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Mathematical Modeling of COVID-19 Transmission and Intervention in South Korea: A Review of Literature.

Hyojung LeeSol KimMinyoung JeongEunseo ChoiHyeonjeong AhnJeehyun Lee
Published in: Yonsei medical journal (2022)
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.
Keyphrases
  • coronavirus disease
  • sars cov
  • randomized controlled trial
  • respiratory syndrome coronavirus
  • systematic review
  • public health
  • small molecule
  • climate change
  • machine learning
  • high density