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Remotely-sensed Enviroclimatic patterns and Ebola outbreaks: linkages and early warning. Dan Slayback Jorge Pinzon Compton Tucker 8 September 2004. Biospheric Science Branch, Code 923 NASA Goddard Space Flight Center Greenbelt MD 20771 USA. Outline. Ebola outbreaks: facts and hypotheses
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Remotely-sensed Enviroclimatic patterns and Ebola outbreaks:linkages and early warning Dan Slayback Jorge Pinzon Compton Tucker 8 September 2004 Biospheric Science Branch, Code 923 NASA Goddard Space Flight Center Greenbelt MD 20771 USA
Outline • Ebola outbreaks: facts and hypotheses • Environmental links to remotely sensed data • Spatial & temporal specificity of environmental trigger events • Conclusions From: Trigger events: enviroclimatic coupling of Ebola hemorrhagic fever outbreaks. 2004. JE Pinzon, JM Wilson, CJ Tucker, R Arthur, PB Jahrling, and P Formenty, American Journal of Tropical Medicine and Hygiene. (in press)
Many Ebola outbreaks have occurred in African closed tropical forest • Some Ebola outbreaks have occurred in African gallery tropical forest within a savanna matrix
Outbreak Severity 385 210 79 47
Transmission Scenarios Community Epidemic Scenario • Secondary transmission within species. • Reciprocal transmission between species. APES/HUMANS INTERMEDIATE HOST RESERVOIR Peter Walsh et al. Nature (2003) Just because a species tests positive for virus or antibodies does not mean that it is a link in the chain of transmission to apes. “Cul de Sac” Hosts Cul de Sac HOST--HUMANS? APES RESERVOIR
Possible Ebola Transmission(s)no usual suspects! It is unknown where the virus dwells…
Environmental Links withRemotely Sensed Data:available datasets 1980 1985 1990 1995 2000 2005 2010 Moderate-resolution (1-10’s kms) environmental satellites MODISes NOAA-16 AVHRR NPOESS NOAA 14 AVHRR NOAA 11 AVHRR NOAA 9 AVHRR SPOT NOAA 7 AVHRR SeaWiFS NOAA9
NOAA AVHRR 8-km NDVI Data Set Radiation
VIS/NIR/SWIR Band Comparison SPOT-VGT SeaWiFS AVHRR MODIS
Major Dataset Differences Global NDVI anomalies
Are there unique environmental characteristics at outbreak sites, during the outbreak year?
Canonical Correlation Analysis (CCA) • CCA is a method that maximizes the variance between two datasets. Here, we use CCA to identify areas and times that exhibit enviroclimatic signals typical of those at known outbreak sites and dates. • CCA(A) = [U,S,V] • A: paired-mode correlation matrix between yearly NDVI signals and corresponding NDVI signals from the outbreak sites at outbreak years. • U: orthonormal vector of satellite NDVI signals • S: percentage of covariance explained by canonical factors • V: orthonormal vector of Ebola sites • The analysis conducted only over areas with high enviroclimatic correlation to previous outbreak sites (r2 > 0.95)