Éditeur(s) : HAL CCSD BioMed Central
Résumé : International audience
BACKGROUND: Sampling design is a key issue when establishing species inventories and characterizing habitats within highly heterogeneous landscapes. Sampling efforts in such environments may be constrained and many field studies only rely on subjective and/or qualitative approaches to design collection strategy. The region of Cacao, in French Guiana, provides an excellent study site to understand the presence and abundance of Anopheles mosquitoes, their species dynamics and the transmission risk of malaria across various environments. We propose an objective methodology to define a stratified sampling design. Following thorough environmental characterization, a factorial analysis of mixed groups allows the data to be reduced and non-collinear principal components to be identified while balancing the influences of the different environmental factors. Such components defined new variables which could then be used in a robust k-means clustering procedure. Then, we identified five clusters that corresponded to our sampling strata and selected sampling sites in each stratum. RESULTS: We validated our method by comparing the species overlap of entomological collections from selected sites and the environmental similarities of the same sites. The Morisita index was significantly correlated (Pearson linear correlation) with environmental similarity based on i) the balanced environmental variable groups considered jointly (p = 0.001) and ii) land cover/use (p-value<0.001). The Jaccard index was significantly correlated with land cover/use-based environmental similarity (p-value = 0.001). CONCLUSIONS: The results validate our sampling approach. Land cover/use maps (based on high spatial resolution satellite images) were shown to be particularly useful when studying the presence, density and diversity of Anopheles mosquitoes at local scales and in very heterogeneous landscapes.
BMC Ecology

pasteur-00914104
https://hal-riip.archives-ouvertes.fr/pasteur-00914104
https://hal-riip.archives-ouvertes.fr/pasteur-00914104/document
DOI : 10.1186/1472-6785-13-45
PUBMED : 24289184

Éditeur(s) : HAL CCSD IRD
Résumé : International audience
Malaria remains a major health problem in French Guiana despite the decrease in the number of cases since 2010. A previous study in Camopi, an Amerindian village on the Oyapock River, revealed that Plasmodium falciparum malaria incidence was significantly related to landscape features and that its spatial distribution exhibited some obvious patterns. In the present study, we first identified the spatial patterns that exhibit a significant Moran's index of spatial auto-correlation and that significantly explain P. falciparum malaria incidence within the multiple linear regression framework. Secondly, we linked these patterns with remotely sensed environmental features. The selected model is composed of five spatial components: three patterns, representing 50.7% of the total variance, are associated with large scale variations of the incidence, and the remaining patterns are associated with local scale variations and represent 28.7% of the total variance. Different hamlet clusters that have specificities in terms of P. falciparum malaria incidence rate, environmental characteristics and mosquito control strategies have been identified. The methodology proposed in the present study can provide useful knowledge on the spatial distribution of the P. falciparum malaria incidence in Camopi at different scales and on possible explanation of such distribution, as a function of the scale.
Symposium of the Latin American Society for Remote Sensing and Spatial Information Systems (SELPER)
Cayenne, French Guiana

ird-00797353
http://hal.ird.fr/ird-00797353
http://hal.ird.fr/ird-00797353/document
http://hal.ird.fr/ird-00797353/file/Roux_et_al_SELPER_2012.pdf
IRD : fdi:010058342

Éditeur(s) : HAL CCSD BioMed Central
Résumé : International audience
The nine countries sharing the Amazon forest accounted for 89% of all malaria cases reported in the Americas in 2008. Remote sensing can help identify the environmental determinants of malaria transmission and their temporo-spatial evolution. Seventeen studies characterizing land cover or land use features, and relating them to malaria in the Amazon subregion, were identified. These were reviewed in order to improve the understanding of the land cover/use class roles in malaria transmission. The indicators affecting the transmission risk were summarized in terms of temporal components, landscape fragmentation and anthropic pressure. This review helps to define a framework for future studies aiming to characterize and monitor malaria.
ISSN: 1475-2875

inserm-00834790
http://www.hal.inserm.fr/inserm-00834790
http://www.hal.inserm.fr/inserm-00834790/document
http://www.hal.inserm.fr/inserm-00834790/file/1475-2875-12-192.pdf
DOI : 10.1186/1475-2875-12-192

Éditeur(s) : HAL CCSD MDPI
Résumé : International audience
Malaria remains one of the most common vector-borne diseases in the world and the definition of novel control strategies can benefit from the modeling of transmission processes. However, data-driven models are often difficult to build, as data are very often incomplete, heterogeneous in nature and in quality, and/or biased. In this context, a knowledge-based approach is proposed to build a robust and general landscape-based hazard index for malaria transmission that is tailored to the Amazonian region. A partial knowledge-based model of the risk of malaria transmission in the Amazonian region, based on landscape features and extracted from a systematic literature review, was used. Spatialization of the model was obtained by generating land use and land cover maps of the cross-border area between French Guiana and Brazil, followed by computing and combining landscape metrics to build a set of normalized landscape-based hazard indices. An empirical selection of the best index was performed by comparing the indices in terms of adequacy with the knowledge-based model, intelligibility and correlation with P. falciparum incidence rates. The selected index is easy to interpret and successfully represents the current knowledge about the role played by landscape patterns in malaria transmission within the study area. It was significantly associated with P. falciparum incidence rates, using the Pearson and Spearman correlation coefficients (up to 0.79 and 0.75, respectively; p-value < 0.001), and the linear regression coefficient of determination (reaching 0.63; p-values < 0.001). This study establishes a spatial knowledge-driven, landscape-based hazard malaria index using remote sensing that can be easily produced on a regular basis and might be useful for malaria prediction, surveillance, and control. Keywords: remote sensing; land use and land cover; landscape metric; knowledge-based hazard modeling; malaria; cross-border area between French Guiana and Brazil
ISSN: 2072-4292

hal-01355255
https://hal.archives-ouvertes.fr/hal-01355255
https://hal.archives-ouvertes.fr/hal-01355255/document
https://hal.archives-ouvertes.fr/hal-01355255/file/010066865.pdf
IRD : fdi:010066865

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 IRD
Résumé : International audience
The number of satellites and remote sensing sensors devoted to earth observation becomes increasingly high, providing more and more data and especially images. In the same time the access to such a data and to the tools to process them has been considerably improved. In the presence of such data flow - and regarding the necessity to follow up and predict environmental and societal changes in highly dynamic socio-environmental contexts - we need automatic image interpretation methods. This could be accomplished by exploring some strengths of artificial intelligence. Our main idea consists in inducing classification rules that explicitly take into account structural knowledge, using Aleph, an Inductive Logic Programming (ILP) system. We applied our proposed methodology to three land cover/use maps of the French Guiana littoral. One hundred and forty six classification rules were induced for the 39 land-cover classes of the maps. These rules are expressed in first order logic language which make them intelligible and interpretable by non-experts. A ten-fold cross validation gave average values for classification accuracy, specificity and sensibility equal to, respectively, 98.82 %, 99.65% and 70%. The proposed methodology could be valuably exploited to automatically classify new objects and/or help operators using object-based classification procedures.
Symposium of the Latin American Society for Remote Sensing and Spatial Information Systems (SELPER)
Cayenne, French Guiana

ird-00797337
http://hal.ird.fr/ird-00797337
http://hal.ird.fr/ird-00797337/document
http://hal.ird.fr/ird-00797337/file/Bayoudh_et_al_2012_FP_SELPER-086.pdf
IRD : fdi:010058343

Éditeur(s) : HAL CCSD Elsevier
Résumé : International audience
The number of satellites and sensors devoted to Earth observation has become increasingly elevated, delivering extensive data, especially images. At the same time, the access to such data and the tools needed to process them has considerably improved. In the presence of such data flow, we need automatic image interpretation methods, especially when it comes to the monitoring and prediction of environmental and societal changes in highly dynamic socio-environmental contexts. This could be accomplished via artificial intelligence. The concept described here relies on the induction of classification rules that explicitly take into account structural knowledge, using Aleph, an Inductive Logic Programming (ILP) system, combined with a multi-class classification procedure. This methodology was used to monitor changes in land cover/use of the French Guiana coastline. One hundred and fifty-eight classification rules were induced from 3 diachronic land cover/use maps including 38 classes. These rules were expressed in first order logic language, which makes them easily understandable by non-experts. A 10-fold cross-validation gave significant average values of 84.62%, 99.57% and 77.22% for classification accuracy, specificity and sensitivity, respectively. Our methodology could be beneficial to automatically classify new objects and to facilitate object-based classification procedures.
ISSN: 0098-3004

hal-01369822
https://hal.archives-ouvertes.fr/hal-01369822
https://hal.archives-ouvertes.fr/hal-01369822/document
https://hal.archives-ouvertes.fr/hal-01369822/file/CAGEO-D-13-00538R1_article.pdf
DOI : 10.1016/j.cageo.2014.08.013

Éditeur(s) : The 11th Pacific Science Inter-Congress : Pacific Countries and their Ocean: Facing Local and Global Changes. March 2 - 6, 2009 Tahiti, French Polynesia
Résumé : New Caledonian shrimp farming feasibility studies started in the mid-seventies. Today ca. 2000 tons of Litopenaeus stylirostris, introduced in 1978, are semi-intensively produced each year. Since fifteen years, production has been impacted by two seasonal vibriosis, the “Summer” syndrome caused by Vibrio nigripulchritudo in relation to pond bottom and water column quality, and the “Winter Syndrome” caused by Vibrio penaeicida in relation to drastic temperature drops . With the ambition of elucidating processes possibly leading to mortality outbreaks in ponds, Ifremer has been conducting a research program since 2003 under the DESANS project (2003-2006) and the present DEDUCTION project, equally funded by the South and North Provinces and by the Government of New Caledonia. This program has been designed in a multidisciplinary approach integrating the suspected multifactorial origin of shrimp mortalities. Environment quality in ponds (either sediment or water column) plays a major role in the shrimp ecophysiological status, influencing sensitivity to pathogens . DEDUCTION focuses on a better knowledge of phytoplankton composition and biogeochemical fluxes at the sediment-water interface in ponds. Impact of farm discharges is also investigated. In addition, a more fundamental work is conducted to understand the pathogenicity mechanisms of these two Vibrio species but also to prevent the occurrence of viral infections through a RNA interference approach. Markers of the ecophysiological status of broodstock, larvae, post-larvae and reared animals, such as enzymes testifying from an oxidative stress, are developed. Gain of performance (resistance to pathogens and growth) were obtained on hybrids of the New Caledonian and introduced Hawaiian strains. Finally the database Stylog is exploited in view of discriminating “good” from “bad” rearings on the basis of relevant indicators.
Les études de faisabilité de l'aquaculture de crevettes ont débuté en Nouvelle-Calédonie dans les années soixante dix. Aujourd'hui environ 2000 tonnes de Litopenaeus stylirostris, introduite en 1978, sont produites chaque année de façon semi-intensive. Depuis quinze ans la production a été impactée par deux vibrioses : le syndrome d'été provoqué par Vibrio nigripulchritudo en relation avec la qualité de la tranche d'eau et des fonds de bassins et le syndrome d'hiver provoqué par Vibrio penaeicida en relation avec des chutes rapides de température. Dans le but d'élucider les processus entrainant des mortalités dans les élevages, Ifremer a conduit un programme de recherche depuis 2003 dans le cadre du projet DESANS (2003-2006) puis du présent projet DEDUCTION co-financé par les provinces Nord et Sud et le Gouvernement de la Nouvelle-Calédonie. Ce programme se construit dans une démarche multidisciplinaire intégrant les origines supposées multifactorielles des mortalités de crevettes. La qualité environnementale dans les bassins (les fonds et la colonne d'eau) joue un rôle majeur dans l'état physiologique des animaux, influençant leur sensibilité aux pathogènes. DEDUCTION se focalise sur une meilleure compréhension de la composition phytoplanctonique et des flux bio-géochimiques à l'interface eau/sédiment dans les bassins.L'impact des rejets des fermes est également étudié. En outre, un travail plus fondamental est conduit pour connaître les mécanismes de pathogénicité de ces deux espèces de Vibrio mais aussi pour prévenir les occurences d'infections virales par des approches ARN Interférence. Des marqueurs de l'état physiologique des oeufs, larves, post-larves et animaux en élevage, tels que les enzymes du stress oxydant sont utilisés.Les gains de performance (résistance aux pathogènes et croissance) sont obtenus sur des hybrides issus du croisement de la souche locale avec une souche hawaienne. Finalement la base de données STYLOG est exploitée dans le but de distinguer les bonnes des mauvaises pratiques sur la base d'indicateurs fiables.

Droits : info:eu-repo/semantics/openAccess
http://archimer.ifremer.fr/doc/00143/25438/23591.pdf
http://archimer.ifremer.fr/doc/00143/25438/

Éditeur(s) : HAL CCSD
Résumé : International audience
Le nombre de satellites et de capteurs pour la télédétection dédiés à l'observation de la Terre ne cesse d'augmenter, permettant ainsi d'avoir une masse de données importante en particulier en matière d'images. Parallèlement, un effort permanent vise, d'une part, à améliorer l'accès à ces données et, d'autre part, à développer d'avantages d'outils pour les manipuler. De tels efforts sont particulièrement utiles dans des contextes socio-environnementaux très dynamiques spatialement et temporellement, pour lesquels il est nécessaire de suivre et de prédire les événements environnementaux et sociétaux. En revanche, en présence d'un tel flux de données, nous avons besoin de méthodes automatiques d'interprétation d'images. Une solution envisageable pour répondre à ce besoin est de bénéficier des atouts de l'intelligence artificielle pour l'obtention de cartes d'occupation du sol issues d'une classification des régions des images. Afin de contribuer à l'automatisation de la classification, nous proposons une méthode d'induction de règles interprétables par des non-experts et mettant en évidence, explicitement, des connaissances structurelles. Cette méthode s'appuie sur la programmation logique inductive (PLI) et en particulier sur le système inductif ”Aleph”. L'application de la méthode de classification Multi-class Rule Set Intersection (MRSI) permet ensuite de classifier tout nouvel objet au regard des ses caractéristiques intrinsèques et de celles des objets environnants. Nous avons appliqué notre méthodologie à l'étude de la dynamique du littoral de la Guyane Française. Suite à ce travail, nous avons induit 136 règles de classification pour 38 classes d'occupation du sol. Ces règles sont intelligibles et simples à interpréter de par l'utilisation de la logique du premier ordre. Les performances du système ont été évaluées par la validation croisée. En moyenne, la précision, la spécificité et la sensibilité sont, respectivement, égales à 84,62%, 99,57% et 77,22%. Ces résultats quantitatifs montrent une bonne performance de la méthodologie pour la mise à jour automatique de cartes d'occupation du sol et/ou l'assistance aux opérateurs utilisant l'analyse d'image orientée-objet.
11èmes Rencontres des Jeunes Chercheurs en Intelligence Artificielle
Lille, France

hal-01376400
https://hal.archives-ouvertes.fr/hal-01376400
https://hal.archives-ouvertes.fr/hal-01376400/document
https://hal.archives-ouvertes.fr/hal-01376400/file/Bayoudh_RJCIA2013.pdf

Éditeur(s) : HAL CCSD BioMed Central
Résumé : International audience
UNLABELLED: ABSTRACT: BACKGROUND: Malaria remains a major health problem in French Guiana, with a mean of 3800 cases each year. A previous study in Camopi, an Amerindian village on the Oyapock River, highlighted the major contribution of environmental features to the incidence of malaria attacks. We propose a method for the objective selection of the best multivariate peridomestic landscape characterisation that maximises the chances of identifying relationships between environmental features and malaria incidence, statistically significant and meaningful from an epidemiological point of view. METHODS: A land-cover map, the hydrological network and the geolocalised inhabited houses were used to characterise the peridomestic landscape in eleven discoid buffers with radii of 50, 100, 200, 300, 400, 500, 600, 700, 800, 900 and 1000 metres. Buffer-based landscape characterisations were first compared in terms of their capacity to discriminate between sites within the geographic space and of their effective multidimensionality in variable space. The Akaike information criterion (AIC) was then used to select the landscape model best explaining the incidences of P. vivax and P. falciparum malaria. Finally, we calculated Pearson correlation coefficients for the relationships between environmental variables and malaria incidence, by species, for the more relevant buffers. RESULTS: The optimal buffers for environmental characterisation had radii of 100 m around houses for P. vivax and 400 m around houses for P. falciparum. The incidence of P. falciparum malaria seemed to be more strongly linked to environmental features than that of P. vivax malaria, within these buffers. The incidence of P. falciparum malaria in children was strongly correlated with proportions of bare soil (r = -0.69), land under high vegetation (r = 0.68) and primary forest (r = 0.54), landscape division (r = 0.48) and the number of inhabited houses (r = -0.60). The incidence of P. vivax malaria was associated only with landscape division (r = 0.49). CONCLUSIONS: The proposed methodology provides a simple and general framework for objective characterisation of the landscape to account for field observations. The use of this method enabled us to identify different optimal observation horizons around houses, depending on the Plasmodium species considered, and to demonstrate significant correlations between environmental features and the incidence of malaria.
ISSN: 1476-072X

inserm-00674075
http://www.hal.inserm.fr/inserm-00674075
http://www.hal.inserm.fr/inserm-00674075/document
http://www.hal.inserm.fr/inserm-00674075/file/1476-072X-10-65.pdf
DOI : 10.1186/1476-072X-10-65