Association between climate variability and malaria epidemics in the East African highlands
Association between climate variability and malaria epidemics in the East African highlands
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DOI：
10.1073/pnas.0308714100
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发表时间：
2004-02-24
影响因子：
11.1
通讯作者：
Yan, GY
中科院分区：
文献类型：
--
作者：
Zhou, G;Minakawa, N;Yan, GY
恶性疟原虫流行性疟疾最近在东非高地重新出现的原因存在争议。区域气候变化被认为是一个主要因素;然而，由于气候在空间和时间上的高度变异性以及缺乏关于不同地点疟疾病例的长期数据系列，很难评估气候对疟疾死灰复燃的影响。气候变率被定义为围绕平均气候状态的短期波动，在流行病学上可能比平均气温变化更相关，但其对疟疾流行的影响尚未得到严格审查。在这里，我们使用非线性混合回归模型来研究自回归（在过去的时间段内的疟疾门诊病人的数量），季节性和气候变化，以及过去10-20年的每月疟疾门诊病人的数量在东非的7个高地网站之间的关联。该模型解释了每月疟疾门诊患者数量的65-81%的方差。在所有七个地点的疟疾门诊病人的数量的温度和降雨量的非线性和协同效应。每月疟疾门诊病人的数量的净方差由自回归和季节性引起的网站之间的变化，范围从18至63%（平均值= 38.6%），而12-63%（平均值= 36.1%）的方差归因于气候变异。我们的研究结果表明，有一个高的空间变化的敏感性疟疾门诊人数在高原地区的气候波动，气候变化在启动疟疾流行在东非高原地区发挥了重要作用。
The causes of the recent reemergence of Plasmodium falciparum epidemic malaria in the East African highlands are controversial. Regional climate changes have been invoked as a major factor; however, assessing the impact of climate in malaria resurgence is difficult due to high spatial and temporal climate variability and the lack of long-term data series on malaria cases from different sites. Climate variability, defined as short-term fluctuations around the mean climate state, may be epidemiologically more relevant than mean temperature change, but its effects on malaria epidemics have not been rigorously examined. Here we used nonlinear mixed-regression model to investigate the association between autoregression (number of malaria outpatients during the previous time period), seasonality and climate variability, and the number of monthly malaria outpatients of the past 10-20 years in seven highland sites in East Africa. The model explained 65-81% of the variance in the number of monthly malaria outpatients. Nonlinear and synergistic effects of temperature and rainfall on the number of malaria outpatients were found in all seven sites. The net variance in the number of monthly malaria outpatients caused by autoregression and seasonality varied among sites and ranged from 18 to 63% (mean = 38.6%), whereas 12-63% (mean = 36.1%) of variance is attributed to climate variability. Our results suggest that there was a high spatial variation in the sensitivity of malaria outpatient number to climate fluctuations in the highlands, and that climate variability played an important role in initiating malaria epidemics in the East African highlands.