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
•The novel coronavirus (2019-nCoV) pneumonia has caused 2033 confirmed cases, including 56 deaths in mainland China, by 2020-01-26 17:06.•We aim to estimate the basic reproduction number of 2019-nCoV in Wuhan, China using the exponential growth model method.•We estimated that the mean R0 ranges from...
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| Published in | International journal of infectious diseases Vol. 92; pp. 214 - 217 |
|---|---|
| Main Authors | , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Canada
Elsevier Ltd
01.03.2020
The Author(s). Published by Elsevier Ltd on behalf of International Society for Infectious Diseases Elsevier |
| Subjects | |
| Online Access | Get full text |
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| Abstract | •The novel coronavirus (2019-nCoV) pneumonia has caused 2033 confirmed cases, including 56 deaths in mainland China, by 2020-01-26 17:06.•We aim to estimate the basic reproduction number of 2019-nCoV in Wuhan, China using the exponential growth model method.•We estimated that the mean R0 ranges from 2.24 to 3.58 with an 8-fold to 2-fold increase in the reporting rate.•Changes in reporting likely occurred and should be taken into account in the estimation of R0.
An ongoing outbreak of a novel coronavirus (2019-nCoV) pneumonia hit a major city in China, Wuhan, December 2019 and subsequently reached other provinces/regions of China and other countries. We present estimates of the basic reproduction number, R0, of 2019-nCoV in the early phase of the outbreak.
Accounting for the impact of the variations in disease reporting rate, we modelled the epidemic curve of 2019-nCoV cases time series, in mainland China from January 10 to January 24, 2020, through the exponential growth. With the estimated intrinsic growth rate (γ), we estimated R0 by using the serial intervals (SI) of two other well-known coronavirus diseases, MERS and SARS, as approximations for the true unknown SI.
The early outbreak data largely follows the exponential growth. We estimated that the mean R0 ranges from 2.24 (95%CI: 1.96–2.55) to 3.58 (95%CI: 2.89–4.39) associated with 8-fold to 2-fold increase in the reporting rate. We demonstrated that changes in reporting rate substantially affect estimates of R0.
The mean estimate of R0 for the 2019-nCoV ranges from 2.24 to 3.58, and is significantly larger than 1. Our findings indicate the potential of 2019-nCoV to cause outbreaks. |
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| AbstractList | •The novel coronavirus (2019-nCoV) pneumonia has caused 2033 confirmed cases, including 56 deaths in mainland China, by 2020-01-26 17:06.•We aim to estimate the basic reproduction number of 2019-nCoV in Wuhan, China using the exponential growth model method.•We estimated that the mean R0 ranges from 2.24 to 3.58 with an 8-fold to 2-fold increase in the reporting rate.•Changes in reporting likely occurred and should be taken into account in the estimation of R0.
An ongoing outbreak of a novel coronavirus (2019-nCoV) pneumonia hit a major city in China, Wuhan, December 2019 and subsequently reached other provinces/regions of China and other countries. We present estimates of the basic reproduction number, R0, of 2019-nCoV in the early phase of the outbreak.
Accounting for the impact of the variations in disease reporting rate, we modelled the epidemic curve of 2019-nCoV cases time series, in mainland China from January 10 to January 24, 2020, through the exponential growth. With the estimated intrinsic growth rate (γ), we estimated R0 by using the serial intervals (SI) of two other well-known coronavirus diseases, MERS and SARS, as approximations for the true unknown SI.
The early outbreak data largely follows the exponential growth. We estimated that the mean R0 ranges from 2.24 (95%CI: 1.96–2.55) to 3.58 (95%CI: 2.89–4.39) associated with 8-fold to 2-fold increase in the reporting rate. We demonstrated that changes in reporting rate substantially affect estimates of R0.
The mean estimate of R0 for the 2019-nCoV ranges from 2.24 to 3.58, and is significantly larger than 1. Our findings indicate the potential of 2019-nCoV to cause outbreaks. An ongoing outbreak of a novel coronavirus (2019-nCoV) pneumonia hit a major city in China, Wuhan, December 2019 and subsequently reached other provinces/regions of China and other countries. We present estimates of the basic reproduction number, R , of 2019-nCoV in the early phase of the outbreak. Accounting for the impact of the variations in disease reporting rate, we modelled the epidemic curve of 2019-nCoV cases time series, in mainland China from January 10 to January 24, 2020, through the exponential growth. With the estimated intrinsic growth rate (γ), we estimated R by using the serial intervals (SI) of two other well-known coronavirus diseases, MERS and SARS, as approximations for the true unknown SI. The early outbreak data largely follows the exponential growth. We estimated that the mean R ranges from 2.24 (95%CI: 1.96-2.55) to 3.58 (95%CI: 2.89-4.39) associated with 8-fold to 2-fold increase in the reporting rate. We demonstrated that changes in reporting rate substantially affect estimates of R . The mean estimate of R for the 2019-nCoV ranges from 2.24 to 3.58, and is significantly larger than 1. Our findings indicate the potential of 2019-nCoV to cause outbreaks. • The novel coronavirus (2019-nCoV) pneumonia has caused 2033 confirmed cases, including 56 deaths in mainland China, by 2020-01-26 17:06. • We aim to estimate the basic reproduction number of 2019-nCoV in Wuhan, China using the exponential growth model method. • We estimated that the mean R 0 ranges from 2.24 to 3.58 with an 8-fold to 2-fold increase in the reporting rate. • Changes in reporting likely occurred and should be taken into account in the estimation of R 0 . Backgrounds: An ongoing outbreak of a novel coronavirus (2019-nCoV) pneumonia hit a major city in China, Wuhan, December 2019 and subsequently reached other provinces/regions of China and other countries. We present estimates of the basic reproduction number, R0, of 2019-nCoV in the early phase of the outbreak. Methods: Accounting for the impact of the variations in disease reporting rate, we modelled the epidemic curve of 2019-nCoV cases time series, in mainland China from January 10 to January 24, 2020, through the exponential growth. With the estimated intrinsic growth rate (γ), we estimated R0 by using the serial intervals (SI) of two other well-known coronavirus diseases, MERS and SARS, as approximations for the true unknown SI. Findings: The early outbreak data largely follows the exponential growth. We estimated that the mean R0 ranges from 2.24 (95%CI: 1.96–2.55) to 3.58 (95%CI: 2.89–4.39) associated with 8-fold to 2-fold increase in the reporting rate. We demonstrated that changes in reporting rate substantially affect estimates of R0. Conclusion: The mean estimate of R0 for the 2019-nCoV ranges from 2.24 to 3.58, and is significantly larger than 1. Our findings indicate the potential of 2019-nCoV to cause outbreaks. Keywords: Basic reproduction number, Novel coronavirus (2019-nCoV) An ongoing outbreak of a novel coronavirus (2019-nCoV) pneumonia hit a major city in China, Wuhan, December 2019 and subsequently reached other provinces/regions of China and other countries. We present estimates of the basic reproduction number, R0, of 2019-nCoV in the early phase of the outbreak.BACKGROUNDSAn ongoing outbreak of a novel coronavirus (2019-nCoV) pneumonia hit a major city in China, Wuhan, December 2019 and subsequently reached other provinces/regions of China and other countries. We present estimates of the basic reproduction number, R0, of 2019-nCoV in the early phase of the outbreak.Accounting for the impact of the variations in disease reporting rate, we modelled the epidemic curve of 2019-nCoV cases time series, in mainland China from January 10 to January 24, 2020, through the exponential growth. With the estimated intrinsic growth rate (γ), we estimated R0 by using the serial intervals (SI) of two other well-known coronavirus diseases, MERS and SARS, as approximations for the true unknown SI.METHODSAccounting for the impact of the variations in disease reporting rate, we modelled the epidemic curve of 2019-nCoV cases time series, in mainland China from January 10 to January 24, 2020, through the exponential growth. With the estimated intrinsic growth rate (γ), we estimated R0 by using the serial intervals (SI) of two other well-known coronavirus diseases, MERS and SARS, as approximations for the true unknown SI.The early outbreak data largely follows the exponential growth. We estimated that the mean R0 ranges from 2.24 (95%CI: 1.96-2.55) to 3.58 (95%CI: 2.89-4.39) associated with 8-fold to 2-fold increase in the reporting rate. We demonstrated that changes in reporting rate substantially affect estimates of R0.FINDINGSThe early outbreak data largely follows the exponential growth. We estimated that the mean R0 ranges from 2.24 (95%CI: 1.96-2.55) to 3.58 (95%CI: 2.89-4.39) associated with 8-fold to 2-fold increase in the reporting rate. We demonstrated that changes in reporting rate substantially affect estimates of R0.The mean estimate of R0 for the 2019-nCoV ranges from 2.24 to 3.58, and is significantly larger than 1. Our findings indicate the potential of 2019-nCoV to cause outbreaks.CONCLUSIONThe mean estimate of R0 for the 2019-nCoV ranges from 2.24 to 3.58, and is significantly larger than 1. Our findings indicate the potential of 2019-nCoV to cause outbreaks. |
| Author | He, Daihai Yang, Lin Lin, Qianyin Musa, Salihu S. Wang, Weiming Lou, Yijun Gao, Daozhou Ran, Jinjun Yang, Guangpu Zhao, Shi Wang, Maggie H. |
| Author_xml | – sequence: 1 givenname: Shi orcidid: 0000-0001-8722-6149 surname: Zhao fullname: Zhao, Shi email: shi.zhao@link.cuhk.edu.hk organization: JC School of Public Health and Primary Care, Chinese University of Hong Kong, Hong Kong, China – sequence: 2 givenname: Qianyin surname: Lin fullname: Lin, Qianyin email: qianying.lin@connect.polyu.hk organization: Michigan Institute for Data Science, University of Michigan, Ann Arbor, MI, USA – sequence: 3 givenname: Jinjun surname: Ran fullname: Ran, Jinjun email: jimran@connect.hku.hk organization: School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong, China – sequence: 4 givenname: Salihu S. orcidid: 0000-0001-6335-2335 surname: Musa fullname: Musa, Salihu S. email: salihu-sabiu.musa@connect.polyu.hk organization: Department of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong, China – sequence: 5 givenname: Guangpu surname: Yang fullname: Yang, Guangpu email: kennethgpy@link.cuhk.edu.hk organization: Department of Orthopaedics and Traumatology, Chinese University of Hong Kong, Hong Kong, China – sequence: 6 givenname: Weiming orcidid: 0000-0002-7562-8260 surname: Wang fullname: Wang, Weiming email: weimingwang2003@163.com organization: School of Mathematics and Statistics, Huaiyin Normal University, Huaian, China – sequence: 7 givenname: Yijun surname: Lou fullname: Lou, Yijun email: yijun.lou@polyu.edu.hk organization: Department of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong, China – sequence: 8 givenname: Daozhou surname: Gao fullname: Gao, Daozhou email: dzgao@shnu.edu.cn organization: Department of Mathematics, Shanghai Normal University, Shanghai, China – sequence: 9 givenname: Lin surname: Yang fullname: Yang, Lin email: l.yang@polyu.edu.hk organization: School of Nursing, Hong Kong Polytechnic University, Hong Kong, China – sequence: 10 givenname: Daihai orcidid: 0000-0003-3253-654X surname: He fullname: He, Daihai email: daihai.he@polyu.edu.hk organization: Department of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong, China – sequence: 11 givenname: Maggie H. surname: Wang fullname: Wang, Maggie H. email: maggiew@cuhk.edu.hk organization: JC School of Public Health and Primary Care, Chinese University of Hong Kong, Hong Kong, China |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/32007643$$D View this record in MEDLINE/PubMed |
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| Snippet | •The novel coronavirus (2019-nCoV) pneumonia has caused 2033 confirmed cases, including 56 deaths in mainland China, by 2020-01-26 17:06.•We aim to estimate... An ongoing outbreak of a novel coronavirus (2019-nCoV) pneumonia hit a major city in China, Wuhan, December 2019 and subsequently reached other... • The novel coronavirus (2019-nCoV) pneumonia has caused 2033 confirmed cases, including 56 deaths in mainland China, by 2020-01-26 17:06. • We aim to estimate... Backgrounds: An ongoing outbreak of a novel coronavirus (2019-nCoV) pneumonia hit a major city in China, Wuhan, December 2019 and subsequently reached other... |
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| SubjectTerms | Basic Reproduction Number Betacoronavirus - physiology China - epidemiology Coronavirus Infections - diagnosis Coronavirus Infections - epidemiology Coronavirus Infections - transmission COVID-19 Epidemics Humans Middle East Respiratory Syndrome Coronavirus - physiology Novel coronavirus (2019-nCoV) Pandemics Pneumonia, Viral - diagnosis Pneumonia, Viral - epidemiology Pneumonia, Viral - transmission SARS-CoV-2 Severe acute respiratory syndrome-related coronavirus - physiology World Health Organization |
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| Title | 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 |
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