International Research Institute for Climate and Society (IRI), Earth Institute, Columbia University, New York, USA.
Mailman School of Public Health Department of Environmental Health Sciences, Columbia University, New York, USA.
Infect Dis Poverty. 2018 Aug 10;7(1):81. doi: 10.1186/s40249-018-0460-1.
Climate-based disease forecasting has been proposed as a potential tool in climate change adaptation for the health sector. Here we explore the relevance of climate data, drivers and predictions for vector-borne disease control efforts in Africa.
Using data from a number of sources we explore rainfall and temperature across the African continent, from seasonality to variability at annual, multi-decadal and timescales consistent with climate change. We give particular attention to three regions defined as WHO-TDR study zones in Western, Eastern and Southern Africa. Our analyses include 1) time scale decomposition to establish the relative importance of year-to-year, decadal and long term trends in rainfall and temperature; 2) the impact of the El Niño Southern Oscillation (ENSO) on rainfall and temperature at the Pan African scale; 3) the impact of ENSO on the climate of Tanzania using high resolution climate products and 4) the potential predictability of the climate in different regions and seasons using Generalized Relative Operating Characteristics. We use these analyses to review the relevance of climate forecasts for applications in vector borne disease control across the continent.
Timescale decomposition revealed long term warming in all three regions of Africa - at the level of 0.1-0.3 °C per decade. Decadal variations in rainfall were apparent in all regions and particularly pronounced in the Sahel and during the East African long rains (March-May). Year-to-year variability in both rainfall and temperature, in part associated with ENSO, were the dominant signal for climate variations on any timescale. Observed climate data and seasonal climate forecasts were identified as the most relevant sources of climate information for use in early warning systems for vector-borne diseases but the latter varied in skill by region and season.
Adaptation to the vector-borne disease risks of climate variability and change is a priority for government and civil society in African countries. Understanding rainfall and temperature variations and trends at multiple timescales and their potential predictability is a necessary first step in the incorporation of relevant climate information into vector-borne disease control decision-making.
基于气候的疾病预测已被提议作为卫生部门应对气候变化的一种潜在工具。在这里,我们探讨了气候数据、驱动因素和预测对非洲病媒传播疾病控制工作的相关性。
我们利用来自多个来源的数据,探索了整个非洲大陆的降雨和温度,包括季节性、年度、数十年和与气候变化一致的时间尺度的变化。我们特别关注被世界卫生组织热带病研究和培训特别规划署定义为西部、东部和南部非洲三个研究区的三个地区。我们的分析包括:1)时间尺度分解,以确定降雨和温度的年际、十年和长期趋势的相对重要性;2)泛非尺度上厄尔尼诺南方涛动(ENSO)对降雨和温度的影响;3)利用高分辨率气候产品评估 ENSO 对坦桑尼亚气候的影响;4)利用广义相对运行特性评估不同地区和季节气候的潜在可预测性。我们使用这些分析来审查气候预测在整个非洲大陆病媒传播疾病控制中的应用相关性。
时间尺度分解显示,非洲的三个地区都存在长期变暖现象——在 0.1-0.3°C/十年的水平。所有地区都存在降雨的年代际变化,特别是在萨赫勒地区和东非长雨季(3 月至 5 月)。降雨和温度的年际变化,部分与 ENSO 相关,是任何时间尺度上气候变化的主要信号。观测到的气候数据和季节性气候预测被确定为用于病媒传播疾病早期预警系统的最相关气候信息来源,但后者在不同地区和季节的技能有所不同。
适应气候变异性和变化对病媒传播疾病风险的影响是非洲国家政府和民间社会的当务之急。了解多个时间尺度上的降雨和温度变化和趋势及其潜在的可预测性,是将相关气候信息纳入病媒传播疾病控制决策的必要第一步。