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Dynamics of the 2004 avian influenza H5N1 outbreak in Thailand: The role of duck farming, sequential model fitting and control
The Highly Pathogenic Avian Influenza (HPAI) subtype H5N1 virus persists in many countries and has been circulating in poultry, wild birds. In addition, the virus has emerged in other species and frequent zoonotic spillover events indicate that there remains a significant risk to human health. It is...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Scientific Publishing
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6193140/ https://www.ncbi.nlm.nih.gov/pubmed/30314780 http://dx.doi.org/10.1016/j.prevetmed.2018.09.014 |
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author | Retkute, Renata Jewell, Chris P. Van Boeckel, Thomas P. Zhang, Geli Xiao, Xiangming Thanapongtharm, Weerapong Keeling, Matt Gilbert, Marius Tildesley, Michael J. |
author_facet | Retkute, Renata Jewell, Chris P. Van Boeckel, Thomas P. Zhang, Geli Xiao, Xiangming Thanapongtharm, Weerapong Keeling, Matt Gilbert, Marius Tildesley, Michael J. |
author_sort | Retkute, Renata |
collection | PubMed |
description | The Highly Pathogenic Avian Influenza (HPAI) subtype H5N1 virus persists in many countries and has been circulating in poultry, wild birds. In addition, the virus has emerged in other species and frequent zoonotic spillover events indicate that there remains a significant risk to human health. It is crucial to understand the dynamics of the disease in the poultry industry to develop a more comprehensive knowledge of the risks of transmission and to establish a better distribution of resources when implementing control. In this paper, we develop a set of mathematical models that simulate the spread of HPAI H5N1 in the poultry industry in Thailand, utilising data from the 2004 epidemic. The model that incorporates the intensity of duck farming when assessing transmision risk provides the best fit to the spatiotemporal characteristics of the observed outbreak, implying that intensive duck farming drives transmission of HPAI in Thailand. We also extend our models using a sequential model fitting approach to explore the ability of the models to be used in “real time” during novel disease outbreaks. We conclude that, whilst predictions of epidemic size are estimated poorly in the early stages of disease outbreaks, the model can infer the preferred control policy that should be deployed to minimise the impact of the disease. |
format | Online Article Text |
id | pubmed-6193140 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Elsevier Scientific Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-61931402018-11-01 Dynamics of the 2004 avian influenza H5N1 outbreak in Thailand: The role of duck farming, sequential model fitting and control Retkute, Renata Jewell, Chris P. Van Boeckel, Thomas P. Zhang, Geli Xiao, Xiangming Thanapongtharm, Weerapong Keeling, Matt Gilbert, Marius Tildesley, Michael J. Prev Vet Med Article The Highly Pathogenic Avian Influenza (HPAI) subtype H5N1 virus persists in many countries and has been circulating in poultry, wild birds. In addition, the virus has emerged in other species and frequent zoonotic spillover events indicate that there remains a significant risk to human health. It is crucial to understand the dynamics of the disease in the poultry industry to develop a more comprehensive knowledge of the risks of transmission and to establish a better distribution of resources when implementing control. In this paper, we develop a set of mathematical models that simulate the spread of HPAI H5N1 in the poultry industry in Thailand, utilising data from the 2004 epidemic. The model that incorporates the intensity of duck farming when assessing transmision risk provides the best fit to the spatiotemporal characteristics of the observed outbreak, implying that intensive duck farming drives transmission of HPAI in Thailand. We also extend our models using a sequential model fitting approach to explore the ability of the models to be used in “real time” during novel disease outbreaks. We conclude that, whilst predictions of epidemic size are estimated poorly in the early stages of disease outbreaks, the model can infer the preferred control policy that should be deployed to minimise the impact of the disease. Elsevier Scientific Publishing 2018-11-01 /pmc/articles/PMC6193140/ /pubmed/30314780 http://dx.doi.org/10.1016/j.prevetmed.2018.09.014 Text en © 2018 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Article Retkute, Renata Jewell, Chris P. Van Boeckel, Thomas P. Zhang, Geli Xiao, Xiangming Thanapongtharm, Weerapong Keeling, Matt Gilbert, Marius Tildesley, Michael J. Dynamics of the 2004 avian influenza H5N1 outbreak in Thailand: The role of duck farming, sequential model fitting and control |
title | Dynamics of the 2004 avian influenza H5N1 outbreak in Thailand: The role of duck farming, sequential model fitting and control |
title_full | Dynamics of the 2004 avian influenza H5N1 outbreak in Thailand: The role of duck farming, sequential model fitting and control |
title_fullStr | Dynamics of the 2004 avian influenza H5N1 outbreak in Thailand: The role of duck farming, sequential model fitting and control |
title_full_unstemmed | Dynamics of the 2004 avian influenza H5N1 outbreak in Thailand: The role of duck farming, sequential model fitting and control |
title_short | Dynamics of the 2004 avian influenza H5N1 outbreak in Thailand: The role of duck farming, sequential model fitting and control |
title_sort | dynamics of the 2004 avian influenza h5n1 outbreak in thailand: the role of duck farming, sequential model fitting and control |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6193140/ https://www.ncbi.nlm.nih.gov/pubmed/30314780 http://dx.doi.org/10.1016/j.prevetmed.2018.09.014 |
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