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Youngsuk Ko 3 Articles
Effective vaccination strategies to control COVID-19 in Korea: a modeling study
Youngsuk Ko, Kyong Ran Peck, Yae-Jean Kim, Dong-Hyun Kim, Eunok Jung
Epidemiol Health. 2023;45:e2023084.   Published online September 7, 2023
DOI: https://doi.org/10.4178/epih.e2023084
  • 7,093 View
  • 141 Download
  • 1 Web of Science
  • 1 Crossref
AbstractAbstract AbstractSummary PDFSupplementary Material
Abstract
OBJECTIVES
In Korea, as immunity levels of the coronavirus disease 2019 (COVID-19) in the population acquired through previous infections and vaccinations have decreased, booster vaccinations have emerged as a necessary measure to control new outbreaks. The objective of this study was to identify the most suitable vaccination strategy for controlling the surge in COVID-19 cases.
METHODS
A mathematical model was developed to concurrently evaluate the immunity levels induced by vaccines and infections. This model was then employed to investigate the potential for future resurgence and the possibility of control through the use of vaccines and antivirals.
RESULTS
As of May 11, 2023, if the current epidemic trend persists without further vaccination efforts, a peak in resurgence is anticipated to occur around mid-October of the same year. Under the most favorable circumstances, the peak number of severely hospitalized patients could be reduced by 43% (n=480) compared to the scenario without vaccine intervention (n=849). Depending on outbreak trends and vaccination strategies, the best timing for vaccination in terms of minimizing this peak varies from May 2023 to August 2023.
CONCLUSIONS
Our findings suggest that if the epidemic persist, the best timing for administering vaccinations would need to be earlier than currently outlined in the Korean plan. It is imperative to continue monitoring outbreak trends, as this is key to determining the best vaccination timing in order to manage potential future surges.
Summary
Korean summary
본 연구는 자연감염 혹은 백신으로 획득된 면역의 저하를 고려한 수리모델을 사용하여 COVID-19에 대한 백신 접종 전략 분석 결과를 보인다. 시뮬레이션 결과는 추가 백신 접종이 없을 경우 재유행의 정점이 800명을 넘을 것임을 나타내며, 적절한 시기에 백신을 접종하면 최대 재원 위중증환자수를 약 40%까지 줄일 수 있음을 보인다. 본 연구는 확진자 추세의 지속적인 모니터링이 백신 접종의 적정 시기를 결정하고 미래 COVID-19의 재유행을 효과적으로 관리하는 데 필요하다는 점을 강조한다.
Key Message
Our study analyzes strategies for COVID-19 through vaccination, using a mathematical model considering waning immunity from past infections and vaccinations. Results indicate that a resurgence peak would reach more than 800 without further vaccination, and suggest vaccination in proper timing can reduce the peak size of administered severe patients by up to approximately 40%. The study emphasizes the importance of ongoing monitoring of outbreak trends to manage vaccination timing and future COVID-19 surges effectively.

Citations

Citations to this article as recorded by  
  • Global stability analysis of an extended SUC epidemic mathematical model
    Mengxin Chen, Soobin Kwak, Seokjun Ham, Youngjin Hwang, Junseok Kim
    Zeitschrift für Naturforschung A.2024;[Epub]     CrossRef
Risk of COVID-19 transmission in heterogeneous age groups and effective vaccination strategy in Korea: a mathematical modeling study
Youngsuk Ko, Jacob Lee, Yubin Seo, Eunok Jung
Epidemiol Health. 2021;43:e2021059.   Published online September 8, 2021
DOI: https://doi.org/10.4178/epih.e2021059
  • 11,018 View
  • 158 Download
  • 5 Web of Science
  • 7 Crossref
AbstractAbstract AbstractSummary PDFSupplementary Material
Abstract
OBJECTIVES
This study aims to analyze the possibility and conditions of maintaining an effective reproductive number below 1 using a mathematical model.
METHODS
The total population was divided into five age groups (0-17, 18-29, 30-59, 60-74, and ≥75 years). Maximum likelihood estimation (MLE) was used to estimate the transmission rate of each age group. Mathematical model simulation was conducted until December 31, 2021, by establishing various strategies for vaccination and social distancing without considering variants.
RESULTS
MLE results revealed that the group aged 0-17 years had a lower risk of transmission than other age groups, and the older age group had relatively high risks of infection. If 70% of the population will be vaccinated by the end of 2021, then simulations showed that even if social distancing was eased, the effective reproductive number would remain below 1 near August if it was not at the level of the third re-spreading period. However, if social distancing was eased and it reached the level of the re-spreading period, the effective reproductive number could be below 1 at the end of 2021.
CONCLUSIONS
Considering both stable and worsened situations, simulation results emphasized that sufficient vaccine supply and control of the epidemic by maintaining social distancing to prevent an outbreak at the level of the re-spreading period are necessary to minimize mortality and maintain the effective reproductive number below 1.
Summary
Korean summary
본 연구에서는 질병관리청에서 제공하는 개별 확진자 데이터에 확률통계적 방법을 적용하여 연령군 간의 감염전파 행렬을 추정하였으며 연령군을 고려한 수리모델에 적용되었다. 본 연구에서 우리는 2020년 10월부터 2021년 5월까지 한국에서의 코로나19 유행상황을 정책 구간에 따라 분석하였으며 이를 토대로 거리두기 완화 수준에 따라 거리두기 완화 상태에서도 지속적으로 유효감염재생산지수가 1보다 작아지는 시점이 달라질 수 있음을 보인다.
Key Message
In this research, we estimated age-group-specified transmission rate matrix by applying maximum likelihood estimation into individual based data which was provided by Korea Disease Control and Prevention Agency. Our model simulation showed the moment, when the effective reproductive number is consistently below 1 even the distancing is eased, is ranged from August to the end of 2021 depending on the intensity of the social distancing during eased phase.

Citations

Citations to this article as recorded by  
  • Predictive models for health outcomes due to SARS-CoV-2, including the effect of vaccination: a systematic review
    Oscar Espinosa, Laura Mora, Cristian Sanabria, Antonio Ramos, Duván Rincón, Valeria Bejarano, Jhonathan Rodríguez, Nicolás Barrera, Carlos Álvarez-Moreno, Jorge Cortés, Carlos Saavedra, Adriana Robayo, Oscar H. Franco
    Systematic Reviews.2024;[Epub]     CrossRef
  • Risk of Severe Acute Respiratory Syndrome Coronavirus 2 Transmission in Seoul, Korea
    Jiwoo Sim, Euncheol Son, Minsu Kwon, Eun Jin Hwang, Young Hwa Lee, Young June Choe
    Infection & Chemotherapy.2024; 56(2): 204.     CrossRef
  • 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 vaccination and non-pharmacological interventions on COVID-19: a review of simulation modeling studies in Asia
    Karan Thakkar, Julia Regazzini Spinardi, Jingyan Yang, Moe H. Kyaw, Egemen Ozbilgili, Carlos Fernando Mendoza, Helen May Lin Oh
    Frontiers in Public Health.2023;[Epub]     CrossRef
  • Effective vaccination strategies to control COVID-19 in Korea: a modeling study
    Youngsuk Ko, Kyong Ran Peck, Yae-Jean Kim, Dong-Hyun Kim, Eunok Jung
    Epidemiology and Health.2023; : e2023084.     CrossRef
  • Quantifying the Effects of Non-Pharmaceutical and Pharmaceutical Interventions Against Covid-19 Epidemic in the Republic of Korea: Mathematical Model-Based Approach Considering Age Groups and the Delta Variant
    Youngsuk Ko, Victoria May P. Mendoza, Yubin Seo, Jacob Lee, Yeonju Kim, Donghyok Kwon, Eunok Jung, E. Augeraud, M. Banerjee, J.-S. Dhersin, A. d'Onofrio, T. Lipniacki, S. Petrovskii, Chi Tran, A. Veber-Delattre, E. Vergu, V. Volpert
    Mathematical Modelling of Natural Phenomena.2022; 17: 39.     CrossRef
  • Dietary Behavior and Diet Quality in the Korean Adult Population by Income Level before and after the COVID-19 Pandemic: Using the Korean National Health and Nutrition Examination Survey (2019-2020)
    Hye-Min Na, Bok-Mi Jung
    The Korean Journal of Community Living Science.2022; 33(3): 397.     CrossRef
Ebola virus disease outbreak in Korea: use of a mathematical model and stochastic simulation to estimate risk
Youngsuk Ko, Seok-Min Lee, Soyoung Kim, Moran Ki, Eunok Jung
Epidemiol Health. 2019;41:e2019048.   Published online November 24, 2019
DOI: https://doi.org/10.4178/epih.e2019048
  • 13,808 View
  • 217 Download
  • 1 Web of Science
  • 1 Crossref
AbstractAbstract AbstractSummary PDFSupplementary Material
Abstract
OBJECTIVES
According to the World Health Organization, there have been frequent reports of Ebola virus disease (EVD) since the 2014 EVD pandemic in West Africa. We aim to estimate the outbreak scale when an EVD infected person arrives in Korea.
METHODS
Western Africa EVD epidemic mathematical model SEIJR or SEIJQR was modified to create a Korean EVD outbreak model. The expected number of EVD patients and outbreak duration were calculated by stochastic simulation under the scenarios of Best case, Diagnosis delay, and Case missing.
RESULTS
The 2,000 trials of stochastic simulation for each scenario demonstrated the following results: The possible median number of patients is 2 and the estimated maximum number is 11 when the government intervention is proceeded immediately right after the first EVD case is confirmed. With a 6-day delay in diagnosis of the first case, the median number of patients becomes 7, and the maximum, 20. If the first case is missed and the government intervention is not activated until 2 cases of secondary infection occur, the median number of patients is estimated at 15, and the maximum, at 35.
CONCLUSIONS
Timely and rigorous diagnosis is important to reduce the spreading scale of infection when a new communicable disease is inflowed into Korea. Moreover, it is imperative to strengthen the local surveillance system and diagnostic protocols to avoid missing cases of secondary infection.
Summary
Korean summary
본 연구는 수학적 모델과 확률 시뮬레이션 기법을 이용하여 국내에 유입되지 않았던 에볼라바이러스병(EVD)의 확산 위험도를 정량적으로 예측하는 첫 번째 연구이다. 또한 이 연구를 통해 에볼라바이러스병 환자의 유입 시 발생 가능한 진단 지연 혹은 유입 미인지 상황을 가정하여 발생할 수 있는 2차 감염자 수 및 감염 종식까지의 기간을 계산했고 에볼라바이러스 유입 대비 실시간모니터링의 중요성과 확산 시 상황에 따른 최대 일일 환자수를 합리적으로 제시할 수 있다.

Citations

Citations to this article as recorded by  
  • Estimating the Transmission Risk of COVID-19 in Nigeria: A Mathematical Modelling Approach
    Irany FA, Akwafuo SE, Abah T, Mikler AR
    Journal of Health Care and Research.2020; 1(3): 135.     CrossRef

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