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Anticipating the Prevalence of Avian Influenza Subtypes H9 and H5 in Live-Bird Markets
An ability to forecast the prevalence of specific subtypes of avian influenza viruses (AIV) in live-bird markets would facilitate greatly the implementation of preventative measures designed to minimize poultry losses and human exposure. The minimum requirement for developing predictive quantitative...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3567063/ https://www.ncbi.nlm.nih.gov/pubmed/23409145 http://dx.doi.org/10.1371/journal.pone.0056157 |
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author | Pepin, Kim M. Wang, Jia Webb, Colleen T. Hoeting, Jennifer A. Poss, Mary Hudson, Peter J. Hong, Wenshan Zhu, Huachen Guan, Yi Riley, Steven |
author_facet | Pepin, Kim M. Wang, Jia Webb, Colleen T. Hoeting, Jennifer A. Poss, Mary Hudson, Peter J. Hong, Wenshan Zhu, Huachen Guan, Yi Riley, Steven |
author_sort | Pepin, Kim M. |
collection | PubMed |
description | An ability to forecast the prevalence of specific subtypes of avian influenza viruses (AIV) in live-bird markets would facilitate greatly the implementation of preventative measures designed to minimize poultry losses and human exposure. The minimum requirement for developing predictive quantitative tools is surveillance data of AIV prevalence sampled frequently over several years. Recently, a 4-year time series of monthly sampling of hemagglutinin subtypes 1–13 in ducks, chickens and quail in live-bird markets in southern China has become available. We used these data to investigate whether a simple statistical model, based solely on historical data (variables such as the number of positive samples in host X of subtype Y time t months ago), could accurately predict prevalence of H5 and H9 subtypes in chickens. We also examined the role of ducks and quail in predicting prevalence in chickens within the market setting because between-species transmission is thought to occur within markets but has not been measured. Our best statistical models performed remarkably well at predicting future prevalence (pseudo-R(2) = 0.57 for H9 and 0.49 for H5), especially considering the multi-host, multi-subtype nature of AIVs. We did not find prevalence of H5/H9 in ducks or quail to be predictors of prevalence in chickens within the Chinese markets. Our results suggest surveillance protocols that could enable more accurate and timely predictive statistical models. We also discuss which data should be collected to allow the development of mechanistic models. |
format | Online Article Text |
id | pubmed-3567063 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-35670632013-02-13 Anticipating the Prevalence of Avian Influenza Subtypes H9 and H5 in Live-Bird Markets Pepin, Kim M. Wang, Jia Webb, Colleen T. Hoeting, Jennifer A. Poss, Mary Hudson, Peter J. Hong, Wenshan Zhu, Huachen Guan, Yi Riley, Steven PLoS One Research Article An ability to forecast the prevalence of specific subtypes of avian influenza viruses (AIV) in live-bird markets would facilitate greatly the implementation of preventative measures designed to minimize poultry losses and human exposure. The minimum requirement for developing predictive quantitative tools is surveillance data of AIV prevalence sampled frequently over several years. Recently, a 4-year time series of monthly sampling of hemagglutinin subtypes 1–13 in ducks, chickens and quail in live-bird markets in southern China has become available. We used these data to investigate whether a simple statistical model, based solely on historical data (variables such as the number of positive samples in host X of subtype Y time t months ago), could accurately predict prevalence of H5 and H9 subtypes in chickens. We also examined the role of ducks and quail in predicting prevalence in chickens within the market setting because between-species transmission is thought to occur within markets but has not been measured. Our best statistical models performed remarkably well at predicting future prevalence (pseudo-R(2) = 0.57 for H9 and 0.49 for H5), especially considering the multi-host, multi-subtype nature of AIVs. We did not find prevalence of H5/H9 in ducks or quail to be predictors of prevalence in chickens within the Chinese markets. Our results suggest surveillance protocols that could enable more accurate and timely predictive statistical models. We also discuss which data should be collected to allow the development of mechanistic models. Public Library of Science 2013-02-07 /pmc/articles/PMC3567063/ /pubmed/23409145 http://dx.doi.org/10.1371/journal.pone.0056157 Text en © 2013 Pepin et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Pepin, Kim M. Wang, Jia Webb, Colleen T. Hoeting, Jennifer A. Poss, Mary Hudson, Peter J. Hong, Wenshan Zhu, Huachen Guan, Yi Riley, Steven Anticipating the Prevalence of Avian Influenza Subtypes H9 and H5 in Live-Bird Markets |
title | Anticipating the Prevalence of Avian Influenza Subtypes H9 and H5 in Live-Bird Markets |
title_full | Anticipating the Prevalence of Avian Influenza Subtypes H9 and H5 in Live-Bird Markets |
title_fullStr | Anticipating the Prevalence of Avian Influenza Subtypes H9 and H5 in Live-Bird Markets |
title_full_unstemmed | Anticipating the Prevalence of Avian Influenza Subtypes H9 and H5 in Live-Bird Markets |
title_short | Anticipating the Prevalence of Avian Influenza Subtypes H9 and H5 in Live-Bird Markets |
title_sort | anticipating the prevalence of avian influenza subtypes h9 and h5 in live-bird markets |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3567063/ https://www.ncbi.nlm.nih.gov/pubmed/23409145 http://dx.doi.org/10.1371/journal.pone.0056157 |
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