Weather variability and influenza A (H7N9) transmission in Shanghai, China: A Bayesian spatial analysis

Hu, Wenbiao, Zhang, Wenyi, Huang, Xiaodong, Clements, Archie, Mengersen, Kerrie and Tong, Shilu (2015) Weather variability and influenza A (H7N9) transmission in Shanghai, China: A Bayesian spatial analysis. Environmental Research, 136 405-412. doi:10.1016/j.envres.2014.07.033

Author Hu, Wenbiao
Zhang, Wenyi
Huang, Xiaodong
Clements, Archie
Mengersen, Kerrie
Tong, Shilu
Title Weather variability and influenza A (H7N9) transmission in Shanghai, China: A Bayesian spatial analysis
Journal name Environmental Research   Check publisher's open access policy
ISSN 1096-0953
Publication date 2015-01
Year available 2014
Sub-type Article (original research)
DOI 10.1016/j.envres.2014.07.033
Open Access Status
Volume 136
Start page 405
End page 412
Total pages 8
Place of publication Maryland Heights, MO United States
Publisher Academic Press
Collection year 2015
Language eng
Formatted abstract

A novel avian influenza A (H7N9) virus was first found in humans in Shanghai, and infected over 433 patients in China. To date, very little is known about the spatiotemporal variability or environmental drivers of the risk of H7N9 infection. This study explored the spatial and temporal variation of H7N9 infection and assessed the effects of temperature and rainfall on H7N9 incidence.


A Bayesian spatial conditional autoregressive (CAR) model was used to assess the spatiotemporal distribution of the risk of H7N9 infection in Shanghai, by district and fortnight for the period 19th February–14th April 2013. Data on daily laboratory-confirmed H7N9 cases, and weather variability including temperature (°C) and rainfall (mm) were obtained from the Chinese Information System for Diseases Control and Prevention and Chinese Meteorological Data Sharing Service System, respectively, and aggregated by fortnight.


High spatial variations in the H7N9 risk were mainly observed in the east and centre of Shanghai municipality. H7N9 incidence rate was significantly associated with fortnightly mean temperature (Relative Risk (RR): 1.54; 95% credible interval (CI): 1.22–1.94) and fortnightly mean rainfall (RR: 2.86; 95% CI: 1.47–5.56).


There was a substantial variation in the spatiotemporal distribution of H7N9 infection across different districts in Shanghai. Optimal temperature and rainfall may be one of the driving forces for H7N9.
Keyword Avian influenza
H7N9 virus
Spatial Bayesian conditional autoregressive model
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ
Additional Notes Published online ahead of print 25 Nov 2014

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2015 Collection
School of Public Health Publications
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