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These Researchers Are Exploring Satellite Data To Predict Malaria Outbreak Months In Advance


Malaria is one most deadly diseases in the world and claims over a million lives yearly. About 90 percent of those deaths are recorded in Africa and according to UNICEF (United Nations Children’s Fund), many of the victims are children under the age of five.

Mosquitoes are the carriers of the disease and are usually found in warmer areas that have a stagnant water. While medicine is helping us fight the disease, what if there was a way to predict these outbreaks before they happen which means we would be able to prevent outbreaks altogether? Well that’s what some researchers are now doing. They are using NASA satellite data to identify areas that may be breeding grounds for mosquitoes.

Researchers are turning to the Land Data Assimilation System, or LDAS: a land-surface modeling effort supported by NASA and other organizations. NASA satellites, such as Landsat, Global Precipitation Measurement, and Terra and Aqua, serve as inputs for LDAS, which in turn provides ongoing information on precipitation, temperature, soil moisture and vegetation around the world.

This data is able to monitor areas that may be breeding grounds for mosquitoes using data like air temperature, rainfall (flooding) and soil properties. But there is the human contribution in the form of deforestation. Deforestation leaves huge chunks of wood on the ground which means they can prevent the free flow of water. This in turn can make it easier for the mosquito population to thrive.

By being able to more accurately tell which areas are breeding hotspots for mosquitoes, treatment and other preventive techniques can be administered faster. So instead of distributing medical resources over a large geographical space, it can better be concentrated on identified areas thereby saving more lives.

The lead researcher, William Pan said;

Integrating environmental data through LDAS not only places mosquito populations on the map but also helps to inform human movement, for example, by detecting rising rivers during the rainy season. “It’s much easier to float logs down a river when its high, and at the same time mosquitos thrive because pockets of water emerge along the riverbank, so these types of conditions correspond with high malaria risk.

The model proposed here can predict outbreaks 3 months before they happen and as good as this may sound, there’s still work to be done before they can say for sure that it’s ready for prime time. But seeing as they are in the third year of the research, it could just be a few more years before we can start using this method of combatting malaria.

Right now in many parts of Africa, there are so many malaria preventive and curative drugs but the challenge still remains that quality healthcare is still out of the reach of many. While these medicines are there, they are becoming expensive because of demand but one major challenge governments across the continent continue to face is distribution.

But with Pan’s model for example, we can know specific areas that may need the help in advance and what this saves money on two fronts with the first being that they would have a more streamlined distribution of medicine and this translates to lower budgeting as well. The other thing is that if we can know in advance that there will be an outbreak, adequate steps can be taken to clean up those areas before an outbreak. This saves money that would otherwise have been spent on buying malaria medicine.

As these researchers explore satellite data, others are working on vaccines but in any case, it looks like we may have better ways of combatting the disease in future than just medicine.

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