Zhou Guofa, Minakawa Noboru, Githeko Andrew K, Yan Guiyun
Department of Biological Sciences, State University of New York, Buffalo, NY 14260, USA.
Proc Natl Acad Sci U S A. 2004 Feb 24;101(8):2375-80. doi: 10.1073/pnas.0308714100.
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.
东非高地近期恶性疟原虫流行性疟疾再度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来自不同地点的疟疾病例长期数据系列,评估气候对疟疾复发的影响很困难。气候变异性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温度变化更具相关性,但其对疟疾流行的影响尚未得到严格检验。在此,我们使用非线性混合回归模型来研究自回归(前一时期疟疾门诊患者数量)、季节性和气候变异性与东非七个高地地点过去10 - 20年每月疟疾门诊患者数量之间的关联。该模型解释了每月疟疾门诊患者数量方差的65 - 81%。在所有七个地点都发现了温度和降雨对疟疾门诊患者数量的非线性和协同效应。自回归和季节性导致的每月疟疾门诊患者数量的净方差在不同地点有所不同,范围从18%到63%(平均 = 38.6%),而12%到63%(平均 = 36.1%)的方差归因于气候变异性。我们的结果表明,高地疟疾门诊患者数量对气候波动的敏感性存在高度空间变化,并且气候变异性在东非高地引发疟疾流行中发挥了重要作用。