气象因素对云南省西南地区恙虫病流行的影响与滞后效应研究

李文; 牛彦麟; 赵哲; 任红艳; 李贵昌; 刘小波; 高源; 王君; 鲁亮; 刘起勇

Abstract

李文,牛彦麟,赵哲,任红艳,李贵昌,刘小波,高源,王君,鲁亮,刘起勇.气象因素对云南省西南地区恙虫病流行的影响与滞后效应研究[J].Chinese journal of Epidemiology,2021,42(7):1235-1239

气象因素对云南省西南地区恙虫病流行的影响与滞后效应研究

Meteorological factors and related lag effects on scrub typhus in southwestern Yunnan

Received:August 28, 2020

DOI：10.3760/cma.j.cn112338-20200828-01106

KeyWord: 恙虫病气象因素分布滞后非线性模型

English Key Word: Scrub typhus Meteorological factors Distributed nonlinear lag model

FundProject:国家科技基础资源调查专项（2017FY101202）；气候变化健康风险评估策略与技术研究；气候变化引起的公共卫生问题研究（202046）

Author Name	Affiliation	E-mail
Li Wen	National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
Niu Yanlin	National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China Beijing Center for Disease Prevention and Control, Beijing 100013, China
Zhao Zhe	Department of Epidemiology, School of Public Health, Shandong University, Ji'nan 250012, China
Ren Hongyan	State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Li Guichang	National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
Liu Xiaobo	National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
Gao Yuan	National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
Wang Jun	National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
Lu Liang	National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China	luliang@icdc.cn
Liu Qiyong	National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China

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Abstract:

目的分析气象因素对云南省西南部地区恙虫病流行的影响与滞后效应，为采取相应的防控措施提供参考依据。方法收集2007-2018年云南省西南部保山、临沧、德宏地区恙虫病资料及同期气象资料，构建分布滞后非线性模型研究气温、湿度和降雨对恙虫病发病的累积滞后效应。结果 2007-2018年云南省西南部地区共报告恙虫病19 975例；周平均气温、周平均相对湿度与恙虫病发病风险均呈J形曲线，周平均气温>23℃、周平均相对湿度>80%以及周平均降雨量在20~60 mm之间和>100 mm时，恙虫病累积发病风险增加；以M为参考，较低气温（11.22℃，14.83℃）、较低湿度（53.18%，65.36%）、较低降雨（0.00 mm，0.55 mm）可降低发病风险，较高气温（22.27℃，23.45℃）、较高湿度（80.14%，84.38%）以及较高降雨（37.17 mm，74.42 mm）都可增加发病风险，气温滞后效应可分别持续10、16周，在暴露当周发病风险最大；湿度滞后效应可分别持续10、17周；降雨滞后效应可持续25周，第4周发病风险最大。结论气温、湿度和降雨对恙虫病发病具有非线性影响和滞后效应，高温、高湿及强降雨会增加恙虫病的发病风险，提示有关部门应根据气象条件实施干预和防控，提高防控效率。

English Abstract:

Objective To analyze the influence and related lag effects of meteorological factors on scrub typhus (ST) in southwestern Yunnan, to provide a reference for the corresponding prevention and treatment measures.Methods Data on ST and meteorology in Yunnan province from 2007 to 2018 were collected. A distributed lag nonlinear model was conducted to study the cumulative lag effects of temperature, relative humidity, and rainfall on ST. Results From 2007-2018, a total of 19 975 ST cases were reported in southwestern Yunnan. Weekly mean temperature, mean relative humidity, and the risk of ST all showed J-shaped curves. The cumulative risk of ST increased with mean temperature >23℃, mean relative humidity >80%, and cumulative rainfall between 20 and 60 mm or over 100 mm, weekly. Taking the median value as the reference, higher temperature (22.27℃, 23.45℃), relative humidity (80.14%, 84.38%) and rainfall (37.17 mm, 74.42 mm) all increased the risk of disease while lower temperature (11.22℃,14.83℃), relative humidity (53.18%,65.36%) and rainfall (0.00 mm,0.55 mm) showed opposite effects. The temperature-lag effect lasted for 10 and 16 weeks, respectively, with ST's risk the highest during the week of exposure. Humidity-lag effects usually last for 10 and 17 weeks. The lag effect of rainfall lasted for 25 weeks, while the disease's risk was the highest in the 4^th week. Conclusion Factors as temperature, relative humidity, and precipitation showed nonlinear and lag effects on ST. High temperature, high relative humidity, and an appropriate amount of rainfalls increase the risk of ST. The authorities of public health should implement effective prevention and control measures according to meteorological conditions.

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