About: Real time estimation of the risk of death from novel coronavirus (2019-nCoV) infection: Inference using exported cases

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	Real time estimation of the risk of death from novel coronavirus (2019-nCoV) infection: Inference using exported cases
Creator	Nishiura, Hiroshi Hayashi, Katsuma Jung, Sung-Mok Kinoshita, Ryo Kobayashi, Tetsuro »more»
source	MedRxiv
abstract	The exported cases of 2019 novel coronavirus (2019-nCoV) infection who were confirmed in other countries provide a chance to estimate the cumulative incidence and confirmed case fatality risk (cCFR) in China. Knowledge of the cCFR is critical to characterize the severity and understand pandemic potential of 2019-nCoV in the early stage of epidemic. Using the exponential growth rate of the incidence, the present study statistically estimated the cCFR and the basic reproduction number, i.e., the average number of secondary cases generated by a single primary case in a naive population. As of 24 January 2020, with 23 exported cases, and estimating the growth rate from 8 December 2019 (scenario 1) and using the data since growth of exported cases (scenario 2), the cumulative incidence in China was estimated at 5433 cases (95% confidence interval (CI): 3883, 7160) and 17780 cases (95% CI: 9646, 28724), respectively. The latest estimates of the cCFR were 4.6% (95% CI: 3.1-6.6) for scenario 1 and 7.7% (95% CI: 4.9-11.3%) for scenario 2, respectively. The basic reproduction number was estimated to be 2.2 (95% CI: 2.1, 2.3) and 3.7 (95% CI: 3.1, 4.3) for scenarios 1 and 2, respectively. Based on the results, we note that current 2019-nCoV epidemic has a substation potential to cause a pandemic. The proposed approach can provide insights into early risk assessment using only publicly available data.
has issue date	2020-02-02(xsd:dateTime)
bibo:doi	10.1101/2020.01.29.20019547
has license	medrxiv
sha1sum (hex)	2afff5fe89a3e3ec270a41c2b929dfeec68d7d50
schema:url	https://doi.org/10.1101/2020.01.29.20019547
resource representing a document's title	Real time estimation of the risk of death from novel coronavirus (2019-nCoV) infection: Inference using exported cases
resource representing a document's body	covid:2afff5fe89a3e3ec270a41c2b929dfeec68d7d50#body_text
is schema:about of	named entity 'statistically' named entity 'coronavirus' named entity 'cases' named entity 'China' named entity 'incidence' »more»

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