Individual-based simulation model for COVID-19 transmission in Daegu, Korea

Area of Science:

• Epidemiology
• Mathematical Modeling
• Public Health

Background:

• Daegu, South Korea, experienced a significant COVID-19 outbreak, accounting for over 70% of national cases by March 2020.
• Understanding transmission dynamics within densely populated areas is crucial for effective control strategies.

Purpose of the Study:

• To model the COVID-19 epidemic in Daegu using an individual-based approach.
• To predict future disease spread under various public health intervention scenarios.
• To analyze the specific impact of school reopening on transmission patterns.

Main Methods:

• An individual-based simulation model was developed using synthetic population data.
• Transmission pathways included household, work/school, and social/religious gatherings.
• A specific cohort (9,000 individuals) representing the Shincheonji Church was incorporated as a high-transmission 'hotspot'.

Main Results:

• The model accurately reproduced the cumulative confirmed COVID-19 cases in Daegu up to March 26, 2020.
• The Shincheonji Church cluster demonstrated a distinct infection probability compared to the general Daegu population.
• Three scenarios were simulated: school closure, early school reopening, and delayed reopening with increased hospitalization time.

Conclusions:

• Scenario III, involving delayed school reopening and increased hospitalization delay, projected an additional 107 cases.
• This scenario also predicted a 92-day delay in the occurrence of the last COVID-19 case in Daegu.
• These findings highlight the significant impact of delayed interventions on epidemic duration and case numbers.