Researchers use phone data to track spread of infectious disease

The rise and fall of rubella spikes in Kenya were accurately predicted by using the data analysis model.
By Stephen Feller  |  Aug. 20, 2015 at 5:04 PM
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WASHINGTON, Aug. 20 (UPI) -- Researchers may have found an accurate way to track the seasonal spread of diseases by studying people's travel patterns using cellphone data, according to a new study.

The method was tested by researchers who tracked rubella in Kenya by using the anonymous locations of daily cellphone use and comparing that data to historical paths of rubella spreading through the country.

"One of the unique opportunities of mobile phone data is the ability to understand how travel patterns change over time," said C. Jessica Metcalf, an assistant professor of ecology and evolutionary biology and public affairs at Princeton's Woodrow Wilson School of Public and International Affairs, in a press release. "And rubella is a well-known seasonal disease that has been hypothesized to be driven by human population dynamics, making it a good system for us to test."

Researchers used the locations of cell towers and timing of calls and messages to roughly determine daily phone users. This information for more than 12 billion cellular interactions was compared with datasets about seasonal rubella spikes in the country. Researchers were able to predict, for instance, that spikes happen at the start of school or after holiday breaks.

Using mobile phone data, the researchers constructed these maps to characterize rubella fluxes across the country. Section A shows the risk of rubella during a major holiday and school-term break. Section B shows the risk of rubella while school is in session. Most provinces have lower risks during the school year with higher outbreak rates during breaks and holidays. Photo by Amy Wesolowski and C. Jessica Metcalf/Princeton University

In addition eventually using the method of data analysis to study flu and other epidemics, the researchers plan to next apply it to measles, malaria and cholera.

"Our analysis shows that mobile phone data may be used to capture seasonal human movement patterns that are relevant for understanding childhood infectious diseases," Metcalf said. "In particular, phone data can describe within-country movement patterns on a large scale, which could be especially helpful for localized treatment."

The study is published in The Proceedings of the National Academy of Sciences.

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