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<title lang=en>Mining local climate data to assess spatiotemporal dengue fever epidemic patterns in French Guiana</title>
<creator>Bringay, Sandra</creator>
<creator>Flamand, Claude</creator>
<creator>Fabrègue, Mickaël</creator>
<creator>Ardillon, Vanessa</creator>
<creator>Philippe, Quenel</creator>
<creator>Desenclos, Jean-Claude</creator>
<creator>Teisseire, Maguelonne</creator>
<contributor>Département de Mathématiques et Informatique Appliquées (MIAP) ; Université Paul-Valéry - Montpellier 3 (UM3)</contributor>
<contributor>ADVanced Analytics for data SciencE (ADVANSE) ; Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM) ; Université de Montpellier (UM) - Centre National de la Recherche Scientifique (CNRS) - Université de Montpellier (UM) - Centre National de la Recherche Scientifique (CNRS)</contributor>
<contributor>Institut de Veille Sanitaire (INVS) ; Institut de Veille Sanitaire (INVS)</contributor>
<contributor>Territoires, Environnement, Télédétection et Information Spatiale (UMR TETIS) ; Centre de Coopération Internationale en Recherche Agronomique pour le Développement (CIRAD) - AgroParisTech - Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)</contributor>
<contributor>Laboratoire des sciences de l'ingénieur, de l'informatique et de l'imagerie (ICube) ; École Nationale du Génie de l'Eau et de l'Environnement de Strasbourg (ENGEES) - Université de Strasbourg (UNISTRA) - Institut National des Sciences Appliquées (INSA)</contributor>
<contributor>Cellule Inter Régionale d'Epidémiologie des Antilles - Guyane ; Institut de Veille Sanitaire</contributor>
<contributor>Cellule Interrégionale d'Epidémiologie Antilles-Guyane ; Cellule interrégionale d'épidémiologie Antilles-Guyane [CIRE]</contributor>
<contributor>Institut de recherche, santé, environnement et travail [Rennes] (Irset) ; Université d'Angers (UA) - Université des Antilles et de la Guyane (UAG) - Université de Rennes 1 (UR1) - École des Hautes Études en Santé Publique [EHESP] (EHESP) - Institut National de la Santé et de la Recherche Médicale (INSERM) - Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique )</contributor>
<contributor>Département des maladies infectieuses ; Institut de Veille Sanitaire (INVS)</contributor>
<description>International audience</description>
<source>ISSN: 1067-5027</source>
<source>EISSN: 1527-974X</source>
<source>Journal of the American Medical Informatics Association</source>
<publisher>BMJ Publishing Group</publisher>
<identifier>lirmm-01379072</identifier>
<identifier>https://hal-lirmm.ccsd.cnrs.fr/lirmm-01379072</identifier>
<source>https://hal-lirmm.ccsd.cnrs.fr/lirmm-01379072</source>
<source>Journal of the American Medical Informatics Association, BMJ Publishing Group, 2014, 21 (e2), pp.232-240. 〈10.1136/amiajnl-2013-002348〉</source>
<identifier>DOI : 10.1136/amiajnl-2013-002348</identifier>
<relation>info:eu-repo/semantics/altIdentifier/doi/10.1136/amiajnl-2013-002348</relation>
<identifier>PUBMED : 24549761</identifier>
<relation>info:eu-repo/semantics/altIdentifier/pmid/24549761</relation>
<language>en</language>
<subject lang=en>Data Mining</subject>
<subject lang=en> Dengue fever</subject>
<subject lang=en> Epidemiologic surveillance</subject>
<subject lang=en> French Guiana</subject>
<subject lang=en> Infectious diseases</subject>
<subject lang=en> Meteorological factors</subject>
<subject>[INFO] Computer Science [cs]</subject>
<type>info:eu-repo/semantics/article</type>
<type>Journal articles</type>
<description lang=en>OBJECTIVE:To identify local meteorological drivers of dengue fever in French Guiana, we applied an original data mining method to the available epidemiological and climatic data. Through this work, we also assessed the contribution of the data mining method to the understanding of factors associated with the dissemination of infectious diseases and their spatiotemporal spread.METHODS:We applied contextual sequential pattern extraction techniques to epidemiological and meteorological data to identify the most significant climatic factors for dengue fever, and we investigated the relevance of the extracted patterns for the early warning of dengue outbreaks in French Guiana.RESULTS:The maximum temperature, minimum relative humidity, global brilliance, and cumulative rainfall were identified as determinants of dengue outbreaks, and the precise intervals of their values and variations were quantified according to the epidemiologic context. The strongest significant correlations were observed between dengue incidence and meteorological drivers after a 4-6-week lag.DISCUSSION:We demonstrated the use of contextual sequential patterns to better understand the determinants of the spatiotemporal spread of dengue fever in French Guiana. Future work should integrate additional variables and explore the notion of neighborhood for extracting sequential patterns.CONCLUSIONS:Dengue fever remains a major public health issue in French Guiana. The development of new methods to identify such specific characteristics becomes crucial in order to better understand and control spatiotemporal transmission.Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.</description>
<date>2014-10</date>
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