Wearable devices or smartphone apps can provide personal health and lifestyle data which may help identify college students at risk of catching the flu, researchers have found.
With help from a mobile app that monitors who students interact with and when, epidemiologist Allison Aiello of the University of North Carolina-Chapel Hill and statistician Katherine Heller of Duke University have developed a model that enables them to predict the spread of influenza from one person to the next over time.
Unlike most infection models, which focus on population-level changes in the proportion of people likely to get sick, this approach gives a personalised daily forecast for each patient, Heller said. Close living quarters, low flu vaccination rates and busy social calendars make college students particularly prone to catching the virus, researchers said.
Of the 18 million undergraduates in US, more than one in five are likely to get the flu this year, researchers estimated. That could mean up to two weeks of fever, chills, muscle aches, scratchy throat, runny stuffy nose, congestion and sneezing, not to mention missed classes and extracurriculars.
To test the model, the researchers applied it to a study of roughly 100 students at the University of Michigan. For 10 weeks during the 2013 flu season, the students carried Google Android smartphones with built-in software, iEpi, that used Wi-Fi, Bluetooth and GPS technology to monitor where they went and who they came in contact with from moment to moment.
The students also recorded their symptoms every week online. Students who reported coughing and fever, chills or aches provided throat swabs to determine whether they had a cold or the flu. The model then returned the odds that each student would spread or contract the flu on a given day, and identified the personal health habits - such as hand-washing or getting a flu shot - that might help them beat the odds or hasten their recovery.
Not surprisingly, when a student got sick, his or her friends were more likely to get sick too. The researchers also found that students who smoked or drank took longer to recover. "We didn't have this kind of personalised health data until a few years ago," Heller said.
"But now, smartphones and wearable health and fitness devices allow us to collect information like a person's heart rate, blood pressure, social interactions and activity levels with much more regularity and more accurately than was possible before. You can keep a continuous logbook," she said.
"We want to leverage that data to predict what people's individual risk factors are, and give them advice to help them reduce their chances of getting sick," Heller said. The researchers presented their findings at the 21st International Conference on Knowledge Discovery and Data Mining in Sydney, Australia.