Wangjian Zhang1, Zhicheng Du2, Dingmei Zhang3, Shicheng Yu4, Yuantao Hao5. 1. Department of Medical Statistics and Epidemiology, Health Information Research Center, Guangdong Key Laboratory of Medicine, School of Public Health, Sun Yat-sen University, Guangzhou, 510080 Guangdong Province, China. Electronic address: zhangwj35@mail2.sysu.edu.cn. 2. Department of Medical Statistics and Epidemiology, Health Information Research Center, Guangdong Key Laboratory of Medicine, School of Public Health, Sun Yat-sen University, Guangzhou, 510080 Guangdong Province, China. Electronic address: duzhch3@mail2.sysu.edu.cn. 3. Department of Medical Statistics and Epidemiology, Health Information Research Center, Guangdong Key Laboratory of Medicine, School of Public Health, Sun Yat-sen University, Guangzhou, 510080 Guangdong Province, China. Electronic address: zhdingm@mail.sysu.edu.cn. 4. Chinese Center for Disease Control and Prevention, Beijing 102206, China. Electronic address: shicheng_yu@hotmail.com. 5. Department of Medical Statistics and Epidemiology, Health Information Research Center, Guangdong Key Laboratory of Medicine, School of Public Health, Sun Yat-sen University, Guangzhou, 510080 Guangdong Province, China. Electronic address: haoyt@mail.sysu.edu.cn.
Abstract
BACKGROUND: Hand, foot and mouth disease (HFMD) is a common childhood infection and has become a major public health issue in China. Considerable research has focused on the role of meteorological factors in HFMD development. Nonlinear relationship, delayed effects and collinearity problems are key issues for achieving robust and accurate estimations in this kind of weather-health relationship explorations. The current study was designed to address these issues and assess the impact of meteorological factors on HFMD in Guangdong, China. METHODS: Case-based HFMD surveillance data and daily meteorological data collected between 2010 and 2012 was obtained from China CDC and the National Meteorological Information Center, respectively. After a preliminary variable selection, for each dataset boosted regression tree (BRT) models were applied to determine the optimal lag for meteorological factors at which the variance of HFMD cases was most explained, and to assess the impacts of these meteorological factors at the optimal lag. RESULTS: Variance of HFMD cases was explained most by meteorological factors about 1 week ago. Younger children and those from the Pearl-River Delta Region were more sensitive to weather changes. Temperature had the largest contribution to HFMD epidemics (28.99-71.93%), followed by precipitation (6.52-16.11%), humidity (3.92-17.66%), wind speed (3.84-11.37%) and sunshine (6.21-10.36%). Temperature between 10°C and 25°C, as well as humidity between 70% and 90%, had a facilitating effect on the epidemic of HFMD. Sunshine duration above 9h and wind speed below 2.5m/s also contributed to an elevated risk of HFMD. The positive relationship between HFMD and precipitation reversed when the daily amount of rainfall exceeded 25 mm. CONCLUSIONS: This study indicated significantly facilitating effects of five meteorological factors within some range on the epidemic of HFMD. Results from the current study were particularly important for developing early warning and response system on HFMD in the context of global climate change.
BACKGROUND: Hand, foot and mouth disease (HFMD) is a common childhood infection and has become a major public health issue in China. Considerable research has focused on the role of meteorological factors in HFMD development. Nonlinear relationship, delayed effects and collinearity problems are key issues for achieving robust and accurate estimations in this kind of weather-health relationship explorations. The current study was designed to address these issues and assess the impact of meteorological factors on HFMD in Guangdong, China. METHODS: Case-based HFMD surveillance data and daily meteorological data collected between 2010 and 2012 was obtained from China CDC and the National Meteorological Information Center, respectively. After a preliminary variable selection, for each dataset boosted regression tree (BRT) models were applied to determine the optimal lag for meteorological factors at which the variance of HFMD cases was most explained, and to assess the impacts of these meteorological factors at the optimal lag. RESULTS: Variance of HFMD cases was explained most by meteorological factors about 1 week ago. Younger children and those from the Pearl-River Delta Region were more sensitive to weather changes. Temperature had the largest contribution to HFMD epidemics (28.99-71.93%), followed by precipitation (6.52-16.11%), humidity (3.92-17.66%), wind speed (3.84-11.37%) and sunshine (6.21-10.36%). Temperature between 10°C and 25°C, as well as humidity between 70% and 90%, had a facilitating effect on the epidemic of HFMD. Sunshine duration above 9h and wind speed below 2.5m/s also contributed to an elevated risk of HFMD. The positive relationship between HFMD and precipitation reversed when the daily amount of rainfall exceeded 25 mm. CONCLUSIONS: This study indicated significantly facilitating effects of five meteorological factors within some range on the epidemic of HFMD. Results from the current study were particularly important for developing early warning and response system on HFMD in the context of global climate change.
Authors: Chengdong Xu; Gexin Xiao; Jinfeng Wang; Xiangxue Zhang; Jinjun Liang Journal: Int J Environ Res Public Health Date: 2017-12-29 Impact factor: 3.390
Authors: Chao Song; Yaqian He; Yanchen Bo; Jinfeng Wang; Zhoupeng Ren; Huibin Yang Journal: Int J Environ Res Public Health Date: 2018-07-12 Impact factor: 3.390