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 Réseau « Développement durable et territoires fragiles »
Résumé : National audience
Dans le contexte d'un besoin d'observation généralisé du territoire, le double recours au paysage, en tant que source d'information et vecteur de participation, recouvre diverses modalités dont les limites tiennent à des contraintes techniques et politiques. Après une mise en perspective de l'approche centrée sur l'objet paysage de la plupart des observatoires photographiques du paysage, qui contribue parfois à la mobilisation des acteurs locaux mais sous-utilise généralement le potentiel informatif du paysage, cette contribution rend compte de deux démarches d'observation du territoire qui confèrent au paysage un statut central, en tant qu'outil d'observation et en tant que source d'information privilégiée, la première dans le PNR du Haut-Languedoc (réalisation d'un diagnostic territorial préalable à la révision de la charte du Parc, 2004-2008), la seconde, encore en phase de démarrage, en Amazonie Brésilienne (Haut-Solimoes), où l'association approche paysagère et images de satellite devrait palier les carences locales en information et fournir à terme des données spatialisées en matière d'usage des sols, de bio et d'agrodiversité
Développement Durable et territoires

halshs-00914494
https://halshs.archives-ouvertes.fr/halshs-00914494

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