Department of Infectious Disease Control and Prevention, Guangzhou Center for Disease Control and Prevention, Baiyun District Qi De Road in Guangzhou, Guangdong Province 510440, China.
Guangzhou Center for Disease Control and Prevention, Baiyun District Qi De Road in Guangzhou, Guangdong Province 510440, China.
Sci Total Environ. 2020 Aug 1;728:138777. doi: 10.1016/j.scitotenv.2020.138777. Epub 2020 Apr 19.
To analyze the correlation between climatic factors and the incidence of varicella in Guangzhou, and improve the prevention measures about public health.
Data for daily climatic variables and varicella incidence from 2006 to 2018 in Guangzhou were collected from the Guangzhou Meteorological Bureau and the National Notifiable Disease Report System. Distributed lag nonlinear models were applied to evaluate the association between climatic factors and varicella incidence.
The nonlinear effects of meteorological factors were observed. At lag day21，when the mean temperature was 31.8 °C, the relative risk was the highest as 1.11 (95% CI: 1.07-1.16). When the diurnal temperature range was 24.0 °C at lag day 20, the highest RR was 1.11 (95% CI: 1.05-1.17). For rainfall, the highest RR was 1.09 (95% CI: 1.01-1.19) at lag day 21，when the aggregate rainfall was 160 mm. When air pressure was 1028 hPa, the highest RR was 1.08 (95% CI: 1.04-1.13) at lag day 21. When wind speed was 0.7 m/s, the highest RR was 1.07 (95% CI: 1.04-1.11) at lag day 7. When the hours of sunshine were 9.0 h at lag day 21, the RR was highest as 1.04 (95% CI: 1.02-1.05). Aggregate rainfall, air pressure, and sunshine hours were positively correlated with the incidence of varicella, which was inconsistent with the wind velocity. Mean temperature showed a reverse U-shape curve relationship with varicella, while the diurnal temperature range showed a binomial distribution curve. The extreme effect of climatic factors on the varicella cases was statistically significant, apart from the extremely low effect of rainfall.
Our preliminary results offered fundamental knowledge which might be benefit to give an insight into epidemic trends of varicella and develop an early warning system. We could use our findings about influential factors to strengthen the intervention and prevention of varicella.
分析广州地区气象因素与水痘发病率的相关性，为制定公共卫生预防措施提供依据。
收集 2006 年至 2018 年广州逐日气象资料和水痘发病资料，来源于广州市气象局和国家法定传染病报告系统。采用分布滞后非线性模型分析气象因素与水痘发病率的关联。
气象因素存在非线性效应。滞后 21 天，平均气温为 31.8℃时，RR 最高为 1.11（95%CI：1.07-1.16）；滞后 20 天，日温差为 24.0℃时，RR 最高为 1.11（95%CI：1.05-1.17）。对于降雨量，当累积降雨量为 160mm 时，RR 最高为 1.09（95%CI：1.01-1.19），滞后 21 天；当大气压为 1028hPa 时，RR 最高为 1.08（95%CI：1.04-1.13），滞后 21 天；当风速为 0.7m/s 时，RR 最高为 1.07（95%CI：1.04-1.11），滞后 7 天；滞后 21 天，日照时数为 9.0h 时，RR 最高为 1.04（95%CI：1.02-1.05）。累积降雨量、大气压和日照时数与水痘发病率呈正相关，与风速不一致。平均气温与水痘呈反“U”型曲线关系，日温差呈二项分布曲线。除降雨量的极值效应较低外，气象因素对水痘病例的极端效应具有统计学意义。
本研究初步探讨了气象因素与水痘发病率的关系，为了解水痘流行趋势和建立预警系统提供了基础数据，也为水痘的干预和预防提供了有参考价值的依据。
