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An Exploratory Study of the Comprehension, Retention and Action of the Denton County Older Population in Regards to Disaster Preparedness Education

Description: The purpose of this exploratory study was to operationalize the responses from a sample of the community dwelling older population from Denton County, Texas on disaster preparedness education given by Denton County Health Department (DCHD) personnel. The goals and objectives were drawn from the Texas Public Health and Medical Emergency Management 5-Year Strategic Plan 2012-2016. It was hypothesized that after the disaster preparedness education was received, then comprehension, retention, and application of the information would increase and the goals set forth by the DCHD would be reached. Thirteen sites were used to educate the 224 participants between August 2011 and April 2012. The data were received using a pre-test survey before the training, a post-test immediately after the training, and a follow-up survey call approximately 30 days later. Using Cronbach's alpha, logistic regression and regression analysis through SAS, the data revealed that all DCHD goals were met by this training method and outcome which include the sample population increasing comprehension, retention, and action on the information learned.
Date: December 2012
Creator: Knight, Rebekah P.
Partner: UNT Libraries

Factors Affecting Household Disaster Preparedness: A Study of the Canadian Context

Description: This study addresses the issue of household disaster preparedness. This work contributes two elements to disaster research. The first contribution improve the knowledge of the factors that affect household disaster preparedness. The review of literature yielded three categories of variables that can jointly explain household disaster preparedness: household structure, demographics, and risk-perception factors. In this study 19 variables compose these factors. A second contribution constitutes a theoretical exploration of the concept of disaster preparedness. In this work, four different constructs of disaster preparedness were tested. These constructs include material preparedness, preparedness activities, a combined index, and a weighted and combined index. The study presents the logic and methodology of the index construction and validation. The data used in this study came from households in the Montreal Urban Community (MUC) in Canada. A random sample of 1,003 English- and French-speaking heads of households adequately represents the 1.8 million persons within the MUC. An independent survey firm conducted the interviews in 1996. Results show that the weighted combined household disaster preparedness index constitutes the best construct to represent the concepts under study. Study results also reveal that risk-perception variables (attitudinal factors) offered the strongest explanatory power. Household structure and demographic variables collectively explained less than 8% of the dependent variable. The model used in this study yielded a coefficient of determination of .320, explaining 32% of the variance in the household disaster preparedness level. Concluding this study, the discussion offers implications for both disaster managers and researchers. Researchers should add to their analysis the household perspective as a complement to the organizational one. Also, it is clear that many other conceptual issues must be explored in understanding and measuring disaster preparedness. Disaster managers should base their efforts on sound research rather than on misconceptions about social behavior. Such implications can contribute to ...
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Date: December 2000
Creator: Doré, Michel C
Partner: UNT Libraries

The Preparedness for Emergency Conditions of Public Schools in Texas

Description: A survey of Texas public schools was conducted to determine the state of their emergency preparedness programs with particular interest in hazard analysis, disaster experience, chain of command of responsibility, personnel training, and inter-agency cooperation. A model emergency management plan was proposed. A stratified random sample of all Texas public school districts was drawn from the twenty education service center regions and university interscholastic league district size classifications. Of the 275 districts sampled, 214 questionnaires were completed for a 78% return. The strong return justified a generalization to the entire population.
Date: August 1994
Creator: Warlick, James S.
Partner: UNT Libraries

A Framework for Analyzing and Optimizing Regional Bio-Emergency Response Plans

Description: The presence of naturally occurring and man-made public health threats necessitate the design and implementation of mitigation strategies, such that adequate response is provided in a timely manner. Since multiple variables, such as geographic properties, resource constraints, and government mandated time-frames must be accounted for, computational methods provide the necessary tools to develop contingency response plans while respecting underlying data and assumptions. A typical response scenario involves the placement of points of dispensing (PODs) in the affected geographic region to supply vaccines or medications to the general public. Computational tools aid in the analysis of such response plans, as well as in the strategic placement of PODs, such that feasible response scenarios can be developed. Due to the sensitivity of bio-emergency response plans, geographic information, such as POD locations, must be kept confidential. The generation of synthetic geographic regions allows for the development of emergency response plans on non-sensitive data, as well as for the study of the effects of single geographic parameters. Further, synthetic representations of geographic regions allow for results to be published and evaluated by the scientific community. This dissertation presents methodology for the analysis of bio-emergency response plans, methods for plan optimization, as well as methodology for the generation of synthetic geographic regions.
Date: December 2010
Creator: Schneider, Tamara
Partner: UNT Libraries

Computational Methods to Optimize High-Consequence Variants of the Vehicle Routing Problem for Relief Networks in Humanitarian Logistics

Description: Optimization of relief networks in humanitarian logistics often exemplifies the need for solutions that are feasible given a hard constraint on time. For instance, the distribution of medical countermeasures immediately following a biological disaster event must be completed within a short time-frame. When these supplies are not distributed within the maximum time allowed, the severity of the disaster is quickly exacerbated. Therefore emergency response plans that fail to facilitate the transportation of these supplies in the time allowed are simply not acceptable. As a result, all optimization solutions that fail to satisfy this criterion would be deemed infeasible. This creates a conflict with the priority optimization objective in most variants of the generic vehicle routing problem (VRP). Instead of efficiently maximizing usage of vehicle resources available to construct a feasible solution, these variants ordinarily prioritize the construction of a minimum cost set of vehicle routes. Research presented in this dissertation focuses on the design and analysis of efficient computational methods for optimizing high-consequence variants of the VRP for relief networks. The conflict between prioritizing the minimization of the number of vehicles required or the minimization of total travel time is demonstrated. The optimization of the time and capacity constraints in the context of minimizing the required vehicles are independently examined. An efficient meta-heuristic algorithm based on a continuous spatial partitioning scheme is presented for constructing a minimized set of vehicle routes in practical instances of the VRP that include critically high-cost penalties. Multiple optimization priority strategies that extend this algorithm are examined and compared in a large-scale bio-emergency case study. The algorithms designed from this research are implemented and integrated into an existing computational framework that is currently used by public health officials. These computational tools enhance an emergency response planner's ability to derive a set of vehicle routes specifically ...
Date: August 2018
Creator: Urbanovsky, Joshua C
Partner: UNT Libraries