Malaria early warnings based on seasonal climate forecasts from multi-model ensembles
Malaria early warnings based on seasonal climate forecasts from multi-model ensembles
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DOI：
10.1038/nature04503
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发表时间：
2006-02-02
期刊：
影响因子：
64.8
通讯作者：
Palmer, TN
中科院分区：
文献类型：
--
作者：
Thomson, MC;Doblas-Reyes, FJ;Palmer, TN
控制疟疾流行是国际卫生界的一项优先事项，已经商定了及早发现和有效控制疟疾流行的具体目标(1)。年际气候变化是非洲部分地区流行病的重要决定因素(2)，那里的气候驱动蚊子媒介动态和寄生虫发展速度(3)。因此，熟练的季节性气候预报可能会为疫情易发地区的风险变化提供早期预警。在这里，我们讨论了利用欧洲开发的领先的全球海洋-大气耦合气候模式，利用动态的、季节-时间尺度的、多模式集合气候预测来预测异常高和低疟疾发病率的可能性的系统的开发。该预报系统被成功地应用于博茨瓦纳的疟疾风险预报，那里疟疾和气候变异性之间的联系已建立得很好(4)，比根据观测降雨量发布的疟疾预警提前四个月，并且具有相对较高的概率预报技能水平。在预测概率分布与气候学分布不同的年份，疟疾决策者可以利用这些信息来改进资源分配。
The control of epidemic malaria is a priority for the international health community and specific targets for the early detection and effective control of epidemics have been agreed(1). Interannual climate variability is an important determinant of epidemics in parts of Africa(2) where climate drives both mosquito vector dynamics and parasite development rates(3). Hence, skilful seasonal climate forecasts may provide early warning of changes of risk in epidemic-prone regions. Here we discuss the development of a system to forecast probabilities of anomalously high and low malaria incidence with dynamically based, seasonal-timescale, multi-model ensemble predictions of climate, using leading global coupled ocean - atmosphere climate models developed in Europe. This forecast system is successfully applied to the prediction of malaria risk in Botswana, where links between malaria and climate variability are well established(4), adding up to four months lead time over malaria warnings issued with observed precipitation and having a comparably high level of probabilistic prediction skill. In years in which the forecast probability distribution is different from that of climatology, malaria decision-makers can use this information for improved resource allocation.