https://www.sciencedaily.com/releases/2022/02/220201143945.htm

At USC, researchers are advocating for a new approach to predict the chance of infection from Covid-19: combining anonymized cellphone location data with mobility patterns -- broad patterns of how people move from place to place.

To produce "risk scores" for specific locations and times, the team used a large dataset of anonymous, real-world location signals from cell phones across the US in 2019 and 2020. The system shows a 50% improvement in accuracy compared to current systems, said the researchers.