Study Predicted Outbreak of Deadly Virus
Sunday, February 15, 2009
Assaf Anyamba and the NASA Earth Observatory
An early warning system,
more than a decade in development, successfully predicted the
2006-2007 outbreak of the deadly Rift Valley fever in northeast
Africa, according to a new study led by NASA scientists.
Valley fever is unique in that its emergence is closely linked to
interannual climate variability. Utilizing that link, researchers
including Assaf Anyamba, a geographer and remote sensing
scientist with the University of Maryland Baltimore County and
NASA's Goddard Space Flight Center in Greenbelt, Md., used a
blend of NASA and National Oceanic and Atmospheric Administration
measurements of sea surface temperatures, precipitation, and
vegetation cover to predict when and where an outbreak would
The final product, a Rift Valley fever "risk
map," gave public health officials in East Africa up to six
weeks of warning for the 2006-2007 outbreak, enough time to
lessen human impact. The researchers described their findings in
the Proceedings of the National Academy of Sciences.
first-of-its-kind prediction is the culmination of decades of
research. During an intense El Niño event in 1997, the
largest known outbreak of Rift Valley fever spread across the
Horn of Africa. About 90,000 people were infected with the virus,
which is carried by mosquitoes and transmitted to humans by
mosquito bites or through contact with infected livestock.
1997 outbreak provoked the formation of a working group--funded
by the U.S. Department of Defense Global Emerging Infections
Surveillance and Response System--to see if predictions of an
outbreak could be made operational. Such predictions would not
only aid mitigation efforts in the endemic countries and protect
the global public, but would help protect American civilian and
military personnel located and traveling overseas, ensure the
safety of imported goods and animals, and prevent infected humans
or mosquitoes from entering the United States.
all that, we need to understand a disease in the endemic region,"
The link between the mosquito life cycle and
vegetation growth was first described in a 1987 Science paper by
co-authors Kenneth Linthicum of the U.S. Department of
Agriculture and Compton Tucker of NASA Goddard. Then, a
subsequent 1999 Science paper described link between the disease
and the El Niño-Southern Oscillation (ENSO). ENSO is a
cyclical, global phenomenon of sea surface temperature changes
that can contribute to extreme climate events around the world.
For some areas, the warm phase of ENSO brings drought,
while in some areas like the Horn of Africa, ENSO leads to
above-normal rainfall. Excessive, sustained rainfall awakens the
eggs of mosquitoes infected with Rift Valley fever that can
remain dormant for up to 15 years in dried-out dambos—shallow
wetlands common in the region.
Building on that research,
Anyamba and colleagues set out to predict when conditions were
ripe for excessive rainfall, and thus an outbreak. They started
by examining satellite measurements of sea surface temperatures.
One of the first indicators that ENSO will bring an abundance of
rainfall is a rise in the surface temperature of the eastern
equatorial Pacific Ocean and the western equatorial Indian Ocean.
But perhaps the most telling indicator of a potential
outbreak is a measure of the mosquito habitat itself. The
researchers used a satellite-derived vegetation data
set--processed at NASA Goddard and called the Normalized
Difference Vegetation Index—that measures the landscape's
"greenness." Greener regions have more than the average
amount of vegetation, which means more water and more potential
habitat for infected mosquitoes.
habitat and represents life," Anyamba said. "Without
such systematic, continuous Earth system measurements from
satellites, we would not be able to translate the information
into outbreak predictions."
The final product is a
risk map for Rift Valley fever, showing areas of anomalous
rainfall and vegetation growth over a three-month period. The
forecast is updated and issued monthly as a means to guide
ground-based mosquito and virus surveillance.
As early as
September 2006, the monthly advisory from Anyamba and colleagues
indicated an elevated risk of Rift Valley fever activity in East
Africa. By November, Kenya's government had begun collaborating
with non-governmental organizations to implement disease
mitigation measures—restricting animal movement,
distributing mosquito bed nets, informing the public, and
enacting programs to control mosquitoes and vaccinate animals.
"There is no human vaccine," Anyamba said, "so
prevention is critical."
Between two and six weeks
later—depending on the location—the disease was
detected in humans.
"Satellite data is a valuable
tool that allowed us to look remotely at large sections of land
in Africa and understand what was happening on the ground,"
After the 2006-2007 outbreak, Anyamba and
colleagues assessed the effectiveness of the warning maps. They
compared locations that had been identified as "at risk"
with the locations where Rift Valley fever was reported.
the 1,088 cases reported in Kenya, Somalia, and Tanzania, 64
percent fell within areas delineated on the risk map. The other
36 percent of cases did not occur within "at risk"
areas, but none were more than 30 miles away, leading the
researchers believe that they had identified most of the initial
The potential for mapping the risk of
disease outbreaks is not limited to Africa. Previous research has
shown that risk maps are possible whenever the abundance of a
virus can be linked to extremes in climate conditions.
Chikungunya in east Africa and Hantavirus and West Nile virus in
the United States, for example, have been linked to conditions of
"We are coming up on almost 30
years of vegetation data from satellites, which provides us with
a good basis for predicting," Linthicum said upon returning
from a Rift Valley fever workshop in Cairo, Egypt in January. "At
this meeting, it was clear that using this tool as a basis for
predictions has become accepted as the norm."
NASA / Goddard Space Flight Center / Kathryn Hansen
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