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Using remote sensing and geographic information systems to identify villages at high risk for rhodesiense sleeping sickness in Uganda

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Title Using remote sensing and geographic information systems to identify villages at high risk for rhodesiense sleeping sickness in Uganda
 
Creator Odiit, M.
Bessell, P.R.
Fèvre, Eric M.
Robinson, Timothy P.
Kinoti, J.
Coleman, P.G.
Welburn, S.C.
McDermott, John J.
Woolhouse, M.E.J.
 
Subject TRYPANOSOMA RHODESIENSE
TRYPANOSOMIASIS
GEOGRAPHICAL INFORMATION SYSTEMS
REMOTE SENSING
UGANDA
VILLAGES
 
Description Geographic information systems (GIS) and remote sensing were used to identify villages at high risk for sleeping sickness, as defined by reported incidence. Landsat Enhanced Thematic Mapper (ETM) satellite data were classified to obtain a map of land cover, and the Normalised Difference Vegetation Index (NDVI) and Landsat band 5 were derived as unclassified measures of vegetation density and soil moisture, respectively. GIS functions were used to determine the areas of land cover types and mean NDVI and band 5 values within 1.5 km radii of 389 villages where sleeping sickness incidence had been estimated. Analysis using backward binary logistic regression found proximity to swampland and low population density to be predictive of reported sleeping sickness presence, with distance to the sleeping sickness hospital as an important confounding variable. These findings demonstrate the potential of remote sensing and GIS to characterize village-level risk of sleeping sickness in endemic regions.
 
Date 2013-06-11T09:24:26Z
2013-06-11T09:24:26Z
2006
 
Type Journal Article
 
Identifier Transactions of the Royal Society of Tropical Medicine and Hygiene;100(4): 354-362
0035-9203
http://hdl.handle.net/10568/29673
 
Language en
 
Source Transactions of the Royal Society of Tropical Medicine and Hygiene