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Estimation of swine movement network at farm level in the US from the Census of Agriculture data

Swine movement networks among farms/operations are an important source of information to understand and prevent the spread of diseases, nearly nonexistent in the United States. An understanding of the movement networks can help the policymakers in planning effective disease control measures. The obj...

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Autores principales: Moon, Sifat A., Ferdousi, Tanvir, Self, Adrian, Scoglio, Caterina M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6470308/
https://www.ncbi.nlm.nih.gov/pubmed/30996237
http://dx.doi.org/10.1038/s41598-019-42616-w
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author Moon, Sifat A.
Ferdousi, Tanvir
Self, Adrian
Scoglio, Caterina M.
author_facet Moon, Sifat A.
Ferdousi, Tanvir
Self, Adrian
Scoglio, Caterina M.
author_sort Moon, Sifat A.
collection PubMed
description Swine movement networks among farms/operations are an important source of information to understand and prevent the spread of diseases, nearly nonexistent in the United States. An understanding of the movement networks can help the policymakers in planning effective disease control measures. The objectives of this work are: (1) estimate swine movement probabilities at the county level from comprehensive anonymous inventory and sales data published by the United States Department of Agriculture - National Agriculture Statistics Service database, (2) develop a network based on those estimated probabilities, and (3) analyze that network using network science metrics. First, we use a probabilistic approach based on the maximum information entropy method to estimate the movement probabilities among different swine populations. Then, we create a swine movement network using the estimated probabilities for the counties of the central agricultural district of Iowa. The analysis of this network has found evidence of the small-world phenomenon. Our study suggests that the US swine industry may be vulnerable to infectious disease outbreaks because of the small-world structure of its movement network. Our system is easily adaptable to estimate movement networks for other sets of data, farm animal production systems, and geographic regions.
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spelling pubmed-64703082019-04-25 Estimation of swine movement network at farm level in the US from the Census of Agriculture data Moon, Sifat A. Ferdousi, Tanvir Self, Adrian Scoglio, Caterina M. Sci Rep Article Swine movement networks among farms/operations are an important source of information to understand and prevent the spread of diseases, nearly nonexistent in the United States. An understanding of the movement networks can help the policymakers in planning effective disease control measures. The objectives of this work are: (1) estimate swine movement probabilities at the county level from comprehensive anonymous inventory and sales data published by the United States Department of Agriculture - National Agriculture Statistics Service database, (2) develop a network based on those estimated probabilities, and (3) analyze that network using network science metrics. First, we use a probabilistic approach based on the maximum information entropy method to estimate the movement probabilities among different swine populations. Then, we create a swine movement network using the estimated probabilities for the counties of the central agricultural district of Iowa. The analysis of this network has found evidence of the small-world phenomenon. Our study suggests that the US swine industry may be vulnerable to infectious disease outbreaks because of the small-world structure of its movement network. Our system is easily adaptable to estimate movement networks for other sets of data, farm animal production systems, and geographic regions. Nature Publishing Group UK 2019-04-17 /pmc/articles/PMC6470308/ /pubmed/30996237 http://dx.doi.org/10.1038/s41598-019-42616-w Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Moon, Sifat A.
Ferdousi, Tanvir
Self, Adrian
Scoglio, Caterina M.
Estimation of swine movement network at farm level in the US from the Census of Agriculture data
title Estimation of swine movement network at farm level in the US from the Census of Agriculture data
title_full Estimation of swine movement network at farm level in the US from the Census of Agriculture data
title_fullStr Estimation of swine movement network at farm level in the US from the Census of Agriculture data
title_full_unstemmed Estimation of swine movement network at farm level in the US from the Census of Agriculture data
title_short Estimation of swine movement network at farm level in the US from the Census of Agriculture data
title_sort estimation of swine movement network at farm level in the us from the census of agriculture data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6470308/
https://www.ncbi.nlm.nih.gov/pubmed/30996237
http://dx.doi.org/10.1038/s41598-019-42616-w
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