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

By Shi Zhao, Qianying Lin, Jinjun Ran, S. Musa, G. Yang, Weiming Wang, Yuan Lou, Daozhou Gao, L. Yang, D. He and 1 more. bioRxiv, 2020

1,806 citations recorded by the source corpus.

Backgrounds An ongoing outbreak of a novel coronavirus (2019-nCoV) pneumonia hit a major city of China, Wuhan, December 2019 and subsequently reached other provinces/regions of China and 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 significantly larger than 1. Our findings indicate the potential of 2019-nCoV to cause outbreaks.

View Paper: https://www.semanticscholar.org/paper/8e17ea7b9c4abe89c6235293ca8ade930590b117

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Citations in the corpus

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2): An Update (2020, background): “Based on the evidence of a rapidly increasing incidence of infections and the possibility of transmission by asymptomatic carriers, SARS-CoV-2 can be transmitted effectively among humans and exhibits high potential for a pandemic [6,33-36].”
The epidemiology, diagnosis and treatment of COVID-19 (2020, background): “Another study estimated the basic reproduction number as ranging from 2.24 to 3.58 [11] .”
Pathogenicity and transmissibility of 2019-nCoV—A quick overview and comparison with other emerging viruses (2020, unknown): “5 (likely to be below 5 but above 3 with rising report rate) [10], which appeared slightly higher than those of SARS-CoV (R0: 2e5).”
Modelling the COVID-19 epidemic and implementation of population-wide interventions in Italy (2020, unknown): “s with individuals showing no or mild symptoms of the disease. The estimated basic reproduction number (R 0) for SARS-CoV-2 is higher than both for SARS-CoV and for MERS-CoV (ranging from 2.0 to 3.5) [12, 13, 14]. Additionally, high viral loads of SARS-CoV-2 were found in upper respiratory specimens”
Machine learning using intrinsic genomic signatures for rapid classification of novel pathogens: COVID-19 case study (2020, background): “Prior work elucidating the evolutionary history of the Wuhan COVID-19 virus had 258 suggested an origin from bats prior to zoonotic transmission [12,34, 36, 39, 42, 61].”
Data-based analysis, modelling and forecasting of the COVID-19 outbreak (2020, background): “39) in the early phase of the outbreak [10].”
Estimation of the Transmission Risk of the 2019-nCoV and Its Implication for Public Health Interventions (2020, result): “Furthermore, we noted that more recently published studies based on datasets during periods comparable with ours reported similar findings in terms of a high basic reproduction number (for instance, Reference [29], where authors, using an exponential growth method, computed a basic reproduction numb”
SARS-CoV-2 and Coronavirus Disease 2019: What We Know So Far (2020, background): “58 [31] although the World Health Organization estimates it is between 1.”
An updated estimation of the risk of transmission of the novel coronavirus (2019-nCov) (2020, unknown): “Speci ﬁ cally, Zhao and coworkers (Zhao et al., 2020) have assessed from a quantitative standpoint the under-reporting rate of coronavirus cases, modeling the epidemic growth curve using the exponential growing Poisson process.”