Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2020 Mar:92:214-217.
doi: 10.1016/j.ijid.2020.01.050. Epub 2020 Jan 30.

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

Shi Zhao  1 , Qianyin Lin  2 , Jinjun Ran  3 , Salihu S Musa  4 , Guangpu Yang  5 , Weiming Wang  6 , Yijun Lou  7 , Daozhou Gao  8 , Lin Yang  9 , Daihai He  10 , Maggie H Wang  11
Affiliations

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

Shi Zhao et al. Int J Infect Dis. 2020 Mar.

Abstract

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).

PubMed Disclaimer

Figures

Figure 1
Figure 1
The scenarios of the change in the reporting rate (top panels) and the exponential growth fitting (bottom panels). The top panels, i.e., (a), (c), (e), (g), (i) and (k), show the assumed change in the reporting rate. The bottom panels, i.e., (b), (d), (f), (h), (j) and (l), show the reported (or observed, green circles), adjusted (blue dots) and fitted (blue curve) number of 2019-nCoV infections, and the blue dashed lines are the 95%CI. The vertical grey line represents the date of January 16, 2020, after which the official diagnostic protocol was released by the WHO (World Health Organization, 2020). Panels (a) and (b) show the scenarios that the reporting rate was unchanged. Panels (c) and (d) show the scenarios that the reporting rate increased by 0.5-fold. Panels (e) and (f) show the scenarios that the reporting rate increased by 1-fold. Panels (g) and (h) show the scenarios that the reporting rate increased by 2-fold. Panels (i) and (j) show the scenarios that the reporting rate increased by 4-fold. Panels (k) and (l) show the scenarios that the reporting rate increased by 8-fold.
See this image and copyright information in PMC

Comment in

References

    1. Assiri A., McGeer A., Perl T.M., Price C.S., Al Rabeeah A.A., Cummings D.A., Alabdullatif Z.N., Assad M., Almulhim A., Makhdoom H. Hospital outbreak of Middle East respiratory syndrome coronavirus. New Engl J Med. 2013;369(5):407–416. - PMC - PubMed
    1. Bauch C.T., Lloyd-Smith J.O., Coffee M.P., Galvani A.P. Dynamically modeling SARS and other newly emerging respiratory illnesses: past, present, and future. Epidemiol (Cambridge, Mass) 2005;16(6):791–801. - PubMed
    1. Bogoch I.I., Watts A., Thomas-Bachli A., Huber C., Kraemer M.U., Khan K. Pneumonia of unknown etiology in Wuhan, China: potential for international spread via commercial air travel. J Travel Med. 2020 doi: 10.1093/jtm/taaa1008. - DOI - PMC - PubMed
    1. Cowling B.J., Fang V.J., Riley S., Peiris J.M., Leung G.M. Estimation of the serial interval of influenza. Epidemiology (Cambridge, Mass) 2009;20(3):344. - PMC - PubMed
    1. de Silva U., Warachit J., Waicharoen S., Chittaganpitch M. A preliminary analysis of the epidemiology of influenza A (H1N1) v virus infection in Thailand from early outbreak data, June-July 2009. Eurosurveillance. 2009;14(31):19292. - PubMed

MeSH terms