ISLAMABAD: Tracking mobile phone data can help predict how infectious diseases will spread seasonally, a large-scale study has found.
Researchers from Princeton University and Harvard University used anonymous mobile phone records for more than 15 million people to track the spread of rubella in Kenya and were able to quantitatively show for the first time that mobile phone data can predict seasonal disease patterns, Medical Xpress reported.
Harnessing mobile phone data in this way could help policymakers guide and evaluate health interventions like the timing of vaccinations and school closings, the researchers said.
The researchers’ methodology also could apply to a number of seasonally transmitted diseases such as the flu and measles.
“One of the unique opportunities of mobile phone data is the ability to understand how travel patterns change over time,” said lead author C Jessica Metcalf, assistant professor at the Princeton University’s Woodrow Wilson School of Public and International Affairs.
Using the location of the routing tower and the timing of each call and text message, the researchers were able to determine a daily location for each user as well as the number of trips these users took between the provinces each day.
The researchers hope to next apply their methodology to measles and other infections shaped by human movement like malaria and cholera.