Social-network analysis of Mycobacterium bovis transmission among captive brushtail possums (Trichosurus vulpecula)

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Detail(s)

Original languageEnglish
Pages (from-to)147-167
Journal / PublicationPreventive Veterinary Medicine
Volume59
Issue number3
Publication statusPublished - 12 Jun 2003
Externally publishedYes

Abstract

Wild brushtail possums (Trichosurus vulpecula) are the main source of Mycobacterium bovis infection for New Zealand livestock. The disease is spread principally by infectious aerosol; therefore, social interactions determine disease transmission. In captive possums, den-sharing behaviour provided the greatest risk of tuberculosis transmission between animals. Den sharing between individual possums was used as the basic measurement for quantifying close proximity between animals over extended periods. Social-network analysis (SNA) was used to model patterns of social behaviour and to predict tuberculosis transmission. There was great diversity between groups in their social behaviour - but there were consistent trends in the SNA measures (closeness and flow-betweenness). With time, the social distance between possums in the same group increased, the social network became more homogeneous and the possums less differentiated from each other. Alteration of the physical environment of the pens (such as changing the number of dens or relocating the group to a new pen) had an inconsistent effect on social structure when comparing different groups. During the infection-transmission study, the possums that became infected had greater closeness and flow-betweenness scores than those that remained free of infection. Although standard statistical descriptive measures (such as the number of partners and the frequency of den-sharing events) were greater for the infected than the infection-free possums, the SNA-specific measures were more precise and could be compared across time and between groups. © 2003 Elsevier Science B.V. All rights reserved.

Research Area(s)

  • Bovine tuberculosis, Brushtail possum, Disease transmission, Social-network analysis, Wildlife diseases