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


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.

SUBMITTER: Pelletier ST 

PROVIDER: S-EPMC3627490 | biostudies-literature | 2012 Oct

REPOSITORIES: biostudies-literature

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

Pelletier Sky T K ST   Rorres Chris C   Macko Peter C PC   Peters Sarah S   Smith Gary G  

Tropical animal health and production 20120403 7


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  ...[more]

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