In a breakthrough discovery, researchers have developed a smartphone app which identifies when the user is at risk for disease.
New methods for analysing personal health and lifestyle data captured through wearable devices or smartphone apps can help identify college students at risk of catching the flu, say researchers at Duke University and the University of North Carolina-Chapel Hill.
Katherine Heller of North Carolina-Chapel Hill developed a model that enabled them to predict the spread of influenza from one person to the next over time.
Heller said this approach gave a personalised daily forecast for each patient.
To test the model, the researchers applied it to a study of roughly 100 students 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 model then returned the odds that each student would spread or contract the flu on a given day, and identified the personal health habits that might help them beat the odds or hasten their recovery.
The researchers found that when a student got sick, his or her friends were more likely to get sick too.
They also found that students who smoked or drank took longer to recover.
Heller said that smartphones and wearable health and fitness devices allowed them 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.
The study is published in the journal Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.