# United States cattle market location and annual market sales estimate data

**Authors:** Samuel M. Smith, Clayton Hallman, Tom Lindström, Stefan Sellman, Ryan S. Miller, Katie Portacci, Colleen T. Webb, Lindsay M. Beck-Johnson

PMC · DOI: 10.1016/j.dib.2025.111877 · Data in Brief · 2025-07-11

## TL;DR

This paper provides a dataset of U.S. cattle market locations and estimated annual sales to better understand cattle industry dynamics and disease spread risks.

## Contribution

A novel spatial autoregressive model is used to estimate cattle market sales in data-scarce counties, enhancing cattle movement and disease modeling.

## Key findings

- A dataset of 1619 cattle markets across 1131 U.S. counties from 2012–2016 was compiled.
- A spatial autoregressive lag model estimated annual sales in counties with missing data.
- The dataset supports improved modeling of cattle movements and transboundary animal disease surveillance.

## Abstract

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 may 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 1619 known cattle markets with and without market sales data from 1131 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.

## Full-text entities

- **Diseases:** TAD (MESH:D000820)
- **Species:** Bos taurus (bovine, species) [taxon 9913]

## Full text

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## Figures

3 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12301815/full.md

## References

16 references — full list in the complete paper: https://tomesphere.com/paper/PMC12301815/full.md

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Source: https://tomesphere.com/paper/PMC12301815