Publications des scientifiques de l'IRD

Adde A., Roucou P., Mangeas Morgan, Ardillon V., Desenclos J. C., Rousset D., Girod R., Briolant S., Quenel P., Flamand C. (2016). Predicting dengue fever outbreaks in French Guiana using climate indicators. Plos Neglected Tropical Diseases, 10 (4), p. e0004681 [16 p.]. ISSN 1935-2735.

Titre du document
Predicting dengue fever outbreaks in French Guiana using climate indicators
Année de publication
2016
Type de document
Article référencé dans le Web of Science WOS:000375376700086
Auteurs
Adde A., Roucou P., Mangeas Morgan, Ardillon V., Desenclos J. C., Rousset D., Girod R., Briolant S., Quenel P., Flamand C.
Source
Plos Neglected Tropical Diseases, 2016, 10 (4), p. e0004681 [16 p.] ISSN 1935-2735
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.
Plan de classement
Sciences du milieu [021] ; Entomologie médicale / Parasitologie / Virologie [052]
Description Géographique
GUYANE FRANCAISE
Localisation
Fonds IRD [F B010066856]
Identifiant IRD
fdi:010066856
Contact