About: On the reliability of model-based predictions in the context of the current COVID epidemic event: impact of outbreak peak phase and data paucity

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About: On the reliability of model-based predictions in the context of the current COVID epidemic event: impact of outbreak peak phase and data paucity Goto Sponge NotDistinct Permalink

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 reliability of model-based predictions in the context of the current COVID epidemic event: impact of outbreak peak phase and data paucity
Creator	Daunizeau, Jean Friston, Karl Moran, Rosalyn Mattout, Jérémie
source	MedRxiv
abstract	The pandemic spread of the COVID-19 virus has, as of 20th of April 2020, reached most countries of the world. In an effort to design informed public health policies, many modelling studies have been performed to predict crucial outcomes of interest, including ICU solicitation, cumulated death counts, etc... The corresponding data analyses however, mostly rely on restricted (openly available) data sources, which typically include daily death rates and confirmed COVID cases time series. In addition, many of these predictions are derived before the peak of the outbreak has been observed yet (as is still currently the case for many countries). In this work, we show that peak phase and data paucity have a substantial impact on the reliability of model predictions. Although we focus on a recent model of the COVID pandemics, our conclusions most likely apply to most existing models, which are variants of the so-called 'Susceptible-Infected-Removed' or SIR framework. Our results highlight the need for performing systematic reliability evaluations for all models that currently inform public health policies. They also motivate a plea for gathering and opening richer and more reliable data time series (e.g., ICU occupancy, negative test rates, social distancing commitment reports, etc).
has issue date	2020-04-29(xsd:dateTime)
bibo:doi	10.1101/2020.04.24.20078485
has license	medrxiv
sha1sum (hex)	ebe2921e0a4e7a91076887a03a26e88805679ebb
schema:url	https://doi.org/10.1101/2020.04.24.20078485
resource representing a document's title	On the reliability of model-based predictions in the context of the current COVID epidemic event: impact of outbreak peak phase and data paucity
resource representing a document's body	covid:ebe2921e0a4e7a91076887a03a26e88805679ebb#body_text
is schema:about of	named entity 'death rates' named entity 'COVID-19 virus' named entity 'public health' named entity 'social distancing' named entity 'model-based' »more»

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