John DeGroote

Landscape, demographic, entomological, and climatic associations with human disease incidence of West Nile virus in the state of Iowa, USA

BackgroundWest Nile virus (WNV) emerged as a threat to public and veterinary health in the Midwest United States in 2001 and continues to cause significant morbidity and mortality annually. To investigate biotic and abiotic factors associated with disease incidence, cases of reported human disease caused by West Nile virus (WNV) in the state of Iowa were aggregated by census block groups in Iowa for the years 2002–2006. Spatially explicit data on landscape, demographic, and climatic conditions were collated and analyzed by census block groups. Statistical tests of differences between means and distributions of landscape, demographic, and climatic variables for census block groups with and without WNV disease incidence were carried out. Entomological data from Iowa were considered at the state level to add context to the potential ecological events taking place.ResultsNumerous statistically significant differences were shown in the means and distributions of various landscape and demographic variables for census block groups with and without WNV disease incidence. Census block groups with WNV disease incidence had significantly lower population densities than those without. Landscape variables showing differences included stream density, road density, land cover compositions, presence of irrigation, and presence of animal feeding operations. Statistically significant differences in the annual means of precipitations, dew point, and minimum temperature for both the year of WNV disease incidence and the prior year, were detected in at least one year of the analysis for each parameter. However, the differences were not consistent between years.ConclusionThe analysis of human WNV disease incidence by census block groups in Iowa demonstrated unique landscape, demographic, and climatic associations. Our results indicate that multiple ecological WNV transmission dynamics are most likely taking place in Iowa. In 2003 and 2006, drier conditions were associated with WNV disease incidence. In a significant novel finding, rural agricultural settings were shown to be strongly associated with human WNV disease incidence in Iowa.

Spatial Decision Support Systems: Principles and Practices

Although interest in Spatial Decision Support Systems (SDSS) continues to grow rapidly in a wide range of disciplines, students, planners, managers, and the research community have lacked a book that covers the fundamentals of SDSS along with the advanced design concepts required for building SDSS. Filling this need, Spatial Decision Support Systems: Principles and Practices provides a comprehensive examination of the various aspects of SDSS evolution, components, architecture, and implementation. It integrates research from a variety of disciplines, including the geosciences, to supply a complete overview of SDSS technologies and their application from an interdisciplinary perspective. This groundbreaking reference provides thorough coverage of the roots of SDSS. It explains the core principles of SDSS, how to use them in various decision making contexts, and how to design and develop them using readily available enabling technologies and commercial tools. The book consists of four major parts, each addressing different topic areas in SDSS: Presents an introduction to SDSS and the evolution of SDSS Covers the essential and optional components of SDSS Focuses on the design and implementation of SDSS Reviews SDSS applications from various domains and disciplinesinvestigating current challenges and future directions The text includes numerous detailed case studies, example applications, and methods for tailoring SDSS to your work environment. It also integrates sample code segments throughout. Addressing the technical and organizational challenges that affect the success or failure of SDSS, the book concludes by considering future directions of this rapidly emerging field of study.

Spatio-temporal cluster analysis of county-based human West Nile virus incidence in the continental United States

BackgroundWest Nile virus (WNV) is a vector-borne illness that can severely affect human health. After introduction on the East Coast in 1999, the virus quickly spread and became established across the continental United States. However, there have been significant variations in levels of human WNV incidence spatially and temporally. In order to quantify these variations, we used Kulldorffs spatial scan statistic and Anselins Local Morans I statistic to uncover spatial clustering of human WNV incidence at the county level in the continental United States from 2002–2008. These two methods were applied with varying analysis thresholds in order to evaluate sensitivity of clusters identified.ResultsThe spatial scan and Local Morans I statistics revealed several consistent, important clusters or hot-spots with significant year-to-year variation. In 2002, before the pathogen had spread throughout the country, there were significant regional clusters in the upper Midwest and in Louisiana and Mississippi. The largest and most consistent area of clustering throughout the study period was in the Northern Great Plains region including large portions of Nebraska, South Dakota, and North Dakota, and significant sections of Colorado, Wyoming, and Montana. In 2006, a very strong cluster centered in southwest Idaho was prominent. Both the spatial scan statistic and the Local Morans I statistic were sensitive to the choice of input parameters.ConclusionSignificant spatial clustering of human WNV incidence has been demonstrated in the continental United States from 2002–2008. The two techniques were not always consistent in the location and size of clusters identified. Although there was significant inter-annual variation, consistent areas of clustering, with the most persistent and evident being in the Northern Great Plains, were demonstrated. Given the wide variety of mosquito species responsible and the environmental conditions they require, further spatio-temporal clustering analyses on a regional level is warranted.

Spatiotemporal Investigation of Adult Mosquito (Diptera: Culicidae) Populations in an Eastern Iowa County, USA

Abstract Landscape and climatic factors regulate distributions of mosquitoes (Diptera: Culicidae) over time and space. The anthropogenic control of mosquito populations is often carried out at a local administrative scale, and it is applied based on the relevant agency’s experiential knowledge rather than systematic analysis of spatial and temporal data. To address this shortcoming, a spatial and temporal analysis of landscape and climatic parameters in relation to mosquito populations in Black Hawk County, IA, USA, has been carried out. Adult mosquito sampling took place using CDC light traps from May to August 2003 in representative landscapes. Mosquitoes were identified to species level with Aedes trivittatus (Coquillet) and Aedes vexans (Meigen) dominating the collection totals. The best publicly available spatial data on landscape and demographic attributes were collated and included land cover, human census, soils, floodplain, elevation, wetlands, hydrography, roads, and vegetation indices derived from satellite imagery. Spatial processing was carried out to organize landscape attributes for statistical comparison with abundance data from the potentially important West Nile virus (family Flaviviridae, genus Flavivirus, WNV) vector species Ae. vexans and Ae. trivittatus. Landscape parameters shown to be significantly correlated with mosquito counts included soil hydrological properties, presence in floodplain, wetland areas, and deciduous and bottomland forest cover. Data on temperature and precipitation were used to investigate the climatic influence on the temporal occurrence of mosquito population abundances. Late spring rain provided ample moisture for mosquito development, but low temperatures delayed widespread emergence of Ae. trivittatus and Ae. vexans until June 2003. Landscape and climatic impacts on adult mosquito population distributions were demonstrated, and these results could form the basis for the development of a spatiotemporal modeling framework that would inform anthropogenic mosquito control and vector-borne disease surveillance. A qualitative discussion concerning Culex pipiens (L.) and Culex restuans Theobald is included.

LiDAR data reduction using vertex decimation and processing with GPGPU and multicore CPU technology

Airborne light detection and ranging (LiDAR) topographic data provide highly accurate representations of the earths surface. However, large data volumes pose computing issues when disseminating and processing the data. The main goals of this paper are to evaluate a vertex decimation algorithm used to reduce the size of the LiDAR data and to test parallel computation frameworks, particularly multicore CPU and GPU, in processing the data. In this paper we use a vertex decimation technique to reduce the number of vertices available in a triangulated irregular network (TIN) representation of LiDAR data. In order to validate and verify the algorithm, the authors have used last returns only (LRO) and all returns (AR) of points from four tiles of LiDAR data taken from flat and undulating terrains. The results for flat terrain data showed decimation rates of roughly 95% for last returns only and 55% for all returns without significant loss of accuracy in terrain representation. Accordingly, file sizes were reduced by about 96.5% and 60.5%. The processing speed greatly benefited from parallel programming using the multicore CPU framework. The GPU usage demonstrated an additional impediment caused by noncomputational overhead. Nonetheless, tremendous acceleration was demonstrated by the GPU environment in the computational part alone.

National and Regional Associations Between Human West Nile Virus Incidence and Demographic, Landscape, and Land Use Conditions in the Coterminous United States

The incidence of human West Nile virus (WNV) varies spatially and temporally and is influenced by a wide range of biotic and abiotic factors. There are numerous important vector species, with variable geographic ranges and ecologies, considered crucial to the transmission of WNV in the coterminous United States. To date there has been a lack of a systematic investigation in the United States, at a regional scale, of the wide variety of landscape, land use, and demographic influences on WNV incidence. In this study, we use published vector species distribution maps, as well as prominent landscape features, to define six distinct regions of the coterminous United States. We relate data on demographic, landscape, and land use conditions to the incidence of human WNV by region recorded at county level in the coterminous United States from 2002-2009. The observed relationships varied by region with the Great Plains, Northwest, and Southwest regions showing high WNV incidence associated with rural irrigated landscapes, indicating the importance of Culex tarsalis as the primary vector. In the Southeast, the percent of the population in poverty was positively associated with high WNV incidence, potentially indicating the quality of housing in relation to the vector Culex quinquefasciatus, a mosquito that often feeds indoors. The Northeast region human WNV incidence was positively associated with agricultural landscapes, potentially implying the importance of Culex restuans in a region generally thought of as being dominated by Culex pipiens transmission. There was strong spatial autocorrelation in most of the regions, but with a spatial autologistic term accounted for in binary logistic regression models, there were significant landscape, land use, and demographic covariates for each region.

Development and Application of a Spreadsheet-Based Spatial Decision Support System SDSS

Spatial decision support systems SDSS are decision support tools which have been used widely in addressing complicated issues involving a spatial component. The use of SDSS has increased greatly over the last few decades especially in fields such as planning, natural resources management, and environmental science. Traditionally, SDSS have been developed with Geographic Information Systems GIS technology as a major component and used in application areas in which the use of GIS technology has been common. GIS software is often expensive and requires significant expertise, which can lead to under-utilization of GIS-based SDSS. In this paper, we describe the development of a freely available SDSS extension developed for Microsoft Excel, a very commonly used spreadsheet application. The purpose of this SDSS is to expand potential SDSS use to a wider potential audience for research, management, and teaching purposes.

Evaluating forest harvesting to reduce its hydrologic impact with a spatial decision support system

Timber harvesting changes the condition of forest ecosystems, which are a major influence on the characteristics of headwater streams. Such characteristics include the quantity and timing of base flow and storm flow, concentrations of sediment and dissolved nutrients, water temperature, and the stability of the stream channels. This paper explores previous studies dealing with the relationship between timber harvesting and its hydrologic effects, especially long term water yield increase. The watershed disturbance threshold theory is raised and investigated in detail. The development and evaluation of a spatial decision support system, the Harvest Schedule Review System (HSRS), is then described. The HSRS will aid in the minimization of hydrological impacts of forest harvesting, along with its related, negative environmental influences. It provides a spatially and temporally explicit tool for users to analyze the hydrologic impact of forest harvest schedules.