Automatic classification of farms and traders in the pig production chain

Automatic classification of farms and traders in the pig production chain The trade in live pigs is an essential risk factor in the spread of animal diseases. Traders play a key role in the trade network, as they are logistics hubs and responsible for large animal movements. In order to implement targeted control measures in case of a disease outbreak, it is hence strongly advisable to use information about the holding type in the pig production chain. However, in many datasets the types of the producing farms or the fact whether the agent is a trader are unknown.In this paper we introduce two indices that can be used to identify the position of a producing farm in the pig production chain and more importantly, identify traders. This was realized partially through a novel dynamic programming algorithm. Analyzing the pig trade network in Germany from 2005 to 2007, we demonstrate that our algorithm is very sensitive in detecting traders. Since the methodology can easily be applied to trade networks in other countries with similar infrastructure and legislation, we anticipate its use for augmenting the datasets in further network analyses and targeting control measures. For further usage, we have developed an R package which can be found in the supplementary material to this manuscript. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Preventive Veterinary Medicine Elsevier

Automatic classification of farms and traders in the pig production chain

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Publisher
Elsevier
Copyright
Copyright © 2017 Elsevier B.V.
ISSN
0167-5877
eISSN
1873-1716
D.O.I.
10.1016/j.prevetmed.2017.12.003
Publisher site
See Article on Publisher Site

Abstract

The trade in live pigs is an essential risk factor in the spread of animal diseases. Traders play a key role in the trade network, as they are logistics hubs and responsible for large animal movements. In order to implement targeted control measures in case of a disease outbreak, it is hence strongly advisable to use information about the holding type in the pig production chain. However, in many datasets the types of the producing farms or the fact whether the agent is a trader are unknown.In this paper we introduce two indices that can be used to identify the position of a producing farm in the pig production chain and more importantly, identify traders. This was realized partially through a novel dynamic programming algorithm. Analyzing the pig trade network in Germany from 2005 to 2007, we demonstrate that our algorithm is very sensitive in detecting traders. Since the methodology can easily be applied to trade networks in other countries with similar infrastructure and legislation, we anticipate its use for augmenting the datasets in further network analyses and targeting control measures. For further usage, we have developed an R package which can be found in the supplementary material to this manuscript.

Journal

Preventive Veterinary MedicineElsevier

Published: Feb 1, 2018

References

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