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

TL;DR

This study analyzes COVID-19 patient data from South Korea to understand transmission patterns and evaluate potential containment strategies through simulation, aiding in informed decision-making for public health measures.

Contribution

It provides a data-driven approach to characterize patient mobility and simulate virus spread scenarios, enhancing understanding of COVID-19 transmission dynamics.

Findings

Patient mobility patterns identified

Simulation of containment measures conducted

Insights into timing of interventions gained

Abstract

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.