COVID-19 epidemic under the K-quarantine model: Network approach
K Choi1, Hoyun Choi1, B Kahng2,3
1CCSS, CTP and Department of Physics and Astronomy, Seoul National University, Seoul 08826, Korea.
Chaos, Solitons, and Fractals
|February 16, 2022
Summary
South Korea
Area of Science:
- Epidemiology
- Network Science
- Mathematical Modeling
Background:
- The COVID-19 pandemic has caused unprecedented global damage.
- South Korea implemented a local quarantine strategy instead of a global lockdown to mitigate economic impact and disease spread.
- Understanding the dynamics of local quarantine is crucial for effective pandemic control.
Purpose of the Study:
- To model the spread of COVID-19 using the Susceptible-Exposed-Infected-Recovered (SEIR) model on complex networks.
- To analyze the impact of local quarantine measures on disease transmission dynamics.
- To investigate the consequences of potential breakdowns in quarantine and social distancing.
Main Methods:
- Utilized the Susceptible-Exposed-Infected-Recovered (SEIR) model integrated with complex network theory.
- Modeled quarantine by dynamically disconnecting and reinstating network links for infected individuals.
- Performed numerical simulations using reaction rates derived from empirical data.
Main Results:
- The network model successfully reproduced the temporal pattern of accumulated COVID-19 cases.
- Local quarantine measures led to the detection of numerous asymptomatic infected individuals.
- The study considered the potential impact of local quarantine failures and weakened social distancing.
Conclusions:
- Local quarantine strategies, when modeled on complex networks, can effectively control COVID-19 spread.
- Dynamic network link adjustments accurately reflect quarantine interventions.
- Asymptomatic case detection is enhanced through integrated quarantine approaches.
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