Xiaocheng Wu1, Lingling Lang2, Wenjun Ma2, Tie Song3, Min Kang3, Jianfeng He3, Yonghui Zhang3, Liang Lu4, Hualiang Lin1, Li Ling5. 1. Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China. 2. Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China. 3. Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China. 4. State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China. 5. Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China; Center for Migrant Health Policy, Sun Yat-sen University, Guangzhou, China. Electronic address: lingli@mail.sysu.edu.cn.
Abstract
BACKGROUND: Dengue fever is an important infectious disease in Guangzhou, China; previous studies on the effects of weather factors on the incidence of dengue fever did not consider the linearity of the associations. METHODS: This study evaluated the effects of daily mean temperature, relative humidity and rainfall on the incidence of dengue fever. A generalized additive model with splines smoothing function was performed to examine the effects of daily mean, minimum and maximum temperatures, relative humidity and rainfall on incidence of dengue fever during 2006-2014. RESULTS: Our analysis detected a non-linear effect of mean, minimum and maximum temperatures and relative humidity on dengue fever with the thresholds at 28°C, 23°C and 32°C for daily mean, minimum and maximum temperatures, 76% for relative humidity, respectively. Below the thresholds, there was a significant positive effect, the excess risk in dengue fever for each 1°C in the mean temperature at lag7-14days was 10.21%, (95% CI: 6.62% to 13.92%), 7.10% (95% CI: 4.99%, 9.26%) for 1°C increase in daily minimum temperature in lag 11days, and 2.27% (95% CI: 0.84%, 3.72%) for 1°C increase in daily maximum temperature in lag 10days; and each 1% increase in relative humidity of lag7-14days was associated with 1.95% (95% CI: 1.21% to 2.69%) in risk of dengue fever. CONCLUSIONS: Future prevention and control measures and epidemiology studies on dengue fever should consider these weather factors based on their exposure-response relationship.
BACKGROUND:Dengue fever is an important infectious disease in Guangzhou, China; previous studies on the effects of weather factors on the incidence of dengue fever did not consider the linearity of the associations. METHODS: This study evaluated the effects of daily mean temperature, relative humidity and rainfall on the incidence of dengue fever. A generalized additive model with splines smoothing function was performed to examine the effects of daily mean, minimum and maximum temperatures, relative humidity and rainfall on incidence of dengue fever during 2006-2014. RESULTS: Our analysis detected a non-linear effect of mean, minimum and maximum temperatures and relative humidity on dengue fever with the thresholds at 28°C, 23°C and 32°C for daily mean, minimum and maximum temperatures, 76% for relative humidity, respectively. Below the thresholds, there was a significant positive effect, the excess risk in dengue fever for each 1°C in the mean temperature at lag7-14days was 10.21%, (95% CI: 6.62% to 13.92%), 7.10% (95% CI: 4.99%, 9.26%) for 1°C increase in daily minimum temperature in lag 11days, and 2.27% (95% CI: 0.84%, 3.72%) for 1°C increase in daily maximum temperature in lag 10days; and each 1% increase in relative humidity of lag7-14days was associated with 1.95% (95% CI: 1.21% to 2.69%) in risk of dengue fever. CONCLUSIONS: Future prevention and control measures and epidemiology studies on dengue fever should consider these weather factors based on their exposure-response relationship.
Authors: Asim Anwar; Noman Khan; Muhammad Ayub; Faisal Nawaz; Asim Shah; Antoine Flahault Journal: Int J Environ Res Public Health Date: 2019-06-28 Impact factor: 3.390