Skip to content
Home
About Us
Resources
Profiles Metrics
Authors Directory
Institutions Directory
Top Authors
Top Institutions
Top Sponsors
AI Digest
Contact Us
Menu
Home
About Us
Resources
Profiles Metrics
Authors Directory
Institutions Directory
Top Authors
Top Institutions
Top Sponsors
AI Digest
Contact Us
Home
About Us
Resources
Profiles Metrics
Authors Directory
Institutions Directory
Top Authors
Top Institutions
Top Sponsors
AI Digest
Contact Us
Menu
Home
About Us
Resources
Profiles Metrics
Authors Directory
Institutions Directory
Top Authors
Top Institutions
Top Sponsors
AI Digest
Contact Us
Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
Using high spatial resolution remote sensing for risk mapping of malaria occurrence in the Nouna district, Burkina Faso
Global Health Action, Volume 2, No. 1, Article 2094, Year 2009
Notification
URL copied to clipboard!
Description
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. © 2009 Peter Dambach et al.
Authors & Co-Authors
Dambach, Peter
Germany, Heidelberg
Universität Heidelberg
Sié, Alie
Burkina Faso
Centre de Recherche en Santéde Nouna
Lacaux, Jean Pierre
France, Toulouse
Université Toulouse Iii - Paul Sabatier
France, Paris
Cnes Centre National D'etudes Spatiales
Vignolles, Cécile
France, Paris
Cnes Centre National D'etudes Spatiales
MacHault, Vanessa
France, Paris
Cnes Centre National D'etudes Spatiales
France, Marseille
Imtssa Institut de Médecine Tropicale du Service de Santé Des Armées
Sauerborn, Rainer S.
Germany, Heidelberg
Universität Heidelberg
Sweden, Umea
Umeå Universitet
Statistics
Citations: 54
Authors: 6
Affiliations: 6
Identifiers
Doi:
10.3402/gha.v2i0.2094
Research Areas
Environmental
Infectious Diseases
Study Locations
Burkina Faso
Participants Gender
Female