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  Modelling the domestic poultry population in the United States: A novel approach leveraging remote sensing and synthetic data methods

  Kelly A. Patyk, Mary J. McCool-Eye, David D. South, Christopher L. Burdett, Susan A. Maroney, Andrew Fox, Grace Kuiper, Sheryl Magzamen

  10-12-2020

  https://doi.org/10.4081/gh.2020.913

  3537

  PDF: 1317

  HTML: 156
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  Predominance and geo-mapping of avian influenza H5N1 in poultry sectors in Egypt

  Abdelsatar Arafa, Ihab El-Masry, Shereen Khoulosy, Mohammed K. Hassan, Moussa Soliman, Olubunmi G. Fasanmi, Folorunso O. Fasina, Gwenaelle Dauphin, Juan Lubroth, Yilma M. Jobre

  28-11-2016

  https://doi.org/10.4081/gh.2016.492

  2686

  PDF: 1132

  APPENDIX: 458

  HTML: 1513
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  Using object-based image analysis to map commercial poultry operations from high resolution imagery to support animal health outbreaks and events

  Susan Maroney, MaryJane McCool-Eye, Andrew Fox, Christopher Burdett

  10-12-2020

  https://doi.org/10.4081/gh.2020.919

  2473

  PDF: 833

  HTML: 117

• Contacts between poultry farms, their spatial dimension and their relevance for avian influenza preparedness

  Lena Fiebig, Timo Smieszek, Jennifer Saurina, Jan Hattendorf, Jakob Zinsstag

  79-95

  01-11-2009

  https://doi.org/10.4081/gh.2009.212

  1805

  PDF: 851

• Identifying areas of Australia at risk of H5N1 avian influenza infection from exposure to migratory birds: a spatial analysis

  Iain J. East, Samuel Hamilton, Graeme Garner

  203-213

  01-05-2008

  https://doi.org/10.4081/gh.2008.244

  1778

  PDF: 1108

• Identifying areas of Australia at risk for H5N1 avian influenza infection from exposure to nomadic waterfowl moving throughout the Australo-Papuan region

  Iain J. East, Samuel A. Hamilton, Louise A. Sharp, Michael G. Garner

  17-27

  01-11-2008

  https://doi.org/10.4081/gh.2008.228

  1523

  PDF: 1617