| Philip Polgreen, MD |
Iowa City, Iowa
Years on Job: 6
Most outbreaks begin with one unlucky person, who's typically not easy to find. At the start of the 2002 SARS epidemic, epidemiologists relied on hospital logs and patients' memories to identify the first victim and trace the path of exposure. But Philip Polgreen, who worked in a virology lab at the University of Iowa at the time, believed that technology could more accurately track how diseases spread. After becoming assistant professor of medicine and epidemiology at Iowa's Carver College of Medicine in 2006, he co-founded the Computational Epidemiology Group, an interdisciplinary research team. They use mathematical and scientific tools to collect data and build models about contagion. "It's an incubator for ideas," he says. "There's always a new infection and a new way to track transmission."
Tracking Disease Through Technology
Roughly five of every 100 patients will acquire a bacterial infection in a hospital. To help decrease those odds, Polgreen designed sensors, or motes, to find what he calls a hospital's Kevin Bacons—people who are especially well-connected and thus more likely to spread contagion. Carried by healthcare staff, the motes report time-stamped location data to a base station every few seconds. Polgreen uses that data to build models showing how healthcare workers might spread infectious diseases.
After the H1N1 outbreak in 2009, Polgreen's team used data from the Centers for Disease Control to develop algorithms that mine Twitter, extracting keywords to determine which tweets were associated with more disease activity. The algorithms predicted flu levels geographically and in real time with an average error of only 0.28 percent from the CDC reported results, which are released one to two weeks after the fact. These algorithms may one day serve as an early warning system for distributing vaccines and mobilizing healthcare workers.
Less than 50 percent of healthcare workers practice adequate hand-washing hygiene. Hospitals typically hire independent monitors to shadow employees and track compliance on paper, but Polgreen and his colleagues saw another opportunity to use technology to solve a problem. They created iScrub, an app that human monitors use to input data. It minimizes entry errors, standardizes recording, and provides real-time feedback.