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This study uses geographic information systems to determine if the aggregation of census block data are better than census block group data for analyzing social vulnerability. This was done by applying a social vulnerability method that used census block group data for a countywide analysis and converting it to use census blocks for a countywide analysis and a municipal-wide analysis to determine which level of aggregation provided a more precise representation of social vulnerability. In addition to calculating the social vulnerability, the results were overlaid with an evacuation zone for the threat of a train derailment, determining which aggregation better depicted at-risk populations. The results of the study showed that the census blocks enable a more exact measurement of social vulnerability because they are better at capturing small pockets of high-risk areas. This study concludes that census block are more advantageous than census block groups because they are more sensitive and geographically exact in measuring social vulnerability, allow for a better interpretation of social vulnerability for smaller areas, and show spatial patterns of vulnerability at a finer spatial scale.

Between 1850 and 1922, agriculturalists built 1,700 kilometers of levees to convert 250,000 hectares of tidal marsh to farmland where the San Joaquin and Sacramento Rivers enter the San Francisco Bay (the Delta). Drained, farmed and isolated from the water channels, the organic soils behind the levees subsided to elevations as low as 8 meters below sea level, turning "levees" into "dams" that hold back water constantly. Engineers built water transfer projects in the mid-20th century, transferring water from the south Delta to 25 million Californians who now rely on the "dams" accidentally converted into supply channels. In 1972, however, a levee failure caused a salt-water intrusion into the Delta, raising the prominence of the polemic Peripheral Canal which, if built would replace the levees in the trans-Delta water transport role. Levee failures in 2004 (the Delta) and 2005 (New Orleans) have re-ignited the debate, fueled by comments made by public officials who warned that the Delta levees posed more risk of failure than did the pre-Katina Louisiana levees. This background motivates two research questions: What are the social perspectives regarding levee failures of the experts managing the Delta; and what is the history of levee failures that might support their perspectives? The research employed Q-Method to identify and describe four social perspectives: Delta Sustainers, Abandon the Levees, Levee Pragmatists, and Multi-Purpose Levee Advocates. A critical element underlying differences among the perspectives revolved around the perceived history of failures of Delta levees. This dissertation employed semi-structured interviews, archival record searches, and historic map and aerial photograph comparisons to compile a history of 265 levee failures since 1868, many of which are referenced to location, segment, and levee type. In addition, the dissertation compiled a list of emergency repairs and successful flood-fights. The history of failures indicates that important levees of the Delta have performed significantly better than previously identified. Sharing these social perspectives and research results among the key actors addressing Delta issues may lead to improved consensus decisions.

The steep, mountainous terrain of southwestern Norway is prone to a high frequency of rockslides. It is known that many of these rockslides are triggered by meteorological conditions, yet there have been few studies dedicated to quantifying the link between rockslides and the runoff conditions and freeze/thaw processes that trigger failure. With recent climate research indicating that southwestern Norway will experience warmer temperatures and increased precipitation, it has become apparent that a better understanding of this link is required to help prepare for future events. Rockslides in Norway lead to road closures, property damage and fatalities every year, and one of the biggest challenges for Norwegian authorities is to react to rockslides as they happen and to reopen roads as soon as possible. This is especially true when several rockslides occur on the same day in multiple locations. As a result, authorities wish to implement a hazard mapping system that uses a weather forecast to predict when and where geohazards are likely to occur. To this end, this thesis is aimed at providing a rockslide forecast map that changes every day based on the weather forecast. By comparing a rockslide database to historic weather records, the work carried out for this thesis has indicated that extreme runoff during winter storms is responsible for triggering the majority of rockslides in the region. Using this knowledge as a basis, two potential hazard mapping systems are proposed, one based on trigger threshold exceedance and the other based on weights-of-evidence susceptibility mapping. Both of these methods operate by mapping areas experiencing extreme runoff conditions. Several runoff parameters were tested for possible inclusion, and it was found that 48-hr antecedent runoff, normalized by mean monthly precipitation had the best correlation with rockslide occurrence. Verification of these methods indicates that both approaches are successful in predicting days with extreme conditions, thereby alerting authorities that a high frequency of rockslides is likely. Due to the complex nature of rockslide triggering, it is not fully understood how climate change will affect future rockslide activity; however, this thesis attempts to answer these questions and to provide a basis for future studies. / Thesis (Master, Geological Sciences & Geological Engineering) -- Queen's University, 2010-01-28 08:12:43.316

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Background: Survival analysis is sometimes called time-to-event analysis. The Cox model is used widely in survival analysis, where the covariates act multiplicatively on unknown baseline hazards. However, the Cox model requires the proportionality assumption, which limits its applications. The additive hazards model has been used as an alternative to the Cox model, where the covariates act additively on unknown baseline hazards. Objectives and methods: In this thesis, performance of the Cox multiplicative hazards model and the additive hazards model have been demonstrated and applied to the transfer, lifting and repositioning (TLR) injury prevention study. The TLR injury prevention study was a retrospective, pre-post intervention study that utilized a non-randomized control group. There were 1,467 healthcare workers from six hospitals in Saskatchewan, Canada who were injured from January 1, 1999 to December 1, 2006. De-identified data sets were received from the Saskatoon Health Region and Regina Quappelle Health Region. Time to repeated TLR injury was considered as the outcome variable. The models goodness of fit was also assessed. Results: Of a total of 1,467 individuals, 149 (56.7%) in the control group and 114 (43.3%) in the intervention group had repeated injuries during the study period. Nurses and nursing aides had the highest repeated TLR injuries (84.8%) among occupations. Back, neck and shoulders were the most common body parts injured (74.9%). These covariates were significant in both Cox multiplicative and additive hazards models. The intervention group had 27% fewer repeated injuries than the control group in the multiplicative hazards model (HR= 0.63; 95% CI=0.48-0.82; p-value=0.0002). In the additive model, the hazard difference between the intervention and the control groups was 0.002. Conclusion: Both multiplicative and additive hazards models showed similar results, indicating that the TLR injury prevention intervention was effective in reducing repeated injuries. The additive hazards model is not widely used, but the coefficient of the covariates is easy to interpret in an additive manner. The additive hazards model should be considered when the proportionality assumption of the Cox model is doubtful.

Background: Survival analysis is sometimes called time-to-event analysis. The Cox model is used widely in survival analysis, where the covariates act multiplicatively on unknown baseline hazards. However, the Cox model requires the proportionality assumption, which limits its applications. The additive hazards model has been used as an alternative to the Cox model, where the covariates act additively on unknown baseline hazards. Objectives and methods: In this thesis, performance of the Cox multiplicative hazards model and the additive hazards model have been demonstrated and applied to the transfer, lifting and repositioning (TLR) injury prevention study. The TLR injury prevention study was a retrospective, pre-post intervention study that utilized a non-randomized control group. There were 1,467 healthcare workers from six hospitals in Saskatchewan, Canada who were injured from January 1, 1999 to December 1, 2006. De-identified data sets were received from the Saskatoon Health Region and Regina Quappelle Health Region. Time to repeated TLR injury was considered as the outcome variable. The models goodness of fit was also assessed. Results: Of a total of 1,467 individuals, 149 (56.7%) in the control group and 114 (43.3%) in the intervention group had repeated injuries during the study period. Nurses and nursing aides had the highest repeated TLR injuries (84.8%) among occupations. Back, neck and shoulders were the most common body parts injured (74.9%). These covariates were significant in both Cox multiplicative and additive hazards models. The intervention group had 27% fewer repeated injuries than the control group in the multiplicative hazards model (HR= 0.63; 95% CI=0.48-0.82; p-value=0.0002). In the additive model, the hazard difference between the intervention and the control groups was 0.002. Conclusion: Both multiplicative and additive hazards models showed similar results, indicating that the TLR injury prevention intervention was effective in reducing repeated injuries. The additive hazards model is not widely used, but the coefficient of the covariates is easy to interpret in an additive manner. The additive hazards model should be considered when the proportionality assumption of the Cox model is doubtful.

Source: Dissertation Abstracts International, Volume: 54-08, Section: B, page: 3941. Supervisor: Robert J. Hardy. Includes bibliographical references (leaves 109-114).