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  • Modeling the Association of Space, Time, and Host Species with Variation of the HA, NA, and NS Genes of H5N1 Highly Pathogenic Avian Influenza Viruses Isolated from Birds in Romania in 2005–2007

    Author(s)
    Alkhamis, Mohammad
    Perez, Andres
    Batey, Nicole
    Howard, Wendy
    Baillie, Greg
    Watson, Simon
    Franz, Stephanie
    Focosi-Snyman, Raffaella
    Onita, Iuliana
    Cioranu, Raluca
    Turcitu, Mihai
    Kellam, Paul
    H. Brown, Ian
    C. Breed, Andrew
    Griffith University Author(s)
    Baillie, Greg
    Year published
    2013
    Metadata
    Show full item record
    Abstract
    Molecular characterization studies of a diverse collection of avian influenza viruses (AIVs) have demonstrated that AIVs' greatest genetic variability lies in the HA, NA, and NS genes. The objective here was to quantify the association between geographical locations, periods of time, and host species and pairwise nucleotide variation in the HA, NA, and NS genes of 70 isolates of H5N1 highly pathogenic avian influenza virus (HPAIV) collected from October 2005 to December 2007 from birds in Romania. A mixed-binomial Bayesian regression model was used to quantify the probability of nucleotide variation between isolates and its ...
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    Molecular characterization studies of a diverse collection of avian influenza viruses (AIVs) have demonstrated that AIVs' greatest genetic variability lies in the HA, NA, and NS genes. The objective here was to quantify the association between geographical locations, periods of time, and host species and pairwise nucleotide variation in the HA, NA, and NS genes of 70 isolates of H5N1 highly pathogenic avian influenza virus (HPAIV) collected from October 2005 to December 2007 from birds in Romania. A mixed-binomial Bayesian regression model was used to quantify the probability of nucleotide variation between isolates and its association with space, time, and host species. As expected for the three target genes, a higher probability of nucleotide differences (odds ratios [ORs] > 1) was found between viruses sampled from places at greater geographical distances from each other, viruses sampled over greater periods of time, and viruses derived from different species. The modeling approach in the present study maybe useful in further understanding the molecular epidemiology of H5N1 HPAI virus in bird populations. The methodology presented here will be useful in predicting the most likely genetic distance for any of the three gene segments of viruses that have not yet been isolated or sequenced based on space, time, and host species during the course of an epidemic.
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    Journal Title
    Avian Diseases
    Volume
    57
    Issue
    3
    DOI
    https://doi.org/10.1637/10494-011713-Reg.1
    Subject
    Microbiology not elsewhere classified
    Microbiology
    Zoology
    Veterinary Sciences
    Publication URI
    http://hdl.handle.net/10072/62037
    Collection
    • Journal articles

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