Avian Influenza H5N1

14,000,000 Leading Edge Experts on the ideXlab platform

Scan Science and Technology

Contact Leading Edge Experts & Companies

Scan Science and Technology

Contact Leading Edge Experts & Companies

The Experts below are selected from a list of 31335 Experts worldwide ranked by ideXlab platform

Michael P. Ward - One of the best experts on this subject based on the ideXlab platform.

  • Identifying spatio-temporal patterns of transboundary disease spread: examples using Avian Influenza H5N1 outbreaks
    Veterinary Research, 2009
    Co-Authors: Matthew L. Farnsworth, Michael P. Ward
    Abstract:

    Characterizing spatio-temporal patterns among epidemics in which the mechanism of spread is uncertain is important for generating disease spread hypotheses, which may in turn inform disease control and prevention strategies. Using a dataset representing three phases of highly pathogenic Avian Influenza H5N1 outbreaks in village poultry in Romania, 2005� 2006, spatio- temporal patterns were characterized. We first fit a set of hierarchical Bayesian models that quantified changes in the spatio-temporal relative risk for each of the 23 affected counties. We then modeled spatial synchrony in each of the three epidemic phases using non-parametric covariance functions and Thin Plate Spline regression models. We found clear differences in the spatio-temporal patterns among the epidemic phases (local versus regional correlated processes), which may indicate differing spread mechanisms (for example wild bird versus human-mediated). Elucidating these patterns allowed us to postulate that a shift in the primary mechanism of disease spread may have taken place between the second and third phases of this epidemic. Information generated by such analyses could assist affected countries in determining the most appropriate control programs to implement, and to allocate appropriate resources to preventing contact between domestic poultry and wild birds versus enforcing bans on poultry movements and quarantine. The methods used in this study could be applied in many different situations to analyze transboundary disease data in which only location and time of occurrence data are reported. disease spread / spatio-temporal analysis / epidemic pattern / Avian Influenza / poultry

  • Identifying spatio-temporal patterns of transboundary disease spread: examples using Avian Influenza H5N1 outbreaks
    Veterinary Research, 2009
    Co-Authors: Matthew L. Farnsworth, Michael P. Ward
    Abstract:

    Characterizing spatio-temporal patterns among epidemics in which the mechanism of spread is uncertain is important for generating disease spread hypotheses, which may in turn inform disease control and prevention strategies. Using a dataset representing three phases of highly pathogenic Avian Influenza H5N1 outbreaks in village poultry in Romania, 2005-2006, spatio-temporal patterns were characterized. We first fit a set of hierarchical Bayesian models that quantified changes in the spatio-temporal relative risk for each of the 23 affected counties. We then modeled spatial synchrony in each of the three epidemic phases using non-parametric covariance functions and Thin Plate Spline regression models. We found clear differences in the spatio-temporal patterns among the epidemic phases (local versus regional correlated processes), which may indicate differing spread mechanisms (for example wild bird versus human-mediated). Elucidating these patterns allowed us to postulate that a shift in the primary mechanism of disease spread may have taken place between the second and third phases of this epidemic. Information generated by such analyses could assist affected countries in determining the most appropriate control programs to implement, and to allocate appropriate resources to preventing contact between domestic poultry and wild birds versus enforcing bans on poultry movements and quarantine. The methods used in this study could be applied in many different situations to analyze transboundary disease data in which only location and time of occurrence data are reported.

Matthew L. Farnsworth - One of the best experts on this subject based on the ideXlab platform.

  • Identifying spatio-temporal patterns of transboundary disease spread: examples using Avian Influenza H5N1 outbreaks
    Veterinary Research, 2009
    Co-Authors: Matthew L. Farnsworth, Michael P. Ward
    Abstract:

    Characterizing spatio-temporal patterns among epidemics in which the mechanism of spread is uncertain is important for generating disease spread hypotheses, which may in turn inform disease control and prevention strategies. Using a dataset representing three phases of highly pathogenic Avian Influenza H5N1 outbreaks in village poultry in Romania, 2005� 2006, spatio- temporal patterns were characterized. We first fit a set of hierarchical Bayesian models that quantified changes in the spatio-temporal relative risk for each of the 23 affected counties. We then modeled spatial synchrony in each of the three epidemic phases using non-parametric covariance functions and Thin Plate Spline regression models. We found clear differences in the spatio-temporal patterns among the epidemic phases (local versus regional correlated processes), which may indicate differing spread mechanisms (for example wild bird versus human-mediated). Elucidating these patterns allowed us to postulate that a shift in the primary mechanism of disease spread may have taken place between the second and third phases of this epidemic. Information generated by such analyses could assist affected countries in determining the most appropriate control programs to implement, and to allocate appropriate resources to preventing contact between domestic poultry and wild birds versus enforcing bans on poultry movements and quarantine. The methods used in this study could be applied in many different situations to analyze transboundary disease data in which only location and time of occurrence data are reported. disease spread / spatio-temporal analysis / epidemic pattern / Avian Influenza / poultry

  • Identifying spatio-temporal patterns of transboundary disease spread: examples using Avian Influenza H5N1 outbreaks
    Veterinary Research, 2009
    Co-Authors: Matthew L. Farnsworth, Michael P. Ward
    Abstract:

    Characterizing spatio-temporal patterns among epidemics in which the mechanism of spread is uncertain is important for generating disease spread hypotheses, which may in turn inform disease control and prevention strategies. Using a dataset representing three phases of highly pathogenic Avian Influenza H5N1 outbreaks in village poultry in Romania, 2005-2006, spatio-temporal patterns were characterized. We first fit a set of hierarchical Bayesian models that quantified changes in the spatio-temporal relative risk for each of the 23 affected counties. We then modeled spatial synchrony in each of the three epidemic phases using non-parametric covariance functions and Thin Plate Spline regression models. We found clear differences in the spatio-temporal patterns among the epidemic phases (local versus regional correlated processes), which may indicate differing spread mechanisms (for example wild bird versus human-mediated). Elucidating these patterns allowed us to postulate that a shift in the primary mechanism of disease spread may have taken place between the second and third phases of this epidemic. Information generated by such analyses could assist affected countries in determining the most appropriate control programs to implement, and to allocate appropriate resources to preventing contact between domestic poultry and wild birds versus enforcing bans on poultry movements and quarantine. The methods used in this study could be applied in many different situations to analyze transboundary disease data in which only location and time of occurrence data are reported.

James V. Rogers - One of the best experts on this subject based on the ideXlab platform.

Iain Stephenson - One of the best experts on this subject based on the ideXlab platform.

William R. Richte - One of the best experts on this subject based on the ideXlab platform.

  • Articles Effect of Drying and Exposure to Vaporous Hydrogen Peroxide on the Inactivation of Highly Pathogenic Avian Influenza (H5N1) on Non-porous Surfaces
    2013
    Co-Authors: James V. Rogers, Young W. Choi, William R. Richte
    Abstract:

    This study demonstrated the combined effect of drying and vaporous hydrogen peroxide exposure on inactivating highly pathogenic Avian Influenza (H5N1) on the non-porous materials glass, Hypalon ® rubber glove, and stainless steel. Approximately 7.7 log10 TCID50 (median 50 % tissue culture infectious dose)/mL of A/Vietnam/1203/2004 H5N1 in allantoic fluid was dried on coupons of each type of test surface and exposed to vaporous hydrogen peroxide fumigation within a ~15 m 3 chamber. A significant reduction in the total log10 TCID50 of H5N1 on all test materials was observed between the controls evaluated after a 1-hour drying time and unexposed controls evaluated after decontamination. The H5N1 exhibited a 2-3 log decrease in viability, and vaporous hydrogen peroxide further inactivated the virus to below detectable levels. In parallel, Geobacillus stearothermophilus biological indicators exposed to vaporous hydrogen peroxide exhibited no growth after 1 and 7 days ’ incubation. This study provides information on the persistence in viability of H5N1 on non-porous surfaces that can be mitigated by vaporous hydrogen peroxide fumigation of a large chamber