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Reconstructing a COVID-19 outbreak within a religious group using social network analysis simulation in Korea
Namje Kim1,2, Su Jin Kang3, Sangwoo Tak3
1Department of Economics, Seoul National University, Seoul, Korea.
Epidemiology and Health
|October 4, 2021
Summary
Simulations show that if the Sarang Jeil church had followed mask-wearing guidelines, the coronavirus disease 2019 (COVID-19) outbreak could have been 20 times smaller. Social network analysis is key for controlling infectious disease spread.
Area of Science:
- Epidemiology
- Mathematical Modeling
- Social Network Analysis
Background:
- Large outbreaks of infectious diseases, such as coronavirus disease 2019 (COVID-19), can emerge from specific settings like religious gatherings.
- Understanding the transmission dynamics within these clusters is crucial for effective public health interventions.
Purpose of the Study:
- To reconstruct a COVID-19 outbreak at a church setting to understand its spread before detection.
- To estimate the potential effectiveness of adhering to government-recommended mask-wearing guidelines.
Main Methods:
- Utilized a discrete-time stochastic simulation model combined with social network analysis (SNA).
- Simulated COVID-19 transmission within the Sarang Jeil church.
- Conducted a counterfactual experiment to assess the impact of increased mask compliance.
Main Results:
- The model estimated a 67% mask-wearing ratio, aligning with observed outbreak data (953.8 cases).
- A counterfactual scenario with 95% mask compliance predicted significantly fewer cases (45.6).
- Proper adherence to mask-wearing guidelines could have reduced the outbreak size by approximately 20-fold.
Conclusions:
- Social network analysis (SNA) proves effective for monitoring and controlling infectious disease outbreaks.
- Simulation results highlight the significant benefits of social distancing and mask-wearing, even with limitations.
- Developing targeted guidelines for high-risk settings is essential for preventing future cluster outbreaks.
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