  Background: The impact of individual non-pharmaceutical interventions (NPI)
such as state-wide stay-at-home orders, school closures and gathering size
limitations, on the COVID-19 epidemic is unknown. Understanding the impact that
above listed NPI have on disease transmission is critical for policy makers,
particularly as case counts increase again in some areas.
  Methods: Using a Bayesian framework, we reconstructed the incidence and
time-varying reproductive number (Rt) curves to investigate the relationship
between Rt, individual mobility as measured by Google Community Mobility
Reports, and NPI.
  Results: We found a strong relationship between reproductive number and
mobility, with each 10% drop in mobility being associated with an expected
10.2% reduction in Rt compared to baseline. The effects of limitations on the
size of gatherings, school and business closures, and stay-at-home orders were
dominated by the trend over time, which was associated with a 48% decrease in
the reproductive number, adjusting for the NPI.
  Conclusions: We found that the decrease in mobility associated with time may
be due to individuals changing their behavior in response to perceived risk or
external factors.
