Tuesday, 24 January 2017
4E (Washington State Convention Center )
Malaria in Ethiopia is highly sensitive to climate, with epidemics historically occurring in unusually warm and wet years. The climate of Ethiopia, one of the most complex in Africa, is in part driven by global processes associated with the El Niño-Southern Oscillation (ENSO). This study aims to evaluate the premise that Ethiopian malaria epidemics/outbreaks are associated with ENSO and potentially predictable.
A review of the published and grey literature was conducted to identify epidemic/outbreak events and their temporal and spatial characteristics in Ethiopia for the period 1951-2014. The timing and geographic locations (where known) of the observed epidemics were then associated with their respective ENSO phases (El Niño, Neutral or La Niña) using the ONI SST index for El Niño 3.4. In order to account for the delayed impact of changes in SST on ambient air temperature, the SST analysis was lagged by 3 months. In addition, a detailed analysis of the spatial and temporal impact of ENSO on temperature and rainfall for the periods of 1981-2014 and 1983-2014, respectively, was undertaken using high resolution climate data made available through the Enhancing National Climate Services (ENACTS) initiative implemented at the Ethiopian National Meteorological Agency. The significance of the seasonal and spatial impact of ENSO on climate variables was calculated using the right tail area of the hypergeometric distribution and performing the Fisher’s exact test.
Only nine of the 24 publications and reports note above normal rainfall and/or temperature in association with the observed malaria epidemic/outbreak events. Although no strong association was revealed between the 27 identified epidemic/outbreak events and ENSO phase, 12 malaria events were found to be associated with El Niño; six with La Niña; six with Neutral years; and three with ENSO periods, characterized by a year in which SST modulated between both El Niño and La Nina states. Within the historical analysis of epidemic/outbreak events classified as widespread events, nine were associated with El Niño; two with La Niña; two with Neutral years; and two with ENSO periods. The impact of ENSO on the seasonal climate of Ethiopia was found to be highly significant (p<0.05). For example and during an El Niño, July – September rainfall was below normal while higher minimum temperatures were present from June – December for large regions of the country.
This study reiterates the complexity of the Ethiopian climate and its significant relationship to ENSO phases which vary by region and season. An historical analysis of the literature revealed significant weaknesses in the available data which constrains any conclusions other than climate being frequently identified as a key driver of malaria epidemics in Ethiopia. While the malaria-climate analysis is constrained by weak epidemic/outbreak event reporting, robust climate analysis is now possible with national coverage and local relevance. The ENACTS climate database permitted a detailed analysis of the spatial and temporal relationship of climate variables and their global drivers. Future work should concentrate on detailed climate analysis where suitable epidemiological time series are also available. The ENSO analysis and ENACTS climate database could also be applied equally for other vector-borne diseases as well as other climate-sensitive health outcomes.
A review of the published and grey literature was conducted to identify epidemic/outbreak events and their temporal and spatial characteristics in Ethiopia for the period 1951-2014. The timing and geographic locations (where known) of the observed epidemics were then associated with their respective ENSO phases (El Niño, Neutral or La Niña) using the ONI SST index for El Niño 3.4. In order to account for the delayed impact of changes in SST on ambient air temperature, the SST analysis was lagged by 3 months. In addition, a detailed analysis of the spatial and temporal impact of ENSO on temperature and rainfall for the periods of 1981-2014 and 1983-2014, respectively, was undertaken using high resolution climate data made available through the Enhancing National Climate Services (ENACTS) initiative implemented at the Ethiopian National Meteorological Agency. The significance of the seasonal and spatial impact of ENSO on climate variables was calculated using the right tail area of the hypergeometric distribution and performing the Fisher’s exact test.
Only nine of the 24 publications and reports note above normal rainfall and/or temperature in association with the observed malaria epidemic/outbreak events. Although no strong association was revealed between the 27 identified epidemic/outbreak events and ENSO phase, 12 malaria events were found to be associated with El Niño; six with La Niña; six with Neutral years; and three with ENSO periods, characterized by a year in which SST modulated between both El Niño and La Nina states. Within the historical analysis of epidemic/outbreak events classified as widespread events, nine were associated with El Niño; two with La Niña; two with Neutral years; and two with ENSO periods. The impact of ENSO on the seasonal climate of Ethiopia was found to be highly significant (p<0.05). For example and during an El Niño, July – September rainfall was below normal while higher minimum temperatures were present from June – December for large regions of the country.
This study reiterates the complexity of the Ethiopian climate and its significant relationship to ENSO phases which vary by region and season. An historical analysis of the literature revealed significant weaknesses in the available data which constrains any conclusions other than climate being frequently identified as a key driver of malaria epidemics in Ethiopia. While the malaria-climate analysis is constrained by weak epidemic/outbreak event reporting, robust climate analysis is now possible with national coverage and local relevance. The ENACTS climate database permitted a detailed analysis of the spatial and temporal relationship of climate variables and their global drivers. Future work should concentrate on detailed climate analysis where suitable epidemiological time series are also available. The ENSO analysis and ENACTS climate database could also be applied equally for other vector-borne diseases as well as other climate-sensitive health outcomes.
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