encephalitis in Florida

Background: Eastern Equine Encephalitis virus (EEEV) is an alphavirus with high pathogenicity in both humans and horses. Florida continues to have the highest occurrence of human cases in the USA, with four fatalities recorded in 2010. Unlike other states, Florida supports year-round EEEV transmission. This research uses GIS to examine spatial patterns of documented horse cases during 2005–2010 in order to understand the relationships between habitat and transmission intensity of EEEV in Florida. Methods: Cumulative incidence rates of EEE in horses were calculated for each county. Two cluster analyses were performed using density-based spatial clustering of applications with noise (DBSCAN). The first analysis was based on regional clustering while the second focused on local clustering. Ecological associations of EEEV were examined using compositional analysis and Euclidean distance analysis to determine if the proportion or proximity of certain habitats played a role in transmission. Results: The DBSCAN algorithm identified five distinct regional spatial clusters that contained 360 of the 438 horse cases. The local clustering resulted in 18 separate clusters containing 105 of the 438 cases. Both the compositional analysis and Euclidean distance analysis indicated that the top five habitats positively associated with horse cases were rural residential areas, crop and pastureland, upland hardwood forests, vegetated non-forested wetlands, an

Lesbian, Gay, Bisexual School Counselors: What Influences Their Decision-Making Regarding Coming Out at Work

The prospect of coming out in the workplace may generate considerable fear for lesbian, gay, or bisexual (LGB) individuals. This includes fears of job discrimination and loss of employment, and verbal and physical harassment. Surveys of heterosexuals found that a vast majority (approximately 79%) believed that job performance, not one‘s sexual orientation, should determine how an employee is judged. Even so, LGB individuals continue to experience discrimination. As in other workplaces, LGB educators may function in environments that are unsupportive and non-affirming, and as a result, they may find it difficult to manage their sexual identity at work. While there is some understanding of the coming out experiences of the LGB educator, only one research study specifically examined the experiences of LGB school counselors (Miller, 1998). In order to develop a greater understanding of the decision-making process regarding coming out at work for these important professionals, a qualitative study utilizing interviews with 12 LGB school counselors was completed. This study sought to explore the influence a specific event or experience may have had on the school counselor‘s decision whether to come out at work. The experiences reported by participants fell into two broad categories. Typically, these counselors described inhibiting experiences or facilitating experiences that influenced the disclosure of their LGB identity. Many of the findings in the study are in line with previous research of other educators while it is worth noting that fear is still the most significant concern among these participants despite reported changes in more affirming policies and laws in protection of LGB employees. More research is needed to further examine school counselors‘ decision-making regarding coming out at work and the potential impact, if any, on their role as leaders and advocates for students

Mapping Sex Offender Activity Spaces Relative to Crime Using Time-Geographic Methods

Activity spaces describe the physical area typically encountered by an individual person during his or her routine daily activities. Activity spaces encompass a person’s anchor points – locations that are frequented regularly, such as home, work, school, and recreational areas – and the travel paths that connect them. Activity spaces of criminals are routinely mapped in order to better understand the spatial patterns and processes of crime at the individual level. Although many geographic information system-based methods have been used to map activity spaces over the years, potential path areas are becoming a preferred method since they incorporate both spatial and temporal data, as well as time budget and mobility constraints. This paper extends potential path areas for mapping activity spaces of criminals in two ways. First, time-geographic density estimation (TGDE) is used to estimate individual activity spaces using potential path areas that have associated probability densities. Second, activity spaces of numerous individuals are combined into a single intensity surface that maps areas of a city that are more frequented by offenders and, accordingly, expected to support higher crime rates. The approach is demonstrated using a dataset of home and work addresses of registered sex offenders in the city of St. Louis. The final density surface of their combined activity spaces is related to the locations of reported sex crimes. The results highlight how sex crimes are concentrated in offender activity spaces and suggest the approach might be useful for predictive policing

Time-Geographic Density Estimation for Moving Point Objects

This research presents a time-geographic method of density estimation for moving point objects. The approach integrates traditional kernel density estimation (KDE) with techniques of time geography to generate a continuous intensity surface that characterises the spatial distribution of a moving object over a fixed time frame. This task is accomplished by computing density estimates as a function of a geo-ellipse generated for each consecutive pair of control points in the object’s space-time path and summing those values at each location in a manner similar to KDE. The main advantages of this approach are: (1) that positive intensities are only assigned to locations within a moving object’s potential path area and (2) that it avoids arbitrary parameter selection as the amount of smoothing is controlled by the object’s maximum potential velocity. The time-geographic density estimation technique is illustrated with a sample dataset, and a discussion of limitations and future work is provided

Calling: Earth #007 - Joni Downs Firat, Wildlife Ecologist

Joni Downs Firat, the Associate Chair of the USF School of Geosciences, discusses her research into wildlife ecology and her interest in supporting teaching and research for graduate and undergraduate students. More about Joni can be found here: http://hennarot.forest.usf.edu/main/depts/geosci/faculty/jdowns

Lesbian, Gay, Bisexual School Counselors: What Influences Their Decision-Making Regarding Coming Out At Work

Coming out in the education workplace creates a unique set of challenges for the Lesbian, Gay, or Bisexual (LGB) individual. Harbeck (1997) describes the struggle in public education with regard to homosexuality as one of the most publicly volatile and personally threatening debates in our national history (p.1 ). The principal mission of schools has traditionally been to pass on societal values to a younger generation and educators have been hired to serve as role models for such values as well as for their teaching competencies. Depending on the community environment related to issues of sexual orientation, if an educator were to publicly reveal her/his sexual orientation it may be considered deviating from the societal norms that the institution wants to reinforce. As a result, the educator\u27s choice to come out in the workplace is complicated by the fear of possible job loss, harassment, loss of credibility, and discriminatory practices ranging from subtle to overt (Griffin, 1992; Jennings, 2005; Woods & Harbeck, 1992)..

Footprint Generation using Fuzzy-Neighborhood Clustering

Geometric footprints, which delineate the region occupied by a spatial point pattern, serve a variety of functions in GIScience. This research explores the use of two density-based clustering algorithms for footprint generation. First, the Density-Based Spatial Clustering with Noise (DBSCAN) algorithm is used to classify points as core points, non-core points, or statistical noise; then a footprint is created from the core and non-core points in each cluster using convex hulls. Second, a Fuzzy-Neighborhood (FN)-DBSCAN algorithm, which incorporates fuzzy set theory, is used to assign points to clusters based on membership values. Then, two methods are presented for delineating footprints with FN-DBSCAN: (1) hull-based techniques and (2) contouring methods based on interpolated membership values. The latter approach offers increased flexibility for footprint generation, as it provides a continuous surface of membership values from which precise contours can be delineated. Then, a heuristic parameter selection method is described for FN-DBSCAN, and the approach is demonstrated in the context of wildlife home range estimation, where the goal is to a generate footprint of an animal’s movements from tracking data. Additionally, FN-DBSCAN is applied to produce crime footprints for a county in Florida. The results are used to guide a discussion of the relative merits of the new techniques. In summary, the fuzzy clustering approach offers a novel method of footprint generation that can be applied to characterize a variety of point patterns in GIScience

Integrating People and Place: a Density-Based Measure for Assessing Accessibility to Opportunities

Mobile object analysis is a well-studied area of transportation and geographic information science (GIScience). Mobile objects may include people, animals, or vehicles. Time geography remains a key theoretical framework for understanding mobile objects\u27 movement possibilities. Recent efforts have sought to develop probabilistic methods of time geography by exploring questions of data uncertainty, spatial representation, and other limitations of classical approaches. Along these lines, work has blended time geography and kernel density estimation in order to delineate the probable locations of mobile objects in both continuous and discrete network space. This suite of techniques is known as time geographic density estimation (TGDE). The present paper explores a new direction for TGDE, namely the creation of a density-based accessibility measure for assessing mobile objects\u27 potential for interacting with opportunity locations. As accessibility measures have also garnered widespread attention in the literature, the goal here is to understand the magnitude and nature of the opportunities a mobile object had access to, given known location points and a time budget for its movement. New accessibility measures are formulated and demonstrated with synthetic trip diary data. The implications of the new measures are discussed in the context of people-based vs. placed-based accessibility analyses

Integrating People and Place: a Density-Based Measure for Assessing Accessibility to Opportunities

Mobile object analysis is a well-studied area of transportation and geographic information science (GIScience). Mobile objects may include people, animals, or vehicles. Time geography remains a key theoretical framework for understanding mobile objects\u27 movement possibilities. Recent efforts have sought to develop probabilistic methods of time geography by exploring questions of data uncertainty, spatial representation, and other limitations of classical approaches. Along these lines, work has blended time geography and kernel density estimation in order to delineate the probable locations of mobile objects in both continuous and discrete network space. This suite of techniques is known as time geographic density estimation (TGDE). The present paper explores a new direction for TGDE, namely the creation of a density-based accessibility measure for assessing mobile objects\u27 potential for interacting with opportunity locations. As accessibility measures have also garnered widespread attention in the literature, the goal here is to understand the magnitude and nature of the opportunities a mobile object had access to, given known location points and a time budget for its movement. New accessibility measures are formulated and demonstrated with synthetic trip diary data. The implications of the new measures are discussed in the context of people-based vs. placed-based accessibility analyses