Insecticide resistance management in Burkina Faso and Côte d'Ivoire: research on vector control strategies

The fight against malaria faces now the challenge of the emergence and expansion of the resistance to both curative (drugs) and preventive (vector control) tools. Vector control which relies primarily on mass distribution of long lasting pyrethroid-treated nets contributes to the reduction of malaria transmission. The resistance of Anopheles vectors to pyrethroids, the only insecticide class recommended to treat bed nets, is threatening the considerable progresses made over the last decade. The REACT project aims to assess whether addition of complementary vector control strategies to long- lasting insecticidal mosquito nets provides additional protection against clinical malaria in areas with pyrethroid-resistant vectors in rural Burkina Faso and Ivory Coast. The tested strategies are 1) Indoor residual sprayings of insecticide; 2) intensive communication for human behavioural changes; 3) larviciding with natural toxins of Bacillus thurengiensis israelensis; 4) Use of Ivermectin both in human and cattle.
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Ground-truth georeferenced dataset used for training and test in the classification
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Layer style to open the LULC raster in QGIS
JPEG Image - 3.0 MB - MD5: 5143281d0b40a33ab73de7e0a813368d
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Map as a .jpeg image (for visualization purposes only)
Adobe PDF - 287.9 KB - MD5: cea541cd8a4c10bddb5dd2221f56ea29
Documentation
Detailed methodology used to generate the data, with the resulting confusion matrix (in english)
Adobe PDF - 284.1 KB - MD5: 53a0b031be6a8f6ebc9c0f297822dbe1
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Detailed methodology used to generate the data, with the resulting confusion matrix (in french)
Adobe PDF - 2.5 MB - MD5: 53ae10019bf192228abbe94096f84d63
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Representative pictures of the land cover classes
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Raster attribute table, including definitions of the land cover classes in english and french (data dictionary) (pdf format)
R Source Code - 107.2 KB - MD5: 7832daf447042a67961ab075cb06de6f
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R script used to create the product, using an Object Based Image Analysis approach
Tabular Data - 2.2 KB - 5 Variables, 49 Observations - UNF:6:LnVV3AfYCGr7lVjLojotCQ==
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