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Preventive veterinary medicine2012; 106(2); 123-135; doi: 10.1016/j.prevetmed.2012.01.020

Adding the spatial dimension to the social network analysis of an epidemic: investigation of the 2007 outbreak of equine influenza in Australia.

Abstract: Equine influenza is a highly contagious and widespread viral respiratory disease of horses and other equid species, characterised by fever and a harsh dry cough. In 2007, in the first reported outbreak in Australia, the virus spread through the horse populations of two states within 4 months. Most of the geographic spread occurred within the first 10 days and was associated with the movement of infected horses prior to the implementation of movement controls. This study applies social network analysis to describe spread of equine influenza between horse premises infected in the early outbreak period, identifying spread occurring through a contact network and secondary local spatial spread. Social networks were constructed by combining contact-tracing data on horse movements with a distance matrix between all premises holding horses infected within the first 10 days of the outbreak. These networks were analysed to provide a description of the epidemic, identify premises that were central to disease spread and to estimate the relative proportion of premises infected through infected horse movements and through local spatial spread. We then explored the effect of distance on disease spread by estimating the range of local spread (through direct contact, transmission on fomites and windborne transmission) based on the level of fragmentation in the network and also by directly estimating the shape of the outbreak's spatial transmission kernel. During the first 10 days of this epidemic, 197 horse premises were infected; 70 of these were included in the contact-traced network. Most local spread occurred within 5 km. Local spread was estimated to have occurred up to a distance of 15.3 km - based on the contact-and-proximity network - and at a very low incidence beyond this distance based on the transmission kernel estimate. Of the 70 premises in the contact network, spread to 14 premises (95% CI: 9, 20 premises) was likely to have occurred through local spatial spread from nearby infected premises, suggesting that 28.3% of spread in the early epidemic period was 'network-associated' (95% CI: 25.6, 31.0%). By constructing a 'maximal network' of contact and proximity (based on a distance cut-off of 15.3 km), 44 spatial clusters were described, and the horse movements that initiated infection in these locations were identified. Characteristics of the combined network, incorporating both spatial and underlying contact relationships between infected premises, explained the high rate of spread, the sequence of cluster formation and the widespread dispersal experienced in the early phase of this epidemic. These results can inform outbreak control planning by guiding the imposition of appropriate control zone diameters around infected premises and the targeting of surveillance and interventions.
Copyright © 2012 Elsevier B.V. All rights reserved.
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Publication Date: 2012-02-23 PubMed ID: 22365721PubMed Central: PMC7126086DOI: 10.1016/j.prevetmed.2012.01.020Google Scholar: Lookup
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Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

The study uses social network analysis to examine how the 2007 outbreak of equine influenza in Australia spread amongst horse populations. The study reveals that both the movement of infected horses and local spatial spread contributed to the dispersion of the virus.

Understanding the Study

  • The research looks into the outbreak of equine influenza in Australia in 2007, which affected horse populations in two states within four months.
  • It applies social network analysis as a tool to describe how the disease has spread between different horse premises (farms, stables, etc.), spotlighting the spread through both a contact network (infected horse movement) and secondary, local spatial spread.
  • The social network was constructed using data from contact-tracing of horse movements and a derived distance matrix regarding all the premises harbouring infected horses during the first 10-days of the outbreak.

Analyzing the Spreading of Disease

  • This analysis helps provide a detailed description of the epidemic, highlights specific premises that were central to disease spread, and estimates the relative proportion of premises infected through horse movement and local spatial dispersion.
  • The researchers explored the effect of distance on disease spread by estimating the range of local spread through direct contact, transmission on fomites (objects carrying the virus), and windborne transmission, relying on the level of fragmentation in the network and an estimate of the outbreak’s spatial transmission kernel (a mathematical representation of disease spread).

Results and Implications

  • In the first 10 days of the epidemic, 197 horse premises were infected. Of the 70 premises included in the contact-traced network, the spread to 14 premises was likely due to local spatial spreading from nearby infected premises.
  • Features of the combined network, which includes both spatial and underlying contact correlations between infected premises, account for the rapid spread, sequence of cluster formation, and widespread dispersion observed in the early stages of this epidemic.
  • The study’s findings can inform outbreak control planning, guiding decisions such as the size of control zones around infected premises and the direction of surveillance and interventions.

Cite This Article

APA
Firestone SM, Christley RM, Ward MP, Dhand NK. (2012). Adding the spatial dimension to the social network analysis of an epidemic: investigation of the 2007 outbreak of equine influenza in Australia. Prev Vet Med, 106(2), 123-135. https://doi.org/10.1016/j.prevetmed.2012.01.020

Publication

Preventive veterinary medicine
ISSN: 1873-1716
NlmUniqueID: 8217463
Country: Netherlands
Language: English
Volume: 106
Issue: 2
Pages: 123-135

Researcher Affiliations

Firestone, Simon M
  • Faculty of Veterinary Science, The University of Sydney, 425 Werombi Road, Camden, NSW 2570, Australia.
Christley, Robert M
    Ward, Michael P
      Dhand, Navneet K

        MeSH Terms

        • Animals
        • Australia / epidemiology
        • Contact Tracing / methods
        • Contact Tracing / veterinary
        • Disease Outbreaks / veterinary
        • Horse Diseases / epidemiology
        • Horse Diseases / transmission
        • Horse Diseases / virology
        • Horses
        • Incidence
        • Influenza A Virus, H3N8 Subtype / physiology
        • Orthomyxoviridae Infections / epidemiology
        • Orthomyxoviridae Infections / transmission
        • Orthomyxoviridae Infections / veterinary
        • Orthomyxoviridae Infections / virology
        • Transportation

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