Satellites help predict malaria outbreaks months in advance

Malaria is one of the greatest health threats in tropical regions like the Amazon, but predicting its spread is difficult. While it’s no secret that mosquitoes prefer warm air and standing pools of water, how do you translate that awareness to a large scale? By getting a little help from orbit, apparently. Researchers are using data from NASA satellites (such as the Landsat series) to predict malaria outbreaks by identifying areas where the soil moisture creates prime breeding grounds for the mosquitoes that transmit malaria. They know that floods and deforestation tend to create mosquito-friendly pools of water — compare that with fine-grained models of human behavior (say, loggers or miners who work in wet conditions) and you have a unified system that can anticipate outbreaks about 3 months in advance, right down to individual households.

The satellite-based modeling will need refinement before it’s ready for service, but it could be active within a few years. If so, it might not only help prevent malaria outbreaks through timely responses, but could lead to more efficient ways of fighting the illness. Right now, countries like Peru have to distribute bed nets, sprays and other tools on a very broad level, as they only have a vague idea of where outbreaks are likely to occur. This new model could focus aid on specific neighborhoods, saving resources that could be put to use somewhere else.

Source: NASA

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Post Author: martin

Martin is an enthusiastic programmer, a webdeveloper and a young entrepreneur. He is intereted into computers for a long time. In the age of 10 he has programmed his first website and since then he has been working on web technologies until now. He is the Founder and Editor-in-Chief of BriefNews.eu and PCHealthBoost.info Online Magazines. His colleagues appreciate him as a passionate workhorse, a fan of new technologies, an eternal optimist and a dreamer, but especially the soul of the team for whom he can do anything in the world.

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