Wearable health tech and the digitized self promise to help reduce illness by detecting disease even before symptoms appear. The hope is that early detection leads to early treatment that is more effective and lower cost. I can think of few situations where this might be more important than during a pandemic.
Researchers at the University of California San Francisco (UCSF) have launched the TempPredict study that hopes to find physiological data that can predict COVID-19 symptom patterns for onset, progression, and recovery. The study will gather data from healthcare workers and the general population.
The study will rely on data from the Oura ring that can track body temperature, respiratory rate, and heart rate, along with daily symptom surveys. More than 2,000 healthcare workers at UCSF will receive the smart rings to track their biometrics. A second phase will open the study to Oura ring owners who volunteer to join in. They will be able to apply through the Oura app or by applying online.
This project is an excellent example how big data analytics can be used to look for correlations hidden an enormous collection of information. If this study is successful, it could point the way to monitoring methods that could predict other sorts of infection as well.