Author(s): Prosper, B.L., Duker, A.A.
Published in: International Journal of Engineering Research & Technology
License: This work is licensed under a Creative Commons Attribution 4.0 International License.
Volume/Issue: Vol.1 - Issue 6 (August- 2012)
In this study, Poisson variograms were used determine the spatial dependency of the risk of malaria which was then used to create surface maps from 2004 to 2009. Bayesian geostatitical approach was used to correlate the relationship between the elevation and the disease risk. Geographic Information System (GIS) was used to create the risk surfaces and overlays in the study. Buffered distances of 500, 1000, 1500 and 2000 m were used to overlay the disease risk map with forest, rivers/streams to find out its effects with the disease prevalence. The risk map created in this study showed an average of 20% rise yearly from 2004 to 2009. The results in the semi-variogram analysis with an average range of 2000 m showed that the disease incidence was local and not global. Areas which were more than 2km away from the water source (rivers/streams) recorded relatively higher cases except for some few within 1km of the Offin and Oda rivers. There was a varied effect of elevation with the disease prevalence was and a general trend of high incidence of the disease between 1 to 3 km from the edge of the forest.
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