“Malaria is a vector-borne disease, which means you have to have a vector, or mosquito, in this case, transmit the disease,” explained principal investigator William Pan, an assistant professor of global environmental health at Duke University, in a NASA report. “The key to our malaria forecasting tool lies in pinpointing areas where prime breeding grounds for these mosquitos overlap simultaneously with human populations.”
These breeding grounds, as many know, are usually puddles and ponds, and using NASA’s Land Data Assimilation System (LDAS), scientists can predict where these standing pools of water are likely to form. For example, if heavy rains are on the horizon, researchers know that this will likely result in flooding conditions, resulting in prime mosquito habitats. LDAS is also capable of tracking deforestation, another key indicator for malaria outbreaks.
“It’s an exercise in indirect reasoning,” said Ben Zaitchik, the project’s co-investigator responsible for the LDAS component and an associate professor at Johns Hopkins University’s Department of Earth and Planetary Sciences. “These models let us predict where the soil moisture is going to be in a condition that will allow for breeding sites to form.”
Ultimately, this data could be used to assess the “probability of when, where, and how many people are expected to get bitten and infected with the disease,” NASA explained. And this information could be used by governments to take preventive measures, such as distributing bed nets, sprays, and anti-malaria treatment.
While the focus of the project is currently malaria, there’s no reason the same technology couldn’t be used more broadly. “I think that government health agencies will find not just one but many uses for the system that can benefit a lot people,” Pan said. “That’s always been our goal.”
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