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Eunok Jung 5 Articles
Korea Seroprevalence Study of Monitoring of SARS-COV-2 Antibody Retention and Transmission (K-SEROSMART): findings from national representative sample
Jina Han, Hye Jin Baek, Eunbi Noh, Kyuhyun Yoon, Jung Ae Kim, Sukhyun Ryu, Kay O Lee, No Yai Park, Eunok Jung, Sangil Kim, Hyukmin Lee, Yoo-Sung Hwang, Jaehun Jung, Hun Jae Lee, Sung-il Cho, Sangcheol Oh, Migyeong Kim, Chang-Mo Oh, Byengchul Yu, Young-Seoub Hong, Keonyeop Kim, Sun Jae Jung, Mi Ah Han, Moo-Sik Lee, Jung-Jeung Lee, Young Hwangbo, Hyeon Woo Yim, Yu-Mi Kim, Joongyub Lee, Weon-Young Lee, Jae-Hyun Park, Sungsoo Oh, Heui Sug Jo, Hyeongsu Kim, Gilwon Kang, Hae-Sung Nam, Ju-Hyung Lee, Gyung-Jae Oh, Min-Ho Shin, Soyeon Ryu, Tae-Yoon Hwang, Soon-Woo Park, Sang Kyu Kim, Roma Seol, Ki-Soo Park, Su Young Kim, Jun-wook Kwon, Sung Soon Kim, Byoungguk Kim, June-Woo Lee, Eun Young Jang, Ah-Ra Kim, Jeonghyun Nam, The Korea Community Health Survey Group, Soon Young Lee, Dong-Hyun Kim
Epidemiol Health. 2023;45:e2023075.   Published online August 17, 2023
DOI: https://doi.org/10.4178/epih.e2023075
  • 3,273 View
  • 172 Download
  • 1 Web of Science
AbstractAbstract AbstractSummary PDFSupplementary Material
Abstract
OBJECTIVES
We estimated the population prevalence of antibodies to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), including unreported infections, through a Korea Seroprevalence Study of Monitoring of SARS-CoV-2 Antibody Retention and Transmission (K-SEROSMART) in 258 communities throughout Korea.
METHODS
In August 2022, a survey was conducted among 10,000 household members aged 5 years and older, in households selected through two stage probability random sampling. During face-to-face household interviews, participants self-reported their health status, COVID-19 diagnosis and vaccination history, and general characteristics. Subsequently, participants visited a community health center or medical clinic for blood sampling. Blood samples were analyzed for the presence of antibodies to spike proteins (anti-S) and antibodies to nucleocapsid proteins (anti-N) SARS-CoV-2 proteins using an electrochemiluminescence immunoassay. To estimate the population prevalence, the PROC SURVEYMEANS statistical procedure was employed, with weighting to reflect demographic data from July 2022.
RESULTS
In total, 9,945 individuals from 5,041 households were surveyed across 258 communities, representing all basic local governments in Korea. The overall population-adjusted prevalence rates of anti-S and anti-N were 97.6% and 57.1%, respectively. Since the Korea Disease Control and Prevention Agency has reported a cumulative incidence of confirmed cases of 37.8% through July 31, 2022, the proportion of unreported infections among all COVID-19 infection was suggested to be 33.9%.
CONCLUSIONS
The K-SEROSMART represents the first nationwide, community-based seroepidemiologic survey of COVID-19, confirming that most individuals possess antibodies to SARS-CoV-2 and that a significant number of unreported cases existed. Furthermore, this study lays the foundation for a surveillance system to continuously monitor transmission at the community level and the response to COVID-19.
Summary
Korean summary
인구집단을 기반으로 하여 대표성 있는 표본을 추출하여 COVID-19 항체유병률 조사를 전국적으로 수행함으로 지역사회 단위에서 지속적으로 모니터링할 수 있는 COVID-19 감시체계 구축의 기반을 마련하였다. 2022년 8월 우리나라 국민의 대부분이 COVID-19에 대한 항체를 보유하고 있었고 인구 3명 중 1명은 미확진 감염자로 추정되었다.
Key Message
The K-SEROSMART represents the first nationwide, community-based seroepidemiologic survey of COVID-19. In August 2022, most of the Korean people had antibodies to COVID-19, and one in three people was estimated to have an unreported infection. This study lays the foundation for a surveillance system to continuously monitor transmission at the community level and the response to COVID-19.
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
  • 2,717 View
  • 105 Download
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.
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
  • 7,678 View
  • 145 Download
  • 4 Web of Science
  • 5 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  
  • 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
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  • 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
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    Hye-Min Na, Bok-Mi Jung
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Prediction of COVID-19 transmission dynamics using a mathematical model considering behavior changes in Korea
Soyoung Kim, Yu Bin Seo, Eunok Jung
Epidemiol Health. 2020;42:e2020026.   Published online April 13, 2020
DOI: https://doi.org/10.4178/epih.e2020026
  • 19,829 View
  • 1,280 Download
  • 46 Web of Science
  • 46 Crossref
AbstractAbstract AbstractSummary PDFSupplementary Material
Abstract
OBJECTIVES
Since the report of the first confirmed case in Daegu on February 18, 2020, local transmission of coronavirus disease 2019 (COVID-19) in Korea has continued. In this study, we aimed to identify the pattern of local transmission of COVID-19 using mathematical modeling and predict the epidemic size and the timing of the end of the spread.
METHODS
We modeled the COVID-19 outbreak in Korea by applying a mathematical model of transmission that factors in behavioral changes. We used the Korea Centers for Disease Control and Prevention data of daily confirmed cases in the country to estimate the nationwide and Daegu/Gyeongbuk area-specific transmission rates as well as behavioral change parameters using a least-squares method.
RESULTS
The number of transmissions per infected patient was estimated to be about 10 times higher in the Daegu/Gyeongbuk area than the average of nationwide. Using these estimated parameters, our models predicts that about 13,800 cases will occur nationwide and 11,400 cases in the Daegu/Gyeongbuk area until mid-June.
CONCLUSIONS
We mathematically demonstrate that the relatively high per-capita rate of transmission and the low rate of changes in behavior have caused a large-scale transmission of COVID-19 in the Daegu/Gyeongbuk area in Korea. Since the outbreak is expected to continue until May, non-pharmaceutical interventions that can be sustained over the long term are required.
Summary
Korean summary
본 논문은 행동변화를 고려한 수학적 모델을 이용하여 코로나바이러스병-19의 유행 양상을 분석하고 총 환자수와 유행기간을 예측하고자 한다. 질병관리본부 확진자 데이터를 이용하여 전국과 대구·경북 지역의 감염전파율과 행동변화율을 추정하였다. 3월 10일까지의 데이터를 기준으로 전국적으로 6월 중순까지 약 13,000명, 대구·경북지역의 경우 5월 말까지 약 11,000명의 환자가 발생할 것으로 예측된다.

Citations

Citations to this article as recorded by  
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    Elena R. Meskina
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    Vitor Hugo Moreau
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    Hafeez Aderinsayo Adekola, Ibrahim Ayoade Adekunle, Haneefat Olabimpe Egberongbe, Sefiu Adekunle Onitilo, Idris Nasir Abdullahi
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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
  • 10,487 View
  • 207 Download
  • 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

Epidemiol Health : Epidemiology and Health