Author(s): GebreMichael T, Malone JB, Balkew M, Ali A, Berhe N,
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Abstract The distribution of two principal vectors of kala-azar in East Africa, Phlebotomus martini and Phlebotomus orientalis were analysed using geographic information system (GIS) based on (1) earth observing satellite sensor data: Normalized Difference Vegetation Index (NDVI) and midday Land Surface Temperature (LST) derived from advanced very high resolution radiometer (AVHRR) of the global land 1km project of United States Geological Survey (USGS), (2) agroclimatic data from the FAO Crop Production System Zone (CPSZ) of the Intergovernmental Authority on Development (IGAD) sub-region, and (3) the FAO 1998 soils digital map for the IGAD sub-region. The aim was to produce a predictive risk model for the two vectors. Data used for the analysis were based on presence and absence of the two species from previous survey collections in the region (mainly Ethiopia, Kenya and Somalia). Annual, wet season and dry season models were constructed. Although all models resulted in more than 85\% positive predictive values for both species, the best fit for the distribution of P. martini was the dry season composite (NDVI 0.07-0.38 and LST 22-33 degrees C) with a predictive value of 93.8\%, and the best fit for P. orientalis was the wet season composite (NDVI -0.01 to 0.34 and LST 23-34 degrees C) with a predictive value of 96.3\%. The two seasonal composites models derived from satellite data were largely similar with best fit models developed based on the CPSZ climate data: average altitude (12-1900m), average annual mean temperature (15-30 degrees C), annual rainfall (274-1212mm), average annual potential evapotranspiration (1264-1938mm) and readily available soil moisture (62-113mm) for P. martini; and average altitude (200-2200m), annual rainfall (180-1050mm), annual mean temperature (16-36 degrees C) and readily available soil moisture (67-108mm) for P. orientalis. Logistic regression analysis indicated LST dry season composite of the satellite data, average altitude, mean annual temperature and readily available soil moisture of the CPSZ data as the best ecological determinants for P. martini while LST annual composite was the only important ecological determinant for P. orientalis. Spearman's rank correlation revealed several factors to be important determinants for the distribution of the two vectors. None of the soil types analysed appeared to be important determinant for the two species in East Africa, unlike in Sudan where P. orientalis is mainly associated with eutric vertisol (black cotton clay soil).
This article was published in Acta Trop
and referenced in Journal of Remote Sensing & GIS