Landscape, demographic and climatic associations with human West Nile virus occurrence regionally in 2012 in the United States of America.

After several years of low West Nile virus (WNV) occurrence in the United States of America (USA), 2012 witnessed large outbreaks in several parts of the country. In order to understand the outbreak dynamics, spatial clustering and landscape, demographic and climatic associations with WNV occurrence were investigated at a regional level in the USA. Previous research has demonstrated that there are a handful of prominent WNV mosquito vectors with varying ecological requirements responsible for WNV transmission in the USA. Published range maps of these important vectors were georeferenced and used to define eight functional ecological regions in the coterminous USA. The number of human WNV cases and human populations by county were attained in order to calculate a WNV rate for each county in 2012. Additionally, a binary value (high/low) was calculated for each county based on whether the county WNV rate was above or below the rate for the region it fell in. Global Moran's I and Anselin Local Moran's I statistics of spatial association were used per region to examine and visualize clustering of the WNV rate and the high/low rating. Spatial data on landscape, demographic and climatic variables were compiled and derived from a variety of sources and then investigated in relation to human WNV using both Spearman rho correlation coefficients and Poisson regression models. Findings demonstrated significant spatial clustering of WNV and substantial inter-regional differences in relationships between WNV occurrence and landscape, demographic and climatically related variables. The regional associations were consistent with the ecologies of the dominant vectors for those regions. The large outbreak in the Southeast region was preceded by higher than normal winter and spring precipitation followed by dry and hot conditions in the summer.

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.

Ecological niche modeling of potential West Nile virus vector mosquito species in Iowa.

Ecological niche modeling (ENM) algorithms, Maximum Entropy Species Distribution Modeling (Maxent) and Genetic Algorithm for Rule-set Prediction (GARP), were used to develop models in Iowa for three species of mosquito - two significant, extant West Nile virus (WNV) vectors (Culex pipiens L and Culex tarsalis Coquillett (Diptera: Culicidae)), and the nuisance mosquito, Aedes vexans Meigen (Diptera: Culicidae), a potential WNV bridge vector. Occurrence data for the three mosquito species from a state-wide arbovirus surveillance program were used in combination with climatic and landscape layers. Maxent successfully created more appropriate niche models with greater accuracy than GARP. The three Maxent species' models were combined and the average values were statistically compared to human WNV incidence at the census block group level. The results showed that the Maxent-modeled species' niches averaged together were a useful indicator of WNV human incidence in the state of Iowa. This simple method for creating probability distribution maps proved useful for understanding WNV dynamics and could be applied to the study of other vector-borne diseases.

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

BACKGROUND: West 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 Kulldorff's spatial scan statistic and Anselin's Local Moran's 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. RESULTS: The spatial scan and Local Moran's 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 Moran's I statistic were sensitive to the choice of input parameters. CONCLUSION: Significant 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.

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

BACKGROUND: West 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. RESULTS: Numerous 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. CONCLUSION: The 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.

Surface Temperature Mapping of the University of Northern Iowa Campus Using High Resolution Thermal Infrared Aerial Imageries.

The goal of this project was to map the surface temperature of the University of Northern Iowa campus using high-resolution thermal infrared aerial imageries. A thermal camera with a spectral bandwidth of 3.0-5.0 µm was flown at the average altitude of 600 m, achieving ground resolution of 29 cm. Ground control data was used to construct the pixelto-temperature conversion model, which was later used to produce temperature maps of the entire campus and also for validation of the model. The temperature map then was used to assess the building rooftop conditions and steam line faults in the study area. Assessment of the temperature map revealed a number of building structures that may be subject to insulation improvement due to their high surface temperatures leaks. Several hot spots were also identified on the campus for steam pipelines faults. High-resolution thermal infrared imagery proved highly effective tool for precise heat anomaly detection on the campus, and it can be used by university facility services for effective future maintenance of buildings and grounds.

Seasonal Effect on Tree Species Classification in an Urban Environment Using Hyperspectral Data, LiDAR, and an Object- Oriented Approach.

The objective of the current study was to analyze the seasonal effect on differentiating tree species in an urban environment using multi-temporal hyperspectral data, Light Detection And Ranging (LiDAR) data, and a tree species database collected from the field. Two Airborne Imaging Spectrometer for Applications (AISA) hyperspectral images were collected, covering the Summer and Fall seasons. In order to make both datasets spatially and spectrally compatible, several preprocessing steps, including band reduction and a spatial degradation, were performed. An object-oriented classification was performed on both images using training data collected randomly from the tree species database. The seven dominant tree species (Gleditsia triacanthos, Acer saccharum, Tilia Americana, Quercus palustris, Pinus strobus and Picea glauca) were used in the classification. The results from this analysis did not show any major difference in overall accuracy between the two seasons. Overall accuracy was approximately 57% for the Summer dataset and 56% for the Fall dataset. However, the Fall dataset provided more consistent results for all tree species while the Summer dataset had a few higher individual class accuracies. Further, adding LiDAR into the classification improved the results by 19% for both fall and summer. This is mainly due to the removal of shadow effect and the addition of elevation data to separate low and high vegetation.

Spatiotemporal investigation of adult mosquito (Diptera: Culicidae) populations in an eastern Iowa county, USA.

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 anld vector-borne disease surveillance. A qualitative discussion concerning Culex pipiens (L.) and Culex restuans Theobald is included.