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

Bong Gu Kang, Hee-Mun Park, Mi Jang and Kyung-Min Seo
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Bong Gu Kang: Research Institute of Industrial Technology Convergence, Korea Institute of Industrial Technology (KITECH), Ansan 15588, Korea
Hee-Mun Park: Department of Computer Engineering, Korea University of Technology and Education (KOREATECH), Cheonan 31253, Korea
Mi Jang: Department of Computer Engineering, Korea University of Technology and Education (KOREATECH), Cheonan 31253, Korea
Kyung-Min Seo: Department of Future Technology, Korea University of Technology and Education (KOREATECH), Cheonan 31253, Korea

IJERPH, 2021, vol. 18, issue 21, 1-17

Abstract: 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.

Keywords: simulation; SIRD model; discrete-event model; data-based learning; COVID-19 epidemic (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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