INTEGRATING COMPLEX SYSTEM DYNAMICS OF PANDEMIC INFLUENZA WITH A MULTI-CRITERIA DECISION MAKING MODEL FOR EVALUATING PUBLIC HEALTH STRATEGIES
Identifieur interne : 001857 ( Main/Merge ); précédent : 001856; suivant : 001858INTEGRATING COMPLEX SYSTEM DYNAMICS OF PANDEMIC INFLUENZA WITH A MULTI-CRITERIA DECISION MAKING MODEL FOR EVALUATING PUBLIC HEALTH STRATEGIES
Auteurs : Ozgur M. Araz [États-Unis]Source :
- Journal of Systems Science and Systems Engineering [ 1004-3756 ] ; 2013.
Descripteurs français
- Pascal (Inist)
- Système complexe, Epidémie, Analyse multicritère, Prise de décision, Informatique théorique, Processus hiérarchie analytique, Politique sanitaire, Grippe, Santé publique, Urgence, Développement maladie, Politique publique, Système aide décision, Epidémiologie, Modélisation, Préférence, Modèle dynamique, ..
- Wicri :
- topic : Prise de décision, Santé publique.
English descriptors
- KwdEn :
Abstract
Recent developments in computational sciences and computer modeling have allowed emergency preparedness exercises to include simulation models as supporting tools. These simulation models are generally built for predicting temporal and geographic patterns of disease spread. However sole use of simulation models in exercise design falls short in terms of incorporating policy decision makers' preferences into decision-making processes. In this paper, a general framework for exercising public health preparedness plans with a decision support system is presented to integrate estimation of key epidemiological parameters with a system dynamics model of an outbreak. A multi-criteria decision making framework, an Analytical Hierarchy Process model, is then developed and integrated with the simulation model to help public health policy makers prioritize their response goals and evaluate mitigation strategies in a table-top exercise environment.
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Pascal:14-0149794Le document en format XML
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Araz</name><affiliation wicri:level="1"><inist:fA14 i1="01"><s1>College of Public Health, University of Nebraska Medical Center</s1><s3>USA</s3><sZ>1 aut.</sZ></inist:fA14><country>États-Unis</country><wicri:noRegion>College of Public Health, University of Nebraska Medical Center</wicri:noRegion></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">INIST</idno><idno type="inist">14-0149794</idno><date when="2013">2013</date><idno type="stanalyst">PASCAL 14-0149794 INIST</idno><idno type="RBID">Pascal:14-0149794</idno><idno type="wicri:Area/PascalFrancis/Corpus">000095</idno><idno type="wicri:Area/PascalFrancis/Curation">001D24</idno><idno type="wicri:Area/PascalFrancis/Checkpoint">000260</idno><idno type="wicri:explorRef" wicri:stream="PascalFrancis" wicri:step="Checkpoint">000260</idno><idno type="wicri:doubleKey">1004-3756:2013:Araz O:integrating:complex:system</idno><idno type="wicri:Area/Main/Merge">001857</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a">INTEGRATING COMPLEX SYSTEM DYNAMICS OF PANDEMIC INFLUENZA WITH A MULTI-CRITERIA DECISION MAKING MODEL FOR EVALUATING PUBLIC HEALTH STRATEGIES</title><author><name sortKey="Araz, Ozgur M" sort="Araz, Ozgur M" uniqKey="Araz O" first="Ozgur M." last="Araz">Ozgur M. Araz</name><affiliation wicri:level="1"><inist:fA14 i1="01"><s1>College of Public Health, University of Nebraska Medical Center</s1><s3>USA</s3><sZ>1 aut.</sZ></inist:fA14><country>États-Unis</country><wicri:noRegion>College of Public Health, University of Nebraska Medical Center</wicri:noRegion></affiliation></author></analytic><series><title level="j" type="main">Journal of Systems Science and Systems Engineering</title><title level="j" type="abbreviated">J. Syst. Sci. Syst. Eng.</title><idno type="ISSN">1004-3756</idno><imprint><date when="2013">2013</date></imprint></series></biblStruct></sourceDesc><seriesStmt><title level="j" type="main">Journal of Systems Science and Systems Engineering</title><title level="j" type="abbreviated">J. Syst. Sci. Syst. Eng.</title><idno type="ISSN">1004-3756</idno></seriesStmt></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Analytic hierarchy process</term><term>Complex system</term><term>Computer theory</term><term>Decision making</term><term>Decision support system</term><term>Disease development</term><term>Dynamic model</term><term>Emergency</term><term>Epidemic</term><term>Epidemiology</term><term>Health policy</term><term>Influenza</term><term>Modeling</term><term>Multicriteria analysis</term><term>Preference</term><term>Public health</term><term>Public policy</term></keywords><keywords scheme="Pascal" xml:lang="fr"><term>Système complexe</term><term>Epidémie</term><term>Analyse multicritère</term><term>Prise de décision</term><term>Informatique théorique</term><term>Processus hiérarchie analytique</term><term>Politique sanitaire</term><term>Grippe</term><term>Santé publique</term><term>Urgence</term><term>Développement maladie</term><term>Politique publique</term><term>Système aide décision</term><term>Epidémiologie</term><term>Modélisation</term><term>Préférence</term><term>Modèle dynamique</term><term>.</term></keywords><keywords scheme="Wicri" type="topic" xml:lang="fr"><term>Prise de décision</term><term>Santé publique</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Recent developments in computational sciences and computer modeling have allowed emergency preparedness exercises to include simulation models as supporting tools. These simulation models are generally built for predicting temporal and geographic patterns of disease spread. However sole use of simulation models in exercise design falls short in terms of incorporating policy decision makers' preferences into decision-making processes. In this paper, a general framework for exercising public health preparedness plans with a decision support system is presented to integrate estimation of key epidemiological parameters with a system dynamics model of an outbreak. A multi-criteria decision making framework, an Analytical Hierarchy Process model, is then developed and integrated with the simulation model to help public health policy makers prioritize their response goals and evaluate mitigation strategies in a table-top exercise environment.</div></front></TEI><affiliations><list><country><li>États-Unis</li></country></list><tree><country name="États-Unis"><noRegion><name sortKey="Araz, Ozgur M" sort="Araz, Ozgur M" uniqKey="Araz O" first="Ozgur M." last="Araz">Ozgur M. Araz</name></noRegion></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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