Literature DB >> 27836049

Mapping U.S. cattle shipment networks: Spatial and temporal patterns of trade communities from 2009 to 2011.

Erin E Gorsich1, Angela D Luis2, Michael G Buhnerkempe3, Daniel A Grear4, Katie Portacci4, Ryan S Miller4, Colleen T Webb5.   

Abstract

The application of network analysis to cattle shipments broadens our understanding of shipment patterns beyond pairwise interactions to the network as a whole. Such a quantitative description of cattle shipments in the U.S. can identify trade communities, describe temporal shipment patterns, and inform the design of disease surveillance and control strategies. Here, we analyze a longitudinal dataset of beef and dairy cattle shipments from 2009 to 2011 in the United States to characterize communities within the broader cattle shipment network, which are groups of counties that ship mostly to each other. Because shipments occur over time, we aggregate the data at various temporal scales to examine the consistency of network and community structure over time. Our results identified nine large (>50 counties) communities based on shipments of beef cattle in 2009 aggregated into an annual network and nine large communities based on shipments of dairy cattle. The size and connectance of the shipment network was highly dynamic; monthly networks were smaller than yearly networks and revealed seasonal shipment patterns consistent across years. Comparison of the shipment network over time showed largely consistent shipping patterns, such that communities identified on annual networks of beef and diary shipments from 2009 still represented 41-95% of shipments in monthly networks from 2009 and 41-66% of shipments from networks in 2010 and 2011. The temporal aspects of cattle shipments suggest that future applications of the U.S. cattle shipment network should consider seasonal shipment patterns. However, the consistent within-community shipping patterns indicate that yearly communities could provide a reasonable way to group regions for management.
Copyright © 2016 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Cattle shipment; Community detection; Dynamic network; Interstate Certificate of Veterinary Inspection; Network analysis; U.S. cattle industry

Mesh:

Year:  2016        PMID: 27836049     DOI: 10.1016/j.prevetmed.2016.09.023

Source DB:  PubMed          Journal:  Prev Vet Med        ISSN: 0167-5877            Impact factor:   2.670


  6 in total

Review 1.  BOARD INVITED REVIEW: Prospects for improving management of animal disease introductions using disease-dynamic models.

Authors:  Ryan S Miller; Kim M Pepin
Journal:  J Anim Sci       Date:  2019-05-30       Impact factor: 3.159

2.  Effects of regional differences and demography in modelling foot-and-mouth disease in cattle at the national scale.

Authors:  Kimberly Tsao; Stefan Sellman; Lindsay M Beck-Johnson; Deedra J Murrieta; Clayton Hallman; Tom Lindström; Ryan S Miller; Katie Portacci; Michael J Tildesley; Colleen T Webb
Journal:  Interface Focus       Date:  2019-12-13       Impact factor: 3.906

3.  Application of network analysis and cluster analysis for better prevention and control of swine diseases in Argentina.

Authors:  Jerome N Baron; Maria N Aznar; Mariela Monterubbianesi; Beatriz Martínez-López
Journal:  PLoS One       Date:  2020-06-17       Impact factor: 3.240

4.  Spatio-temporal patterns and characteristics of swine shipments in the U.S. based on Interstate Certificates of Veterinary Inspection.

Authors:  Erin E Gorsich; Ryan S Miller; Holly M Mask; Clayton Hallman; Katie Portacci; Colleen T Webb
Journal:  Sci Rep       Date:  2019-03-08       Impact factor: 4.379

5.  Cattle transport network predicts endemic and epidemic foot-and-mouth disease risk on farms in Turkey.

Authors:  José L Herrera-Diestra; Michael Tildesley; Katriona Shea; Matthew J Ferrari
Journal:  PLoS Comput Biol       Date:  2022-08-19       Impact factor: 4.779

6.  Hierarchical Structures in Livestock Trade Networks-A Stochastic Block Model of the German Cattle Trade Network.

Authors:  Laura Brzoska; Mareike Fischer; Hartmut H K Lentz
Journal:  Front Vet Sci       Date:  2020-05-27
  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.