Hybrid Model-Based Simulation Analysis on the Effects of Social Distancing Policy of the COVID-19 Epidemic
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kang, Bong Gu | - |
dc.contributor.author | Park, Hee-Mun | - |
dc.contributor.author | Jang, Mi | - |
dc.contributor.author | Seo, Kyung-Min | - |
dc.date.accessioned | 2023-08-16T07:41:22Z | - |
dc.date.available | 2023-08-16T07:41:22Z | - |
dc.date.issued | 2021-11 | - |
dc.identifier.issn | 1661-7827 | - |
dc.identifier.issn | 1660-4601 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/114066 | - |
dc.description.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. | - |
dc.format.extent | 17 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | Multidisciplinary Digital Publishing Institute (MDPI) | - |
dc.title | Hybrid Model-Based Simulation Analysis on the Effects of Social Distancing Policy of the COVID-19 Epidemic | - |
dc.type | Article | - |
dc.publisher.location | 스위스 | - |
dc.identifier.doi | 10.3390/ijerph182111264 | - |
dc.identifier.scopusid | 2-s2.0-85117940905 | - |
dc.identifier.wosid | 000719489700001 | - |
dc.identifier.bibliographicCitation | International Journal of Environmental Research and Public Health, v.18, no.21, pp 1 - 17 | - |
dc.citation.title | International Journal of Environmental Research and Public Health | - |
dc.citation.volume | 18 | - |
dc.citation.number | 21 | - |
dc.citation.startPage | 1 | - |
dc.citation.endPage | 17 | - |
dc.type.docType | 정기학술지(Article(Perspective Article포함)) | - |
dc.description.isOpenAccess | Y | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | ssci | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Environmental Sciences & Ecology | - |
dc.relation.journalResearchArea | Public, Environmental & Occupational Health | - |
dc.relation.journalWebOfScienceCategory | Environmental Sciences | - |
dc.relation.journalWebOfScienceCategory | Public, Environmental & Occupational Health | - |
dc.subject.keywordPlus | MODIFIED SIRD MODEL | - |
dc.subject.keywordPlus | STATES | - |
dc.subject.keywordPlus | OPTIMIZATION | - |
dc.subject.keywordPlus | SPREAD | - |
dc.subject.keywordPlus | DESIGN | - |
dc.subject.keywordPlus | SYSTEM | - |
dc.subject.keywordAuthor | COVID-19 epidemic | - |
dc.subject.keywordAuthor | Data-based learning | - |
dc.subject.keywordAuthor | Discrete-event model | - |
dc.subject.keywordAuthor | Simulation | - |
dc.subject.keywordAuthor | SIRD model | - |
dc.identifier.url | https://www.scopus.com/record/display.uri?eid=2-s2.0-85117940905&origin=inward&txGid=fb8dee83c19b910b53ddfdd537fc2c7d | - |
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