Browsing by Author "Hill, Ashley E., advisor"
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Item Open Access A holistic approach to veterinary public health in animal shelters and other sites(Colorado State University. Libraries, 2009) Steneroden, Kay K., author; Salman, M. D., advisor; Hill, Ashley E., advisorAnimal health and human health are intimately linked. Directly, through contact with or exposure to animals and their environments, and indirectly by way of food production, food safety and antimicrobial drug residues, humans are dependent upon and vulnerable to the health of animals. Veterinary public health is concerned with the interface of human and animal health and addressing problems at that interface. The potential impact of such exploration is greater human and animal health. Epidemiological needs assessment, problem investigation and subsequent outreach programs are essential tools of veterinary public health practice. These tools are used to explore infection control, infectious and zoonotic disease awareness, environmental contamination with infectious/zoonotic agents and monitoring the consequences of treatment of infectious and zoonotic diseases with antimicrobial drugs (i.e. antimicrobial drug resistance). The specific venues for these explorations for this dissertation include animal shelters, a veterinary teaching hospital, a former Soviet country and a United States governmental program. A holistic approach is used with animal shelters to assess infection control and zoonotic disease awareness needs, investigate environmental contamination with a zoonotic disease, develop training tools and train animal shelter workers and volunteers. The needs assessment provided valuable information on characteristics of animal shelters, provided impetus for the problem investigation and the basis for outreach training. The problem investigation tool provided the first available information on the prevalence and extent of salmonella contamination in Colorado animal shelters. The outreach components provided a tool and reference for training; the training itself indicated gaps in knowledge in various aspects of infection control and zoonotic disease awareness that could be addressed with training. Further, problem investigation is explored through the success of active surveillance in discovery and control of a zoonotic disease outbreak in a veterinary teaching hospital. Results of a needs assessment survey in the Republic of Armenia provide the basis for development of outreach materials for veterinarians, farmers and school-age children on their national animal health program. And a system of antimicrobial drug resistance monitoring is examined and challenged for completeness. Taken together, these studies further the examination of veterinary public health issues and highlight a holistic approach to their exploration.Item Open Access Construction and evaluation of epidemiologic simulation models for the within- and among-unit spread and control of infectious diseases of livestock and poultry(Colorado State University. Libraries, 2012) Reeves, Aaron, author; Salman, M. D., advisor; Hill, Ashley E., advisor; Keefe, Thomas J., committee member; Wagner, Bruce A., committee memberEpidemiologic modeling is an increasingly common method of estimating the potential impact of outbreaks of highly contagious diseases, such as foot-and-mouth disease (FMD) and highly pathogenic avian influenza (HPAI), in populations of domesticated animals. Disease models are also used to inform policy decisions regarding disease control methods and outbreak response plans, to estimate the possible magnitude of an outbreak, and to estimate the resources needed for outbreak response. Although disease models are computationally sophisticated, the quality of the results of modeling studies depends on the quality and accuracy of the data on which they are based, and on the conceptual soundness and validity of the models themselves. For such models to be credibly applied, they should realistically represent the systems they are intended to reflect, should be based to as great an extent as possible on valid data, and should be subjected to careful and ongoing scrutiny. Two key steps in the evaluation of epidemiologic models are model verification and model validation. Verification is the demonstration that a computer-driven model is operating correctly, and conforms to its intended design. Validation refers to the process of determining how well a model corresponds to the system that it intended to represent. For a veterinary epidemiologic model, validation would address issues such as how well the model represents the dynamics of the disease in question in a population to which the model is applied, and how well the model represents the application of different measures for disease control. Among the steps that can be taken by epidemiologic modelers to facilitate the processes of model verification and validation are to clearly state the purpose, assumptions, and limitations of a model; to provide a detailed description of the conceptual model for use by everyone who might be tasked with evaluation of a model; document steps already taken to test the model; and thoroughly describe the data sources and the process used to produce model input parameters from data. The realistic representation of the dynamics of spread of disease within individual herds or flocks can have important implications for disease detection and surveillance, as well as for disease transmission between herds or flocks. We have developed a simulation model of within-unit (within-herd or within-flock) disease spread that operates at the level of the individual animal, and fully incorporates sources of individual-level variation such as variability in the durations of incubating and infectious periods, the stochastic nature of disease spread among individuals, and the effects of vaccination. We describe this stochastic model, along with the processes employed for verification and validation. The incorporation of this approach to modeling of within-unit disease dynamics into models of between-unit disease spread should improve the utility of these models for emergency preparedness and response planning by making it possible to assess the value of different approaches to disease detection and surveillance, in populations with or without some existing level of vaccine immunity. Models rely not only on realistic representations of the systems of interest, but also on valid and realistic information. For spatially explicit models of the spread and control of disease in populations of livestock and poultry, this means a heavy reliance upon valid spatial representations of the populations of interest, including such characteristics as the geographic locations of farms and their proximity to others in the population. In the United States, limited information regarding the locations of actual farm premises is available, and modeling work often makes use of artificially generated population datasets. In order to evaluate the accuracy and validity of the use of such artificially generated datasets, we compared the outcomes of mechanistic epidemiologic simulation models that were run using an empirical population dataset to those of models that made use of several different synthetic population datasets. Although we found generally good qualitative agreement among models run using various population datasets, the quantitative differences in model outcomes could be substantial. When quantitative outcomes from epidemiologic models are desired or required, care should be taken to adequately capture or describe the uncertainty in model-based outcomes due to the use of synthetic population datasets.Item Open Access Prevalence and risk factors associated with bluetongue virus among Colorado sheep flocks(Colorado State University. Libraries, 2010) Mayo, Christie Ellen, author; Hill, Ashley E., advisor; Bowen, Richard A., committee member; Van Metre, David C., committee member; Callan, Robert J., committee memberTo view the abstract, please see the full text of the document.