Steven Yuk-Fai Lau1, Enfu Chen2, Maggie Wang3, Wei Cheng4, Benny Chung-Ying Zee5, Xiaoran Han6, Zhao Yu7, Riyang Sun8, Ka Chun Chong9, Xiaoxiao Wang10. 1. Division of Biostatistics, JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, New Territories, Hong Kong, China. Electronic address: stevenlau@cuhk.edu.hk. 2. Zhejiang Province Centre for Disease Control and Prevention, 3399 Binsheng Road, Binjiang District, Hangzhou, Zhejiang 310051, China. Electronic address: enfchen@cdc.zj.cn. 3. Division of Biostatistics, JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, New Territories, Hong Kong, China; Clinical Trials and Biostatistics Laboratory, Shenzhen Research Institute, The Chinese University of Hong Kong, No. 10, 2nd Yuexing Road, Nanshan District, Shenzhen, China. Electronic address: maggiew@cuhk.edu.hk. 4. Zhejiang Province Centre for Disease Control and Prevention, 3399 Binsheng Road, Binjiang District, Hangzhou, Zhejiang 310051, China. Electronic address: wcheng@cdc.zj.cn. 5. Division of Biostatistics, JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, New Territories, Hong Kong, China; Clinical Trials and Biostatistics Laboratory, Shenzhen Research Institute, The Chinese University of Hong Kong, No. 10, 2nd Yuexing Road, Nanshan District, Shenzhen, China. Electronic address: bzee@cuhk.edu.hk. 6. Division of Biostatistics, JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, New Territories, Hong Kong, China. 7. Zhejiang Province Centre for Disease Control and Prevention, 3399 Binsheng Road, Binjiang District, Hangzhou, Zhejiang 310051, China. Electronic address: zhy@cdc.zj.cn. 8. Division of Biostatistics, JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, New Territories, Hong Kong, China. Electronic address: anna_Sun@link.cuhk.edu.hk. 9. Division of Biostatistics, JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, New Territories, Hong Kong, China; Clinical Trials and Biostatistics Laboratory, Shenzhen Research Institute, The Chinese University of Hong Kong, No. 10, 2nd Yuexing Road, Nanshan District, Shenzhen, China. Electronic address: marc@cuhk.edu.hk. 10. Zhejiang Province Centre for Disease Control and Prevention, 3399 Binsheng Road, Binjiang District, Hangzhou, Zhejiang 310051, China. Electronic address: xxwang@cdc.zj.cn.
Abstract
BACKGROUND: 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.
BACKGROUND:Humaninfection 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 humaninfection is reported. Studies showed that the prevalence of influenza A subtype H7 in environmental samples is associated with the number of humanH7N9 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 humanH7N9 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.
Authors: Yijing Wang; Yingsi Lai; Zhicheng Du; Wangjian Zhang; Chenyang Feng; Ruixue Li; Yuantao Hao Journal: Int J Environ Res Public Health Date: 2019-04-03 Impact factor: 3.390