Éditeur(s) : HAL CCSD Public Library of Science
Résumé : International audience
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.
ISSN: 1935-2727

Droits : http://creativecommons.org/licenses/by/
pasteur-01247037
https://hal-riip.archives-ouvertes.fr/pasteur-01247037
https://hal-riip.archives-ouvertes.fr/pasteur-01247037/document
https://hal-riip.archives-ouvertes.fr/pasteur-01247037/file/journal.pntd.0004211.pdf
DOI : 10.1371/journal.pntd.0004211

Éditeur(s) : HAL CCSD Public Library of Science
Résumé : International audience
Local variation in the density of Anopheles mosquitoes and the risk of exposure to bites are essential to explain the spatial and temporal heterogeneities in the transmission of malaria. Vector distribution is driven by environmental factors. Based on variables derived from satellite imagery and meteorological observations, this study aimed to dynamically model and map the densities of Anopheles darlingi in the municipality of Saint-Georges de l’Oyapock (French Guiana). Longitudinal sampling sessions of An. darlingi densities were conducted between September 2012 and October 2014. Landscape and meteorological data were collected and processed to extract a panel of variables that were potentially related to An. darlingi ecology. Based on these data, a robust methodology was formed to estimate a statistical predictive model of the spatial-temporal variations in the densities of An. darlingi in Saint-Georges de l’Oyapock. The final cross-validated model integrated two landscape variables—dense forest surface and built surface—together with four meteorological variables related to rainfall, evapotranspiration, and the minimal and maximal temperatures. Extrapolation of the model allowed the generation of predictive weekly maps of An. darlingi densities at a resolution of 10-m. Our results supported the use of satellite imagery and meteorological data to predict malaria vector densities. Such fine-scale modeling approach might be a useful tool for health authorities to plan control strategies and social communication in a cost-effective, targeted, and timely manner.
ISSN: 1932-6203

hal-01383486
https://hal.archives-ouvertes.fr/hal-01383486
https://hal.archives-ouvertes.fr/hal-01383486/document
https://hal.archives-ouvertes.fr/hal-01383486/file/Adde_et_al_PlosONE_2016.pdf
DOI : 10.1371/journal.pone.0164685

Éditeur(s) : HAL CCSD
Résumé : Satellite and in situ chlorophyll concentration data collected as part of VALidation HYperspectral of a BIOgeochemical model (ValHyBio), a PNTS-sponsored project dedicated to satellite ocean-colour imaging of the Southwest Pacific, are analyzed to describe chlorophyll variability in the Coral Sea, a vast oligotrophic region characterized by a deep chlorophyll maximum and blue waters of high transparency. Average chlorophyll concentrations estimated from MODIS-Aqua are very low (<0.2 mg m-3) except in the vicinity of main islands and coral reefs, where enrichment may occur due to upwelling or internal waves that bring nutrients to the euphotic zone from the deep part of the water column. During the summer season, blooms of cyanobacteria (Trichodesmium) develop in the surface waters and may form large slicks. The nitrogen fixed by these slicks is a potential source of new nitrogen later assimilated by picoplankton and the marine food chain. Coastal areas exhibit higher chlorophyll concentrations because of nutrient input from the land, as observed in 2008 around New Caledonia. In lagoon areas, the sea colour is influenced by turbidity and bathymetry, and the MODIS OC3 algorithm is inadequate, with a systematic overestimation of chlorophyll concentration in the New Caledonia lagoon. Improved bio-optical algorithms are needed for those turbid and shallow waters, to allow not only a better description of chlorophyll variability, but also evaluation of chlorophyll simulations by recently developed biogeochemical models.
of the 12th International Coral Reef Symposium, 18E
CAIRNS, Australia

hal-00746470
https://hal.archives-ouvertes.fr/hal-00746470
https://hal.archives-ouvertes.fr/hal-00746470/document