Literature DB >> 28237226

Unraveling the contact patterns and network structure of pig shipments in the United States and its association with porcine reproductive and respiratory syndrome virus (PRRSV) outbreaks.

Kyuyoung Lee1, Dale Polson2, Erin Lowe2, Rodger Main3, Derald Holtkamp3, Beatriz Martínez-López4.   

Abstract

The analysis of the pork value chain is becoming key to understanding the risk of infectious disease dissemination in the swine industry. In this study, we used social network analysis to characterize the swine shipment network structure and properties in a typical multisite swine production system in the US. We also aimed to evaluate the association between network properties and porcine respiratory and reproductive syndrome virus (PRRSV) transmission between production sites. We analyzed the 109,868 swine shipments transporting over 93 million swine between more than 500 production sites from 2012 to 2014. A total of 248 PRRSV positive occurrences were reported from 79 production sites during those 3 years. The temporal dynamics of swine shipments was evaluated by computing network properties in one-month and three-month networks. The association of PRRS occurrence in sow farms with centrality properties from one-month and three-month networks was assessed by using the multilevel logistic regression. All monthly networks showed a scale-free network topology with positive degree assortativity. The regression model revealed that out-degree centrality had a negative association with PRRS occurrence in sow farms in both one-month and three-month networks [OR=0.79 (95% CI, 0.63-0.99) in one-month network and 0.56 (95% CI, 0.36, 0.88) in three-month network] and in-closeness centrality model was positively associated with PRRS occurrence in sow farms in the three-month network [OR=2.45 (95% CI, 1.14-5.26)]. We also describe how the occurrence of porcine epidemic diarrheac (PED) outbreaks severely affected the network structure as well as the PRRS occurrence reports and its association with centrality measures in sow farms. The structure of the swine shipment network and the connectivity between production sites influenced on the PRRSV transmission. The use of network topology and characteristics combining with spatial analysis based on fine scale geographical location of production sites will be useful to inform the design of more cost-efficient, risk-based surveillance and control measures for PRRSV as well as other diseases in the US swine industry.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Infectious disease; PED; PRRS; Pork value chain; Social network analysis; Swine

Mesh:

Year:  2017        PMID: 28237226     DOI: 10.1016/j.prevetmed.2017.02.001

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


  16 in total

1.  Estimation of swine movement network at farm level in the US from the Census of Agriculture data.

Authors:  Sifat A Moon; Tanvir Ferdousi; Adrian Self; Caterina M Scoglio
Journal:  Sci Rep       Date:  2019-04-17       Impact factor: 4.379

2.  Pig movements in France: Designing network models fitting the transmission route of pathogens.

Authors:  Morgane Salines; Mathieu Andraud; Nicolas Rose
Journal:  PLoS One       Date:  2017-10-19       Impact factor: 3.240

3.  Modeling the live-pig trade network in Georgia: Implications for disease prevention and control.

Authors:  Esther Andrea Kukielka; Beatriz Martínez-López; Daniel Beltrán-Alcrudo
Journal:  PLoS One       Date:  2017-06-09       Impact factor: 3.240

4.  Modeling the spatio-temporal dynamics of porcine reproductive & respiratory syndrome cases at farm level using geographical distance and pig trade network matrices.

Authors:  Sara Amirpour Haredasht; Dale Polson; Rodger Main; Kyuyoung Lee; Derald Holtkamp; Beatriz Martínez-López
Journal:  BMC Vet Res       Date:  2017-06-07       Impact factor: 2.741

5.  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

6.  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

7.  Identifying outbreaks of Porcine Epidemic Diarrhea virus through animal movements and spatial neighborhoods.

Authors:  Gustavo Machado; Carles Vilalta; Mariana Recamonde-Mendoza; Cesar Corzo; Montserrat Torremorell; Andrez Perez; Kimberly VanderWaal
Journal:  Sci Rep       Date:  2019-01-24       Impact factor: 4.379

8.  Role of animal movement and indirect contact among farms in transmission of porcine epidemic diarrhea virus.

Authors:  Kimberly VanderWaal; Andres Perez; Montse Torremorrell; Robert M Morrison; Meggan Craft
Journal:  Epidemics       Date:  2018-04-12       Impact factor: 4.396

9.  Pig trade networks through live pig markets in Guangdong Province, China.

Authors:  Yin Li; Baoxu Huang; Chaojian Shen; Chang Cai; Youming Wang; John Edwards; Guihong Zhang; Ian D Robertson
Journal:  Transbound Emerg Dis       Date:  2020-01-13       Impact factor: 4.521

10.  Network Analysis of Swine Shipments in China: The First Step to Inform Disease Surveillance and Risk Mitigation Strategies.

Authors:  Kathleen O'Hara; Rui Zhang; Yong-Sam Jung; Xiaobing Zhou; Yingjuan Qian; Beatriz Martínez-López
Journal:  Front Vet Sci       Date:  2020-04-28
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