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Phone data can predict infectious disease outbreaks

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A team of Princeton and Harvard researchers analyzed the phone call records of 15 million users in Kenya -- not to spy on people, but to study the spread of seasonal disease. The team wanted to see if the movement of phone users can predict outbreaks of seasonal diseases like rubella or German measles. So, they used anonymous records from between June 2008 and June 2009, including locations where people made phone calls. They then compared the data to the areas where cases of rubella were reported in the country. The result? Well, it turns out the subjects' movement patterns matched the locations with the highest risk of rubella within that year-long period.

Princeton assistant professor and lead author C. Jessica Metcalf said:

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

In the future, the researchers plan to test if the same method is as effective in forecasting malaria and cholera outbreaks and eventually be used by doctors and other medical professionals.

[Image credit: SIMON MAINA/AFP/GettyImages]

Source: Harvard, PNAS, Princeton
In this article: harvard, mobilepostcross, princeton
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