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Article

Hybrid Model-Based Simulation Analysis on the Effects of Social Distancing Policy of the COVID-19 Epidemic

1
Research Institute of Industrial Technology Convergence, Korea Institute of Industrial Technology (KITECH), Ansan 15588, Korea
2
Department of Computer Engineering, Korea University of Technology and Education (KOREATECH), Cheonan 31253, Korea
3
Department of Future Technology, Korea University of Technology and Education (KOREATECH), Cheonan 31253, Korea
*
Author to whom correspondence should be addressed.
Academic Editors: Alberto Fernández Isabel, Isaac Martín De Diego, Juan Francisco Blanco Blanco and Paul B. Tchounwou
Int. J. Environ. Res. Public Health 2021, 18(21), 11264; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph182111264
Received: 16 August 2021 / Revised: 11 October 2021 / Accepted: 20 October 2021 / Published: 27 October 2021
This study utilizes modeling and simulation to analyze coronavirus (COVID-19) infection trends depending on government policies. Two modeling requirements are considered for infection simulation: (1) the implementation of social distancing policies and (2) the representation of population movements. To this end, we propose an extended infection model to combine analytical models with discrete event-based simulation models in a hybrid form. Simulation parameters for social distancing policies are identified and embedded in the analytical models. Administrative districts are modeled as a fundamental simulation agent, which facilitates representing the population movements between the cities. The proposed infection model utilizes real-world data regarding suspected, infected, recovered, and deceased people in South Korea. As an application, we simulate the COVID-19 epidemic in South Korea. We use real-world data for 160 days, containing meaningful days that begin the distancing policy and adjust the distancing policy to the next stage. We expect that the proposed work plays a principal role in analyzing how social distancing effectively affects virus prevention and provides a simulation environment for the biochemical field. View Full-Text
Keywords: simulation; SIRD model; discrete-event model; data-based learning; COVID-19 epidemic simulation; SIRD model; discrete-event model; data-based learning; COVID-19 epidemic
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MDPI and ACS Style

Kang, B.G.; Park, H.-M.; Jang, M.; Seo, K.-M. Hybrid Model-Based Simulation Analysis on the Effects of Social Distancing Policy of the COVID-19 Epidemic. Int. J. Environ. Res. Public Health 2021, 18, 11264. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph182111264

AMA Style

Kang BG, Park H-M, Jang M, Seo K-M. Hybrid Model-Based Simulation Analysis on the Effects of Social Distancing Policy of the COVID-19 Epidemic. International Journal of Environmental Research and Public Health. 2021; 18(21):11264. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph182111264

Chicago/Turabian Style

Kang, Bong G., Hee-Mun Park, Mi Jang, and Kyung-Min Seo. 2021. "Hybrid Model-Based Simulation Analysis on the Effects of Social Distancing Policy of the COVID-19 Epidemic" International Journal of Environmental Research and Public Health 18, no. 21: 11264. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph182111264

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