A study of more than 47,000 Fitbit users in the United States found that heart rate and sleep data can be used to predict and alert public health officials to real-time outbreaks.
Researchers from the Scripps Research Translational Institute found such data could make predictions more accurately than current surveillance methods.
The resting heart rate and sleep duration of Fitbit users were monitored for deviations of measurements outside a user’s normal range.
If a user’s weekly average resting heart rate was above average while their weekly average sleep was not below their average, the results were flagged as abnormal.
Users were arranged by the state in which they resided, then researchers compared the data to the US Centers for Disease Control’s weekly estimates for flu-like illness.
The researchers reviewed de-identified data from users wearing Fitbits, as the company’s privacy policy allows potential use of such data for research.
The study suggests fitness trackers hold promise as a new disease surveillance tool, with traditional surveillance reporting taking up to three weeks.
