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Mathematical Modeling of COVID-19 Transmission and Intervention in South Korea: A Review of Literature.
Lee, Hyojung; Kim, Sol; Jeong, Minyoung; Choi, Eunseo; Ahn, Hyeonjeong; Lee, Jeehyun.
  • Lee H; Department of Statistics, Kyungpook National University, Daegu, Korea.
  • Kim S; School of Mathematics and Computing (Mathematics), Yonsei University, Seoul, Korea.
  • Jeong M; School of Mathematics and Computing (Mathematics), Yonsei University, Seoul, Korea.
  • Choi E; Department of Statistics, Kyungpook National University, Daegu, Korea.
  • Ahn H; Department of Statistics, Kyungpook National University, Daegu, Korea.
  • Lee J; School of Mathematics and Computing (Mathematics), Yonsei University, Seoul, Korea. ezhyun@yonsei.ac.kr.
Yonsei Med J ; 64(1): 1-10, 2023 Jan.
Article in English | MEDLINE | ID: covidwho-2198650
ABSTRACT
South Korea implemented interventions to curb the spread of the novel coronavirus disease 2019 (COVID-19) pandemic with discovery of the first case in early 2020. Mathematical modeling designed to reflect the dynamics of disease transmission has been shown to be an important tool for responding to COVID-19. This study aimed to review publications on the structure, method, and role of mathematical models focusing on COVID-19 transmission dynamics in Korea. In total, 42 papers published between August 7, 2020 and August 21, 2022 were studied and reviewed. This study highlights the construction and utilization of mathematical models to help craft strategies for predicting the course of an epidemic and evaluating the effectiveness of control strategies. Despite the limitations caused by a lack of available epidemiological and surveillance data, modeling studies could contribute to providing scientific evidence for policymaking by simulating various scenarios.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study Limits: Humans Country/Region as subject: Asia Language: English Journal: Yonsei Med J Year: 2023 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study Limits: Humans Country/Region as subject: Asia Language: English Journal: Yonsei Med J Year: 2023 Document Type: Article