In Canada, as in many other affluent nations, private well water consumers remain at risk for gastrointestinal (GI) illness due to fecal contamination of groundwater. There have been numerous documented outbreaks of GI illness related to contaminated drinking water. While the general risk to well water consumers has been established, the risk in southern Ontario is poorly understood. As a preliminary step towards understanding this risk, a study of Escherichia coli (E. coli) contamination in private well water was undertaken. Spatial scan statistics were employed to determine the extent of contamination for over 30,000 private wells in southeastern Ontario between 2008 and 2012, inclusive. This analysis revealed one large, temporally stable elevated risk region, and three significant smaller regions within it. The methodology utilized in the primary investigation was then applied to a 2012 dataset for all of southern Ontario, resulting in the identification of three regions of elevated risk. The presence of E. coli, a traditional fecal indicator organism, indicates lack of water potability. To provide knowledge regarding the origins of fecal contamination in southeastern Ontario, a molecular microbial source tracking (MST) study was undertaken. A quantitative real-time Bacteroidales PCR assay specifically targeting human, bovine, and general (specific to 10 hosts) was optimized and applied to 716 private well water samples. Almost half of the samples showed evidence of human fecal contamination, whereas only 13% contained evidence of bovine fecal contamination. Approximately one quarter of well samples tested positive for the general host Bacteroidales assay, with an additional one quarter testing negative for all MST assays. Additionally, spatial scan statistics revealed a region of human-sourced contamination, which geographically corresponded with the E. coli contamination cluster for the same study year. The presence of E. coli contamination clusters among private wells reveals an at-risk group of well water consumers. As such, public health practitioners may use this information to target well stewardship programs in higher risk regions. Humans were the predominant contributors of fecal contamination to private wells within the primary study region. These findings may enable future preventative measures by providing insight into the true origins of groundwater fecal pollution. / Thesis (Master, Pathology & Molecular Medicine) -- Queen's University, 2014-06-02 14:50:16.685

Thesis (Ph.D.)--University of Texas at Dallas, 2007. / Includes vita. Includes bibliographical references (leaves 103-107)

Thesis (M.Sc.). / Written for the Dept. of Geography. Title from title page of PDF (viewed 2008/12/10). Includes bibliographical references.

Thesis (Ph.D.) -- University of Adelaide, School of Social Sciences, Discipline of Geographical and Environmental Studies, 2008. / "December 2007" Bibliography: leaves 247-253. Also available in print form.

abstract: Our dependence on fossil fuels is driving anthropogenic climate change. Solar energy is the most abundant and cleanest alternative to fossil fuels, but its practicability is influenced by a complex interplay of factors (policy, geospatial, and market) and scales (global, national, urban). This thesis provides a holistic evaluation of these factors and scales with the goal of improving our understanding of the mechanisms and challenges of transitioning to solar energy. This analysis used geospatial, demographic, policy, legislative record, environmental, and industry data, plus a series of semi-structured, in-person interviews. Methods included geostatistical calculation, statistical linear regression and multivariate modeling, and qualitative inductive analysis. The results reveal valuable insights at each scale, but moreover a gestalt model across the factors and scales draws out a larger pattern at play of the transmutational weighting and increasing complexity of interplay as the level of analysis cascades down through the three geographic scales. / Dissertation/Thesis / Doctoral Dissertation Sustainability 2017

Recent changes in Arctic Ocean climate dynamics and marine activity in the region require re-evaluation of physical operating conditions, ship traffic patterns, and policy requirements. This study used (1) government surveys, (2) vessel reports, and (3) Automatic Identification System (AIS) messages to characterize the spatial and temporal variability of surface vessel traffic in relation to various sea-ice conditions on the Arctic Ocean during a year-long study from 1 April 2010 to 31 March 2011. Data sources, methods of analysis, and errors were discussed. Three principal topics were examined. First, sea-ice cover on the Arctic Ocean was analysed to determine the physical access for marine operations. Daily sea-ice concentration data based on satellite passive microwave measurements were used to calculate the extent of open water and duration of the sea-ice season. Second, ship traffic on the Arctic Ocean was analysed to determine the present patterns of human activity. Time-stamped AIS messages encoded with Global Navigation Satellite System (GNSS) positions received by a commercial satellite constellation from north of the Arctic Circle (66·56°N) were used to calculate the distribution of vessels per unit area. Satellite AIS data from SpaceQuest, Limited, were compared with land-based vessel observations during the study period from the Marine Exchange of Alaska and the Port of Longyearbyen. Third, the spatial and temporal relationship between sea ice and surface vessels on the Arctic Ocean was analysed to determine potential policy implications. Three groups of marine operations with distinct characteristics were determined from the analysis: operations in perennial open water, operations in the seasonal ice zone, and operations in the perennial ice zone. Throughout the study year, most ships north of 66·56°N operated in perennially icefree areas, but year-round operations also occurred in ice-covered areas. The results from this study identify new pathways of information to enable consistent pan-Arctic assessment of physical operating conditions and ship traffic patterns. This approach provides novel considerations to sustainably develop a safe, secure, and environmentally protected Arctic Ocean.

Master of Regional and Community Planning / Department of Architecture / Brent C. Chamberlain / As urban development continues, it is imperative we understand how infrastructural policies impact well-being in order to design functional and healthy cities. The growth in wearable sensors and real-time data offer a way to assess the day-to-day influence of built infrastructure on health. The aim of this research is to determine if and how much characteristics of the built environment affect individual physiological responses. The purpose of this research is two-fold: 1) quantify and understand the linkages between form and function of the built environment on human affect and 2) identify practices for collecting and mining sensor data that can be used by planners. Subjects (n = 24) were sent on a walk through downtown Manhattan, Kansas. The route was carefully designated to expose individuals to different architectural and environmental features such as: vegetation, infrastructure (broadly), building height and area, land use, trees and street conditions. The study explores the associations of nearly a dozen environmental characteristics with the real-time feedback from sensor data. The sensors used in this study measure electrodermal activity (EDA) and heart rate (HR) which were linked spatially using GPS. The results enable a spatio-temporal analysis to identify correlations between environmental characteristics and spatial representations of urban form. Differences of stress-related responses are identified through statistical analysis. The data and spatial analyses were also used by colleagues to develop a machine learning approach to explore methods for estimating stress. In addition to quantifying urban form additional subject information was collected, such as demographic information, fitness level, sense of place, feeling of community, and feeling of exposure in the built environment. This work builds upon a previous study by Parker Ruskamp (MLA 2016). His qualitative results indicate that areas with lower lighting (at night) and higher-density infrastructure caused increased stress reactions. The efforts in this report, added additional participants and worked to spatially quantify urban form in order to conduct quantitative assessments to characterize the influence of environmental features against stress. Through the analysis it was discovered there is a relationship to biophysical measures and relationship to vegetation presence, building façades, building area or envelope, zoning and parking lots. In particular, the most influential characteristics were the amount of parking in close proximity to participants at night and the quality of the sidewalks during the day. While effects were discovered, further work should be done to confirm and generalize these findings. These initial results demonstrate how using biophysical measures can help planners evaluate the effectiveness of policies and built-environments toward improving the well-being of citizens. Further, this study provides a basis on how designs can be better informed by geospatial analysis, enhanced through an extensive environmental characteristic literature review, and statistical analysis to promote health and well-being through urban design.

6 pp. / Remotely sensed data are valuable for monitoring, assessing, and managing impacts to arid and semi-arid lands caused by drought or other changes in the natural environment. With this in mind, we collaborated with scientists and technologists to redevelop DroughtView, a web-based decision-support tool that combines satellite-derived measures of surface greenness with additional geospatial data so that users can visualize and evaluate vegetation dynamics across space and over time. To date, users of DroughtView have been local drought impact groups, ranchers, federal and state land management staff, environmental scientists, and plant geographers. Potential new applications may include helping to track wildland fire danger. Here, we present the functionality of DroughtView, including new capabilities to report drought impacts and share map information, as well as the data behind it.

The thesis addresses the problem of capturing and tracking multi-user interpretations of 3D spatial datasets. These interpretations are completed after the end of the visualization pipeline to identify and extract features of interest, and are subjective to human intuition and knowledge. Users may also assess regions of these interpretations. Consequently, the thesis proposes a provenance-enabled interpretation pipeline. It adopts and extends the W3C PROV data model, producing a provenance model for visual interpretations. This was implemented for seismic imaging interpretation in a proof-of-concept prototype architecture and application. Accumulation of users' interpretations and annotations are captured by the provenance model in a fine-grained form. The captured provenance information can be utilised to filter data. The work of this thesis was evaluated in three parts. First, a usability evaluation by geoscientists was conducted by postgraduate students in the field of geoscience to illustrate the system's ability in allowing users to amend others' interpretations and trace the history of amendments. Second, a conceptual evaluation of this research was approached by interviewing domain experts. The importance of this research to the industry was assured. Interviewees perceived and shared potential implementations of this work in the workflow of seismic interpretation. Limitations and concerns of the work were highlighted. Third, a performance evaluation was conducted to illustrate the behaviour of the architecture on commodity machines as well as on a multi-node parallel database, such that a new functionality in fine-grained provenance can be implemented simply but with an acceptable performance in realistic visualization tasks. The measures suggested that the current implementation achieved an acceptable performance in comparison to conventional methods. The proposed provenance model in an interpretation pipeline is believed to be a promising shift in methods of data management and storage which can record and preserve interpretations by users as a result of visualization. The approach and software development in this thesis represented a step in this direction.

Background: The incidence and prevalence of chronic disease (CD) has increased in recent decades due to the advent of CD management and life-extending technologies. To address this burden on the population and healthcare system, evidence-based CD prevention programs have been developed to reduce the incidence and therefore the prevalence of these diseases. Despite the development and dissemination of effective interventions, African-Americans and Hispanics have disproportionately higher prevalence of CD and associated risk factors and disproportionately lower participation in CD prevention programs. Overweight/obesity and CDs may have intergenerational effects, with overweight adults being more likely to have overweight children who are in turn more likely to become overweight adults with CDs. These dissertative projects sought to disrupt this intergenerational cycle of CD by exploring how to engage people of minority background in CD prevention programs, to determine the acceptability and feasibility of a CD prevention program adapted to social media, the preferred method of health education for women of childbearing age, and to identify areas in Florida that would benefit from a CD prevention program such as this. Methods: Four focus groups of residents of disadvantaged and medically underserved areas and nine key informant interviews with local business owners were conducted using a standardized questionnaire to asses health beliefs, barriers to healthy behaviors, and preferred methods of health communication among the target population. These data were thematically analyzed in Atlas.ti version 8.0. Results of this analysis informed the adaptation of an existing CD prevention program, the national Diabetes Prevention Program (nDPP), to a social media platform, Facebook, to address the needs of the community. The first four weeks of the nDPP were adapted to Facebook using Powtoon and Canva software, were assessed for fidelity by a certified nDPP Lifestyle Coach, and underwent an iterative editing process in collaboration with a community partner, REACHUP, Inc., to ensure cultural appropriateness. Height, weight, and waist circumference were measured pre- and post-intervention via a standardized protocol. Perceived stress, social support, depressive symptoms, and health-related quality of life were also assessed pre- and post-intervention. The final dissertative project utilized the Centers for Disease Control and Prevention and Robert Wood Johnson Foundation’s 500 Cities Data in conjunction with USDHHS locations of existing federally qualified health centers (FQHCs) to identify urban census tracts in Florida with high prevalence of CD and associated risk factors and inadequate access to FQHCs. Results: Overall, residents and business owners in medically underserved areas of west central Florida identified distrust of medical professionals and pharmaceuticals as a barrier to receiving health care. Lack of transportation and safe recreational areas, were barriers to participating in health behaviors, though participants were concerned about how to prevent and manage diabetes, heart disease, and cancer. The preferred identified method of health communication for women of childbearing was social media, with Facebook being the most used social medium. The nDPP was chosen for adaptation to Facebook because it addressed most of the concerns of the target community. This Facebook-based adaptation of the nDPP, called HealthyLIFE, had no statistically significant results, though there were encouraging reductions in depressive symptom, perceived stress, and health-related quality of life. Tampa, St. Petersburg, Lakeland, and Jacksonville were the urban areas of Florida with the greatest prevalence of CD and associated risk factors, with areas with low insurance, low physical activity, poor physical health, high levels of poverty, high concentration of people of minority background, and high prevalence of stroke and diabetes were statistically significantly more likely to be within 0.5 miles of an FQHC. Discussion: The results of this dissertation demonstrate the need for qualitative research to inform interventions to disrupt the etiology of chronic disease at the population level, particularly for people of minority background and low socioeconomic status who may experience greater barriers to participating in healthy behaviors and accessing preventive healthcare services. Integrating this type of data into the design and implementation of chronic disease prevention programs and targeting these programs to geographic areas with high prevalence of CD and associated risk factors can increase uptake by populations with historically low participation in these programs. With FQHCs serving less than 25% of urban census tracts with high prevalence of chronic disease and associated risk factors, there is a need for cost-efficient, effective, scalable, and accessible chronic disease prevention programs like HealthyLIFE to improve population health and reduce health disparities between racial and socioeconomic groups.