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Quantifying predictors for the spatial diffusion of avian influenza virus in China

BACKGROUND: Avian influenza virus (AIV) causes both severe outbreaks and endemic disease among poultry and has caused sporadic human infections in Asia, furthermore the routes of transmission in avian species between geographic regions can be numerous and complex. Using nucleotide sequences from the...

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Autores principales: Lu, Lu, Leigh Brown, Andrew J., Lycett, Samantha J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5237338/
https://www.ncbi.nlm.nih.gov/pubmed/28086751
http://dx.doi.org/10.1186/s12862-016-0845-3
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author Lu, Lu
Leigh Brown, Andrew J.
Lycett, Samantha J.
author_facet Lu, Lu
Leigh Brown, Andrew J.
Lycett, Samantha J.
author_sort Lu, Lu
collection PubMed
description BACKGROUND: Avian influenza virus (AIV) causes both severe outbreaks and endemic disease among poultry and has caused sporadic human infections in Asia, furthermore the routes of transmission in avian species between geographic regions can be numerous and complex. Using nucleotide sequences from the internal protein coding segments of AIV, we performed a Bayesian phylogeographic study to uncover regional routes of transmission and factors predictive of the rate of viral diffusion within China. RESULTS: We found that the Central area and Pan-Pearl River Delta were the two main sources of AIV diffusion, while the East Coast areas especially the Yangtze River delta, were the major targets of viral invasion. Next we investigated the extent to which economic, agricultural, environmental and climatic regional data was predictive of viral diffusion by fitting phylogeographic discrete trait models using generalised linear models. CONCLUSIONS: Our results highlighted that the economic-agricultural predictors, especially the poultry population density and the number of farm product markets, are the key determinants of spatial diffusion of AIV in China; high human density and freight transportation are also important predictors of high rates of viral transmission; Climate features (e.g. temperature) were correlated to the viral invasion in the destination to some degree; while little or no impacts were found from natural environment factors (such as surface water coverage). This study uncovers the risk factors and enhances our understanding of the spatial dynamics of AIV in bird populations. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12862-016-0845-3) contains supplementary material, which is available to authorized users.
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spelling pubmed-52373382017-01-18 Quantifying predictors for the spatial diffusion of avian influenza virus in China Lu, Lu Leigh Brown, Andrew J. Lycett, Samantha J. BMC Evol Biol Research Article BACKGROUND: Avian influenza virus (AIV) causes both severe outbreaks and endemic disease among poultry and has caused sporadic human infections in Asia, furthermore the routes of transmission in avian species between geographic regions can be numerous and complex. Using nucleotide sequences from the internal protein coding segments of AIV, we performed a Bayesian phylogeographic study to uncover regional routes of transmission and factors predictive of the rate of viral diffusion within China. RESULTS: We found that the Central area and Pan-Pearl River Delta were the two main sources of AIV diffusion, while the East Coast areas especially the Yangtze River delta, were the major targets of viral invasion. Next we investigated the extent to which economic, agricultural, environmental and climatic regional data was predictive of viral diffusion by fitting phylogeographic discrete trait models using generalised linear models. CONCLUSIONS: Our results highlighted that the economic-agricultural predictors, especially the poultry population density and the number of farm product markets, are the key determinants of spatial diffusion of AIV in China; high human density and freight transportation are also important predictors of high rates of viral transmission; Climate features (e.g. temperature) were correlated to the viral invasion in the destination to some degree; while little or no impacts were found from natural environment factors (such as surface water coverage). This study uncovers the risk factors and enhances our understanding of the spatial dynamics of AIV in bird populations. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12862-016-0845-3) contains supplementary material, which is available to authorized users. BioMed Central 2017-01-13 /pmc/articles/PMC5237338/ /pubmed/28086751 http://dx.doi.org/10.1186/s12862-016-0845-3 Text en © The Author(s). 2017 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
Lu, Lu
Leigh Brown, Andrew J.
Lycett, Samantha J.
Quantifying predictors for the spatial diffusion of avian influenza virus in China
title Quantifying predictors for the spatial diffusion of avian influenza virus in China
title_full Quantifying predictors for the spatial diffusion of avian influenza virus in China
title_fullStr Quantifying predictors for the spatial diffusion of avian influenza virus in China
title_full_unstemmed Quantifying predictors for the spatial diffusion of avian influenza virus in China
title_short Quantifying predictors for the spatial diffusion of avian influenza virus in China
title_sort quantifying predictors for the spatial diffusion of avian influenza virus in china
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5237338/
https://www.ncbi.nlm.nih.gov/pubmed/28086751
http://dx.doi.org/10.1186/s12862-016-0845-3
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