This dissertation addresses the development of optimization models for hospital evacuation logistics, as well as the analyses of various resource management strategies in terms of the equity of evacuation plans generated. We first formulate the evacuation transportation problem of a hospital as an integer programming model that minimizes the total evacuation risk consisting of the threat risk necessitating evacuation and the transportation risk experienced en route. Patients, categorized based on medical conditions and care requirements, are allocated to a limited fleet of vehicles with various medical capabilities and capacities to be transported to receiving beds, categorized much like patients, at the alternative facilities. We demonstrate structural properties of the underlying transportation network that enables the model to be used for both strategic planning and operational decision making. Next, we examine the resource management and equity issues that arise when multiple hospitals in a region are evacuated. The efficiency and equity of the allocation of resources, including a fleet of vehicles, receiving beds, and each hospital\'s loading capacity, determine the performance of the optimal evacuation plan. We develop an equity modeling framework, where we consider equity among evacuating hospitals and among patients. The range of equity of optimal solutions is investigated and properties of optimal and equitable solutions based on risk-based utility functions are analyzed. Finally, we study the integration of the transportation problem with the preceding hospital building evacuation. Since, in practice, the transportation plan depends on the pace of building evacuation, we develop a model that would generate the transportation plan subject to the output of hospital building evacuation. The optimal evacuation plans are analyzed with respect to resource utilization and patient prioritization schemes. Parametric analysis of the resource constraints is provided along with managerial insights into the assessment of evacuation requirements and resource allocation. In order to demonstrate the performance of the proposed models, computational results are provided using case studies with real data obtained from the second largest hospital in Virginia. / Ph. D.

Master of Landscape Architecture / Department of Landscape Architecture/Regional and Community Planning / Howard Hahn / Evolving needs for universities, municipalities, and corporations demand more sustainable and efficient techniques for data management. Geographic Information Systems (GIS) enables decision makers to spatially analyze the built environment to better understand facility usage by running test scenarios to evaluate current efficiencies and identify opportunities for investment. This can only be conducted when data is organized and leveraged across many departments in a collaborative environment. Data organization through GIS encourages interdepartmental collaboration uniting all efforts on a common front. An organized system facilitates a working relationship between the university and the community of Manhattan increasing efficiency, developing sustainable practices, and enhancing the health and safety of Kansas State University and larger community. Efficiency is increased through automation of many current practices such as work requests and routine maintenance. Sustainable practices will be developed by generating self-guided campus tours and identifying area appropriate for bioswales. Lastly, safety will be enhanced throughout campus by increasing emergency response access, determining areas within buildings difficult to reach in emergency situations, and identifying unsafe areas on campus. Evolving needs for universities, municipalities, and corporations demand more sustainable and efficient techniques for data management. Geographic Information Systems (GIS) enables decision makers to spatially analyze the built environment to better understand facility usage by running test scenarios to evaluate current efficiencies and identify opportunities for investment. This can only be conducted when data is organized and leveraged across many departments in a collaborative environment. Data organization through GIS encourages interdepartmental collaboration uniting all efforts on a common front. An organized system facilitates a working relationship between the university and the community of Manhattan increasing efficiency, developing sustainable practices, and enhancing the health and safety of Kansas State University and larger community. Efficiency is increased through automation of many current practices such as work requests and routine maintenance. Sustainable practices will be developed by generating self-guided campus tours and identifying area appropriate for bioswales. Lastly, safety will be enhanced throughout campus by increasing emergency response access, determining areas within buildings difficult to reach in emergency situations, and identifying unsafe areas on campus. Optimizing data management for Kansas State University was conducted in three phases. First, a baseline assessment for facility management at Kansas State University was conducted through discussions with campus departments. Second, case study interviews and research was conducted with leaders in GIS management. Third, practices for geospatial data management were adapted and implemented for Kansas State University: the building of a centralized database, constructing a 3-dimensional routing network, and modeling a virtual campus in 3D.

In the decades following World War II, the Louisiana National Guard evolved due to world, national, and local events. In response to the United States’ Cold War policies to contain Communism, the Guard expanded, professionalized, and was occasionally called to federal service. In conjunction with Cold War fears of external attack and internal subversion, a civil defense mission brought coordination between federal, state and local response agencies. Despite the lack of large scale war service or an attack on the U.S. homeland , the skills and responsibilities acquired by the Louisiana Guard during this time period resulted in an enhanced ability to respond to Louisiana’s biggest practical threat, i.e. natural disasters.

Comprehensive emergency management and response is crucial for disaster prevention and health emergencies. However, in African countries with an abundance of natural disasters and a rising surge in cardiovascular and obstetric emergencies, little research exists on emergency response. This study examines the fire emergency response in Kumasi Metropolitan Assembly (KMA), Ghana's second largest city. We use Geographic Information Systems (GIS) tools including location -allocation modeling to evaluate the existing system of fire facilities, identify gaps in service, and suggest locations for new fire stations to maximize population coverage. Our results show that fire stations within KMA are poorly distributed and large portions of the metropolis are underserved, a situation that is partly responsible for the huge losses of lives and property during fire outbreaks.

Sunken oil is difficult to locate because remote sensing techniques cannot as yet provide views of sunken oil over large areas. Moreover, the oil may re-suspend and sink with changes in salinity, sediment load, and temperature, making deterministic fate models difficult to deploy and calibrate when even the presence of sunken oil is difficult to assess. For these reasons, together with the expense of field data collection, there is a need for a statistical technique integrating limited data collection with stochastic transport modeling. Predictive Bayesian modeling techniques have been developed and demonstrated for exploiting limited information for decision support in many other applications. These techniques brought to a multi-modal Lagrangian modeling framework, representing a near-real time approach to locating and tracking sunken oil driven by intrinsic physical properties of field data collected following a spill after oil has begun collecting on a relatively flat bay bottom. Methods include (1) development of the conceptual predictive Bayesian model and multi-modal Gaussian computational approach based on theory and literature review; (2) development of an object-oriented programming and combinatorial structure capable of managing data, integration and computation over an uncertain and highly dimensional parameter space; (3) creating a new bi-dimensional approach of the method of images to account for curved shoreline boundaries; (4) confirmation of model capability for locating sunken oil patches using available (partial) real field data and capability for temporal projections near curved boundaries using simulated field data; and (5) development of a stand-alone open-source computer application with graphical user interface capable of calibrating instantaneous oil spill scenarios, obtaining sets maps of relative probability profiles at different prediction times and user-selected geographic areas and resolution, and capable of performing post-processing tasks proper of a basic GIS-like software. The result is a predictive Bayesian multi-modal Gaussian model, SOSim (Sunken Oil Simulator) Version 1.0rc1, operational for use with limited, randomly-sampled, available subjective and numeric data on sunken oil concentrations and locations in relatively flat-bottomed bays. The SOSim model represents a new approach, coupling a Lagrangian modeling technique with predictive Bayesian capability for computing unconditional probabilities of mass as a function of space and time. The approach addresses the current need to rapidly deploy modeling capability without readily accessible information on ocean bottom currents. Contributions include (1) the development of the apparently first pollutant transport model for computing unconditional relative probabilities of pollutant location as a function of time based on limited available field data alone; (2) development of a numerical method of computing concentration profiles subject to curved, continuous or discontinuous boundary conditions; (3) development combinatorial algorithms to compute unconditional multimodal Gaussian probabilities not amenable to analytical or Markov-Chain Monte Carlo integration due to high dimensionality; and (4) the development of software modules, including a core module containing the developed Bayesian functions, a wrapping graphical user interface, a processing and operating interface, and the necessary programming components that lead to an open-source, stand-alone, executable computer application (SOSim - Sunken Oil Simulator). Extensions and refinements are recommended, including the addition of capability for accepting available information on bathymetry and maybe bottom currents as Bayesian prior information, the creation of capability of modeling continuous oil releases, and the extension to tracking of suspended oil (3-D).

Disasters (e.g. earthquakes) and emergencies (e.g. fire) threaten the safety of occupants in the buildings and cause injuries and mortalities. These harmful effects are even more dangerous when secondary hazards (e.g. post-earthquake fires) emerge and it is commonly observed that the disasters/emergencies trigger secondary hazards.An effective indoor emergency guidance and navigation approach for occupants and first responders can decrease the number of injuries and mortalities during building emergencies by improving the evacuation process and response operations. For this reason, this research will propose a model-based guidance and vulnerability assessment approach for facilities that are under the threat of multi-hazard emergencies. The approach can be used to guide occupants from the facility affected by disasters/emergencies to safer zones and to direct the first responders by supplying them necessary building related information such as identified vulnerable locations in the indoor environments. An integrated utilization of Building Information Modeling tools, sensors, shortest path algorithms, and vulnerability assessment algorithms is proposed for the system in this research. The research steps of this thesis include (1) determination of requirements of an indoor navigation during emergency response and disaster management,(2) review, comparison, and evaluation of shortest path algorithms from an emergency response and disaster management point of view, (3) proposing a vulnerability assessment approach, and (4) proposing a real-time indoor emergency guidance and navigation system framework for buildings under the threat of multi-hazard emergencies. The findings of the research can be used in future studies on emergency response and disaster management domains.

Exemplified by fire crews, SWAT teams, and emergency surgical units, critical teams are a subset of action teams whose work is marked by finality, pressure, and potentially fatal outcomes (Ishak & Ballard, 2012). Using communicative and temporal lenses, this study investigates how organizations prime and prepare their embedded critical teams to deal with improvisation. This study explicates how organizations both encourage and discourage improvisation for their embedded critical teams. Throughout the training process, organizations implement a structured yet flexible “roadmap”-type approach to critical team work, an approach that is encapsulated through three training goals. The first goal is to make events routine to members. The second goal is to help members deal with non-routine events. The third goal is to help members understand how to differentiate between what is routine and non-routine. The grounded theory analysis in this study also surfaced three tools that are used within the parameters of the roadmap approach: experience, communicative decision making, and sensemaking. Using Dewey’s (1939, 1958) theory of experience, I introduce a middle-range adapted theory of critical team experience. In this theory, experience and sensemaking are synthesized through communicative decision making to produce decisions, actions, and outcomes in time-limited, specialized, stressful environments. Critical teams have unique temporal patterns that must be considered in any study of their work. Partially based on the nested phase model (Ishak & Ballard, 2012), I also identify three phases of critical team process as critical-interactive, meaning that they are specific to action/critical teams, and they are engaged in by critical teams for the expressed purpose of interaction. These phases are simulation, adaptation, and debriefing. These tools and phases are then placed in the Critical-Action-Response Training Outcomes Grid (CARTOG) to create nine interactions that are useful in implementing a structured yet flexible approach to improvisation in the work of critical teams. Data collection consisted of field observations, semi-structured interviews, and impromptu interviews at work sites. In total, I engaged in 55 hours of field observations at 10 sites. I conducted 31 semi-structured interviews with members of wildland and urban fire crews; emergency medical teams; and tactical teams, including SWAT teams and a bomb squad. I also offer practical implications and future directions for research on the temporal and communicative aspects of critical teams, their parent organizations, and considerations of improvisation in their work. / text

The introduction of FMD into the US would have serious economic and societal effects on the livelihoods and sustainability of affected livestock producers. Livestock producers serve as an important line of defense in both detecting an introduction of FMD as well, helping to prevent disease spread. However, due to the complexity of moral, social, and economic issues surrounding the control of highly contagious diseases, producer cooperation during an outbreak may not be assured. This study was conducted using a mixed-methods approach, including qualitative analysis of interviews and quantitative analysis of a postal survey, in order to explore the factors likely to influence producer cooperation in FMD detection and control in Texas. Reporting of cattle with clinical signs of FMD in the absence of an outbreak was related to producers´ beliefs about the consequences of reporting, beliefs about what other producers would do, trust in agricultural agencies, and their perception of the risk posed by FMD. During a hypothetical outbreak, intentions to report were determined by beliefs about the consequences of reporting, and perception of the risk posed by FMD. Intentions to gather and hold cattle when requested during an outbreak were determined by beliefs about the consequences of gathering and holding, beliefs about barriers to gathering and holding, trust in other producers, and perception of the risk posed by FMD. Compliance with animal movement restrictions was determined by experiential attitudes, beliefs about the availability of feed, space, and disinfection procedures, beliefs about what other producers would do, and perception of the risk posed by FMD. Recommendations for improving producer cooperation include targeting specific beliefs in both planning and communication, increasing transparency in the post-reporting process, planning for and communicating plans for maintaining business continuity in order to better inform risk perception, and partnering with organizations to ensure sustained and meaningful communication that supports trust between producers within the affected agricultural community.

Ce travail de recherche vise à développer une méthode pour l'analyse de la robustesse des plans de secours industriels. Des défaillances peuvent survenir lors de la mise en œuvre de ces plans, qui peuvent entrainer à un fonctionnement en mode dégradé des dispositifs. Les approches existantes d’analyse de ces plans ne permettent pas une analyse structurée du dispositif de gestion de crise. La méthodologie proposée dans le cadre de ce travail repose sur une formalisation structuro-fonctionnelle et générique des plans de secours industriels, décrivant à la fois les fonctions et les ressources permettant la réalisation de ces fonctions. De plus, ce travail s’est accompagné de retours d’expérience à partir de 159 rapports d’accidents et de 61 exercices POI/PPI, qui ont permis d’identifier des défaillances pouvant survenir lors de la mise en œuvre des POI/PPI. Le modèle développé et les informations obtenues par le retour d’expérience permettent de structurer l’analyse des dysfonctionnements pouvant se manifester lors de la mise en œuvre des plans. Cette analyse de la robustesse est basée sur une évaluation du risque de défaillance des fonctions du plan. La probabilité de défaillance est estimée à partir des questions d’évaluation et des arbres de défaillances des ressources et des fonctions. La gravité de la défaillance de chaque fonction est déterminée en utilisant les études de dangers de l’installation, en suivant la règle des dommages maximum qu’elle peut provoquer. La criticité de défaillance de chaque fonction est ainsi obtenue, et la criticité du plan résulte de l'agrégation des criticités de ses fonctions. Cette méthodologie constitue ainsi une boite à outils qui peut être utilisée à la fois pour l’évaluation des plans existants, mais aussi pour l’élaboration du dispositif défini dans un plan de secours industriel. / The objective of this research thesis is to develop a methodology for the analysis of robustness of industrial emergency plans. Failures can occur when these plans are put into action; they can result to deteriorated operating conditions for these systems. Existing emergency plan analysis approaches do not allow for a structured analysis of the emergency response mechanism. The methodology developed in this research project is based on a structuro-functional and generic formalization of industrial emergency plans, which describes both the functions of the plans and the resources necessary for accomplishing them. Furthermore, lessons learned through the analysis of 159 industrial accidents and 61 internal and external industrial emergency plan exercises have led to the identification of failures that may occur during the use of industrial emergency plans for emergency response. The model that was developed and the information obtained through experience feedback result in a structured analysis of failures of these plans. This robustness analysis is based on the failure risk assessment of the plan’s functions. The failure probability is estimated through assessment questions and the plan’s functions and resources fault trees. The failure severity of each function is determined by using the facility’s hazard study and by applying the maximum damage rule. The failure criticality of each function is hence obtained, and the plan’s criticality results from the aggregation of the criticalities of the plan’s functions. The approach followed is hence based on a failure risk analysis, which in turn is built upon lessons learned and the critical analysis of the plan’s model. This methodology therefore constitutes a toolbox that can be used both for the analysis of existing plans and the development of emergency response mechanism.

This chapter defines and describes hazardous wastes and their adverse health effects. Historical evolution of the management and public understanding of waste issues is traced. Other parts of the chapter describe hazardous waste management, including disposal landfills, land farming, incineration, and toxics use reduction. Various regulatory measures are described as well as nonregulatory measures for prevention and control of adverse health effects from hazardous wastes. Approaches to evaluating human health effects at hazardous waste sites are described, emphasizing special challenges and opportunities in environmental epidemiology. Social aspects of community involvement are noted. Steps of the Superfund clean-up process are delineated. Governmental contingency plans for coordination in emergency response situations are reviewed. In addition, a section describes pollution prevention and toxics use reduction.