Hydrological modeling of geophysical parameters of arboviral and protozoan disease vectors in Internally Displaced People camps in Gulu, Uganda

Abstract

BackgroundThe 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.ResultsThe main LULC change in urban Gulu IDP camps was non-urban to urban, which included about 71.5 % of the land cover. The regression models indicate that counts of An. gambiae s.l. larvae were associated with shade while Cx. quinquefasciatus were associated with floating vegetation. Moran's I and the General G statistics for mosquito density by species and instars, identified significant clusters of high densities of Anopheles; larvae, however, Culex are not consistently clustered. A stepwise negative binomial regression decomposed the immature An. gambiae s.l. data into empirical orthogonal bases. The data suggest the presence of roughly 11% to 28 % redundant information in the larval count samples. The DEM suggest a positive correlation for Culex (0.24) while for Anopheles there was a negative correlation (-0.23) for a local model distance to stream.ConclusionThese data demonstrate that optical remote sensing; geostatistics and DEMs can be used to identify parameters associated with Culex and Anopheles aquatic habitats.

A Cartographic Analysis Using Spatial Filter Logistic Model Specifications for Implementing Mosquito Control in Kenya

“…People who settle in these densely populated peri-urban zones encounter communities already trying to overcome widespread poverty, as well as environmental degradation. These phenomena have resulted in overcrowding and increased densities of vectors due to excess land cover change (Jacob et al, 2003(Jacob et al, , 2006b(Jacob et al, , 2007(Jacob et al, , 2008d. Because the status and trends of land use and urbanization significantly impact vector mosquito habitat productivity, accurate, up-to-date, and spatiallyerror-free data of georeferenced spatiotemporal-sampled data are required to implement larval control strategies that target prolific habitats in SSA urban environments.…”

“…Densely packed housing in shantytowns and slums, inadequate drinking water supplies, excessive trash, and dysfunctional surface-water drainage systems in urban areas of Sub-Saharan Africa (SSA) have combined to create favorable habitats for the proliferation of vectors and reservoirs of communicable diseases Afrine et al, 2004;Mwangangi et al, 2007;Jacob et al, 2008d). As a consequence, vector-borne diseases such as malaria, lymphatic filariasis, and dengue fever are becoming major public health problems.…”

Quantifying stochastic error propagation in Bayesian parametric estimates using non-linear parameters of Anopheles gambiae s.l. habitats

“…gambiae s.l. aquatic habitats, in urban environments, can be influenced by vector control activities host density (Snow et al 1998, Mutero et al 2000, Jacob et al 2005, 2008c, proximity to larval habitats and blood-meal hosts (Washino and Tempelis 1983, Minakawa et al 2002, quality of the larval habitats (Lyimo and Takken 1993, Gimnig et al 2002, Okech et al 2007), availability of domestic animals , Mwangangi et al 2007, Sota and Mogi 2008 and inter-human variation in mosquito preferences, based on host odours and other cues Knols 1999, Muturi et al 2007a). Studies have also shown that transitions in land use land cover (LULC) in urban areas can create variations in geographical locations of An.…”

“…gambiae s.l. aquatic habitats and their larval productivity (Khambea et al 1994, Chinery 1995, Jacob et al 2003, 2008c, Diuk-Wasser et al 2007). If spatial autocorrelation patterns remain present in an An.…”

Adjusting Second Moment Bias in Eigenspace Using Bayesian Empirical Estimators, Dirichlet Tessellations and Worldview I Data for Predicting Culex quinquefasciatus Habitats in Trinidad

“…The four possibilities of stereo image processing for DEM generation are Fore-Aft, Fore-Nadir, Aft-Nadir and Fore-Aft-Nadir images as a pair [19]. The simultaneous acquisition of along-track stereo data has a strong advantage in terms of radiometric variation versus the multi-date acquisition of across-track stereo data which has been traditionally employed in past research for identifying terrain-related explanatory covariates of floodwater mosquito habitats [20]. The across-track approach has been applied frequently since 1980, first with Landsat from two adjacent orbits, then with SPOT using across-track steering capabilities and finally with IRS-I C/D.…”