AcknowledgementsChapter OneChapter TwoIntroductionMethodsSimulation ModelParameter EstimationSurvivalDispersal (??Disease transmission ()Other Model ParametersSensitivity AnalysesResultsField Data Parameter EstimatesSensitivity AnalysesModel Results Without DispersalDiscussionChapter ThreeIntroductionMethodsHeuristic Simulation ModelAfrican Buffalo in the KNP: Field MethodsBuffalo Data RandomizationStatistical AnalysisResultsHeuristic SimulationsBuffalo Association PatternsDiscussionApplication of the FDIChapter FourIntroductionMethodsAssociation dataDisease ModellingResultsAssociation dataSimulation ResultsDiscussionFuture directionsChapter FiveIntroductionDemonstration of Dueling Timescales EffectPredictors of a PandemicFuture Empirical ResearchFuture Theoretical ResearchConclusionSupplementary MaterialReferencesDisease Invasion and Control in Structured Populations: Bovine Tuberculosis in the Buffalo Population of the Kruger National Park by Paul Chafee Cross B.A. (University of Virginia) 1998 A dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Environmental Science, Policy and Management in the GRADUATE DIVISION of the UNIVERSITY OF CALIFORNIA, BERKELEY Committee in charge: Professor Wayne M. Getz, Chair Professor Steven R. Beissinger Professor Cheryl J. Briggs Professor Johan T. du Toit May 2005Disease Invasion and Control in Structured Populations: Bovine Tuberculosis in the Buffalo Population of the Kruger National Park © 2005 by Paul Chafee CrossAbstract Disease Invasion and Control in Structured Populations: Bovine Tuberculosis in the Buffalo Population of the Kruger National Park by Paul Chafee Cross Doctor of Philosophy in Environmental Science, Policy and Management University of California, Berkeley Professor Wayne M. Getz, Chair From 1991 to 2004, bovine tuberculosis (Mycobacterium bovis, BTB) moved north and increased in prevalence in the African buffalo (Syncerus caffer) population of the Kruger National Park, South Africa. I use this epidemic as a case study to understand how host population structure affects disease dynamics. Radio-tracking data indicated that all sex and age groups moved between herds, but males over eight years old had higher mortality and dispersal rates than any other sex or age category. BTB appeared to have only minor effects upon survival. Models incorporating these data suggest that the success of vaccination programs will depend strongly upon the duration that a vaccine grants protection, which is currently unknown. Even with a lifelong vaccine, 1however, eradication is unlikely unless vaccination is combined with other control strategies. To analyze the radio-tracking and association data, I proposed a new metric of association, the fission decision index (FDI) that significantly reduces the biases that exist in traditional association analyses in fission-fusion societies. Adult female and juvenile buffalo made non-random fission decisions while adult male choices were indistinguishable from a random coin toss. Incorporating the association data into a dynamic social network model suggested that the dynamic nature of the network has a strong influence on disease dynamics, particularly for diseases with shorter infectious periods. Buffalo herds were more tightly associated in 2002 than 2003, perhaps due to drier conditions in 2003 prompting additional movement that would facilitate the spread of disease among herds. Using a metapopulation model, I illustrate how the group-level metric, , which is the average number of groups infected by the initial group, is a better predictor of disease invasion than the traditional individual-level R*R0 in structured host populations. is a function of group size, movement rate, infection rate, and length of the infectious period. Chronic diseases allow for more host mixing between groups; thus they ‘perceive’ a more well-mixed host population. As a result, chronic diseases are more likely to invade structured populations than acute diseases, given the same R*R0, and it is more important to incorporate the spatial structure of the host population for acute diseases than chronic diseases. 2Table of Contents Acknowledgements .......................................................................................................... ii Chapter One...................................................................................................................... 1 Chapter Two .....................................................................................................................8 Chapter Three ................................................................................................................. 39 Chapter Four................................................................................................................... 61 Chapter Five ................................................................................................................... 92 References .................................................................................................................... 118 iAcknowledgements First, I would like to thank my family for all of their support. Craig Hay, Justin Bowers, Julie Wolhuter, Khutani Bulunga, and Augusta Mabunda collected the vast majority of the field data included in this dissertation. Always professional and great companions, they made the last four years in Satara an amazing experience. I am grateful to the managers, scientists, and staff of the Kruger National Park for facilitating the project, and to the United States National Science Foundation Ecology of Infectious Disease Grant DEB-0090323 for funding this research. Drs. Markus Hofmeyr, Peter Buss, Lin-Mari de Klerk, Roy Bengis and Douw Grobler, as well as Marius Kruger, KNP Game Capture, State Veterinary technicians, and many University of Pretoria students assisted in buffalo capture operations. Roy Bengis, Steve Beissinger, Cherie Briggs, Justin Brashares, Charlie Nunn, and Anna Jolles all provided many helpful comments along the way. Martin Haupt and Elmarie Cronje at the University of Pretoria were invaluable in their assistance with equipment and finances. All the students in the Getz Lab including Peter Baxter, Chris Wilmers, Sadie Ryan, Andy Lyons, Allison Bidlack, Wendy Turner, Shirli Bar-David, John Eppley, George Wittemyer, James Lloyd-Smith, and Karen Levy, made it a