Ibulaimu Kakoma

The aim of this study was to determine if remotely sensed data and Digital Elevation Model (DEM) can test relationships between Culex quinquefasciatus and Anopheles gambiae s.l. larval habitats and environmental parameters within Internally Displaced People (IDP) campgrounds in Gulu, Uganda. A total of 65 georeferenced aquatic habitats in various IDP camps were studied to compare the larval abundance of Cx. quinquefasciatus and An. gambiae s.l. The aquatic habitat dataset were overlaid onto Land Use Land Cover (LULC) maps retrieved from Landsat imagery with 150 m × 150 m grid cells stratified by levels of drainage. The LULC change was estimated over a period of 14 years. Poisson regression analyses and Moran's I statistics were used to model relationships between larval abundance and environmental predictors. Individual larval habitat data were further evaluated in terms of their covariations with spatial autocorrelation by regressing them on candidate spatial filter eigenvectors. Multispectral QuickBird imagery classification and DEM-based GIS methods were generated to evaluate stream flow direction and accumulation for identification of immature Cx. quinquefasciatus and An. gambiae s.l. and abundance.

For remote identification of mosquito habitats the first step is often to construct a discrete tessellation of the region. In applications where complex geometries do not need to be represented such as urban habitats, regular orthogonal grids are constructed in GIS and overlaid on satellite images. However, rice land vector mosquito aquatic habitats are rarely uniform in space or character. An orthogonal grid overlaid on satellite data of rice-land areas may fail to capture physical or man-made structures, i.e paddies, canals, berms at these habitats. Unlike an orthogonal grid, digitizing each habitat converts a polygon into a grid cell, which may conform to rice-land habitat boundaries. This research illustrates the application of a random sampling methodology, comparing an orthogonal and a digitized grid for assessment of rice land habitats. A land cover map was generated in Erdas Imagine V8.7^® using QuickBird data acquired July 2005, for three villages within the Mwea Rice Scheme, Kenya. An orthogonal grid was overlaid on the images. In the digitized dataset, each habitat was traced in Arc Info 9.1^®. All habitats in each study site were stratified based on levels of rice stage The orthogonal grid did not identify any habitat while the digitized grid identified every habitat by strata and study site. An analysis of variance test indicated the relative abundance of An. arabiensis at the three study sites to be significantly higher during the post-transplanting stage of the rice cycle. Regions of higher Anopheles abundance, based on digitized grid cell information probably reflect underlying differences in abundance of mosquito habitats in a rice land environment, which is where limited control resources could be concentrated to reduce vector abundance.

Vertical transmission of Brucella abortus in Sprague-Dawley (SD) rats was verified with microbiologic, serologic, and polymerase chain reaction (PCR) methods. The 38 initially Brucella-free SD rats, weighing 200 to 250 g, were injected subcutaneously with 50 microL of a suspension containing 1 x 10(9) colony-forming units (cfu) of B. abortus biotype 1 Korean isolate. The rats were allowed to mate with uninfected SD rats. The isolate was detected by culture and by AMOS (abortus, melitensis, ovis, suis) PCR in testis tissue of infected male rats and splenic tissue of infected female rats. By 7 d after inoculation, the results of both the rose bengal test (RBT) and the plate agglutination test (PAT) were positive for antibody against B. abortus; the reciprocal antibody titre ranged from 200 to 400 in the 1-mo-old offspring and 800 in their dams. The infected rats directly transmitted Brucella to their breeding partners and offspring. Fetuses of infected dams were found to be infected at 20 d of gestation. These data are discussed in relation to a model for epizootic and zoonotic cases possibly involving wild animals. Additional rigorous experiments are warranted to explore the value of this model in developing measures to prevent congenital brucellosis.