A study performed in the U.S. made use of data provided by Fitbit that basically consisted of heart rate and sleep information to predict flu outbreaks. The goal of this research was to be more precise than the present surveillance methods while making public health officials aware of potential flu tendencies using heart rate and sleep data. From five united states, more than 47,000 Fitbit users’ data was used for the research the results of which were published in The Lancet Health Journal. It revealed that using Fitbit data made the flu outburst predictions were quicker and accurate.
According to the calculations of the World Health Organization (WHO) around the world respiratory diseases which are linked to seasonal flu claim the lives of about 650,000 each year. It usually takes about three weeks to detect and fight flu outbreaks using traditional surveillance methods. This covers the time taken for coming up with response measures such as dispensing vaccines, anti-virals and suggesting patients stay in at home but there is always a good chance of a lag.
While using Fitbit’s data, the users’ heart rate at rest and sleep duration were kept a track of and flagged as abnormal. This was determined by if the average weekly heart rate was significantly above their overall average and their weekly average sleep was not below their overall average
The US Centers for Disease Control’s weekly estimates were used to compare the data collected for flu-like illness. However, this work is not thorough and requires more commission to indicate how credible this data will be over time. There is more effort needed to scale these as the ultimate measurements for flu, moreover, it is critical to note that how relevant it really is to have Fitbit users representative of the entire population.