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

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....

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Autores principales:	Bong Gu Kang, Hee-Mun Park, Mi Jang, Kyung-Min Seo
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	simulation SIRD model discrete-event model data-based learning COVID-19 epidemic Medicine R
Acceso en línea:	https://doaj.org/article/f1cb32b73b0e4e278bb54fe772fa4d37
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spelling	oai:doaj.org-article:f1cb32b73b0e4e278bb54fe772fa4d372021-11-11T16:24:56ZHybrid Model-Based Simulation Analysis on the Effects of Social Distancing Policy of the COVID-19 Epidemic10.3390/ijerph1821112641660-46011661-7827https://doaj.org/article/f1cb32b73b0e4e278bb54fe772fa4d372021-10-01T00:00:00Zhttps://www.mdpi.com/1660-4601/18/21/11264https://doaj.org/toc/1661-7827https://doaj.org/toc/1660-4601This 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.Bong Gu KangHee-Mun ParkMi JangKyung-Min SeoMDPI AGarticlesimulationSIRD modeldiscrete-event modeldata-based learningCOVID-19 epidemicMedicineRENInternational Journal of Environmental Research and Public Health, Vol 18, Iss 11264, p 11264 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	simulation SIRD model discrete-event model data-based learning COVID-19 epidemic Medicine R
spellingShingle	simulation SIRD model discrete-event model data-based learning COVID-19 epidemic Medicine R Bong Gu Kang Hee-Mun Park Mi Jang Kyung-Min Seo Hybrid Model-Based Simulation Analysis on the Effects of Social Distancing Policy of the COVID-19 Epidemic
description	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.
format	article
author	Bong Gu Kang Hee-Mun Park Mi Jang Kyung-Min Seo
author_facet	Bong Gu Kang Hee-Mun Park Mi Jang Kyung-Min Seo
author_sort	Bong Gu Kang
title	Hybrid Model-Based Simulation Analysis on the Effects of Social Distancing Policy of the COVID-19 Epidemic
title_short	Hybrid Model-Based Simulation Analysis on the Effects of Social Distancing Policy of the COVID-19 Epidemic
title_full	Hybrid Model-Based Simulation Analysis on the Effects of Social Distancing Policy of the COVID-19 Epidemic
title_fullStr	Hybrid Model-Based Simulation Analysis on the Effects of Social Distancing Policy of the COVID-19 Epidemic
title_full_unstemmed	Hybrid Model-Based Simulation Analysis on the Effects of Social Distancing Policy of the COVID-19 Epidemic
title_sort	hybrid model-based simulation analysis on the effects of social distancing policy of the covid-19 epidemic
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/f1cb32b73b0e4e278bb54fe772fa4d37
work_keys_str_mv	AT bonggukang hybridmodelbasedsimulationanalysisontheeffectsofsocialdistancingpolicyofthecovid19epidemic AT heemunpark hybridmodelbasedsimulationanalysisontheeffectsofsocialdistancingpolicyofthecovid19epidemic AT mijang hybridmodelbasedsimulationanalysisontheeffectsofsocialdistancingpolicyofthecovid19epidemic AT kyungminseo hybridmodelbasedsimulationanalysisontheeffectsofsocialdistancingpolicyofthecovid19epidemic
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Hybrid Model-Based Simulation Analysis on the Effects of Social Distancing Policy of the COVID-19 Epidemic

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