About: On the true numbers of COVID-19 infections: behind the available data

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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	On the true numbers of COVID-19 infections: behind the available data
Creator	Hassouni, Y Qadmiry, M Tahri, E
source	MedRxiv
abstract	In December-2019 China reported several cases of a novel coronavirus later called COVID-19. In this work, we will use a probabilistic method for approximating the true daily numbers of infected. Based on two distribution functions to describe the spontaneous recovered cases on the one hand and the detected cases on the other hand. The impact of the underlying variables of these functions is discussed. The detected rate is predicted to be between 5.3% and 10,8%, which means that there would be about 38 million infected until now (10-May 2020), rather than the officially declared number of 3.99 million worldwide cases.
has issue date	2020-05-28(xsd:dateTime)
bibo:doi	10.1101/2020.05.26.20114074
has license	medrxiv
sha1sum (hex)	29c39c0f0975a47ea2fd88d914964bd9c120fc27
schema:url	https://doi.org/10.1101/2020.05.26.20114074
resource representing a document's title	On the true numbers of COVID-19 infections: behind the available data
resource representing a document's body	covid:29c39c0f0975a47ea2fd88d914964bd9c120fc27#body_text
is schema:about of	named entity 'approximating' named entity 'probabilistic method' named entity 'numbers' named entity 'infections' named entity 'China' »more»

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