About: Transparent Covid-19 prediction

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

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Transparent Covid-19 prediction
Creator	Bandt, Christoph
Source	ArXiv
abstract	We present a very simple and transparent method to interpret time series of confirmed Covid-19 cases. Roughly speaking, the analysis of weekly new infections for each day is a tool for the definition and early detection of the turning point of the epidemic. In Italy, the growth of Covid-19 activity was overcome one week ago, Austria and Switzerland followed suit. This note emphasizes the crucial delay of two weeks between infection and listing of infection in a central database. Our estimates of the time course of Covid-19 activity and reproduction rates can reduce the information gap by several days. We show that Spain and Germany are already beyond the turning point. In general the estimated reproduction rates become undercritical a short time after the main lockdown measures, and the Covid-19 activity starts to decrease afterwards. This note gives a very optimistic outlook for all regions which have taken strict containment measures.
has issue date	2020-04-08(xsd:dateTime)
has license	arxiv
sha1sum (hex)	a22a3a3bdf5b0eaa591545c469cef3c6c69c9655
resource representing a document's title	Transparent Covid-19 prediction
resource representing a document's body	covid:a22a3a3bdf5b0eaa591545c469cef3c6c69c9655#body_text
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