Prevention and Treatment of Traumatic Brain Injury Due to Rapid-Onset Natural Disasters

The prevention and treatment of traumatic brain injury (TBI) attributable to rapid-onset natural disasters is a major challenge confronting disaster preparedness planners and emergency medical personnel responding to those incidents. The kinetic energy released by rapid-onset natural disasters such as earthquakes, hurricanes or typhoons, and tornadoes can cause mild, moderate or severe TBIs. As a result, neurotrauma is a major risk factor for mortality and morbidity outcomes within the spatial domain impacted by a rapid-onset natural disaster. This review article elucidates major challenges associated with immediate emergency medical response, long-term care, and prevention of post-event increases in pediatric TBIs because of child abuse when rapid-onset natural disasters occur

Economic Interest Group Allocations in Open-Seat Senate Elections

Most studies of political action committees (PACs) focus on the incumbent-oriented contribution strategies of PACs, whereas contributions to open-seat candidates remain relatively unexplored. Based on the assumption that open-seat candidates have an insatiable need for campaign money, we model the allocations of PACs to open-seat senate candidates from 1980 to 1994. The results of our analyses indicate that allocations in open-seat senate elections are more partisan than those in incumbent elections, although incumbent-like effects are evident in allocations by corporate, labor, and trade association PACs, which largely support aspirant House of Representatives members who have previously existing connections to monied interests. Unlike the bipartisan behavior exhibited by investor PACs in open house races, labor and investor interests reinforce the partisan divisions in senate contests by engaging in competitive funding of opposing candidates.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline

Linking field-based ecological data with remotely sensed data using a geographic information system in two malaria endemic urban areas of Kenya

BACKGROUND: Remote sensing technology provides detailed spectral and thermal images of the earth's surface from which surrogate ecological indicators of complex processes can be measured. METHODS: Remote sensing data were overlaid onto georeferenced entomological and human ecological data randomly sampled during April and May 2001 in the cities of Kisumu (population ≈ 320,000) and Malindi (population ≈ 81,000), Kenya. Grid cells of 270 meters × 270 meters were used to generate spatial sampling units for each city for the collection of entomological and human ecological field-based data. Multispectral Thermal Imager (MTI) satellite data in the visible spectrum at five meter resolution were acquired for Kisumu and Malindi during February and March 2001, respectively. The MTI data were fit and aggregated to the 270 meter × 270 meter grid cells used in field-based sampling using a geographic information system. The normalized difference vegetation index (NDVI) was calculated and scaled from MTI data for selected grid cells. Regression analysis was used to assess associations between NDVI values and entomological and human ecological variables at the grid cell level. RESULTS: Multivariate linear regression showed that as household density increased, mean grid cell NDVI decreased (global F-test = 9.81, df 3,72, P-value = <0.01; adjusted R(2 )= 0.26). Given household density, the number of potential anopheline larval habitats per grid cell also increased with increasing values of mean grid cell NDVI (global F-test = 14.29, df 3,36, P-value = <0.01; adjusted R(2 )= 0.51). CONCLUSIONS: NDVI values obtained from MTI data were successfully overlaid onto georeferenced entomological and human ecological data spatially sampled at a scale of 270 meters × 270 meters. Results demonstrate that NDVI at such a scale was sufficient to describe variations in entomological and human ecological parameters across both cities

Spatially targeting Culex quinquefasciatus aquatic habitats on modified land cover for implementing an Integrated Vector Management (IVM) program in three villages within the Mwea Rice Scheme, Kenya

BACKGROUND: Continuous land cover modification is an important part of spatial epidemiology because it can help identify environmental factors and Culex mosquitoes associated with arbovirus transmission and thus guide control intervention. The aim of this study was to determine whether remotely sensed data could be used to identify rice-related Culex quinquefasciatus breeding habitats in three rice-villages within the Mwea Rice Scheme, Kenya. We examined whether a land use land cover (LULC) classification based on two scenes, IKONOS at 4 m and Landsat Thematic Mapper at 30 m could be used to map different land uses and rice planted at different times (cohorts), and to infer which LULC change were correlated to high density Cx. quinquefasciatus aquatic habitats. We performed a maximum likelihood unsupervised classification in Erdas Imagine V8.7(® )and generated three land cover classifications, rice field, fallow and built environment. Differentially corrected global positioning systems (DGPS) ground coordinates of Cx. quinquefasciatus aquatic habitats were overlaid onto the LULC maps generated in ArcInfo 9.1(®). Grid cells were stratified by levels of irrigation (well-irrigated and poorly-irrigated) and varied according to size of the paddy. RESULTS: Total LULC change between 1988–2005 was 42.1 % in Kangichiri, 52.8 % in Kiuria and and 50.6 % Rurumi. The most frequent LULC changes was rice field to fallow and fallow to rice field. The proportion of aquatic habitats positive for Culex larvae in LULC change sites was 77.5% in Kangichiri, 72.9% in Kiuria and 73.7% in Rurumi. Poorly – irrigated grid cells displayed 63.3% of aquatic habitats among all LULC change sites. CONCLUSION: We demonstrate that optical remote sensing can identify rice cultivation LULC sites associated with high Culex oviposition. We argue that the regions of higher Culex abundance based on oviposition surveillance sites reflect underlying differences in abundance of larval habitats which is where limited control resources could be concentrated to reduce vector larval abundance

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

<p>Abstract</p> <p>Background</p> <p>The aim of this study was to determine if remotely sensed data and Digital Elevation Model (DEM) can test relationships between <it>Culex quinquefasciatus </it>and <it>Anopheles gambiae </it>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 <it>Cx. quinquefasciatus </it>and <it>An. gambiae </it>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 <it>I </it>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 <it>Cx. quinquefasciatus </it>and <it>An. gambiae </it>s.l. and abundance.</p> <p>Results</p> <p>The 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 <it>An. gambiae </it>s.l. larvae were associated with shade while <it>Cx. quinquefasciatus </it>were associated with floating vegetation. Moran's <it>I </it>and the General G statistics for mosquito density by species and instars, identified significant clusters of high densities of <it>Anopheles</it>; larvae, however, <it>Culex </it>are not consistently clustered. A stepwise negative binomial regression decomposed the immature <it>An. gambiae </it>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 <it>Culex </it>(0.24) while for <it>Anopheles </it>there was a negative correlation (-0.23) for a local model distance to stream.</p> <p>Conclusion</p> <p>These data demonstrate that optical remote sensing; geostatistics and DEMs can be used to identify parameters associated with <it>Culex </it>and <it>Anopheles </it>aquatic habitats.</p

Fiscal Year 1999

In making the transition from weapons production to environmental restoration, DOE has found that it needs to develop reliable means of defining and understanding health and environmental risks and of selecting cost-efficient environmental management technologies so that cleanup activities can be appropriately directed. Through the Technology and Risk Sciences Project, the Entergy Spatial Analysis Research Laboratory attempts to provide DOE with products that incorporate spatial analysis techniques in the risk assessment, communication, and management processes; design and evaluate methods for evaluating innovative environmental technologies; and collaborate and access technical information on risk assessment methodologies, including multimedia modeling and environmental technologies in Russia and the Ukraine, while in addition training and developing the skills of the next generation of scientists and environmental professionals