The potential role of wildlife in the spread and control of foot and mouth disease in an extensive livestock management system
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Foot and mouth disease (FMD) is a highly contagious viral infection that affects all Artiodactyls (cloven-hoofed) species. The United States has been free of FMD since 1929, and the entire population of cloven-hoofed species is therefore susceptible to FMD virus infection. In the face of an outbreak, it is crucial that appropriate control measures be applied rapidly to control the disease. However, in most cases decisions on mitigation strategies must be made with little current or empirical data and in the context of political, economic and social pressures. Disease spread models can be used to evaluate the design of optimal control strategies, for policy formulation, for gap analysis and to develop and refine research agendas when disease is not present. This research project is designed to investigate the potential role of wildlife (deer) in the transmission and spread of FMD in an extensive livestock management system in southern Texas. The spread of FMD was simulated in white tailed deer populations using a Geographic Automata model. Past research has focused primarily on modeling the spread of FMD in livestock populations. There has been limited research into the potential role of wildlife in the spread and maintenance of FMD, specifically in the United States and using a spatial modeling approach. The study area is a nine-county area located in southern Texas, bordering Mexico. It is a region of concern for the introduction of foreign animal diseases, particularly through the movement of wild and feral animal species. It is both a strategic location and is generally representative of the many similar eco-climatic regions throughout the world. It is an ideal model landscape to simulate FMD incursions. In this research project, the potential spread of FMD is simulated based on various spatial estimates of white tailed deer distribution, various estimates of critical model parameters (such as the latent and infectious periods), seasonal population variability and in the face of potential pre-emptive mitigation strategies. Significant differences in the predicted spread were found for each group of simulations. The decision-support system developed in the studies described in this dissertation provide decision-makers and those designing and implementing disease response and control policy with information on the potential spread of a foreign animal disease incursion with a likely wildlife reservoir. Use of such a decision-support system would enhance the disease incursion preparedness and response capacity of the United States.