How Fitbits heart rate and sleep data can help predict flu outbreaks


Fitbit on your wrist not only counts your steps and minutes of sleep, but can also help you know if you have the flu, and warn health authorities to prepare to help you.

A study in the United States found that heart rate and sleep data from physical activity tracking clocks can predict and alert public health officials about real-time flu outbreaks more accurately than current surveillance methods.

The study used data from more than 47,000 Fitbit users in five US states. UU. The results, published in The Lancet Digital Health, showed that using Fitbit data, state predictions of flu outbreaks were improved and accelerated.

The World Health Organization estimates that up to 6.50,000 people worldwide die of respiratory diseases related to seasonal flu each year.

Traditional surveillance reports take up to three weeks, which means that response measures, such as the deployment of vaccines or antiviral drugs and the recommendation to patients to stay at home, can often be delayed.

“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,” said Jennifer Radin, who led that study at the Scripps Research Institute. Translational Institute.

Previous studies that use data from public sources, such as Google Flu Trends and Twitter, have experienced variable success, in part, experts say, because it is impossible to separate the behavior of people with the flu from people seeking information online because to more media and public attention during outbreaks.

For this study, the Radin team identified data from 200,000 people whose Fitbits tracked activity, heart rate and sleep for at least 60 days during the study period from March 2016 to March 2018. Of the 200,000, 47,248 users from California, Texas, New York, Illinois and Pennsylvania constantly used a Fitbit during the period. The average age was 43 years and 60% were women.

The resting heart rate and sleep duration of the users were monitored and marked as abnormal if the average weekly heart rate was significantly above their general average and their weekly average sleep was not below their general average.

These data were compared with the weekly estimates of the Centers for Disease Control in the USA. UU. For flu-like diseases.



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