshi Prefecture (58.17%), Huanggang (57.13%), Xianning (53.23%), and Tianmen (52.23%) whereas, Wuhan showed the lowest cure percentage (19.19%). Rising trend of infected cases was observed among 16 cities throughout the study period, particularly in Wuhan a higher trend was observed after 12-Feb. Gradually declining trend of 2019-nCoV cases was observed during the forecast period (Feb-25 to March-15) in all 16 cities and in overall Hubei Province. Additionally, the future forecast showed that the average number of 2019-nCoV infected cases might be decreased or stable in Hubei province and in Wuhan city in the coming 20 days.

Interpretation: The public must take precautionary measures in order to control and prevent disease spread and avoid extra travelling.

Funding Statement: This research is supported by National Natural Science Foundation of China [Grant No. 11771407]. The APC was funded by Jingli Ren.

Declaration of Interests: The author reports no conflicts of interest in this work.

Keywords: 2019-nCoV, Death, trends, Cities, Wuhan, China

Suggested Citation

Fawad, Muhammad and Mubarik, Sumaira and Shakil Malik, Saima and Hao, Yangyang and Yu, Chuanhua and Ren, Jingli, An Updated Trend Analysis Representing the Outbreak of Novel Coronavirus (2019-nCoV) in 16 Cities of Hubei Province, China Using Logistic S-Curve Model (3/6/2020). Available at SSRN: https://ssrn.com/abstract=3551318 or http://dx.doi.org/10.2139/ssrn.3551318

Muhammad Fawad (Contact Author)

Zhengzhou University - Henan Academy of Big Data

Zhengzhou, 450052
China

Sumaira Mubarik

Wuhan University - Department of Epidemiology and Biostatistics

China

Saima Shakil Malik

University of Gujrat - Department of Zoology

Gujrat, 50700
Pakistan

Yangyang Hao

Zhengzhou University - School of Mathematics and Statistics

Zhengzhou, 450001
China

Chuanhua Yu

Wuhan University - Department of Epidemiology and Biostatistics

China

Jingli Ren

Zhengzhou University - Henan Academy of Big Data ( email )

Zhengzhou, 450052
China

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