About: Data driven inference of the reproduction number (R0) for COVID-19 before and after interventions for 51 European countries

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: Data driven inference of the reproduction number (R0) for COVID-19 before and after interventions for 51 European countries Goto Sponge NotDistinct Permalink

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	Data driven inference of the reproduction number (R0) for COVID-19 before and after interventions for 51 European countries
Creator	Arampatzis, George Karnakov, Petr Kičić, Ivica Koumoutsakos, Petros Papadimitriou, Costas Wermelinger, Fabian Wälchli, Daniel
Source	MedRxiv
abstract	The reproduction number (R0) is broadly considered as a key indicator for the spreading of the COVID-19 pandemic. The estimation of its value with respect to the key threshold of 1.0 is a measure of the need, and eventually effectiveness, of interventions imposed in various countries. Here we present an online tool for the data driven inference and quantification of uncertainties for R0 as well as the time points of interventions for 51 European countries. The study relies on the Bayesian calibration of the simple and well established SIR model with data from reported daily infections. The model is able to fit the data for most countries without individual tuning of parameters. We deploy an open source Bayesian inference framework and efficient sampling algorithms to present a publicly available GUI (https://www.cse-lab.ethz.ch/coronavirus/) that allows the user to assess custom data and compare predictions for pairs of European countries. The results provide a ranking based on the rate of the disease's spread suggesting a metric for the effectiveness of social distancing measures. They also serve to demonstrate how geographic proximity and related times of interventions can lead to similarities in the progression of the epidemic.
has issue date	2020-05-23(xsd:dateTime)
bibo:doi	10.1101/2020.05.21.20109314
has license	medrxiv
sha1sum (hex)	50d1eae25b5b226bcbc9418fc06706679df16044
schema:url	https://doi.org/10.1101/2020.05.21.20109314
resource representing a document's title	Data driven inference of the reproduction number (R0) for COVID-19 before and after interventions for 51 European countries
resource representing a document's body	covid:50d1eae25b5b226bcbc9418fc06706679df16044#body_text
is schema:about of	named entity 'effectiveness' named entity 'sampling' named entity 'Bayesian inference' named entity 'data' named entity 'data' named entity 'The' named entity 'broadly' named entity 'infections' named entity 'coronavirus' named entity 'The' named entity 'deploy' named entity 'disease' named entity 'times' named entity 'coronavirus' named entity 'inference' named entity 'GUI' named entity 'European' named entity 'Bayesian inference' named entity 'Poland' named entity 'open source' named entity 'Norway' named entity 'posterior distribution' named entity 'epidemic' named entity 'Greece' named entity 'Germany' named entity 'social distancing' named entity 'Moldova' named entity 'Sweden' named entity 'SIR model' named entity 'Lithuania' named entity 'World Health Organization' named entity 'reproduction number' named entity 'Bayesian inference' named entity 'Bayesian inference' named entity 'web server' named entity 'exponential growth' named entity 'uncertainty quantification' named entity 'May 23' named entity 'Bayesian inference' named entity 'prior probability distribution' named entity 'ETH Zürich' named entity 'scatter plot' named entity 'posterior distribution' named entity 'SIR model' named entity 'reproduction number' named entity 'predictive model' named entity 'parametrization' named entity 'Bayes' theorem' named entity 'Switzerland' named entity 'Bayesian inference' named entity 'SIR model' named entity 'social distancing' named entity 'reproduction number' named entity 'epidemic' named entity 'social distancing' named entity 'reproduction number' named entity 'Switzerland' named entity 'Poland' named entity 'social distancing' named entity 'Poland' named entity 'Switzerland' named entity 'Germany' named entity 'epidemic' named entity 'social distancing' named entity 'March 2020' named entity 'medRxiv' named entity 'COVID-19 pandemic' named entity 'Ukraine' named entity 'reproduction number' named entity 'algorithm' named entity 'reproduction number' named entity 'medRxiv' named entity 'missing data' named entity 'generative model' named entity 'GUI' named entity 'confidence interval' named entity 'likelihood function' named entity 'reproduction number' named entity 'epidemic'

Faceted Search & Find service v1.13.91 as of Mar 24 2020

Alternative Linked Data Documents: Sponger | ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 07.20.3229 as of Jul 10 2020, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (94 GB total memory)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software