Study finds mobile phone data can help predict seasonal infectious diseases

Mobile phone data could help predict how seasonal infectious diseases are spread and help policymakers make decisions about interventions, researchers from Princeton University, Harvard University and other institutions said in a recently published study. The researchers used anonymous phone records from more than 15 million people to track the spread of rubella in Kenya, quantitatively demonstrating that such data can predict seasonal disease patterns, according to an Aug. 20 press release from Princeton. Changes in people’s movements and where they gather are suspected of driving such disease outbreaks, but historically, there’s been a lack of data on travel behavior and population flux, making it difficult to test the concept, according to the study (pdf) published in the journal Proceedings of the National Academy of Sciences. However, as mobile phone ownership proliferates, including in low-income and undeveloped countries, it’s generating large, complex datasets on millions of people. “One of the unique opportunities of mobile phone...