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, 2015.

Harvard Chan School authors include Postdoctoral Fellow Amy Wesolowski, Adjunct Assistant Professor of Epidemiology Nathan Eagle, and Assistant Professor of Epidemiology 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 PNAS study: Quantifying seasonal population fluxes driving rubella transmission dynamics using mobile phone data

Read Princeton press release: Cellphone data can track infectious diseases

Learn more

Predicting Ebola’s spread using cell phone data (Harvard Chan School news)

Using cell phone data to curb the spread of malaria (Harvard Chan School news)

Mobilizing a revolution: How cellphones are transforming public health (Harvard Public Health)