Vegetation index anomalies and Rift Valley fever (RVF) outbreaks in Africa and Middle East during 2000-2018

The visualization featured on this page showcases the relationship between increase in vegetation and outbreaks of Rift Valley fever (RVF) over Middle East and the African continent for the period of 2000-2018. The data visualized in this animation are: a) Normalized Difference Vegetation Index (NDVI) (low/brown to high/green) over Africa and Middle East and b) locations of Rift Valley fever outbreaks (orange pins). We can see spikes of RVF outbreaks in various regions such as in Middle East, West, East and South Africa. These outbreaks are linked to El Niño-Southern Oscillation (ENSO) teleconnections.

ENSO is an irregularly recurring climate pattern characterized by warmer (El Niño) and colder (La Niña) than usual ocean temperatures in the equatorial Pacific, which creates a ripple effect of anticipated weather changes in far-spread regions of our planet. Weather changes associated with the El Niño-Southern Oscillation phenomenon result in climate anomalies related to each other, such as rainfall, and vegetation anomaly conditions that trigger outbreaks of infectious diseases of public health concern in different regions around the world. These distant weather effects are called teleconnections. Therefore the effects of ENSO are called ENSO teleconnections, highlighting that warmer or colder than usual ocean temperatures in equatorial pacific with extents (5N-5S, 120W-170W) affect areas far from the source typically 2-3 months after.

During the last 20 years NASA scientist Dr. Assaf Anyamba and colleagues have been studying ENSO teleconnections by monitoring various climate datasets, among them Sea Surface Temperature and precipitation anomaly datasets from NASA and National Oceanic and Atmospheric Administration (NOAA) and vegetation data from NASA’s Earth Observing System Moderate Resolution Imaging Spectroradiometer (MODIS) instrument aboard the Terra (EOS AM-1) spacecraft. At the same time, the science team has been collecting, cataloguing and analyzing patterns and sources of disease outbreaks worldwide. To learn more, please refer to entry: Sea Surface Temperature anomalies and patterns of Global Disease Outbreaks: 2009-2018 (4K version)

The relationship between ENSO induced anomalous rainfall and disease outbreaks is clearly illustrated by outbreak patterns of Rift Valley fever (RVF). Typically, during El Niño (Eastern Africa) and La Niña (Southern Africa) events, Africa receives persistent and above normal rainfall, which floods habitats of RVF mosquito vectors triggering hatching of RVF virus infected eggs. The above-normal rainfall is followed by an increase in vegetation creating appropriate habitats for the mosquito vectors setting the stage for RVF outbreak activity, which in simple terms means an uptick in mosquito populations that cause infections of domestic livestock and human populations with the RVF virus.

To learn more about the impacts of weather patterns and teleconnections for the region of South Africa during 2008-2011, please see the following data visualizations:

• ENSO Teleconnections and Rift Valley fever (RVF) Outbreaks
• Precipitation Anomaly and Rift Valley fever (RVF) outbreaks in South Africa: 2008-2011
• Vegetation Index Anomalies and Rift Valley fever (RVF) outbreaks in South Africa region: 2008-2011

• Disease Outbreak data were collected from the Program for Monitoring Emerging Diseases (ProMED) and the World Organisation for Animal Health/Organisation mondiale de la santé animale (OIE).


• Normalized Difference Vegetation Index (NDVI) dataset is derived from NASA’s Earth Observing System Moderate Resolution Imaging Spectroradiometer (MODIS) instrument aboard the Terra (EOS AM-1) spacecraft. We used the MODIS global monthly Climate Modeling Grid (CMG) products with a spatial resolution of 0.05° x 0.05° (~5.5 x 5.5 km). The data is available here. Reference: Townshend, J. & Justice, Christopher. (2002). Towards operational monitoring of terrestrial systems by moderate-resolution remote sensing. Remote Sensing of Environment. Volume 83, Issues 1-2, Pages: 351-359. 10.1016/S0034-4257(02)00082-2.