Literature DB >> 30771888

Characterization of swine movements in the United States and implications for disease control.

A C Kinsley1, A M Perez1, M E Craft2, K L Vanderwaal3.   

Abstract

Understanding between-farm movement patterns is an essential component in developing effective surveillance and control programs in livestock populations. Quantitative knowledge on movement patterns is particularly important for the commercial swine industry, in which large numbers of pigs are frequently moved between farms. Here, we described the annual movement patterns between swine farms in three production systems of the United States and identified farms that may be targeted to increase the efficacy of infectious disease control strategies. Research results revealed a high amount of variability in movement patterns across production systems, indicating that quantities captured from one production system and applied to another may lead to invalid estimations of disease spread. Furthermore, we showed that targeting farms based on their mean infection potential, a metric that captured the temporal sequence of movements, substantially reduced the potential for transmission of an infectious pathogen in the contact network and performed consistently well across production systems. Specifically, we found that by targeting farms based on their mean infection potential, we could reduce the potential spread of an infectious pathogen by 80% when removing approximately 25% of farms in each of the production systems. Whereas other metrics, such as degree, required 26-35% of farms to be removed in two of the production systems to reach the same outcome; this outcome was not achievable in one of the production systems. Our results demonstrate the importance of fine-scale temporal movement data and the need for in-depth understanding of the contact structure in developing more efficient disease surveillance and response strategies in swine production systems.
Copyright © 2019 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Contact network; Infectious disease contact; Movement; Social network analysis; Swine

Mesh:

Year:  2019        PMID: 30771888     DOI: 10.1016/j.prevetmed.2019.01.001

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


  5 in total

1.  Animal movement in a pastoralist population in the Maasai Mara Ecosystem in Kenya and implications for pathogen spread and control.

Authors:  George P Omondi; Vincent Obanda; Kimberly VanderWaal; John Deen; Dominic A Travis
Journal:  Prev Vet Med       Date:  2021-01-05       Impact factor: 2.670

2.  Temporal Dynamics of Co-circulating Lineages of Porcine Reproductive and Respiratory Syndrome Virus.

Authors:  Igor Adolfo Dexheimer Paploski; Cesar Corzo; Albert Rovira; Michael P Murtaugh; Juan Manuel Sanhueza; Carles Vilalta; Declan C Schroeder; Kimberly VanderWaal
Journal:  Front Microbiol       Date:  2019-11-01       Impact factor: 5.640

3.  An investigation of transportation practices in an Ontario swine system using descriptive network analysis.

Authors:  Dylan John Melmer; Terri L O'Sullivan; Amy L Greer; Zvonimir Poljak
Journal:  PLoS One       Date:  2020-01-10       Impact factor: 3.240

4.  Complex network analysis to understand trading partnership in French swine production.

Authors:  Pachka Hammami; Stefan Widgren; Vladimir Grosbois; Andrea Apolloni; Nicolas Rose; Mathieu Andraud
Journal:  PLoS One       Date:  2022-04-07       Impact factor: 3.240

Review 5.  Aerosol Detection and Transmission of Porcine Reproductive and Respiratory Syndrome Virus (PRRSV): What Is the Evidence, and What Are the Knowledge Gaps?

Authors:  Andréia Gonçalves Arruda; Steve Tousignant; Juan Sanhueza; Carles Vilalta; Zvonimir Poljak; Montserrat Torremorell; Carmen Alonso; Cesar A Corzo
Journal:  Viruses       Date:  2019-08-03       Impact factor: 5.048

  5 in total

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