Demonstration of successful malaria forecasts for Botswana using an operational seasonal climate model
Demonstration of successful malaria forecasts for Botswana using an operational seasonal climate model
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DOI：
10.1088/1748-9326/10/4/044005
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发表时间：
2015-04-01
影响因子：
6.7
通讯作者：
Morse, Andrew P.
中科院分区：
文献类型：
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作者：
MacLeod, Dave A.;Jones, Anne;Morse, Andrew P.
季节性疟疾流行的严重程度和时间与气温和降雨量密切相关。因此，根据季节性气候模型对气象条件发出预警，有可能预测异常强烈的流行病事件，建立复原力，并适应此类事件发生频率的可能变化。在这里，我们提出了一个基于过程的，动态的疟疾模型驱动的后报从一个国家的最先进的季节性气候模型从欧洲中期天气预报中心的验证。我们验证气候和疟疾模型对观测到的气象和发病率数据为博茨瓦纳在1982-2006年期间，观测到的发病率数据已被用来验证这种建模系统的最长记录。我们考虑了气候模型偏差的影响，气候和流行病学可预测性之间的关系，以及熟练的疟疾预测的潜力。使用11月初发布的预报，展示了博茨瓦纳疟疾季节（1月至5月）上三分之一疟疾发病率的预报技巧;预报系统预计在观察期内七个上三分之一疟疾季节中有六个。验证时间序列的长度使人们相信，有可能对季节性疟疾风险作出可靠的预测，这是博茨瓦纳健康预警系统的一个关键部分，有助于适应气候变化的努力。
The severity and timing of seasonal malaria epidemics is strongly linked with temperature and rainfall. Advance warning of meteorological conditions from seasonal climate models can therefore potentially anticipate unusually strong epidemic events, building resilience and adapting to possible changes in the frequency of such events. Here we present validation of a process-based, dynamic malaria model driven by hindcasts from a state-of-the-art seasonal climate model from the European Centre for Medium-Range Weather Forecasts. We validate the climate and malaria models against observed meteorological and incidence data for Botswana over the period 1982-2006; the longest record of observed incidence data which has been used to validate a modeling system of this kind. We consider the impact of climate model biases, the relationship between climate and epidemiological predictability and the potential for skillful malaria forecasts. Forecast skill is demonstrated for upper tercile malaria incidence for the Botswana malaria season (January-May), using forecasts issued at the start of November; the forecast system anticipates six out of the seven upper tercile malaria seasons in the observational period. The length of the validation time series gives confidence in the conclusion that it is possible to make reliable forecasts of seasonal malaria risk, forming a key part of a health early warning system for Botswana and contributing to efforts to adapt to climate change.