  We investigate, through a data-driven contact tracing model, the transmission
of COVID-19 inside buses during distinct phases of the pandemic in a large
Brazilian city. From this microscopic approach, we recover the networks of
close contacts within consecutive time windows. A longitudinal comparison is
then performed by upscaling the traced contacts with the transmission computed
from a mean-field compartmental model for the entire city. Our results show
that the effective reproduction numbers inside the buses, $Re^{bus}$, and in
the city, $Re^{city}$, followed a compatible behavior during the first wave of
the local outbreak. Moreover, by distinguishing the close contacts of
healthcare workers in the buses, we discovered that their transmission,
$Re^{health}$, during the same period, was systematically higher than
$Re^{bus}$. This result reinforces the need for special public transportation
policies for highly exposed groups of people.
