Because of an ever-increasing threat of foreign animal disease outbreaks in the United States, there is a desire to develop strategies to prevent the occurrence of a foreign animal disease and control an outbreak if it does occur. Infectious disease models have been developed and are being used to determine reasonable mitigation strategies. However, little information is available concerning premises characteristics and movement of animals in extensively managed livestock areas. Hence adaptation of these models to areas where there is low livestock density is not easy. We collected empirical data, via mail out surveys, from an extensively managed livestock area. This will aid in improving the results of infectious disease models in these areas. In contrast to the intensively managed livestock that have previously been modeled, this study has shown that in areas of low livestock density, multiple livestock types often are managed on the same premises. Direct contacts, facilitated through the planned movement of animals, appear to have a greater seasonality in extensively managed areas as compared to intensively managed areas. Furthermore, wildlife contacts are likely and of potential importance. The results of this study add to the knowledge base used to model the spread of infectious disease in extensively managed livestock populations. Seasonal changes in animal densities and contact rates may impact the results of the models. Additionally, the effect of multiple livestock types on premises should be considered when the expected spread of disease is modeled in extensive livestock areas.

An understanding of the ecology and behavior of white-tailed deer (Odocoileus virginianus) is necessary for proper conservation and management, especially in the face of emerging infectious diseases. The objectives of my study were to estimate juvenile survival, compare methods of quantifying contact rates (simultaneous GPS locations vs. proximity loggers [PLs]), and investigate the impact of group depopulation on contact rates of remnant adult female and juvenile deer. To achieve these goals, I captured, radiotracked, and monitored adult female and juvenile white-tailed deer in southern Illinois during 2011-2014. Survival analysis of juveniles revealed that main causes of mortality were capture related and predation, though some dead animals also showed signs of hemorrhagic disease. Comparison between simultaneous GPS locations and PLs showed evidence that deer coming within the general vicinity of each other are less likely to come in close contact if they are in neighboring social groups than deer whose home ranges overlap little, if at all. Finally, experimental removal of group members caused few if any remnant adult females to alter their contact rates or space-use, but caused remnant juveniles to have lower space-use fidelity compared to control deer and to increase their direct contact rates with other groups temporarily. Using these results, I discuss the large effects that severe weather events can have on juvenile survival, the importance of social structure on the potential transmission of disease agents among female and juvenile deer, and the difference between adult females and juvenile deer in their need for social interactions. My research provides ecologists, wildlife biologists, and managers with valuable information concerning the potential impacts of the environment, infectious diseases, and management strategies on white-tailed deer populations.

For the second study, a web-based survey was developed and distributed to all members of four major health education organizations. A total of 1,925 HEs’ completed the survey and 1,607 responses were utilized in the final analysis. This study indicated that participants had deficient knowledge and unfavorable attitudes toward the CDCproposed genomic competencies. In the third study, a theoretical model was developed to predict HEs’ likelihood to incorporate genomic competencies into their practice. Using techniques from Structural Equation Modeling (SEM), the model was tested with the same data of the second study. Findings supported the proposed theoretical model. While genomic knowledge, attitudes, and self-efficacy were significantly associated with HEs’ likelihood to incorporate genomic competencies into their practice, attitudes was the strongest predictor of likelihood. In summary, these studies indicated that participating HEs had deficient genomic knowledge, unfavorable attitudes toward a set of CDC-proposed genomic competencies, and low likelihood to adopt genomic competencies into health promotion. Relevant training should be developed and advocated. As the SEM analysis results indicated the survey findings supported the proposed theoretical model, which can be utilized to steer future training for HEs. statistics, 2) unadjusted inferential statistics, 3) stratified analysis, and 4) multivariable models. My investigation produced results in accord with generally accepted notions in addition to significant findings that interestingly counter current preconceptions. Intraspecies contact was more common than inter-species, with indirect contact occurring more frequently than direct. Direct contact between species occurred extremely rarely. The most important factors that influenced the rate of contact for both species were water, winter, and cultivated fields. Information regarding probability of infectious agent survival and transfer will be used in the future to advance current epidemiological models, including geographicautomata (Ward et al. 2007: In Press) and cellular automata models (Doran and Laffan 2005) to better understand and manage integrated domestic cattle and free-ranging wildlife populations. Such modeling provides essential and necessary knowledge for developing prevention, detection, response, and recovery strategies – employed in advance, during, and after a disease outbreak, respectively.

Infectious disease models with switching are constructed and investigated in detail. Modelling infectious diseases as switched systems, which are systems that combine continuous dynamics with discrete logic, allows for the use of methods from switched systems theory. These methods are used to analyze the stability and long-term behaviour of the proposed switched epidemiological models. Switching is first incorporated into epidemiological models by assuming the contact rate to be time-dependent and better approximated by a piecewise constant. Epidemiological models with switched incidence rates are also investigated. Threshold criteria are established that are sufficient for the eradication of the disease, and, hence, the stability of the disease-free solution. In the case of an endemic disease, some criteria are developed that establish the persistence of the disease. Lyapunov function techniques, as well as techniques for stability of impulsive or non-impulsive switched systems with both stable and unstable modes are used. These methods are first applied to switched epidemiological models which are intrinsically one-dimensional. Multi-dimensional disease models with switching are then investigated in detail. An important part of studying epidemiology is to construct control strategies in order to eradicate a disease, which would otherwise be persistent. Hence, the application of controls schemes to switched epidemiological models are investigated. Finally, epidemiological models with switched general nonlinear incidence rates are considered. Simulations are given throughout to illustrate our results, as well as to make some conjectures. Some conclusions are made and future directions are given.

Infectious disease models with switching are constructed and investigated in detail. Modelling infectious diseases as switched systems, which are systems that combine continuous dynamics with discrete logic, allows for the use of methods from switched systems theory. These methods are used to analyze the stability and long-term behaviour of the proposed switched epidemiological models. Switching is first incorporated into epidemiological models by assuming the contact rate to be time-dependent and better approximated by a piecewise constant. Epidemiological models with switched incidence rates are also investigated. Threshold criteria are established that are sufficient for the eradication of the disease, and, hence, the stability of the disease-free solution. In the case of an endemic disease, some criteria are developed that establish the persistence of the disease. Lyapunov function techniques, as well as techniques for stability of impulsive or non-impulsive switched systems with both stable and unstable modes are used. These methods are first applied to switched epidemiological models which are intrinsically one-dimensional. Multi-dimensional disease models with switching are then investigated in detail. An important part of studying epidemiology is to construct control strategies in order to eradicate a disease, which would otherwise be persistent. Hence, the application of controls schemes to switched epidemiological models are investigated. Finally, epidemiological models with switched general nonlinear incidence rates are considered. Simulations are given throughout to illustrate our results, as well as to make some conjectures. Some conclusions are made and future directions are given.