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Modelling farm-to-farm disease transmission through personnel movements: from visits to contacts, and back
Infectious diseases in livestock can be transmitted through fomites: objects able to convey infectious agents. Between-farm spread of infections through fomites is mostly due to indirect contacts generated by on-farm visits of personnel that can carry pathogens on their clothes, equipment, or vehicl...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5443770/ https://www.ncbi.nlm.nih.gov/pubmed/28539663 http://dx.doi.org/10.1038/s41598-017-02567-6 |
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author | Rossi, Gianluigi Smith, Rebecca L. Pongolini, Stefano Bolzoni, Luca |
author_facet | Rossi, Gianluigi Smith, Rebecca L. Pongolini, Stefano Bolzoni, Luca |
author_sort | Rossi, Gianluigi |
collection | PubMed |
description | Infectious diseases in livestock can be transmitted through fomites: objects able to convey infectious agents. Between-farm spread of infections through fomites is mostly due to indirect contacts generated by on-farm visits of personnel that can carry pathogens on their clothes, equipment, or vehicles. However, data on farm visitors are often difficult to obtain because of the heterogeneity of their nature and privacy issues. Thus, models simulating disease spread between farms usually rely on strong assumptions about the contribution of indirect contacts on infection spread. By using data on veterinarian on-farm visits in a dairy farm system, we built a simple simulation model to assess the role of indirect contacts on epidemic dynamics compared to cattle movements (i.e. direct contacts). We showed that including in the simulation model only specific subsets of the information available on indirect contacts could lead to outputs widely different from those obtained with the full-information model. Then, we provided a simple preferential attachment algorithm based on the probability to observe consecutive on-farm visits from the same operator that allows overcoming the information gaps. Our results suggest the importance of detailed data and a deeper understanding of visit dynamics for the prevention and control of livestock diseases. |
format | Online Article Text |
id | pubmed-5443770 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-54437702017-05-26 Modelling farm-to-farm disease transmission through personnel movements: from visits to contacts, and back Rossi, Gianluigi Smith, Rebecca L. Pongolini, Stefano Bolzoni, Luca Sci Rep Article Infectious diseases in livestock can be transmitted through fomites: objects able to convey infectious agents. Between-farm spread of infections through fomites is mostly due to indirect contacts generated by on-farm visits of personnel that can carry pathogens on their clothes, equipment, or vehicles. However, data on farm visitors are often difficult to obtain because of the heterogeneity of their nature and privacy issues. Thus, models simulating disease spread between farms usually rely on strong assumptions about the contribution of indirect contacts on infection spread. By using data on veterinarian on-farm visits in a dairy farm system, we built a simple simulation model to assess the role of indirect contacts on epidemic dynamics compared to cattle movements (i.e. direct contacts). We showed that including in the simulation model only specific subsets of the information available on indirect contacts could lead to outputs widely different from those obtained with the full-information model. Then, we provided a simple preferential attachment algorithm based on the probability to observe consecutive on-farm visits from the same operator that allows overcoming the information gaps. Our results suggest the importance of detailed data and a deeper understanding of visit dynamics for the prevention and control of livestock diseases. Nature Publishing Group UK 2017-05-24 /pmc/articles/PMC5443770/ /pubmed/28539663 http://dx.doi.org/10.1038/s41598-017-02567-6 Text en © The Author(s) 2017 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 Rossi, Gianluigi Smith, Rebecca L. Pongolini, Stefano Bolzoni, Luca Modelling farm-to-farm disease transmission through personnel movements: from visits to contacts, and back |
title | Modelling farm-to-farm disease transmission through personnel movements: from visits to contacts, and back |
title_full | Modelling farm-to-farm disease transmission through personnel movements: from visits to contacts, and back |
title_fullStr | Modelling farm-to-farm disease transmission through personnel movements: from visits to contacts, and back |
title_full_unstemmed | Modelling farm-to-farm disease transmission through personnel movements: from visits to contacts, and back |
title_short | Modelling farm-to-farm disease transmission through personnel movements: from visits to contacts, and back |
title_sort | modelling farm-to-farm disease transmission through personnel movements: from visits to contacts, and back |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5443770/ https://www.ncbi.nlm.nih.gov/pubmed/28539663 http://dx.doi.org/10.1038/s41598-017-02567-6 |
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