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

No Thumbnail Available
File version
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)
Primary Supervisor
Other Supervisors
Editor(s)
Date
2013
Size
File type(s)
Location
License
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 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.

Journal Title

Avian Diseases

Conference Title
Book Title
Edition
Volume

57

Issue

3

Thesis Type
Degree Program
School
Publisher link
Patent number
Funder(s)
Grant identifier(s)
Rights Statement
Rights Statement
Item Access Status
Note
Access the data
Related item(s)
Subject

Microbiology not elsewhere classified

Microbiology

Zoology

Veterinary Sciences

Persistent link to this record
Citation
Collections