Inventaire d'enquêtes Demostaf

Information sur la citation

Type Revue - Global Health Action
Titre Using high spatial resolution remote sensing for risk mapping of malaria occurrence in the Nouna district, Burkina Faso
Auteur(s)
Volume 2
Numéro 1
Publication (Jour/Mois/Année) 2009
Numéros de page 2094
URL http://dx.doi.org/10.3402/gha.v2i0.2094
Résumé
Introduction: Malaria control measures such as early diagnosis and treatment, intermittent treatment of pregnant women, impregnated bed nets, indoor spraying and larval control measures are difficult to target specifically because of imprecise estimates of risk at a small-scale level. Ways of estimating local risks for malaria are therefore important.Methods: A high-resolution satellite view from the SPOT 5 satellite during 2008 was used to generate a land cover classification in the malaria endemic lowland of North-Western Burkina Faso. For the area of a complete satellite view of 60×60 km, a supervised land cover classification was carried out. Ten classes were built and correlated to land cover types known for acting as Anopheles mosquito breeding sites.Results: According to known correlations of Anopheles larvae presence and surface water-related land cover, cultivated areas in the riverine vicinity of Kossi River were shown to be one of the most favourable sites for Anopheles production. Similar conditions prevail in the South of the study region, where clayey soils and higher precipitations benefit the occurrence of surface water. Besides pools, which are often directly detectable, rice fields and occasionally flooded crops represent most appropriate habitats. On the other hand, forests, elevated regions on porous soils, grasslands and the dryer, sandy soils in the north-western part turned out to deliver fewer mosquito breeding opportunities.Conclusions: Potential high and low risks for malaria at the village level can be differentiated from satellite data. While much remains to be done in terms of establishing correlations between remotely sensed risks and malaria disease patterns, this is a potentially useful approach which could lead to more focused disease control programmes.

Études utilisées

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Dambach, Peter, Ali Sié, Jean-Pierre Lacaux, Cécile Vignolles, Vanessa Machault, and Rainer Sauerborn. "Using high spatial resolution remote sensing for risk mapping of malaria occurrence in the Nouna district, Burkina Faso." Global Health Action 2, no. 1 (2009): 2094.
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