4.8 Article

Predicting the risk of avian influenza A H7N9 infection in live-poultry markets across Asia

Journal

NATURE COMMUNICATIONS
Volume 5, Issue -, Pages -

Publisher

NATURE PUBLISHING GROUP
DOI: 10.1038/ncomms5116

Keywords

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Funding

  1. Fonds National de la Recherche Scientifique
  2. Bill & Melinda Gates Foundation [OPP1053338]
  3. CGIAR Research Programmes on the Humidtropics, Climate Change, Agriculture and Food Security (CCAFS)
  4. Agriculture for Nutrition and Health (A4NH)
  5. Wellcome Trust [095066]
  6. Li Ka Shing Foundation
  7. RAPIDD program of the Science & Technology Directorate, Department of Homeland Security
  8. Fogarty International Center (FIC), National Institutes of Health (NIH)
  9. Bill and Melinda Gates Foundation [1032350, OPP1068048]
  10. Medical Research Council (UK) Career Development Fellow [K00669X]
  11. Science and Technology Directorate, Department of Homeland Security [HSHQDC-12-C-00058]
  12. US NIH FIC grants [3R01TW007869-03, 1R56TW009502-01]
  13. NIH NIAID grant [1R01AI101028-01A1]
  14. USAID
  15. US NIH [U19 AI51915]
  16. China-U.S. Collaborative Program on Emerging and Re-emerging Infectious Diseases
  17. Ministry of Science and Technology, China [2012 ZX10004-201]
  18. Medical Research Council [MR/K00669X/1] Funding Source: researchfish
  19. MRC [MR/K00669X/1] Funding Source: UKRI

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Two epidemic waves of an avian influenza A (H7N9) virus have so far affected China. Most human cases have been attributable to poultry exposure at live-poultry markets, where most positive isolates were sampled. The potential geographic extent of potential re-emerging epidemics is unknown, as are the factors associated with it. Using newly assembled data sets of the locations of 8,943 live-poultry markets in China and maps of environmental correlates, we develop a statistical model that accurately predicts the risk of H7N9 market infection across Asia. Local density of live-poultry markets is the most important predictor of H7N9 infection risk in markets, underscoring their key role in the spatial epidemiology of H7N9, alongside other poultry, land cover and anthropogenic predictor variables. Identification of areas in Asia with high suitability for H7N9 infection enhances our capacity to target biosurveillance and control, helping to restrict the spread of this important disease.

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