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Predicting the risk of avian influenza A H7N9 infection in live-poultry markets across Asia

Two epidemic waves of an avian influenza A (H7N9) virus have so far affected China. Most human cases have been attributable to poultry exposure at live-poultry markets, where most positive isolates were sampled. The potential geographic extent of potential re-emerging epidemics is unknown, as are th...

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Autores principales: Gilbert, Marius, Golding, Nick, Zhou, Hang, Wint, G. R. William, Robinson, Timothy P., Tatem, Andrew J., Lai, Shengjie, Zhou, Sheng, Jiang, Hui, Guo, Danhuai, Huang, Zhi, Messina, Jane P., Xiao, Xiangming, Linard, Catherine, Van Boeckel, Thomas P., Martin, Vincent, Bhatt, Samir, Gething, Peter W., Farrar, Jeremy J., Hay, Simon I., Yu, Hongjie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4061699/
https://www.ncbi.nlm.nih.gov/pubmed/24937647
http://dx.doi.org/10.1038/ncomms5116
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author Gilbert, Marius
Golding, Nick
Zhou, Hang
Wint, G. R. William
Robinson, Timothy P.
Tatem, Andrew J.
Lai, Shengjie
Zhou, Sheng
Jiang, Hui
Guo, Danhuai
Huang, Zhi
Messina, Jane P.
Xiao, Xiangming
Linard, Catherine
Van Boeckel, Thomas P.
Martin, Vincent
Bhatt, Samir
Gething, Peter W.
Farrar, Jeremy J.
Hay, Simon I.
Yu, Hongjie
author_facet Gilbert, Marius
Golding, Nick
Zhou, Hang
Wint, G. R. William
Robinson, Timothy P.
Tatem, Andrew J.
Lai, Shengjie
Zhou, Sheng
Jiang, Hui
Guo, Danhuai
Huang, Zhi
Messina, Jane P.
Xiao, Xiangming
Linard, Catherine
Van Boeckel, Thomas P.
Martin, Vincent
Bhatt, Samir
Gething, Peter W.
Farrar, Jeremy J.
Hay, Simon I.
Yu, Hongjie
author_sort Gilbert, Marius
collection PubMed
description Two epidemic waves of an avian influenza A (H7N9) virus have so far affected China. Most human cases have been attributable to poultry exposure at live-poultry markets, where most positive isolates were sampled. The potential geographic extent of potential re-emerging epidemics is unknown, as are the factors associated with it. Using newly assembled data sets of the locations of 8,943 live-poultry markets in China and maps of environmental correlates, we develop a statistical model that accurately predicts the risk of H7N9 market infection across Asia. Local density of live-poultry markets is the most important predictor of H7N9 infection risk in markets, underscoring their key role in the spatial epidemiology of H7N9, alongside other poultry, land cover and anthropogenic predictor variables. Identification of areas in Asia with high suitability for H7N9 infection enhances our capacity to target biosurveillance and control, helping to restrict the spread of this important disease.
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spelling pubmed-40616992014-07-10 Predicting the risk of avian influenza A H7N9 infection in live-poultry markets across Asia Gilbert, Marius Golding, Nick Zhou, Hang Wint, G. R. William Robinson, Timothy P. Tatem, Andrew J. Lai, Shengjie Zhou, Sheng Jiang, Hui Guo, Danhuai Huang, Zhi Messina, Jane P. Xiao, Xiangming Linard, Catherine Van Boeckel, Thomas P. Martin, Vincent Bhatt, Samir Gething, Peter W. Farrar, Jeremy J. Hay, Simon I. Yu, Hongjie Nat Commun Article Two epidemic waves of an avian influenza A (H7N9) virus have so far affected China. Most human cases have been attributable to poultry exposure at live-poultry markets, where most positive isolates were sampled. The potential geographic extent of potential re-emerging epidemics is unknown, as are the factors associated with it. Using newly assembled data sets of the locations of 8,943 live-poultry markets in China and maps of environmental correlates, we develop a statistical model that accurately predicts the risk of H7N9 market infection across Asia. Local density of live-poultry markets is the most important predictor of H7N9 infection risk in markets, underscoring their key role in the spatial epidemiology of H7N9, alongside other poultry, land cover and anthropogenic predictor variables. Identification of areas in Asia with high suitability for H7N9 infection enhances our capacity to target biosurveillance and control, helping to restrict the spread of this important disease. Nature Publishing Group 2014-06-17 /pmc/articles/PMC4061699/ /pubmed/24937647 http://dx.doi.org/10.1038/ncomms5116 Text en Copyright © 2014, Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved. http://creativecommons.org/licenses/by-nc-by/3.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Gilbert, Marius
Golding, Nick
Zhou, Hang
Wint, G. R. William
Robinson, Timothy P.
Tatem, Andrew J.
Lai, Shengjie
Zhou, Sheng
Jiang, Hui
Guo, Danhuai
Huang, Zhi
Messina, Jane P.
Xiao, Xiangming
Linard, Catherine
Van Boeckel, Thomas P.
Martin, Vincent
Bhatt, Samir
Gething, Peter W.
Farrar, Jeremy J.
Hay, Simon I.
Yu, Hongjie
Predicting the risk of avian influenza A H7N9 infection in live-poultry markets across Asia
title Predicting the risk of avian influenza A H7N9 infection in live-poultry markets across Asia
title_full Predicting the risk of avian influenza A H7N9 infection in live-poultry markets across Asia
title_fullStr Predicting the risk of avian influenza A H7N9 infection in live-poultry markets across Asia
title_full_unstemmed Predicting the risk of avian influenza A H7N9 infection in live-poultry markets across Asia
title_short Predicting the risk of avian influenza A H7N9 infection in live-poultry markets across Asia
title_sort predicting the risk of avian influenza a h7n9 infection in live-poultry markets across asia
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4061699/
https://www.ncbi.nlm.nih.gov/pubmed/24937647
http://dx.doi.org/10.1038/ncomms5116
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