Visualizing the uncertainty in the relationship between seasonal average climate and malaria risk.
Visualizing the uncertainty in the relationship between seasonal average climate and malaria risk.
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DOI：
10.1038/srep07264
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发表时间：
2014-12-02
影响因子：
4.6
通讯作者：
Morse AP
中科院分区：
文献类型：
--
作者：
MacLeod DA;Morse AP
每年约有16亿美元用于资助抗疟疾行动，尽管疟疾发病率正在下降，但年度流行病的影响仍然很大。虽然疟疾风险可能会随着气候变化而增加，但预测高度不确定，为了避开这种棘手的不确定性，适应努力应该提高社会预测和减轻个别事件的能力。对气候相关事件的预测是通过季节性气候预报实现的，通过季节性气候预报，可以提前几个月发出季节平均气温和降雨量异常的警告。季节性气候后播已被用来驱动基于气候的疟疾模型，显示出对观察到的疟疾发病率的重大技能。然而，季节平均气候与疟疾风险之间的关系仍未量化。在这里，我们使用一个动态的天气驱动的疟疾模型来探索这种关系。我们还通过在模型公式的一阶不确定性之一中引入可变性来量化疟疾模型中的关键不确定性。结果被可视化为特定位置的影响表面：易于与整体季节性气候预报相结合，并直观地传达量化的不确定性。对两个流行地区的方法进行了演示，并不局限于疟疾建模；可视化方法可以应用于任何气候影响。
Around $1.6 billion per year is spent financing anti-malaria initiatives, and though malaria morbidity is falling, the impact of annual epidemics remains significant. Whilst malaria risk may increase with climate change, projections are highly uncertain and to sidestep this intractable uncertainty, adaptation efforts should improve societal ability to anticipate and mitigate individual events. Anticipation of climate-related events is made possible by seasonal climate forecasting, from which warnings of anomalous seasonal average temperature and rainfall, months in advance are possible. Seasonal climate hindcasts have been used to drive climate-based models for malaria, showing significant skill for observed malaria incidence. However, the relationship between seasonal average climate and malaria risk remains unquantified. Here we explore this relationship, using a dynamic weather-driven malaria model. We also quantify key uncertainty in the malaria model, by introducing variability in one of the first order uncertainties in model formulation. Results are visualized as location-specific impact surfaces: easily integrated with ensemble seasonal climate forecasts, and intuitively communicating quantified uncertainty. Methods are demonstrated for two epidemic regions, and are not limited to malaria modeling; the visualization method could be applied to any climate impact.
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影响因子：
64.8
作者：
Thomson, MC;Doblas-Reyes, FJ;Palmer, TN
通讯作者：
Palmer, TN
DOI：
10.1016/s0035-9203(99)90344-9
发表时间：
1999-09-01
影响因子：
2.2
作者：
Lindblade, KA;Walker, ED;Wilson, ML
通讯作者：
Wilson, ML
DOI：
10.1073/pnas.0308714100
发表时间：
2004-02-24
影响因子：
11.1
作者：
Zhou, G;Minakawa, N;Yan, GY
通讯作者：
Yan, GY
影响因子：
1.1
作者：
Semenov, MA;Brooks, RJ;Richardson, CW
通讯作者：
Richardson, CW
影响因子：
3
作者：
Tompkins, Adrian M.;Ermert, Volker
通讯作者：
Ermert, Volker