4.6 Article

Analyses of Contact Networks of Community Dogs on a University Campus in Nakhon Pathom, Thailand

期刊

VETERINARY SCIENCES
卷 8, 期 12, 页码 -

出版社

MDPI
DOI: 10.3390/vetsci8120299

关键词

free-roaming dogs; contact network; network analysis

资金

  1. Saving Animal and Human Lives from Rabies Project following the Determination of HRH Princess Chulabhorn
  2. Faculty of Veterinary Medicine, Kasetsart University while conducting the research in Thailand
  3. Canada-ASEAN Scholarships
  4. Educational Exchanges for Development (SEED) scholarship from Global Affairs Canada

向作者/读者索取更多资源

This study explored the contact network of free-roaming dogs on a university campus and uncovered characteristics of the dog population, such as average contacts and small-world network properties. The acquired network information can be utilized in designing targeted disease control programs.
Free-roaming dogs have been identified as an important reservoir of rabies in many countries including Thailand. There is a need for novel insights to improve current rabies control strategies in these countries. Network analysis is commonly used to study the interactions between individuals or organizations and has been applied in preventive veterinary medicine. However, contact networks of domestic free-roaming dogs are mostly unexplored. The objective of this study was to explore the contact network of free-roaming dogs residing on a university campus. Three one-mode networks were created using co-appearances of dogs as edges. A two-mode network was created by associating the dog with the pre-defined area it was seen in. The average number of contacts a dog had was 6.74. The normalized degree for the weekend network was significantly higher compared to the weekday network. All one-mode networks displayed small-world network characteristics. Most dogs were observed in only one area. The average number of dogs which shared an area was 8.67. In this study, we demonstrated the potential of observational methods to create networks of contacts. The network information acquired can be further used in network modeling and designing targeted disease control programs.

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