  Throughout the recent COVID-19 pandemic when government officials around the
world ordered citizens to quarantine inside their homes, real-time measurements
about the use of roads, hospitals, grocery stores, and other public
infrastructure became vital to accurately forecast viral infection rates and
inform future government decisions. Although mobile phone locations provide
some information about community-level activity, dense distributed geophysical
sensing of ground motions across a city are more complete and also natively
anonymous. In this paper, we demonstrate how fiber-optic Distributed Acoustic
Sensing (DAS) connected to a telecommunication cable beneath Palo Alto, CA
captured seismic and geodetic signals produced by vehicles during the COVID-19
pandemic outbreak and subsequent quarantine. We utilize DAS strain measurements
of roadbed deformation caused by local cars and trucks in an automatic template
matching detection algorithm to count the number of vehicles traveling per day
over a two-month period around the timing of the San Francisco Bay Area
shelter-in-place order. Using a segment of the optical fiber near a major
grocery store on Sand Hill Road we find a 50% decrease in vehicle count
immediately following the order, but data from near Stanford Hospital showed a
far more subtle change due to on-going hospital activities. We compare the
information derived from DAS measurements to other quarantine response metrics
and find a strong correlation with the relative changes reported by Google and
Apple using mobile phone data.
