https://blogs.scientificamerican.com/observations/as-covid-19-accelerates-governments-must-harness-mobile-data-to-stop-spread/

Contact tracing has been used by public health experts for decades to control spread during the initial stage of a communicable disease. It was effective in fights against HIV, measles, SARS-CoV (the 2003 SARS outbreak), and even, in places like Singapore, SARS-CoV2. In 2003, it significantly reduced the transmission risk of SARS in Hong Kong. And before that, it played a pivotal role in the eradication of smallpox by identifying and isolating infected persons and immunizing at-risk contacts and surrounding communities. Traditional contact tracing interviews take place with infected persons to gather data about their movement and people they have been in close contact with. But this manual process is too slow and labor-intensive to effectively stop fast-developing outbreaks, such as SARS-CoV2. Smartphone trajectory data can instead be used to greatly speed up—and scale up—contact tracing for large and rapidly evolving outbreaks of infectious diseases.

Here’s how it might work: One could start with the registry of people who have tested positive for SARS-CoV2 and estimate the onset of the infection which may precede the test by days. This information could then be used to create an infected trajectory dataset, which could be checked against the trajectory of all smartphones to identify the phones that were spatially close for a substantial duration. From there, the spatial distance and exposure time could be processed via an infectious disease transmission model to assess the risk of transmission and the need to notify the exposed. Once the contacts are determined, public safety communication technology such as Reverse 911 could be used to deliver medical advice to those who have potentially been exposed. If smartphone trajectories of non-infected individuals need to be excluded for privacy reasons, the locations and times of potential exposure could be publicly shared without divulging patient names or sensitive medical information.