Background: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-bo...Background: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.Methods: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.Results: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.Conclusions: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.展开更多
基金Funding for the work came from WHO PO 21353027(PI MCT)in support of WHO-TDR IDRC-funded project:“Population health vulnerabilities to vectorborne diseases:increasing resilience under climate change conditions in Africa”WHO PO 201487225(PI MCT)as a technical contribution to the Global Framework for Climate Services.ÁM was supported via the Atmospheric and Oceanic Sciences(AOS)Program at Princeton University.
文摘Background: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.Methods: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.Results: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.Conclusions: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.
