@article {Carroll021980, author = {Ian T. Carroll and Shweta Bansal and Jason E. Lombard}, title = {Livestock market data for modeling disease spread among US cattle}, elocation-id = {021980}, year = {2015}, doi = {10.1101/021980}, publisher = {Cold Spring Harbor Laboratory}, abstract = {Transportation of livestock carries the risk of importing infectious disease into a susceptible population, leading to costly public and private sector expenditures on disease containment and, hopefully, eradication. Individual animal tracing systems implemented outside the US have allowed epidemiologists and veterinarians to model the risks of livestock transportation and prepare responses designed to protect the livestock industry. Within the US, data on livestock transportation available to researchers is not sufficient for direct forcing of disease models, but network models that assimilate limited data provide a platform for disease models that can inform policy. Here, we report on a novel data stream with such potential: the information publicly reported by US livestock markets on the origin of cattle consigned at live-auctions. By aggregating weekly auction reports from markets in several states, some providing multi-year historical archives, we obtain an ego-centric sample of edges from the dynamic cattle transportation network in the US. We first illustrate, using over-simplified disease models, how such data are relevant to the outcome of a disease outbreak. Subsequently, we demonstrate how the sample might be used to infer shipments to unobserved livestock markets in the US, although we find the assumptions of edge prediction by generalized linear models too restrictive. We conclude that in combination with statistical models allowing greater dependence between edges, the market data create potential for inference of a complete transportation network model, one which includes the capacity of markets to spread or control livestock disease.}, URL = {https://www.biorxiv.org/content/early/2015/07/05/021980}, eprint = {https://www.biorxiv.org/content/early/2015/07/05/021980.full.pdf}, journal = {bioRxiv} }