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Using social network analysis to inform disease control interventions.

Nelly Marquetoux1, Mark A Stevenson2, Peter Wilson3

  • 1EpiCentre, Institute of Veterinary, Animal and Biomedical Sciences, Massey University, New Zealand.

Preventive Veterinary Medicine
|February 18, 2016
PubMed
Summary
This summary is machine-generated.

Analyzing livestock movement networks in New Zealand reveals that a few central farms can drive disease spread. However, targeted removal of key "bridge" farms can fragment the network and prevent large epidemics.

Keywords:
Basic reproduction ratioControl strategiesEpidemiologyInfectious diseases dynamicsLivestock movementsNetwork analysis

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Area of Science:

  • Veterinary Epidemiology
  • Mathematical Biology
  • Animal Health Management

Background:

  • Infectious disease transmission is heavily influenced by contact patterns within populations.
  • Social network analysis (SNA) is a valuable tool for understanding pathogen spread by mapping these contacts.
  • Effective disease control strategies rely on understanding population-level contact dynamics.

Purpose of the Study:

  • To apply SNA to a livestock movement network in New Zealand to identify key characteristics relevant to disease control.
  • To explore how network structure influences the potential spread of infectious diseases in animal populations.
  • To inform the development of targeted disease control programs based on network analysis.

Main Methods:

  • Social network analysis (SNA) was employed to map livestock movements.
  • Data from 180 New Zealand farms between 2006 and 2010 were analyzed.
  • Network metrics were used to identify central farms and network bridges.

Main Results:

  • The livestock trading network exhibited consistent annual contact numbers but variable trading partners.
  • A small subset of central farms demonstrated a significant potential to facilitate widespread infection.
  • Network fragmentation was achievable by removing a small proportion of "bridge" farms, reducing epidemic potential.

Conclusions:

  • Understanding livestock movement networks is crucial for developing risk-based disease control strategies.
  • Targeted interventions, informed by SNA, can effectively mitigate infectious disease spread in animal populations.
  • This study provides a comprehensive analysis of pastoral livestock movements in New Zealand for disease prevention and monitoring.