About: COVID-19 mitigation strategies and overview on results from relevant studies in Europe

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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	COVID-19 mitigation strategies and overview on results from relevant studies in Europe
Creator	Heider, Philipp
source	ArXiv
abstract	In December 2019, the first patients in Wuhan, China were diagnosed with a primary atypical pneumonia, which showed to be unknown and contagious. Since then, known as COVID-19 disease, the responsible viral pathogen, SARS-CoV-2, has spread around the world in a pandemic. Decisions on how to deal with the crisis are often based on simulations of the pandemic spread of the virus. The results of some of these, as well as their methodology and possibilities for improvement, will be described in more detail in this paper in order to inform beyond the current public health dogma called%22flatten-the-curve%22. There are several ways to model an epidemic in order to simulate the spread of diseases. Depending on the timeliness, scope and quality of the associated real data, these multivariable models differ in the value of used parameters, but also in the selection of considered influencing factors. It was exemplarily shown that epidemics in their course are simulated more realistically by models that assume subexponential growth. Furthermore, various simulations of the COVID-19 pandemic were presented in an European perspective, compared against each other and discussed in more detail. It is difficult to estimate how credible the simulations of the pandemic models currently are, so it remains to be seen whether the spread of the pandemic can be effectively reduced by the measures taken. Whether a model works well in reality is largely determined by the quality and scope of its underlying data. Past studies have shown that countermeasures are able to reduce reproduction numbers or transmission rates in epidemics. In addition to that, the presented modelling study provides a good framework for the creation of subexponential-growth-models for assessing the spread of COVID-19.
has issue date	2020-05-11(xsd:dateTime)
has license	arxiv
sha1sum (hex)	716c2dd87b6cab56921724b7cdea183d90a282fc
resource representing a document's title	COVID-19 mitigation strategies and overview on results from relevant studies in Europe
resource representing a document's body	covid:716c2dd87b6cab56921724b7cdea183d90a282fc#body_text
is schema:about of	named entity 'methodology' named entity 'Wuhan' named entity 'CHINA' named entity 'DECEMBER' named entity 'DESCRIBED' »more»

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