Our mobile phones, computers, and credit transactions leave invisible data trails behind us that tell intimate, insightful stories about our lives. Public health researchers are now tapping this data to understand the outbreak of epidemics. Scientists teamed up with mobile phone companies and health organizations in Africa to reveal the potential pathways of malaria, and predict where health interventions need to be deployed today, tomorrow, or even weeks from now.
One of the most extensive field tests was in Zanzibar, a semi-autonomous region of Tanzania, where a team from the University of Florida sorted through (anonymous) mobile phone records from more than 21 million calls over three months. By tracking human movements through mobile phone connections with cellular masts, researchers could model the risk of malaria infections in remote areas. The results were striking. Since most people remained in urban areas, or rarely ventured far from home, a minority of travelers posed the greatest risk of introducing malaria to less affected areas, reports the study. By combining these records with maps of malaria prevalence and models of disease transmission, scientists say they can identify likely routes for disease transmission, and mount better malaria elimination campaigns.
Mobile applications have also given disease hunters enhanced tools to track the disease on the ground. Nathan Eagle, a former researcher at MIT’s Media Lab, now head of his own mobile research and marketing firm, Jana, helped the Kenya Medical Research Institute (KEMRI) turn its paper-based system into a mobile-phone based public health platform several years ago. Using cell tower and GPS connectivity to record the location and duration of each visit, the method increased the precision and reliability of of the data, magnifying the effectiveness of a single researcher. “One of the major research goals of the KEMRI is to uncover the fundamental mysteries that underlie malaria, a disease extraordinarily prevalent in the Kilifi district,” Eagle said at the time. “Hopefully increased understanding of this population will lead to increased understanding of the disease.”
Studies and trials are now in the works that hint at a new wave of digital epidemiology. Public health programmers are just around the corner.