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

Marius Gilbert, Nick Golding, Hang Zhou, G. R William Wint, Timothy P. Robinson, Andrew J. Tatem, Shengjie Lai, Sheng Zhou, Hui Jiang, Danhuai Guo, Zhi Huang, Jane P. Messina, Xiangming Xiao, Catherine Linard, Thomas P. Van Boeckel, Vincent Martin, Samir Bhatt, Peter W. Gething, Jeremy J. Farrar, Simon I. HayHongjie Yu

Résultats de recherche: Contribution à un journal/une revueArticleRevue par des pairs

29 Téléchargements (Pure)

Résumé

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.

langue originaleAnglais
Numéro d'article4116
journalNature Communications
Volume5
Les DOIs
Etat de la publicationPublié - 17 juin 2014
Modification externeOui

Empreinte digitale

Examiner les sujets de recherche de « Predicting the risk of avian influenza A H7N9 infection in live-poultry markets across Asia ». Ensemble, ils forment une empreinte digitale unique.

Contient cette citation