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Nat Commun. 2014 Jun 17;5:4116. doi: 10.1038/ncomms5116.

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

Author information

1
1] Biological Control and Spatial Ecology, Université Libre de Bruxelles, av FD Roosevelt 50, B-1050 Brussels, Belgium [2] Fonds National de la Recherche Scientifique, rue d'Egmont 5, B-1000 Brussels, Belgium.
2
Spatial Ecology and Epidemiology Group, Department of Zoology, University of Oxford, Tinbergen Building, South Parks Road, Oxford OX1 3PS, UK.
3
Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, 155 Changbai Road, Changping District, 102206 Beijing, China.
4
Environmental Research Group Oxford, Department of Zoology, University of Oxford, South Parks Road, Oxford OX1 3PS, UK.
5
Livestock Systems and Environment (LSE), International Livestock Research Institute (ILRI), Old Naivasha Road, PO Box 30709, 00100 Nairobi, Kenya.
6
1] Fogarty International Center, National Institutes of Health, Bethesda, Maryland 20892, USA [2] Department of Geography and Environment, University of Southampton, Highfield, Southampton SO17 1BJ, UK.
7
Scientific Data Center, Computer Network Information Center, Chinese Academy of Sciences, Zhongguancun Nansijie, Haidian District, 100190 Beijing, China.
8
1] Department of Microbiology and Plant Biology, Center for Spatial Analysis, University of Oklahoma, 101 David L. Boren Blvd, Norman, Oklahoma 73019, USA [2] Institute of Biodiversity Sciences, Fudan University, 220A Handan Road, Yangpu District, Shanghai 200433, China.
9
Food and Agriculture Organization of the United Nations (FAO), Representation in Senegal, PO Box 3300, Dakar, Senegal.
10
Oxford University Clinical Research Unit-Wellcome Trust Major Overseas Unit, 190 Ben Ham Tu, District 5, Ho Chi Minh City, Vietnam.
11
1] Spatial Ecology and Epidemiology Group, Department of Zoology, University of Oxford, Tinbergen Building, South Parks Road, Oxford OX1 3PS, UK [2] Fogarty International Center, National Institutes of Health, Bethesda, Maryland 20892, USA.

Abstract

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.

PMID:
24937647
PMCID:
PMC4061699
DOI:
10.1038/ncomms5116
[Indexed for MEDLINE]
Free PMC Article

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