Traditional screening for COVID-19 typically includes survey questions about symptoms and travel history as well as temperature measurements. In a recent article in Nature Medicine, researchers discussed the smartphone app they developed that collects smart watch activity tracker data, as well as self-reported symptoms and diagnostic testing results, from individuals in the United States. The researchers have assessed whether symptom and sensor data can differentiate COVID-19 positive versus negative cases in symptomatic individuals.
30,529 participants were enrolled between March 25th and June 7, 2020, 3,811 of whom reported symptoms. Of these symptomatic individuals, 54 reported testing positive and 279 tested negative for COVID-19. The results show that individual changes in physiological measures captured by most smartwatches and activity trackers are able to significantly improve the distinction between symptomatic individuals with and without a diagnosis of COVID-19 beyond symptoms alone.
These results suggest that sensor data can incrementally improve symptom-only-based models to differentiate between COVID-19 positive and COVID-19 negative, symptomatic individuals, with the potential to enhance our ability to identify a cluster before more spread occurs.
Stay strong, stay the course, stay well, mask up, and stay tuned!