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Kyung-Duk Min 1 Article
Dynamics of the COVID-19 epidemic in the post-vaccination period in Korea: a rapid assessment
Kyung-Duk Min, Sangwoo Tak
Epidemiol Health. 2021;43:e2021040.   Published online May 27, 2021
DOI: https://doi.org/10.4178/epih.e2021040
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  • 5 Citations
AbstractAbstract AbstractSummary PDFSupplementary Material
Abstract
OBJECTIVES
Coronavirus disease 2019 (COVID-19) has had a tremendous impact on public health and socioeconomic conditions globally. Although non-pharmaceutical interventions (NPIs) such as social distancing effectively reduced the incidence of COVID-19, especially in Korea, demand for vaccination has increased to minimize the social costs of NPIs. This study estimated the potential benefits of COVID-19 vaccination in Korea.
METHODS
A mathematical model with vaccinated–susceptible–latent–infectious–recovered compartments was used to simulate the COVID-19 epidemic. The compartments were stratified into age groups of 0-19 years, 20-59 years, and 60 years or older. Based on the Korea Disease Control and Prevention Agency national vaccination plan for the second quarter of 2021, announced on March 15, we developed vaccination scenarios (with 150,000 dose/d and 100% compliance as the main scenario). Comparing scenarios without vaccination or with higher/lower vaccination rates and compliance, we estimated the numbers of COVID-19 cases that will be prevented by vaccination.
RESULTS
The results projected 203,135 cases within a year after April 2021 without vaccination, which would be reduced to 71,248 (64.9% decrease) by vaccination. Supposing a vaccination rate of 150,000 dose/d and 100% compliance, social distancing interventions for those aged 20 or more can be retracted after January 1, 2022.
CONCLUSIONS
We expect COVID-19 vaccination to be effective in Korea. Health authorities should minimize delays in vaccination and vaccine avoidance to maximize the effectiveness of vaccination and end social distancing early.
Summary
Korean summary
본 연구에서 국내 백신 접종 시작이후의 코로나19 유행 추이를 수학적 모형을 통하여 예측하였다. 연구 결과, 백신 접종이 전혀 진행되지 않을 경우, 2021년 4월부터 1년간 203,135 건의 확진 사례가 보고될 것으로 예측되었으나, 하루 15만 도즈의 접종이 진행될 경우 같은 기간의 확진자 수를 64.9% 감소시킬 수 있을 것으로 나타났으며, 20세 이상을 대상으로한 사회적 거리두기 정책은 2022년 1월에 중지될 수 있을 것으로 예상되었다.
Key Message
A mathematical model with vaccinated–susceptible–latent–infectious–recovered compartments was used to simulate the COVID-19 epidemic in Korea. The results projected 203,135 cases within a year after April 2021 without vaccination, which would be reduced to 71,248 (64.9% decrease) by vaccination (150,000 doses per day and 100% compliance). Supposing a vaccination rate of 150,000 doses per day and 100% compliance, social distancing intervention for those aged 20 or more can be retracted after January 1, 2022.

Citations

Citations to this article as recorded by  
  • Mathematical Modeling of COVID-19 Transmission and Intervention in South Korea: A Review of Literature
    Hyojung Lee, Sol Kim, Minyoung Jeong, Eunseo Choi, Hyeonjeong Ahn, Jeehyun Lee
    Yonsei Medical Journal.2023; 64(1): 1.     CrossRef
  • Impact of national Covid-19 vaccination Campaign, South Korea
    Seonju Yi, Young June Choe, Do Sang Lim, Hye Roen Lee, Jia Kim, Yoo-Yeon Kim, Ryu Kyung Kim, Eun Jung Jang, Sangwon Lee, Eunjoo Park, Seung-Jin Kim, Young-Joon Park
    Vaccine.2022; 40(26): 3670.     CrossRef
  • Multi-Faceted Analysis of COVID-19 Epidemic in Korea Considering Omicron Variant: Mathematical Modeling-Based Study
    Youngsuk Ko, Victoria May Mendoza, Renier Mendoza, Yubin Seo, Jacob Lee, Jonggul Lee, Donghyok Kwon, Eunok Jung
    Journal of Korean Medical Science.2022;[Epub]     CrossRef
  • The economic impact of COVID-19 interventions: A mathematical modeling approach
    Jung Eun Kim, Heejin Choi, Yongin Choi, Chang Hyeong Lee
    Frontiers in Public Health.2022;[Epub]     CrossRef
  • Analysis of Superspreading Potential from Transmission Clusters of COVID-19 in South Korea
    Hyojung Lee, Changyong Han, Jooyi Jung, Sunmi Lee
    International Journal of Environmental Research and Public Health.2021; 18(24): 12893.     CrossRef

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