The team developed an algorithm that uses data gathered by the watch and ring and predicts whether a user has Covid-19 two days before they are showing symptoms. The technology is akin to a “check engine light” in a car that alerts the user that something might be off, but does not pinpoint what is wrong, said Jeff Schneider, DIU rapid analysis threat exposure program manager.

DIU tracked 11,500 users from June 2020 to September 2021. The final results of the experiment won’t be released until they have been peer-reviewed, Schneider said. However, preliminary results published in August show the algorithm’s projected accuracy is about 82 percent with a false positive rate of 11 percent over a 14-day period.

The test group is using the Garmin Fēnix 6 watch and an Oura ring, which tracks sleep and activity, but officials want participants to eventually use whatever health monitoring device they want, Schneider said.

The watch tracks respiration rate, oxygen saturation and heart rate, while the ring collects heart rate and skin temperature, he said.