  Analyzing the SARS-CoV-2 pandemic outbreak based on actual data while
reflecting the characteristics of the real city provides beneficial information
for taking reasonable infection control measures in the future. We demonstrate
agent-based modeling for Tokyo based on GPS information and official national
statistics and perform a spatiotemporal analysis of the infection situation in
Tokyo. As a result of the simulation during the first wave of SARS-CoV-2 in
Tokyo using real GPS data, the infection occurred in the service industry, such
as restaurants, in the city center, and then the infected people brought back
the virus to the residential area; the infection spread in each area in Tokyo.
This phenomenon clarifies that the spread of infection can be curbed by
suppressing going out or strengthening infection prevention measures in service
facilities. It was shown that pandemic measures in Tokyo could be achieved not
only by strong control, such as the lockdown of cities, but also by thorough
infection prevention measures in service facilities, which explains the curb
phenomena in real Tokyo.
