Led by digital health expert Eric Topol, MD, researchers at the Scripps Research Translational Institute used data from roughly 50,000 people wearing Fitbits between 2016 and 2018 and were able to plot outbreaks of seasonal respiratory infections like the flu.
The first-of-its-kind study tracked sleep patterns, resting heart rate (RHR) and activity among users in Texas, California, New York, Illinois and Pennsylvania, and compared that data to influenza-like illnesses (ILIs) recorded by the US Centers for Disease Control in those states.
Researchers found they could identify and possibly even anticipate an outbreak by the activities of Fitbit users who became sick. People who develop the flu, they noted, tend to have an elevated RHR, sleep more and move around less.
“Activity and physiological trackers are increasingly used in the USA and globally to monitor individual health,” Topol and his colleagues said in a study published this week in The Lancet. “By accessing these data, it could be possible to improve real-time and geographically refined influenza surveillance. This information could be vital to enact timely outbreak response measures to prevent further transmission of influenza cases during outbreaks.”
Joining Topol in the research were Jennifer M. Radin, PhD; Nathan E. Wineinger, PhD, and Steve R. Steinhubl, MD, all of the San Diego-based organization, which has conducted dozens of mHealth and telehealth studies over the past decade.
This study, funded in part by the National Institutes of Health, aims to improve population health management for a virus that annually affects 20 percent of children and 7 percent of adults in the US, and which causes as many as 650,000 deaths worldwide. Traditional surveillance methods usually lag one to three weeks behind the outbreak, putting healthcare providers at a disadvantage in curbing the spread of the virus.
Topol and his colleagues are looking at mHealth to reduce that disadvantage and give providers and public health officials an opportunity to stop and outbreak earlier.
There are some challenges. While roughly 10 percent of the US population, according to a 2016 study, now uses wearables, that percentage has to be higher to make the results more meaningful. In addition, any connected health platform used to gather data shoud be able to draw information from a wide variety of wearables, including smart watches and smart clothing.
And finally, such a platform would need to be careful to distinguish behaviors caused by the onset of the flu with normal behaviors, and sensitive enough to detect those changes in behavior at the earliest possible moment.
“In the future, wearables could include additional sensors to prospectively track blood pressure, temperature, electrocardiogram, and cough analysis, which could be used to further characterize an individual’s baseline and identify abnormalities,” the study concluded. “Capturing physiological and behavioral data from a growing number of wearable device users globally could greatly improve timeliness and precision of public health responses and even inform individual clinical care. It could also fill major gaps in regions where influenza surveillance data are not available.”