Literature DB >> 30220398

Exponential random graph models to evaluate the movement of backyard chickens after the avian influenza crisis in 2004-2005, Thailand.

Chaithep Poolkhet1, Kohei Makita2, Sukanya Thongratsakul3, Kansuda Leelehapongsathon3.   

Abstract

The aim of this study was to use exponential random graph models (ERGMs) to explain networks of movement of backyard chickens in provinces which had been hotspots for avian influenza outbreaks in Thailand during 2004-2005. We used structured questionnaires to collect data for the period January to December 2009 from participants who were involved in the backyard chicken farming network in three avian influenza hotspots (Ratchaburi, Suphan Buri, and Nakhon Pathom provinces) in Thailand. From 557 questionnaires, we identified nodes, points of entry and exit from nodes, and activities relating to backyard chicken farming and movement of chickens, and generated ERGMs based on non-festive periods (Model 1) and the Chinese New Year period (Model 2). In Model 1, k-star (the central node is connected to k other nodes) connections were predominant (P <  0.001). In Model 2, the frequency of movement increased by 10.62 times, k-star connections were still predominant (P <  0.001), and the model was scale-free. Hubs were formed from owners/observers in the arenas/training fields, farmers who raised chickens for consumption only, and traders. In conclusion, our models indicated that, if avian influenza was introduced during non-festive periods, the authorities would need to regularly restrict the movement of chickens. However, during high-frequency periods of movement of backyard chickens, authorities would also need to focus on the network hubs. Our research can be used by the relevant authorities to improve control measures and reduce the risk or lessen the magnitude of disease spread during an avian influenza epidemic.
Copyright © 2018 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Avian influenza; Backyard chicken; Exponential random graph model; Network analysis; Thailand

Mesh:

Year:  2018        PMID: 30220398     DOI: 10.1016/j.prevetmed.2018.07.015

Source DB:  PubMed          Journal:  Prev Vet Med        ISSN: 0167-5877            Impact factor:   2.670


  1 in total

1.  Complex network analysis to understand trading partnership in French swine production.

Authors:  Pachka Hammami; Stefan Widgren; Vladimir Grosbois; Andrea Apolloni; Nicolas Rose; Mathieu Andraud
Journal:  PLoS One       Date:  2022-04-07       Impact factor: 3.240

  1 in total

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