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Spatial and temporal analysis of human infection with avian influenza A(H7N9) virus in China, 2013

W Liu1, K Yang, X Qi

  • 1Department of Acute Infectious Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China.

Euro Surveillance : Bulletin Europeen Sur Les Maladies Transmissibles = European Communicable Disease Bulletin
|December 5, 2013
PubMed

Insights

A novel avian influenza A(H7N9) virus caused a significant outbreak in China, peaking in March-April 2013. Spatial analysis revealed distinct clusters in eastern coastal provinces, highlighting key areas for public health surveillance.

Area of Science:

  • Epidemiology
  • Infectious Diseases
  • Geographic Information Systems

Background:

  • A novel avian influenza A(H7N9) virus emerged in mainland China, causing human infections.
  • The outbreak peaked between March 28 and April 18, 2013, affecting 10 provinces.

Purpose of the Study:

  • To describe the spatial and temporal characteristics of the avian influenza A(H7N9) outbreak.
  • To identify statistically significant clusters of human cases using geographic information system methods.

Main Methods:

  • Descriptive epidemiological methods were employed.
  • Geographic Information System (GIS) techniques, including Cuzick–Edwards’ k-nearest neighbour method and space–time scan analysis, were utilized.
  • Data included 131 reported human infections as of May 31, 2013.

Main Results:

  • The outbreak concentrated in eastern coastal provinces (Zhejiang, Shanghai, Jiangsu), with 106 cases.
  • Statistically significant spatial clustering of human cases was identified.
  • Three spatio-temporal clusters were detected, including a principal cluster in Zhejiang (RR: 26.39) and secondary clusters near Shanghai and Jiangsu (RR: 6.35, 72.48).
  • The peak incidence occurred in March and April 2013.

Conclusions:

  • The avian influenza A(H7N9) outbreak exhibited significant spatio-temporal aggregation, particularly in eastern China.
  • Geographic analysis identified high-risk areas and time periods, crucial for targeted public health interventions.
  • Understanding the spatial dynamics is key to controlling future outbreaks of novel influenza strains.

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