1. Epidemiology and Global Health

Global mapping of highly pathogenic avian influenza H5N1 and H5Nx clade 2.3.4.4 viruses with spatial cross-validation

  1. Madhur S Dhingra
  2. Jean Artois
  3. Timothy P Robinson
  4. Catherine Linard
  5. Celia Chaiban
  6. Ioannis Xenarios
  7. Robin Engler
  8. Robin Liechti
  9. Dimitry Kuznetsov
  10. Xiangming Xiao
  11. Sophie Von Dobschuetz
  12. Filip Claes
  13. Scott H Newman  Is a corresponding author
  14. Gwenaëlle Dauphin  Is a corresponding author
  15. Marius Gilbert  Is a corresponding author
  1. Université Libre de Bruxelles, Belgium
  2. International Livestock Research Institute, Kenya
  3. Swiss Institute of Bioinformatics, Switzerland
  4. University of Oklahoma, United States
  5. Food and Agriculture Organization of the United Nations, Italy
  6. Regional Office for Asia and the Pacific, Thailand
  7. Food and Agriculture Organization of the United Nations, Vietnam
https://doi.org/10.7554/eLife.19571
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Cite this article
  1. Madhur S Dhingra
  2. Jean Artois
  3. Timothy P Robinson
  4. Catherine Linard
  5. Celia Chaiban
  6. Ioannis Xenarios
  7. Robin Engler
  8. Robin Liechti
  9. Dimitry Kuznetsov
  10. Xiangming Xiao
  11. Sophie Von Dobschuetz
  12. Filip Claes
  13. Scott H Newman
  14. Gwenaëlle Dauphin
  15. Marius Gilbert
(2016)
Global mapping of highly pathogenic avian influenza H5N1 and H5Nx clade 2.3.4.4 viruses with spatial cross-validation
eLife 5:e19571.
https://doi.org/10.7554/eLife.19571
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Abstract

Global disease suitability models are essential tools to inform surveillance systems and enable early detection. We present the first global suitability model of highly pathogenic avian influenza (HPAI) H5N1 and demonstrate that reliable predictions can be obtained at global scale. Best predictions are obtained using spatial predictor variables describing host distributions, rather than land use or eco-climatic spatial predictor variables, with a strong association with domestic duck and extensively raised chicken densities. Our results also support a more systematic use of spatial cross-validation in large-scale disease suitability modelling compared to standard random cross-validation that can lead to unreliable measure of extrapolation accuracy. A global suitability model of the H5 clade 2.3.4.4 viruses, a group of viruses that recently spread extensively in Asia and the US, shows in comparison a lower spatial extrapolation capacity than the HPAI H5N1 models, with a stronger association with intensively raised chicken densities and anthropogenic factors.

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The following previously published data sets were used

Article and author information

Author details

  1. Madhur S Dhingra

    Spatial Epidemiology Lab, Université Libre de Bruxelles, Brussels, Belgium
    Competing interests
    The authors declare that no competing interests exist.

  2. Jean Artois

    Spatial Epidemiology Lab, Université Libre de Bruxelles, Brussels, Belgium
    Competing interests
    The authors declare that no competing interests exist.

  3. Timothy P Robinson

    Livestock Systems and Environment, International Livestock Research Institute, Nairobi, Kenya
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4266-963X

  4. Catherine Linard

    Spatial Epidemiology Lab, Université Libre de Bruxelles, Brussels, Belgium
    Competing interests
    The authors declare that no competing interests exist.

  5. Celia Chaiban

    Spatial Epidemiology Lab, Université Libre de Bruxelles, Brussels, Belgium
    Competing interests
    The authors declare that no competing interests exist.

  6. Ioannis Xenarios

    Swiss-Prot & Vital-IT group, Swiss Institute of Bioinformatics, Lausanne, Switzerland
    Competing interests
    The authors declare that no competing interests exist.

  7. Robin Engler

    Swiss-Prot & Vital-IT group, Swiss Institute of Bioinformatics, Lausanne, Switzerland
    Competing interests
    The authors declare that no competing interests exist.

  8. Robin Liechti

    Swiss-Prot & Vital-IT group, Swiss Institute of Bioinformatics, Lausanne, Switzerland
    Competing interests
    The authors declare that no competing interests exist.

  9. Dimitry Kuznetsov

    Swiss-Prot & Vital-IT group, Swiss Institute of Bioinformatics, Lausanne, Switzerland
    Competing interests
    The authors declare that no competing interests exist.

  10. Xiangming Xiao

    Department of Microbiology and Plant Biology, University of Oklahoma, Norman, United States
    Competing interests
    The authors declare that no competing interests exist.

  11. Sophie Von Dobschuetz

    Animal Production and Health Division, Food and Agriculture Organization of the United Nations, Rome, Italy
    Competing interests
    The authors declare that no competing interests exist.

  12. Filip Claes

    Emergency Center for Transboundary Animal Diseases, Regional Office for Asia and the Pacific, Bangkok, Thailand
    Competing interests
    The authors declare that no competing interests exist.

  13. Scott H Newman

    Emergency Center for Transboundary Animal Diseases, Food and Agriculture Organization of the United Nations, Hanoi, Vietnam
    For correspondence
    scott.newman@fao.org
    Competing interests
    The authors declare that no competing interests exist.

  14. Gwenaëlle Dauphin

    Animal Production and Health Division, Food and Agriculture Organization of the United Nations, Rome, Italy
    For correspondence
    Gwenaelle.Dauphin@fao.org
    Competing interests
    The authors declare that no competing interests exist.

  15. Marius Gilbert

    Spatial Epidemiology Lab, Université Libre de Bruxelles, Brussels, Belgium
    For correspondence
    marius.gilbert@gmail.com
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3708-3359

Funding

National Institutes of Health (1R01AI101028-02A1)

  • Madhur S Dhingra
  • Jean Artois
  • Xiangming Xiao
  • Marius Gilbert

United States Agency for International Development (Emerging Pandemic Threats program)

  • Scott H Newman

Biotechnology and Biological Sciences Research Council (BB/L019019/1)

  • Timothy P Robinson

Fonds De La Recherche Scientifique - FNRS (PDR T.0073.13)

  • Catherine Linard
  • Marius Gilbert

Medical Research Council (ESEI UrbanZoo (G1100783/1))

  • Timothy P Robinson

CGIAR (Research Programs on Agriculture for Nutrition and Health (A4NH) and Livestock)

  • Timothy P Robinson

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

© 2016, Dhingra et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Madhur S Dhingra
  2. Jean Artois
  3. Timothy P Robinson
  4. Catherine Linard
  5. Celia Chaiban
  6. Ioannis Xenarios
  7. Robin Engler
  8. Robin Liechti
  9. Dimitry Kuznetsov
  10. Xiangming Xiao
  11. Sophie Von Dobschuetz
  12. Filip Claes
  13. Scott H Newman
  14. Gwenaëlle Dauphin
  15. Marius Gilbert
(2016)
Global mapping of highly pathogenic avian influenza H5N1 and H5Nx clade 2.3.4.4 viruses with spatial cross-validation
eLife 5:e19571.
https://doi.org/10.7554/eLife.19571

Share this article

https://doi.org/10.7554/eLife.19571

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