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A new bovine tuberculosis model for England and Wales (BoTMEW) to simulate epidemiology, surveillance and control
BACKGROUND: Bovine tuberculosis (bTB) is a zoonotic disease of cattle caused by Mycobacterium bovis, widespread in England and Wales. It has high incidence towards the South West of England and Wales, with much lower incidence to the East and North. A stochastic simulation model was developed to sim...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6122770/ https://www.ncbi.nlm.nih.gov/pubmed/30176863 http://dx.doi.org/10.1186/s12917-018-1595-9 |
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author | Birch, Colin P. D. Goddard, Ashley Tearne, Oliver |
author_facet | Birch, Colin P. D. Goddard, Ashley Tearne, Oliver |
author_sort | Birch, Colin P. D. |
collection | PubMed |
description | BACKGROUND: Bovine tuberculosis (bTB) is a zoonotic disease of cattle caused by Mycobacterium bovis, widespread in England and Wales. It has high incidence towards the South West of England and Wales, with much lower incidence to the East and North. A stochastic simulation model was developed to simulate M. bovis transmission among cattle, transfer by cattle movements and transmission from environmental reservoirs (often wildlife and especially badgers). It distinguishes five surveillance streams, including herd tests, pre-movement testing and slaughter surveillance. The model thereby simulates interventions in bTB surveillance and control, and generates outputs directly comparable to detailed disease records. An anonymized version of the executable model with its input data has been released. The model was fitted to cattle bTB records for 2008–2010 in a cross-sectional comparison, and its projection was compared with records from 2010 to 2016 for validation. RESULTS: The fitted model explained over 99% of the variation among numbers of breakdowns in four defined regions and surveillance streams in 2010. It classified 7800 (95% confidence interval c. 5500 – 14,000) holdings within high incidence regions as exposed to infectious environmental reservoirs, out of over 31,000 cattle holdings identified as potentially exposed to such sources. The model was consistent with previous estimates of low M. bovis transmission rate among cattle, but cattle to cattle transmission was clearly required to generate the number of cattle cases observed. When projected to 2016, the model as fitted to 2010 continued to match the distribution of bTB among counties, although it was notable that the actual distribution of bTB in 2010 was itself a close match for its distribution in 2016. CONCLUSIONS: The close model fit demonstrated that cattle movements could generate breakdowns as observed in low incidence regions, if persistent environmental reservoirs such as wildlife maintained infection levels in the high incidence regions. The model suggests that environmental reservoirs may be a challenge for control, because, although many holdings are exposed to infection from wildlife or the environment, they are a minority of holdings. Large impacts on disease in wildlife will be required to avoid each individual transmission event to cattle. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12917-018-1595-9) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6122770 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-61227702018-09-10 A new bovine tuberculosis model for England and Wales (BoTMEW) to simulate epidemiology, surveillance and control Birch, Colin P. D. Goddard, Ashley Tearne, Oliver BMC Vet Res Research Article BACKGROUND: Bovine tuberculosis (bTB) is a zoonotic disease of cattle caused by Mycobacterium bovis, widespread in England and Wales. It has high incidence towards the South West of England and Wales, with much lower incidence to the East and North. A stochastic simulation model was developed to simulate M. bovis transmission among cattle, transfer by cattle movements and transmission from environmental reservoirs (often wildlife and especially badgers). It distinguishes five surveillance streams, including herd tests, pre-movement testing and slaughter surveillance. The model thereby simulates interventions in bTB surveillance and control, and generates outputs directly comparable to detailed disease records. An anonymized version of the executable model with its input data has been released. The model was fitted to cattle bTB records for 2008–2010 in a cross-sectional comparison, and its projection was compared with records from 2010 to 2016 for validation. RESULTS: The fitted model explained over 99% of the variation among numbers of breakdowns in four defined regions and surveillance streams in 2010. It classified 7800 (95% confidence interval c. 5500 – 14,000) holdings within high incidence regions as exposed to infectious environmental reservoirs, out of over 31,000 cattle holdings identified as potentially exposed to such sources. The model was consistent with previous estimates of low M. bovis transmission rate among cattle, but cattle to cattle transmission was clearly required to generate the number of cattle cases observed. When projected to 2016, the model as fitted to 2010 continued to match the distribution of bTB among counties, although it was notable that the actual distribution of bTB in 2010 was itself a close match for its distribution in 2016. CONCLUSIONS: The close model fit demonstrated that cattle movements could generate breakdowns as observed in low incidence regions, if persistent environmental reservoirs such as wildlife maintained infection levels in the high incidence regions. The model suggests that environmental reservoirs may be a challenge for control, because, although many holdings are exposed to infection from wildlife or the environment, they are a minority of holdings. Large impacts on disease in wildlife will be required to avoid each individual transmission event to cattle. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12917-018-1595-9) contains supplementary material, which is available to authorized users. BioMed Central 2018-09-04 /pmc/articles/PMC6122770/ /pubmed/30176863 http://dx.doi.org/10.1186/s12917-018-1595-9 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Birch, Colin P. D. Goddard, Ashley Tearne, Oliver A new bovine tuberculosis model for England and Wales (BoTMEW) to simulate epidemiology, surveillance and control |
title | A new bovine tuberculosis model for England and Wales (BoTMEW) to simulate epidemiology, surveillance and control |
title_full | A new bovine tuberculosis model for England and Wales (BoTMEW) to simulate epidemiology, surveillance and control |
title_fullStr | A new bovine tuberculosis model for England and Wales (BoTMEW) to simulate epidemiology, surveillance and control |
title_full_unstemmed | A new bovine tuberculosis model for England and Wales (BoTMEW) to simulate epidemiology, surveillance and control |
title_short | A new bovine tuberculosis model for England and Wales (BoTMEW) to simulate epidemiology, surveillance and control |
title_sort | new bovine tuberculosis model for england and wales (botmew) to simulate epidemiology, surveillance and control |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6122770/ https://www.ncbi.nlm.nih.gov/pubmed/30176863 http://dx.doi.org/10.1186/s12917-018-1595-9 |
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