Identifying areas with a high risk of human infection with the avian influenza A (H7N9) virus in East Asia

Trevon Fuller, Fiona Havers, Cuiling Xu, Li-Qun Fang, Wu-Chun Cao, Yuelong Shu, Marc-Alain Widdowson, Thomas B Smith

Research output: Contribution to journalA1: Web of Science-articlepeer-review


OBJECTIVES: The rapid emergence, spread, and disease severity of avian influenza A (H7N9) in China has prompted concerns about a possible pandemic and regional spread in the coming months. The objective of this study was to predict the risk of future human infections with H7N9 in China and neighboring countries by assessing the association between H7N9 cases at sentinel hospitals and putative agricultural, climatic, and demographic risk factors.

METHODS: This cross-sectional study used the locations of H7N9 cases and negative cases from China's influenza-like illness surveillance network. After identifying H7N9 risk factors with logistic regression, we used Geographic Information Systems (GIS) to construct predictive maps of H7N9 risk across Asia.

RESULTS: Live bird market density was associated with human H7N9 infections reported in China from March-May 2013. Based on these cases, our model accurately predicted the virus' spread into Guangxi autonomous region in February 2014. Outside China, we find there is a high risk that the virus will spread to northern Vietnam, due to the import of poultry from China.

CONCLUSIONS: Our risk map can focus efforts to improve surveillance in poultry and humans, which may facilitate early identification and treatment of human cases.

Original languageEnglish
JournalJournal of Infection
Issue number2
Pages (from-to)174-81
Number of pages8
Publication statusPublished - 2014


  • Animals
  • Antibodies, Viral/blood
  • China/epidemiology
  • Communicable Diseases/epidemiology
  • Cross-Sectional Studies
  • Disease Outbreaks
  • Epidemiological Monitoring
  • Far East/epidemiology
  • Humans
  • Influenza A Virus, H7N9 Subtype/isolation & purification
  • Influenza in Birds/epidemiology
  • Influenza, Human/epidemiology
  • Logistic Models
  • Poultry/virology
  • Risk Factors


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