Association between meteorological factors, spatiotemporal effects, and prevalence of influenza A subtype H7 in environmental samples in Zhejiang province, China
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AbstractBackground:
Human infection with the H7N9 virus has been reported recurrently since spring 2013. Given low pathogenicity of the virus in poultry, the outbreak cannot be noticed easily until a case of human infection is reported. Studies showed that the prevalence of influenza A subtype H7 in environmental samples is associated with the number of human H7N9 infection, with the latter associated with meteorological factors. Understanding the association between meteorological factors and the prevalence of H7 subtype in the environmental samples can shed light on how the virus propagates in the environment for disease control.

Method:
Environmental samples and meteorological data (precipitation, temperature, relative humidity, sunshine duration, and wind speed) collected in Zhejiang province, China, during 2013–2017 were used. A Bayesian hierarchical binomial logistic spatiotemporal model which captures spatiotemporal effects was adopted to model the prevalence of H7 subtype with the meteorological factors.

Results:
The monthly overall prevalence of H7 subtype in the environmental samples was usually <30%. Compared with the odds at median, moderately low precipitation (49.19–115.60 mm), moderately long sunshine duration (4.22–9.25 h) and low temperature (<9.33 °C) were statistically significantly associated with a higher adjusted odds of detecting an H7-positive sample, whereas moderately high precipitation (119.51–146.85 mm), short and moderately short sunshine duration (<1.77 h; 4.00–4.17 h), and high temperature (>23.09 °C) were statistically significantly associated with a lower adjusted odds. The adjusted odds increased multiplicatively by 1.11 per 1% increase in relative humidity.

Conclusion:
Since the prevalence of H7 subtype in environmental samples was associated with meteorological conditions and the number of human H7N9 infection, an environmental surveillance program which incorporates meteorological conditions in planning allows for early detection of the spread of the virus in the environment and better preparation for the outbreak in the human population.
Acceptance Date30/01/2019
All Author(s) ListLau SYF, Chen E, Wang M, Cheng W, Zee BCY, Han X, Yu Z, Sun R, Chong KC, Wang X
Journal nameScience of the Total Environment
Year2019
Month5
Day1
Volume Number663
Pages793 - 803
ISSN0048-9697
eISSN1879-1026
LanguagesEnglish-United States

Last updated on 2020-02-04 at 01:26