About: On COVID-19 Modelling

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

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	On COVID-19 Modelling
source	ArXiv
abstract	This contribution analyzes the COVID-19 outbreak by comparably simple mathematical and numerical methods. The final goal is to predict the peak of the epidemic outbreak per country with a reliable technique. This is done by an algorithm motivated by standard SIR models and aligned with the standard data provided by the Johns Hopkins University. To reconstruct data for the unregistered Infected, the algorithm uses current values of the infection fatality rate and a data-driven estimation of a specific form of the recovery rate. All other ingredients are data-driven as well. Various examples of predictions are provided for illustration.
has issue date	2020-05-11(xsd:dateTime)
has license	arxiv
sha1sum (hex)	ec9649864624af4669b195c4e95155f8a537dead
resource representing a document's title	On COVID-19 Modelling
resource representing a document's body	covid:ec9649864624af4669b195c4e95155f8a537dead#body_text
is schema:about of	named entity 'difference equations' named entity 'n + 1' named entity 'epidemic' named entity 'COVID-19 disease' named entity 'Germany' »more»

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