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疟疾发病率与气象因素的关系:2005-2012 年中国多地点研究。

Association between malaria incidence and meteorological factors: a multi-location study in China, 2005-2012.

机构信息

School of Public Health, The University of Adelaide,Adelaide, South Australia 5005,Australia.

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 102206,China.

出版信息

Epidemiol Infect. 2018 Jan;146(1):89-99. doi: 10.1017/S0950268817002254. Epub 2017 Dec 17.

Abstract

This study aims to investigate the climate-malaria associations in nine cities selected from malaria high-risk areas in China. Daily reports of malaria cases in Anhui, Henan, and Yunnan Provinces for 2005-2012 were obtained from the Chinese Center for Disease Control and Prevention. Generalized estimating equation models were used to quantify the city-specific climate-malaria associations. Multivariate random-effects meta-regression analyses were used to pool the city-specific effects. An inverted-U-shaped curve relationship was observed between temperatures, average relative humidity, and malaria. A 1 °C increase of maximum temperature (T max) resulted in 6·7% (95% CI 4·6-8·8%) to 15·8% (95% CI 14·1-17·4%) increase of malaria, with corresponding lags ranging from 7 to 45 days. For minimum temperature (T min), the effect estimates peaked at lag 0 to 40 days, ranging from 5·3% (95% CI 4·4-6·2%) to 17·9% (95% CI 15·6-20·1%). Malaria is more sensitive to T min in cool climates and T max in warm climates. The duration of lag effect in a cool climate zone is longer than that in a warm climate zone. Lagged effects did not vanish after an epidemic season but waned gradually in the following 2-3 warm seasons. A warming climate may potentially increase the risk of malaria resurgence in China.

摘要

本研究旨在调查中国疟疾高风险地区九个城市的气候-疟疾关联。我们从中国疾病预防控制中心获取了 2005 年至 2012 年安徽、河南和云南省的疟疾日报告。采用广义估计方程模型量化城市特有气候-疟疾关联。采用多元随机效应荟萃回归分析对城市特有效应进行汇总。我们观察到温度、平均相对湿度与疟疾之间呈倒 U 型曲线关系。最高温度(Tmax)升高 1°C 会导致疟疾增加 6.7%(95%CI 4.6-8.8%)至 15.8%(95%CI 14.1-17.4%),相应的滞后时间从 7 天到 45 天不等。对于最低温度(Tmin),效应估计在 0 到 40 天的滞后时间内达到峰值,范围为 5.3%(95%CI 4.4-6.2%)至 17.9%(95%CI 15.6-20.1%)。疟疾对低温环境下的 Tmin 和高温环境下的 Tmax 更为敏感。在低温气候区,滞后效应的持续时间长于温暖气候区。在一个流行季节之后,滞后效应并没有消失,而是在随后的 2-3 个暖季逐渐减弱。气候变暖可能会增加中国疟疾死灰复燃的风险。

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