Based on a recently published study on The Lancet Digital Health, an open-access journal, Fitbit wearable devices improve the surveillance of infectious diseases. The researchers reviewed data from 200,000 users who own and use Fitbit fitness trackers monthly from March 2016 to March 2018. The collected data include daily activities, heart rate, and sleep quality.
All Fitbit users, including those whose data are included in the said study, are notified that their data could potentially be used for research in the Fitbit Privacy Policy.
Research shows that out of 200,000 users, 47,248 wore a Fitbit device consistently during the study period. This turned in a total of 13,342,651 daily measurements evaluated on the whole duration of the study. The average user was 43 years old and 60% of them were female.
To identify when the average resting heart rate and sleep duration were way beyond the normal range, the said factors were calculated weekly including the deviations. A user was identified as abnormal if his or her weekly average resting heart rate was above the overall average (by more than a half or a full standard deviation), and his or her weekly average sleep was not below their overall average (by more than half a standard deviation). The users were categorized based on their geographical location and the proportion of users above the threshold each week.
By incorporating data from Fitbit trackers, influenza predictions in the United States of America were improved. Compared to weekly estimates for influenza-like illness rates reported by the U.S. Centers for Disease Control (CDC), there was an improvement in real-time surveillance in the states of California, Texas, New York, Illinois, and Pennsylvania.
“Clinical researchers are using wearables to pioneer new ways around how we understand, prevent and treat disease and identify better approaches to keep people healthy and deliver more meaningful health outcomes. Our research relationship with The Scripps Institute, which was announced in early 2019, is one example of that. We’re excited by the potential wearables can play in helping to better predict the flu and the positive impact that can have on both those with the flu and the healthcare system,” Fitbit said in a statement to CNN.
The researchers identified several limitations in their study. A general lack of activity data meant they could not control for seasonal fitness changes or more short-term activity changes. Weekly resting heart rate averages may include days when an individual is both sick and not sick, and this may result in an underestimation of illness by lowering the weekly averages. Other external factors may also increase resting heart rate, including stress or other infections.
Study author Dr. Jennifer Radin of Scripps Research Translational Institute also admitted that further prospective studies will need to be done for defining the fine line between infectious versus non-infectious forecasting. “Responding more quickly to influenza outbreaks can prevent further spread and infection, and we were curious to see if sensor data could improve real-time surveillance at the state level. We demonstrate the potential for metrics from wearable devices to enhance flu surveillance and consequently improve public health responses. In the future as these devices improve, and with access to 24/7 real-time data, it may be possible to identify the rate of influenza on a daily instead of a weekly basis,” she shared.