Guo Cui, Yang Lin, Ou Chun-Quan, Li Li, Zhuang Yan, Yang Jun, Zhou Ying-Xue, Qian Jun, Chen Ping-Yan, Liu Qi-Yong
State Key Laboratory of Organ Failure Research, Department of Biostatistics, School of Public Health and Tropical Medicine, Southern Medical University, Guangzhou, 510515, China.
Department of Nursing, Faculty of Health and Social Sciences, The Hong Kong Polytechnic University, Hong Kong, China.
Malar J. 2015 Mar 18;14:116. doi: 10.1186/s12936-015-0630-6.
The temporal variation of malaria incidence has been linked to meteorological factors in many studies, but key factors observed and corresponding effect estimates were not consistent. Furthermore, the potential effect modification by individual characteristics is not well documented. This study intends to examine the delayed effects of meteorological factors and the sub-population's susceptibility in Guangdong, China.
The Granger causality Wald test and Spearman correlation analysis were employed to select climatic variables influencing malaria. The distributed lag non-linear model (DLNM) was used to estimate the non-linear and delayed effects of weekly temperature, duration of sunshine, and precipitation on the weekly number of malaria cases after controlling for other confounders. Stratified analyses were conducted to identify the sub-population's susceptibility to meteorological effects by malaria type, gender, and age group.
An incidence rate of 1.1 cases per 1,000,000 people was detected in Guangdong from 2005-2013. High temperature was associated with an observed increase in malaria incidence, with the effect lasting for four weeks and a maximum relative risk (RR) of 1.57 (95% confidence interval (CI): 1.06-2.33) by comparing 30°C to the median temperature. The effect of sunshine duration peaked at lag five and the maximum RR was 1.36 (95% CI: 1.08-1.72) by comparing 24 hours/week to 0 hours/week. A J-shaped relationship was found between malaria incidence and precipitation with a threshold of 150 mm/week. Over the threshold, precipitation increased malaria incidence after four weeks with the effect lasting for 15 weeks, and the maximum RR of 1.55 (95% CI: 1.18-2.03) occurring at lag eight by comparing 225 mm/week to 0 mm/week. Plasmodium falciparum was more sensitive to temperature and precipitation than Plasmodium vivax. Females had a higher susceptibility to the effects of sunshine and precipitation, and children and the elderly were more sensitive to the change of temperature, sunshine duration, and precipitation.
Temperature, duration of sunshine and precipitation played important roles in malaria incidence with effects delayed and varied across lags. Climatic effects were distinct among sub-groups. This study provided helpful information for predicting malaria incidence and developing the future warning system.
许多研究已将疟疾发病率的时间变化与气象因素联系起来,但观察到的关键因素及其相应的效应估计并不一致。此外,个体特征对效应的潜在修正作用尚无充分记录。本研究旨在探讨中国广东省气象因素的延迟效应以及亚人群的易感性。
采用格兰杰因果关系Wald检验和Spearman相关分析来选择影响疟疾的气候变量。在控制其他混杂因素后,使用分布滞后非线性模型(DLNM)来估计每周温度、日照时长和降水量对每周疟疾病例数的非线性和延迟效应。进行分层分析,以按疟疾类型、性别和年龄组确定亚人群对气象效应的易感性。
2005 - 2013年期间,广东省检测到的发病率为每100万人中有1.1例。高温与观察到的疟疾发病率增加相关,效应持续四周,将30°C与中位数温度相比,最大相对风险(RR)为1.57(95%置信区间(CI):1.06 - 2.33)。日照时长的效应在滞后五周时达到峰值,将每周24小时与每周0小时相比,最大RR为1.36(95% CI:1.08 - 1.72)。发现疟疾发病率与降水量之间呈J形关系,阈值为每周150毫米。超过阈值后,降水量在四周后增加疟疾发病率,效应持续15周,将每周225毫米与每周0毫米相比,最大RR为1.55(95% CI:1.18 - 2.03),出现在滞后八周时。恶性疟原虫比间日疟原虫对温度和降水量更敏感。女性对日照和降水量效应的易感性更高,儿童和老年人对温度、日照时长和降水量的变化更敏感。
温度、日照时长和降水量在疟疾发病率中起重要作用,效应具有延迟性且在不同滞后时间有所不同。气候效应在亚组之间存在差异。本研究为预测疟疾发病率和开发未来预警系统提供了有用信息。