tetano
Editor, Senior Moderator
PLoS One. 2013;8(2):e56157. doi: 10.1371/journal.pone.0056157. Epub 2013 Feb 7.
Anticipating the prevalence of avian influenza subtypes h9 and h5 in live-bird markets.
Pepin KM, Wang J, Webb CT, Hoeting JA, Poss M, Hudson PJ, Hong W, Zhu H, Guan Y, Riley S.
Source
Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America ; Department of Biology, Colorado State University, Fort Collins, Colorado, United States of America.
Abstract
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.
PMID:
23409145
[PubMed - in process]
Free full text
http://www.ncbi.nlm.nih.gov/pubmed/23409145
Anticipating the prevalence of avian influenza subtypes h9 and h5 in live-bird markets.
Pepin KM, Wang J, Webb CT, Hoeting JA, Poss M, Hudson PJ, Hong W, Zhu H, Guan Y, Riley S.
Source
Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America ; Department of Biology, Colorado State University, Fort Collins, Colorado, United States of America.
Abstract
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.
PMID:
23409145
[PubMed - in process]
Free full text
http://www.ncbi.nlm.nih.gov/pubmed/23409145