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Estimation of distance related probability of animal movements between holdings and implications for disease spread modeling
Authors:Tom Lindstrm  Scott A Sisson  Maria Nremark  Annie Jonsson  Uno Wennergren
Institution:aIFM Theory and Modelling, Linköping University, 581 83 Linköping, Sweden;bSchool of Mathematics and Statistics, University of New South Wales, Sydney 2052, Australia;cDepartment of Disease Control and Epidemiology, SVA, National Veterinary Institute, 751 89 Uppsala, Sweden;dResearch Centre of Systems Biology, Ecological Modelling, University of Skövde, 541 28 Skövde, Sweden
Abstract:Between holding contacts are more common over short distances and this may have implications for the dynamics of disease spread through these contacts. A reliable estimation of how contacts depend on distance is therefore important when modeling livestock diseases. In this study, we have developed a method for analyzing distant dependent contacts and applied it to animal movement data from Sweden. The data were analyzed with two competing models. The first model assumes that contacts arise from a purely distance dependent process. The second is a mixture model and assumes that, in addition, some contacts arise independent of distance. Parameters were estimated with a Bayesian Markov Chain Monte Carlo (MCMC) approach and the model probabilities were compared. We also investigated possible between model differences in predicted contact structures, using a collection of network measures.We found that the mixture model was a much better model for the data analyzed. Also, the network measures showed that the models differed considerably in predictions of contact structures, which is expected to be important for disease spread dynamics. We conclude that a model with contacts being both dependent on, and independent of, distance was preferred for modeling the example animal movement contact data.
Keywords:Markov Chain Monte Carlo  Mixture models  Model selection  Animal movements  Disease transmission  Network analysis
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