Evaluation of COVID-19 intervention policies in South Korea using the stochastic individual-based model.

Autor: Chae MK; Research Team for Transmission Dynamics of Infectious Diseases, National Institute for Mathematical Sciences, Daejeon, 34047, Republic of Korea., Hwang DU; Research Team for Transmission Dynamics of Infectious Diseases, National Institute for Mathematical Sciences, Daejeon, 34047, Republic of Korea., Nah K; Busan Center for Medical Mathematics, National Institute for Mathematical Sciences, Busan, 49241, Republic of Korea., Son WS; Research Team for Transmission Dynamics of Infectious Diseases, National Institute for Mathematical Sciences, Daejeon, 34047, Republic of Korea. wsson@nims.re.kr.
Jazyk: angličtina
Zdroj: Scientific reports [Sci Rep] 2023 Nov 02; Vol. 13 (1), pp. 18945. Date of Electronic Publication: 2023 Nov 02.
DOI: 10.1038/s41598-023-46277-8
Abstrakt: The COVID-19 pandemic has swept the globe, and countries have responded with various intervention policies to prevent its spread. In this study, we aim to analyze the effectiveness of intervention policies implemented in South Korea. We use a stochastic individual-based model (IBM) with a synthetic population to simulate the spread of COVID-19. Using statistical data, we make the synthetic population and assign sociodemographic attributes to each individual. Individuals go about their daily lives based on their assigned characteristics, and encountering infectors in their daily lives stochastically determines whether they are infected. We reproduce the transmission of COVID-19 using the IBM simulation from November 2020 to February 2021 when three phases of increasingly stringent intervention policies were implemented, and then assess their effectiveness. Additionally, we predict how the spread of infection would have been different if these policies had been implemented in January 2022. This study offers valuable insights into the effectiveness of intervention policies in South Korea, which can assist policymakers and public health officials in their decision-making process.
(© 2023. The Author(s).)
Databáze: MEDLINE
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