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

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    Author
    Gilbert, M; Golding, N; Zhou, H; Wint, GRW; Robinson, TP; Tatem, AJ; Lai, S; Zhou, S; Jiang, H; Guo, D; ...
    Date
    2014-06-01
    Source Title
    Nature Communications
    Publisher
    NATURE PUBLISHING GROUP
    University of Melbourne Author/s
    Golding, Nicholas
    Affiliation
    School of BioSciences
    Metadata
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    Document Type
    Journal Article
    Citations
    Gilbert, M., Golding, N., Zhou, H., Wint, G. R. W., Robinson, T. P., Tatem, A. J., Lai, S., Zhou, S., Jiang, H., Guo, D., Huang, Z., Messina, J. P., Xiao, X., Linard, C., Van Boeckel, T. P., Martin, V., Bhatt, S., Gething, P. W., Farrar, J. J. ,... Yu, H. (2014). Predicting the risk of avian influenza A H7N9 infection in live-poultry markets across Asia. NATURE COMMUNICATIONS, 5 (1), https://doi.org/10.1038/ncomms5116.
    Access Status
    Open Access
    URI
    http://hdl.handle.net/11343/258260
    DOI
    10.1038/ncomms5116
    Abstract
    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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