About: Perspectives on model forecasts of the 2014–2015 Ebola epidemic in West Africa: lessons and the way forward

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

About: Perspectives on model forecasts of the 2014–2015 Ebola epidemic in West Africa: lessons and the way forward Goto Sponge NotDistinct Permalink

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	Perspectives on model forecasts of the 2014–2015 Ebola epidemic in West Africa: lessons and the way forward
Creator	Chowell, Gerardo Simonsen, Lone Viboud, Cécile Vespignani, Alessandro Merler, Stefano
source	PMC
abstract	The unprecedented impact and modeling efforts associated with the 2014–2015 Ebola epidemic in West Africa provides a unique opportunity to document the performances and caveats of forecasting approaches used in near-real time for generating evidence and to guide policy. A number of international academic groups have developed and parameterized mathematical models of disease spread to forecast the trajectory of the outbreak. These modeling efforts often relied on limited epidemiological data to derive key transmission and severity parameters, which are needed to calibrate mechanistic models. Here, we provide a perspective on some of the challenges and lessons drawn from these efforts, focusing on (1) data availability and accuracy of early forecasts; (2) the ability of different models to capture the profile of early growth dynamics in local outbreaks and the importance of reactive behavior changes and case clustering; (3) challenges in forecasting the long-term epidemic impact very early in the outbreak; and (4) ways to move forward. We conclude that rapid availability of aggregated population-level data and detailed information on a subset of transmission chains is crucial to characterize transmission patterns, while ensemble-forecasting approaches could limit the uncertainty of any individual model. We believe that coordinated forecasting efforts, combined with rapid dissemination of disease predictions and underlying epidemiological data in shared online platforms, will be critical in optimizing the response to current and future infectious disease emergencies.
has issue date	2017-03-01(xsd:dateTime)
bibo:doi	10.1186/s12916-017-0811-y
bibo:pmid	28245814
has license	cc-by
sha1sum (hex)	201371596cb4ae2f74e14bac9e4061d8cc2228a7
schema:url	https://doi.org/10.1186/s12916-017-0811-y
resource representing a document's title	Perspectives on model forecasts of the 2014–2015 Ebola epidemic in West Africa: lessons and the way forward
has PubMed Central identifier	PMC5331683
has PubMed identifier	28245814
schema:publication	BMC Med
resource representing a document's body	covid:201371596cb4ae2f74e14bac9e4061d8cc2228a7#body_text
is schema:about of	named entity 'future' named entity 'patterns' named entity 'ability' named entity 'subset' named entity 'local' »more»

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 © 2009-2025 OpenLink Software