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Transbound Emerg Dis. 2018 Dec;65(6):1909-1919. doi: 10.1111/tbed.12972. Epub 2018 Sep 8.

Social network analysis for poultry HPAI transmission.

Author information

1
China Animal Health and Epidemiology Center, Qingdao, China.
2
Queensland Centre for Emerging Infectious Diseases, Biosecurity Queensland, Brisbane, QLD, Australia.
3
Anhui Animal Disease Prevent and Control Center, Hefei, China.
4
Liaoning Province Animal Husbandry and Veterinary Bureau, Liaoning, China.
5
Beizhen Animal Disease Prevent and Control Center, Liaoning, China.
6
Feixi Animal Disease Prevent and Control Center, Anhui, China.
7
MorVet Ltd, Palmerston North, New Zealand.

Abstract

In this survey study, the networks among poultry farms and related poultry enterprises in two counties in China (Feixi County in Anhui Province and Beizhen city in Liaoning Province) were analysed and evaluated focusing on the connectivity of contacts, movements, and potential pathogen transmission. The Feixi County poultry production network exhibited greater connectivity, which incorporated approximately 94% of the farms interviewed in a major component (a set of connected farms not linked with each other), mainly due to linkages of backyard farms through local produce stores and individual agents, whilst the Beizhen City network was more fragmented owing to independent in-house operations (from breed, raise, to slaughter and process) of a few large companies, with multiple smaller components. A range of factors influencing the contacts/movements among farms (act as bridges) were identified in this study. Ability to predict the pathway with the network characteristics on the basis of the factors, such as entity type and geographic location, is useful for developing risk-based approaches for disease prevention, surveillance, early detection, and effective controlling.

KEYWORDS:

HPAI; movement pattern; poultry; risk evaluation; social network analysis

PMID:
30194915
DOI:
10.1111/tbed.12972
[Indexed for MEDLINE]

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