  As the COVID-19 outbreak evolves around the world, the World Health
Organization (WHO) and its Member States have been heavily relying on staying
at home and lock down measures to control the spread of the virus. In the last
months, various signs showed that the COVID-19 curve was flattening, but even
the partial lifting of some containment measures (e.g., school closures and
telecommuting) appear to favor a second wave of the disease. The accurate
evaluation of possible countermeasures and their well-timed revocation are
therefore crucial to avoid future waves or reduce their duration. In this
paper, we analyze patient and route data of infected patients from January 20,
2020, to May 31, 2020, collected by the Korean Center for Disease Control &
Prevention (KCDC). This data analysis helps us to characterize patient mobility
patterns and then use this characterization to parameterize simulations to
evaluate different what-if scenarios. Although this is not a definitive model
of how COVID-19 spreads in a population, its usefulness and flexibility are
illustrated using real-world data for exploring virus spread under a variety of
circumstances.
