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Spatial and temporal anomaly patterns of NDVI, SST in relation to RVF outbreaks.

Domain:

climatehealthcaregeospatial

Record type:

dataset
Creator:
AssKenJenKat
Host:avatar

Spatial and temporal anomaly patterns in normalized difference vegetation index for selected areas of South Africa (A: 29°E and 32.5°E, averaged from 23°S to 27°S), Sudan (B: 32.5°E and 34°E, averaged from 11°N to 15°N), Tanzania (C: 34°E and 37°E, averaged from 4.5°S to 8.5°S) and Kenya (D: 37°E and 42.5°E, averaged from 2°S to 2°N). Regions were plotted by geographic position west to east and represent areas with dense concentrations of Rift Valley fever cases. NDVI anomalies are depicted as percent departures from the 2002–2008 long-term mean, and show the response of vegetation to variations in rainfall. Periods shaded in green to purple indicate above-normal vegetation conditions associated with above-normal rainfall. Periods of persistent drought or below normal rainfall are shown in shades of yellow to red. Each Rift Valley fever outbreak was preceded by above-normal vegetation conditions resulting from persistent above-normal rainfall in the Horn of Africa and Sudan in 2006–2007. Chikungunya epidemics occurred over East Africa and Indian Ocean islands during the 2005–2006 drought period shown by negative NDVI anomalies from 2005–2006 [D: red boxed area]. Clusters of epidemics/epizootics of Rift Valley fever in East Africa (2006–2007) and Sudan (2007) occurred during the El Niño event of 2006–2007 when there were concurrent anomalously warmer WIO and Nino 3.4 SSTs. The transition to La Niña conditions in late 2007–early 2008 spatially shifted the area of above-normal rainfall and enhanced vegetation conditions to South Africa and Madagascar between February–March, 2008 and sporadically between February–March, 2009 in South Africa, leading to outbreaks of Rift Valley fever in these regions. This illustrates that spatial displacements in extreme rainfall and ecological conditions driven by large-scale climate mechanisms such as ENSO and regional circulation lead to spatial-temporal shifts in areas at risk for outbreaks of these mosquito-borne diseases.

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Tags

EcologyInformation and Computing SciencesPlant Biologytemporalanomalypatternssstrvf

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CC BY 4.0

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