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As the COVID-19 outbreak evolves around the world, the World HealthOrganization (WHO) and its Member States have been heavily relying on stayingat home and lock down measures to control the spread of the virus. In the lastmonths, various signs showed that the COVID-19 curve was flattening, but eventhe partial lifting of some containment measures (e.g., school closures andtelecommuting) appear to favor a second wave of the disease. The accurateevaluation of possible countermeasures and their well-timed revocation aretherefore crucial to avoid future waves or reduce their duration. In thispaper, 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 mobilitypatterns and then use this characterization to parameterize simulations toevaluate different what-if scenarios. Although this is not a definitive modelof how COVID-19 spreads in a population, its usefulness and flexibility areillustrated using real-world data for exploring virus spread under a variety ofcircumstances.

Characterizing the COVID-19 Transmission in South Korea Using the KCDC Patient Data