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Models of highly pathogenic avian influenza epidemics in commercial poultry flocks in Nigeria and Ghana

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  • Models of highly pathogenic avian influenza epidemics in commercial poultry flocks in Nigeria and Ghana

    Trop Anim Health Prod. 2012 Apr 3. [Epub ahead of print]
    Models of highly pathogenic avian influenza epidemics in commercial poultry flocks in Nigeria and Ghana.
    Pelletier ST, Rorres C, Macko PC, Peters S, Smith G.
    Source

    School of Veterinary Medicine, University of Pennsylvania, New Bolton Center, 382 West Street Road, Kennett Square, PA, 19348, USA.
    Abstract

    State-scale and premises-scale gravity models for the spread of highly pathogenic avian influenza (H5N1) in Nigeria and Ghana were used to provide a basis for risk maps for future epidemics and to compare and rank plausible culling and vaccination strategies for control. Maximum likelihood methods were used to fit the models to the 2006-2007 outbreaks. The sensitivity and specificity of the state-scale model-generated probabilities that any given state would be involved in an epidemic were each 57 %. The premises-based model indicated that reactive, countrywide vaccination strategies, in which the order in which flocks are vaccinated was strictly determined by known risk factors for infection, were more effective in reducing the final size of the epidemic and the epidemic impact than vaccinating flocks at random or ring vaccination. The model suggests that an introduction of highly pathogenic avian influenza (H5N1) into Ghana had a high chance (84 %) of causing a major outbreak. That this did not happen was most probably a result of the very swift Ghanaian response to news of the first introductions.

    PMID:
    22476732
    [PubMed - as supplied by publisher]

    State-scale and premises-scale gravity models for the spread of highly pathogenic avian influenza (H5N1) in Nigeria and Ghana were used to provide a basis for risk maps for future epidemics and to compare and rank plausible culling and vaccination strategies for control. Maximum likelihood methods w …
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