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Tracking Malaria Through Cell Phone Use

It would be a lot easier to end the disease if infected people just stayed put, but they tend to move around and bring malaria with them. But using cell phone data, scientists can help predict where outbreaks will spread, and work to stop them before they start.

The Internet has been a boon to disease tracking, with services like Google Flu Trends and Sickweather aggregating search terms and social media activity to figure out where people are getting sick. In the right setting, this kind of data can really help epidemiologists. But there’s another piece of modern communications technology that can potentially pinpoint disease activity, even in places where people don’t have easy access to the Internet: cell phones. Researchers recently combined mobile phone data from 15 million Kenyans (there is high cell phone penetration in the country) with regional malaria prevalence information to figure out how population movement affects the spread of the disease.

The research, published this month in Science, used data from 11,920 cell towers along with malaria data from the Kenya Medical Research Institute (KEMRI) and the Malaria Atlas Project to suss out the probability of malaria infection in residents as well as the probability that a visitor to an area would be infected on any given day.

"By taking data and coupling it with malaria prevalence, you get an understanding whether or not things like local eradication efforts would be successful," explains Nathan Eagle, a research assistant professor at Northeastern University’s College of Computer and Information Science and co-author of the paper. "If you can eradicate malaria in a geographically constrained region, can you keep the parasite eradicated?"

You could, Eagle says, spend millions of dollars getting rid of malaria in a given area. But if you’re successful, there’s an open question about whether you can maintain eradication if people are visiting from other parts of the country that have a high prevalence of malaria. In the paper, Eagle and his colleagues describe how a large number of malaria infections carried by travelers (known as imported infections) land in Nairobi—because the travelers are coming from other areas of Kenya with high rates of disease.

Eagle’s hope is that he can eventually use big data to help eradicate disease instead of just observing it. A simple survey, offered to high-risk citizens (those who travel often) along with a 10 shilling reward, could more accurately predict where malaria is emerging. Once that data becomes clear, the government could send text message warnings to people traveling in areas with a high malaria prevalence.

"There’s huge potential here to start thinking about providing free mobile talk time for individuals in exchange for more individual-level data. You could turn insights into something that can drive intervention and action," says Eagle.