A new study led by Harvard T.H. Chan School of Public Health and Princeton University researchers shows that data from cell phones captures population fluctuations that can predict infectious disease transmission. The researchers tracked the movements of nearly 15 million anonymous cell phone users in Kenya over the course of a year through call data, and compared them to the locations of rubella cases reported during the same period. They found that the cell phone data was a more accurate predictor of rubella outbreaks than school term dates and weather patterns, which have been looked at in previous studies.
The study appeared online in PNAS on August 17.
Harvard authors include postdoctoral fellow Dr. Amy Wesolowski, adjunct assistant professor of epidemiology Dr. Nathan Eagle, and assistant professor of epidemiology Dr. Caroline Buckee.
“As we move toward elimination goals for measles or other vaccine-preventable infections, mobile phone data offers enormous potential for quantifying daily movement patterns at particular spatial scales,” they write. The data can identify “key areas to target to minimize reintroductions and ongoing spread.” Read more