%0 Journal Article %A Ian T. Carroll %A Jason E. Lombard %A Shweta Bansal %T Livestock market data for modeling disease spread among US cattle %D 2015 %R 10.1101/021980 %J bioRxiv %P 021980 %X Transportation of livestock carries the risk of spreading foreign animal diseases throughout a susceptible population, leading to costly public and private sector expenditures on disease containment and eradication. Individual animal tracing systems that exist in countries other than the US have allowed epidemiologists and veterinarians in those countries to model the risks engendered by livestock movement and prepare responses designed to protect the livestock industry. Within the US, data on livestock movement is not sufficient for direct parameterization of disease models, but network models that assimilate limited data provide a path forward in model development to inform preparedness for disease outbreaks in the US. Here, we report on a novel data stream, the information publicly reported by US livestock markets on the origin of cattle consigned at live-auctions, and demonstrate such potential. By aggregating weekly auction reports from markets in several states, some spanning multiple years, we obtain an ego-centric sample of edges from the dynamic cattle transportation network in the US. We first 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. The sample itself, however, can still be used to parameterize simplified disease models; which we use to demonstrate that the temporal resolution of the data is sufficient to reveal seasonal trends in the risk of disease outbreaks. We conclude that future work on statistical models for dependence between edges will improve the inference of a complete cattle movement network model from market data, one able to addresses the capacity of markets to spread or control livestock disease.Author Summary We have “crowd-sourced” the collection of previously unavailable cattle movement data, benefiting from buyers interest in the origins of cattle sold at live-auction markets, to implement a minimum level of movement surveillance. Using our novel dataset, we demonstrate potential to infer a complete dynamic transportation network and model national-scale livestock epidemics. %U https://www.biorxiv.org/content/biorxiv/early/2015/08/03/021980.full.pdf