Livestock market data for modeling disease spread among US cattle

Transportation of livestock carries the risk of spreading foreign animal diseases 2 throughout a susceptible population, leading to costly public and private sector expenditures on disease containment and eradication. Individual animal tracing 4 systems that exist in countries other than the US have allowed epidemiologists and veterinarians in those countries to model the risks engendered by livestock 6 movement and prepare responses designed to protect the livestock industry. Within the US, data on livestock movement is not su cient for direct parameterization of 8 disease models, but network models that assimilate limited data provide a path forward in model development to inform preparedness for disease outbreaks in the 10 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 12 such potential. By aggregating weekly auction reports from markets in several states, some spanning multiple years, we obtain an ego-centric sample of edges 14 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 16 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 18 simplified disease models; which we use to demonstrate that the temporal resolution of the data is su cient to reveal seasonal trends in the risk of disease outbreaks. We 20 conclude that future work on statistical models for dependence between edges will improve the inference of a complete cattle movement network model from market 22 data, one able to addresses the capacity of markets to spread or control livestock disease. 24