DOI: 10.5061/dryad.cfxpnvxg7
title: Data from: United States cattle market location and annual market sales estimate data

description: Cattle markets, where livestock producers may buy and sell cattle and
 calves, act as major hubs in the shipment network that connect cattle
 populations across the United States (U.S.). Cattle markets can then
 provide insight into the integration of the U.S. cattle industry, thus
 informing how regional price fluctuations can influence cattle prices
 nationally. Despite biosecurity measures and regulatory compliance from
 livestock markets, commingling and re-distribution of animals from
 multiple sources may elevate the risk of disease spread and make tracing
 animal movements more complex, which could pose significant challenges if
 a transboundary animal disease (TAD) were introduced into the U.S.
 Therefore, knowing the size and location of cattle markets in the U.S. is
 critical to understanding cattle industry market dynamics and enhancing
 pandemic scenario modeling efforts. In this article, we present a list of
 cattle markets, their locations, and estimated quarterly cattle sales. We
 compiled a list of 1,619 known cattle markets with and without market
 sales data from 1,131 counties across the U.S. from 2012-2016. To estimate
 unknown market sales data, we fit a spatial autoregressive lag model to
 annual county-level market sales data and used the fit to predict annual
 sales in counties that lacked sales information. County-level sales data
 provide important insight into the structure of the U.S. cattle industry.
 The dataset can be used to improve national-scale cattle movement models,
 livestock disease models, and inform TAD surveillance efforts.
description: # Data from: United States Cattle Market Location and Annual Market Sales
 Estimate Data ## Overview This dataset contains information on cattle
 market locations and estimated annual cattle sales in the United States
 from 2012 to 2016. The data were compiled to enhance the understanding of
 cattle market dynamics and improve modeling efforts related to livestock
 movement and disease spread. ## Repository Contents *
 MarketList_final.csv: Contains detailed information about each cattle
 market, including location data and unique identifiers. *
 Market_Volume_Estimates.csv: Provides county-level annual cattle sales
 estimates, including known and predicted values where data were not
 available. ## Data Description ### MarketList\_final.csv * RecordID:
 Unique identifier for each record (matches MarketID column in the Carroll
 and Bansal de-duplicated market list). * premises.CB: Premises
 designations from Carroll and Bansal [1]. * premises.Beck-Johnson:
 Corrected premises designations. * FIPS: A five-digit Federal Information
 Processing Standard (FIPS) code that uniquely identifies county centroids.
 * Notes: Canada (Canadian markets), Horse (Google searches show auction is
 associated with horses, with no indication of other livestock), No
 Livestock (where Google searches show auction is associated with goods
 other than livestock), Insufficient Location Information (Cannot determine
 county based on available information). * name: Market name from source.
 Different names are present for the same market if sources listed
 different names. * address: The physical location or business address of a
 market. * po: Post Office box. * city: City that the market is located in.
 * state: State the market is located in. * zip: United States Postal
 Service Zone Improvement Plan (ZIP) code. * zip_ext: ZIP code extension
 number. * source: Market information source. * id: Market identification
 number from source. ### Market\_Volume\_Estimates.csv * FIPS: A five-digit
 Federal Information Processing Standard (FIPS) code that uniquely
 identifies county centroids. * number_markets: The number of markets in
 that county. * volume_data: average number of cattle sold per year in that
 county, where known. * estimated_volume: estimated annual cattle sales
 where data were not available. Known sales data (e.g. from volume_data
 column) are in this column where available. #### NA values represent
 'not available' and exist in both datasets where data were
 unavailable.