About: Model-Informed Risk Assessment and Decision Making for an Emerging Infectious Disease in the Asia-Pacific Region

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About: Model-Informed Risk Assessment and Decision Making for an Emerging Infectious Disease in the Asia-Pacific Region 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	Model-Informed Risk Assessment and Decision Making for an Emerging Infectious Disease in the Asia-Pacific Region
Creator	Geard, Nicholas Moss, Robert Black, Jim Hickson, Roslyn Hort, Krishna »more»
source	Medline; PMC
abstract	BACKGROUND: Effective response to emerging infectious disease (EID) threats relies on health care systems that can detect and contain localised outbreaks before they reach a national or international scale. The Asia-Pacific region contains low and middle income countries in which the risk of EID outbreaks is elevated and whose health care systems may require international support to effectively detect and respond to such events. The absence of comprehensive data on populations, health care systems and disease characteristics in this region makes risk assessment and decisions about the provision of such support challenging. METHODOLOGY/PRINCIPAL FINDINGS: We describe a mathematical modelling framework that can inform this process by integrating available data sources, systematically explore the effects of uncertainty, and provide estimates of outbreak risk under a range of intervention scenarios. We illustrate the use of this framework in the context of a potential importation of Ebola Virus Disease into the Asia-Pacific region. Results suggest that, across a wide range of plausible scenarios, preemptive interventions supporting the timely detection of early cases provide substantially greater reductions in the probability of large outbreaks than interventions that support health care system capacity after an outbreak has commenced. CONCLUSIONS/SIGNIFICANCE: Our study demonstrates how, in the presence of substantial uncertainty about health care system infrastructure and other relevant aspects of disease control, mathematical models can be used to assess the constraints that limited resources place upon the ability of local health care systems to detect and respond to EID outbreaks in a timely and effective fashion. Our framework can help evaluate the relative impact of these constraints to identify resourcing priorities for health care system support, in order to inform principled and quantifiable decision making.
has issue date	2016-09-23(xsd:dateTime)
bibo:doi	10.1371/journal.pntd.0005018
bibo:pmid	27661978
has license	cc-by
sha1sum (hex)	f0dbc87d51c4d8a07ff83c5fc53afac5f973a20a
schema:url	https://doi.org/10.1371/journal.pntd.0005018
resource representing a document's title	Model-Informed Risk Assessment and Decision Making for an Emerging Infectious Disease in the Asia-Pacific Region
has PubMed Central identifier	PMC5035030
has PubMed identifier	27661978
schema:publication	PLoS Negl Trop Dis
resource representing a document's body	covid:f0dbc87d51c4d8a07ff83c5fc53afac5f973a20a#body_text
is schema:about of	named entity 'emerging infectious disease' named entity 'epidemics' named entity 'fade-out' named entity 'percent point' named entity 'health care workers' »more»

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