untitled
<OAI-PMH schemaLocation=http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd>
<responseDate>2016-07-04T13:46:34Z</responseDate>
<request identifier=oai:HAL:pasteur-01247037v1 verb=GetRecord metadataPrefix=oai_dc>http://api.archives-ouvertes.fr/oai/hal/</request>
<GetRecord>
<record>
<header>
<identifier>oai:HAL:pasteur-01247037v1</identifier>
<datestamp>2016-04-30</datestamp>
<setSpec>type:ART</setSpec>
<setSpec>subject:sdv</setSpec>
<setSpec>collection:RIIP</setSpec>
<setSpec>collection:RIIP_NOUVELLECALEDONIE</setSpec>
<setSpec>collection:RIIP_PARIS</setSpec>
<setSpec>collection:METEO</setSpec>
<setSpec>collection:GIP-BE</setSpec>
<setSpec>collection:IRD</setSpec>
<setSpec>collection:INSU</setSpec>
<setSpec>collection:CNRS</setSpec>
<setSpec>collection:UNIV-AG</setSpec>
<setSpec>collection:MNHN</setSpec>
<setSpec>collection:UPMC</setSpec>
<setSpec>collection:LOCEAN</setSpec>
<setSpec>collection:AGROPOLIS</setSpec>
</header>
<metadata><dc>
<publisher>HAL CCSD</publisher>
<title lang=en>Socio-economic and Climate Factors Associated with Dengue Fever Spatial Heterogeneity: A Worked Example in New Caledonia.</title>
<creator>Teurlai, Magali</creator>
<creator>Menkès, Christophe Eugène</creator>
<creator>Cavarero, Virgil</creator>
<creator>Degallier, Nicolas</creator>
<creator>Descloux, Elodie</creator>
<creator>Grangeon, Jean-Paul</creator>
<creator>Guillaumot, Laurent</creator>
<creator>Libourel Rouge, Thérèse</creator>
<creator>Lucio, Paulo Sergio</creator>
<creator>Mathieu-Daudé, Françoise</creator>
<creator>Mangeas, Morgan</creator>
<contributor>Institut Pasteur de Nouvelle-Calédonie ; Réseau International des Instituts Pasteur - Institut Pasteur de Nouvelle-Calédonie</contributor>
<contributor>Espace pour le Développement (UMR ESPACE-DEV) ; Université des Antilles et de la Guyane (UAG) - Université de la Réunion - Université de Montpellier (UM) - Institut de Recherche pour le Développement (IRD)</contributor>
<contributor>Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN) ; Muséum National d'Histoire Naturelle (MNHN) - Université Pierre et Marie Curie - Paris 6 (UPMC) - INSU - Centre National de la Recherche Scientifique (CNRS)</contributor>
<contributor>Météo France</contributor>
<contributor>UMR228 ESPACE-DEV ; Université des sciences et techniques Montpellier 2 - IRD</contributor>
<contributor>Service médecine interne ; Centre Hospitalier Territorial de Noumea</contributor>
<contributor>Direction des affaires sanitaires et sociales de Nouvelle-Calédonie</contributor>
<contributor>Centro de ciencias exatas e da terra (CCET) ; Univesidade Federal do Rio Grande do Norte</contributor>
<contributor>Maladies infectieuses et vecteurs : écologie, génétique, évolution et contrôle (MIVEGEC) ; Université de Montpellier (UM) - Centre National de la Recherche Scientifique (CNRS) - Institut de Recherche pour le Développement (IRD [France-Sud])</contributor>
<contributor>MT was supported financially by theProvince Sud of New Caledonia which provided aresearch allocation for supporting Ph.D. students, andby the Institute for Research and Development.</contributor>
<description>International audience</description>
<source>ISSN: 1935-2727</source>
<source>EISSN: 1935-2735</source>
<source>PLoS Neglected Tropical Diseases</source>
<publisher>Public Library of Science</publisher>
<identifier>pasteur-01247037</identifier>
<identifier>https://hal-riip.archives-ouvertes.fr/pasteur-01247037</identifier>
<identifier>https://hal-riip.archives-ouvertes.fr/pasteur-01247037/document</identifier>
<identifier>https://hal-riip.archives-ouvertes.fr/pasteur-01247037/file/journal.pntd.0004211.pdf</identifier>
<source>https://hal-riip.archives-ouvertes.fr/pasteur-01247037</source>
<source>PLoS Neglected Tropical Diseases, Public Library of Science, 2015, 9 (12), pp.e0004211. <10.1371/journal.pntd.0004211></source>
<identifier>DOI : 10.1371/journal.pntd.0004211</identifier>
<relation>info:eu-repo/semantics/altIdentifier/doi/10.1371/journal.pntd.0004211</relation>
<identifier>PUBMED : 26624008</identifier>
<relation>info:eu-repo/semantics/altIdentifier/pmid/26624008</relation>
<identifier>PUBMEDCENTRAL : PMC4666598</identifier>
<language>en</language>
<subject lang=en>Epidemiology</subject>
<subject lang=en>Climate Change</subject>
<subject lang=en>Dengue fever</subject>
<subject lang=en>Climate</subject>
<subject lang=en>Socio-economic factors</subject>
<subject lang=en>Public Health</subject>
<subject lang=en>Statistical Modelling</subject>
<subject lang=fr>Dengue</subject>
<subject lang=fr>Climat</subject>
<subject lang=fr>Facteurs socio-économiques</subject>
<subject lang=fr>Changement climatique</subject>
<subject lang=fr>Epidemiologie</subject>
<subject lang=fr>Santé Publique</subject>
<subject lang=fr>Modélisation statistique</subject>
<subject lang=fr>Analyse spatiale</subject>
<subject>[SDV.MHEP.ME] Life Sciences [q-bio]/Human health and pathology/Emerging diseases</subject>
<subject>[SDV.SPEE] Life Sciences [q-bio]/Public Health and Epidemiology</subject>
<subject>[SDV.EE.SANT] Life Sciences [q-bio]/Ecology, environment/Health</subject>
<subject>[SDV.MHEP.MI] Life Sciences [q-bio]/Human health and pathology/Infectious diseases</subject>
<type>info:eu-repo/semantics/article</type>
<type>Journal articles</type>
<description lang=en>Understanding the factors underlying the spatio-temporal distribution of infectious diseases provides useful information regarding their prevention and control. Dengue fever spatio-temporal patterns result from complex interactions between the virus, the host, and the vector. These interactions can be influenced by environmental conditions. Our objectives were to analyse dengue fever spatial distribution over New Caledonia during epidemic years, to identify some of the main underlying factors, and to predict the spatial evolution of dengue fever under changing climatic conditions, at the 2100 horizon. We used principal component analysis and support vector machines to analyse and model the influence of climate and socio-economic variables on the mean spatial distribution of 24,272 dengue cases reported from 1995 to 2012 in thirty-three communes of New Caledonia. We then modelled and estimated the future evolution of dengue incidence rates using a regional downscaling of future climate projections. The spatial distribution of dengue fever cases is highly heterogeneous. The variables most associated with this observed heterogeneity are the mean temperature, the mean number of people per premise, and the mean percentage of unemployed people, a variable highly correlated with people's way of life. Rainfall does not seem to play an important role in the spatial distribution of dengue cases during epidemics. By the end of the 21st century, if temperature increases by approximately 3°C, mean incidence rates during epidemics could double. In New Caledonia, a subtropical insular environment, both temperature and socio-economic conditions are influencing the spatial spread of dengue fever. Extension of this study to other countries worldwide should improve the knowledge about climate influence on dengue burden and about the complex interplay between different factors. This study presents a methodology that can be used as a step by step guide to model dengue spatial heterogeneity in other countries. </description>
<rights>http://creativecommons.org/licenses/by/</rights>
<date>2015-11-30</date>
</dc>
</metadata>
</record>
</GetRecord>
</OAI-PMH>
