Journal
PREVENTIVE VETERINARY MEDICINE
Volume 193, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.prevetmed.2021.105391
Keywords
U; S; livestock industry; Interstate Certificate of Veterinary Inspection; Social network analysis; Livestock traceability
Categories
Funding
- Department of Homeland Security [GVDM003544- CSU DHS Sub]
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Livestock movements play a crucial role in the spread of infectious diseases, and understanding the contact patterns between different livestock species can help in assessing national transmission risks. Social Network Analysis (SNA) was used in this study to describe the contact structure of livestock movements in the contiguous U.S., revealing strong correlations between beef cattle and dairy cattle movements with the respective cattle populations at the county level. The networks also showed the presence of 4 to 6 large communities, with geographical clustering observed in all networks except for the small ruminant network.
Livestock movements are a common pathway for the spread infectious diseases in a population. An understanding of livestock movement patterns is needed to understand national transmission risks of highly infectious diseases during epidemics. Social Network Analysis (SNA) is an approach that helps to describe the relationships among individuals and the implications of those relationships. We used SNA to describe the contact structure of livestock movements throughout the contiguous U.S. from April 1st, 2015 to March 31st, 2016. We describe 4 network types: beef cattle, dairy cattle, swine, and small ruminant. Livestock movement data were sourced from Interstate Certificates of Veterinary Inspection (ICVI) while county-level farm demographic data were from the National Agricultural Statistics Service (NASS). In the described networks, nodes are represented by counties and arcs by shipments between nodes; the networks were weighted based on the number of shipments between nodes. For the analyses, movement data were aggregated at the county level and on an annual basis. Measures of centrality and cohesiveness were computed and identification of trade-communities in all networks was conducted. During the study period, a total of 219,042 movements were recorded and beef cattle movements accounted for 63 % of all movements. At least 70 % of U.S. counties were present in each of the networks, but the density of arcs was less than 2% in all networks. In the beef cattle network, counties with high out-degree were strongly correlated (0.8) with the number of beef cows per county while for the dairy cattle network a strong correlation (>0.86) was found with the number of dairy cattle per km2 at the county level. All networks were found to have between 4 and 6 large communities (50 counties or more per community), and were geographically clustered except for the communities in the small ruminant network. Outputs reported in these analyses can help to understand the structure of the contact networks for beef cattle, dairy cattle, swine, and small ruminants. They may also be used in conjunction with simulation modeling to evaluate spread of highly infectious disease such as foot-and-mouth disease at the national level and to evaluate the application of intervention strategies.
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