The Scripps Research Translational Institute (Scripps Research) in San Diego, US, is conducting a study to assess the effectiveness of wearable fitness devices in predicting COVID-19 infection.
The two-year DETECT study builds on a previous research that tracked seasonal flu using the Fitbit wearable device. The study aims to recruit one million wearable users and monitor their heart rate, temperature, activity and sleep level data to predict regional clusters of COVID-19.
Seasonal flu and COVID-19, which killed more than a million people across the globe, have similar symptoms. Scripps Research expects that the data procured from fitness devices will help in identifying a potential outbreak and containing its spread.
Additionally, it will encourage the participants to isolate themselves after detecting any anomalies, thereby reducing the risks of transmission further.
Scripps Research published a study on the research using two years of data from 50,000 users in January 2020. The study concluded that Fitbit data, just like Kinsa Health’s smart thermometer data, can be used to predict local flu outbreaks more accurately than the system used by the Centers for Disease Control and Prevention (CDC).
The study also determined that data from these wearables can identify whether a person who reported symptoms is likely to have COVID-19 with approximately 80% prediction accuracy, which is a major improvement compared to other models that used self-reported symptoms.
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By GlobalDataThe DETECT study includes all wearables capable of monitoring heart rate. Participants can join by downloading the MyDataHelps app.