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Predicting dengue fever outbreaks in French Guiana using climate indicators

Authors :
Vanessa Ardillon
Claude Flamand
Dominique Rousset
Antoine Adde
Romain Girod
Sébastien Briolant
Pascal Roucou
Jean-Claude Desenclos
Morgan Mangeas
Philippe Quénel
Unité d'Epidémiologie
Institut Pasteur de la Guyane
Réseau International des Instituts Pasteur ( RIIP ) -Réseau International des Instituts Pasteur ( RIIP )
Unité d'Entomologie Médicale
Biogéosciences [Dijon] ( BGS )
Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique ( CNRS )
Cirad-amis, maison de la télédétection
Centre de Coopération Internationale en Recherche Agronomique pour le Développement
Cellule Interrégionale d'Epidémiologie Antilles-Guyane
Cellule interrégionale d'épidémiologie Antilles-Guyane [CIRE]
Département santé environnement
Institut de Veille Sanitaire
Unité de virologie
Direction Interarmées du Service de Santé en Guyane
Institut de Recherches Biomédicales des Armées
Laboratoire d'étude et de recherche en environnement et santé ( LERES )
École des Hautes Études en Santé Publique [EHESP] ( EHESP )
Study supported by a grant from the 'Ministère de l'Outre-Mer' (http://www.outre-mer.gouv.fr/) and by a CNES-DGA-MRIS scholarship (https://cnes.fr/fr).
Unité d'Epidémiologie [Cayenne, Guyane française]
Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)
Unité d'entomologie médicale
Vectopôle Amazonien Emile Abonnenc [Cayenne, Guyane française]
Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut Pasteur de la Guyane
Biogéosciences [UMR 6282] [Dijon] (BGS)
Université de Bourgogne (UB)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS)
Institut de Recherche pour le Développement (IRD)
Institut de Veille Sanitaire (INVS)
Centre National de Référence pour les Arbovirus - Laboratoire de Virologie [Cayenne, Guyane française] (CNR - laboratoire associé)
Laboratoire d'étude et de recherche en environnement et santé (LERES)
École des Hautes Études en Santé Publique [EHESP] (EHESP)
Biogéosciences [UMR 6282] (BGS)
Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)
Entomologie médicale
Laboratoire de Parasitologie
UMR 228 Espace-Dev, Espace pour le développement
Institut de Recherche pour le Développement (IRD)-Université de Perpignan Via Domitia (UPVD)-Avignon Université (AU)-Université de La Réunion (UR)-Université de Montpellier (UM)-Université de Guyane (UG)-Université des Antilles (UA)
Département des maladies infectieuses
Institut pluridisciplinaire de recherche appliquée dans le domaine du génie pétrolier (IPRADDGP)
Université de Pau et des Pays de l'Adour (UPPA)-Centre National de la Recherche Scientifique (CNRS)
Réseau International des Instituts Pasteur (RIIP)
Vecteurs - Infections tropicales et méditerranéennes (VITROME)
Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Institut de Recherche Biomédicale des Armées (IRBA)
'Ministère de l'Outre-Mer' (http://www.outre-mer.gouv.fr/) and by a CNES-DGA-MRIS scholarship (https://cnes.fr/fr)
Source :
PLoS Neglected Tropical Diseases, PLoS Neglected Tropical Diseases, Public Library of Science, 2016, 10 (4), pp.e0004681. 〈http://journals.plos.org/plosntds/article?id=10.1371/journal.pntd.0004681〉. 〈10.1371/journal.pntd.0004681〉, PLoS Neglected Tropical Diseases, Public Library of Science, 2016, 10 (4), pp.e0004681. ⟨10.1371/journal.pntd.0004681⟩, PLoS Neglected Tropical Diseases, 2016, 10 (4), pp.e0004681. ⟨10.1371/journal.pntd.0004681⟩, PLoS Neglected Tropical Diseases, Vol 10, Iss 4, p e0004681 (2016)
Publication Year :
2016

Abstract

Background Dengue fever epidemic dynamics are driven by complex interactions between hosts, vectors and viruses. Associations between climate and dengue have been studied around the world, but the results have shown that the impact of the climate can vary widely from one study site to another. In French Guiana, climate-based models are not available to assist in developing an early warning system. This study aims to evaluate the potential of using oceanic and atmospheric conditions to help predict dengue fever outbreaks in French Guiana. Methodology/Principal Findings Lagged correlations and composite analyses were performed to identify the climatic conditions that characterized a typical epidemic year and to define the best indices for predicting dengue fever outbreaks during the period 1991–2013. A logistic regression was then performed to build a forecast model. We demonstrate that a model based on summer Equatorial Pacific Ocean sea surface temperatures and Azores High sea-level pressure had predictive value and was able to predict 80% of the outbreaks while incorrectly predicting only 15% of the non-epidemic years. Predictions for 2014–2015 were consistent with the observed non-epidemic conditions, and an outbreak in early 2016 was predicted. Conclusions/Significance These findings indicate that outbreak resurgence can be modeled using a simple combination of climate indicators. This might be useful for anticipating public health actions to mitigate the effects of major outbreaks, particularly in areas where resources are limited and medical infrastructures are generally insufficient.<br />Author Summary Climatic determinants are amongst the most frequently cited in studies aimed at understanding and explaining the dynamics of vector-borne infections, and dengue in particular. French Guiana, a French overseas territory in which the vector Aedes aegypti is well established, experiences an epidemic cycle of dengue with large and prolonged epidemics occurring approximately every 3 years. Dengue is one of the most prioritized infectious diseases, and it requires an intense mobilization of local public health authorities, health services, and health professional and vector control services. A specific surveillance, preparedness and response plan has been developed based upon these needs. Gaining an accurate understanding of the drivers of dengue transmission is required to develop a model to predict the risk of an epidemic and to plan activities aimed at controlling it. Here, we assessed the effects of climatic factors on dengue spread to develop a predictive model of the epidemics in French Guiana on a country-wide scale. The goal of the model is to anticipate and plan both preventive and control activities. Given climate conditions, the model predicts that a dengue epidemic is likely to occur in early 2016. These conditions, which are favorable for Aedes mosquito proliferation, could also enhance the diffusion of other arboviruses, such as the Zika virus, in northeastern South America.

Subjects

Subjects :
Atmospheric Science
Viral Diseases
El Niño-Southern Oscillation
Epidemiology
Climate
Rain
Marine and Aquatic Sciences
Logistic regression
Oceanography
Dengue fever
Disease Outbreaks
Dengue Fever
Dengue
0302 clinical medicine
[SDV.MHEP.MI]Life Sciences [q-bio]/Human health and pathology/Infectious diseases
Oceans
Medicine and Health Sciences
030212 general & internal medicine
Climatology
[SDV.MHEP.ME]Life Sciences [q-bio]/Human health and pathology/Emerging diseases
Ecology
lcsh:Public aspects of medicine
3. Good health
French Guiana
[ SDV.MHEP.MI ] Life Sciences [q-bio]/Human health and pathology/Infectious diseases
[ SDE.MCG ] Environmental Sciences/Global Changes
Geography
Infectious Diseases
[SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology
Epidemiological Methods and Statistics
Equatorial Ocean Regions
Seasons
[ SDU.STU.CL ] Sciences of the Universe [physics]/Earth Sciences/Climatology
Oceans, Ocean temperature, Seasons, El Niño-Southern Oscillation, Rain, Dengue fever, Epidemiology, Equatorial ocean regions
Research Article
Neglected Tropical Diseases
medicine.medical_specialty
lcsh:Arctic medicine. Tropical medicine
lcsh:RC955-962
[SDE.MCG]Environmental Sciences/Global Changes
030231 tropical medicine
03 medical and health sciences
Meteorology
Environmental health
medicine
Humans
Ocean Temperature
Azores High
Models, Statistical
Public health
Public Health, Environmental and Occupational Health
Outbreak
lcsh:RA1-1270
Bodies of Water
medicine.disease
Tropical Diseases
Sea surface temperature
13. Climate action
Earth Sciences
Early warning system
Climate model
[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie
Epidemiologic Methods
Forecasting
Climate Modeling

Details

Language :
English
ISSN :
19352727 and 19352735
Database :
OpenAIRE
Journal :
PLoS Neglected Tropical Diseases, PLoS Neglected Tropical Diseases, Public Library of Science, 2016, 10 (4), pp.e0004681. 〈http://journals.plos.org/plosntds/article?id=10.1371/journal.pntd.0004681〉. 〈10.1371/journal.pntd.0004681〉, PLoS Neglected Tropical Diseases, Public Library of Science, 2016, 10 (4), pp.e0004681. ⟨10.1371/journal.pntd.0004681⟩, PLoS Neglected Tropical Diseases, 2016, 10 (4), pp.e0004681. ⟨10.1371/journal.pntd.0004681⟩, PLoS Neglected Tropical Diseases, Vol 10, Iss 4, p e0004681 (2016)
Accession number :
edsair.doi.dedup.....3b583cf68ec49a39f20443dc1463a05c
Full Text :
https://doi.org/10.1371/journal.pntd.0004681〉.