  During the COVID-19 pandemic, governments faced difficulties in implementing
mobility restriction measures, as no clear quantitative relationship between
human mobility and infection spread in large cities is known. We developed a
model that enables quantitative estimations of the infection risk for
individual places and activities by using smartphone GPS data for the Tokyo
metropolitan area. The effective reproduction number is directly calculated
from the number of infectious social contacts defined by the square of the
population density at each location. The difference in the infection rate of
daily activities is considered, where the `stay-out' activity, staying at
someplace neither home nor workplace, is more than 28 times larger than other
activities. Also, the contribution to the infection strongly depends on
location. We imply that the effective reproduction number is sufficiently
suppressed if the highest-risk locations or activities are restricted. We also
discuss the effects of the Delta variant and vaccination.
