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Identification of meteorological factors associated with human infection with avian influenza A H7N9 virus in Zhejiang Province, China

Authors :
Benny Zee
Steven Yuk-Fai Lau
Enfu Chen
Maggie Haitian Wang
Zhao Yu
Xiaoxiao Wang
Shelan Liu
Ka Chun Chong
Xiaoran Han
Riyang Sun
Source :
Science of The Total Environment. 644:696-709
Publication Year :
2018
Publisher :
Elsevier BV, 2018.

Abstract

Background Since the first reported human infection with an avian-origin influenza A (H7N9) virus in China in early 2013, there have been recurrent outbreaks of the virus in the country. Previous studies have shown that meteorological factors are associated with the risk of human infection with the virus; however, their possible nonlinear and lagged effects were not commonly taken into account. Method To quantify the effect of meteorological factors on the risk of human H7N9 infection, daily laboratory-confirmed cases of human H7N9 infection and meteorological factors including total rainfall, average wind speed, average temperature, average relative humidity, and sunshine duration of the 11 sub-provincial/prefecture cities in Zhejiang during the first four outbreaks (13 March 2013–30 June 2016) were analyzed. Separate models were built for the 6 sub-provincial/prefecture cities with the greatest number of reported cases using a combination of logistic generalized additive model and distributed lag nonlinear models, which were then pooled by a multivariate meta-regression model to determine their overall effects. Results According to the meta-regression model, for rainfall, the log adjusted overall cumulative odds ratio was statistically significant when log of rainfall was >4.0, peaked at 5.3 with a value of 12.42 (95% confidence intervals (CI): [3.23, 21.62]). On the other hand, when wind speed was 2.1–3.0 m/s or 6.3–7.1 m/s, the log adjusted overall cumulative odds ratio was statistically significant, peaked at 7.1 m/s with a value of 6.75 (95% CI: [0.03, 13.47]). There were signs of nonlinearity and lag effects in their associations with the risk of infection. Conclusion As rainfall and wind speed were found to be associated with the risk of human H7N9 infection, weather conditions should be taken into account when it comes to disease surveillance, allowing prompt actions when an outbreak takes place.

Details

ISSN :
00489697
Volume :
644
Database :
OpenAIRE
Journal :
Science of The Total Environment
Accession number :
edsair.doi.dedup.....3eee62983caf0ff1e30ebec4a9a82f19
Full Text :
https://doi.org/10.1016/j.scitotenv.2018.06.390