Hybrid Model-Based Simulation Analysis on the Effects of Social Distancing Policy of the COVID-19 Epidemicopen access
- Authors
- Kang, Bong Gu; Park, Hee-Mun; Jang, Mi; Seo, Kyung-Min
- Issue Date
- Nov-2021
- Publisher
- Multidisciplinary Digital Publishing Institute (MDPI)
- Keywords
- COVID-19 epidemic; Data-based learning; Discrete-event model; Simulation; SIRD model
- Citation
- International Journal of Environmental Research and Public Health, v.18, no.21, pp 1 - 17
- Pages
- 17
- Indexed
- SCIE
SSCI
SCOPUS
- Journal Title
- International Journal of Environmental Research and Public Health
- Volume
- 18
- Number
- 21
- Start Page
- 1
- End Page
- 17
- URI
- https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/114066
- DOI
- 10.3390/ijerph182111264
- ISSN
- 1661-7827
1660-4601
- 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.
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