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COVID-19: Original Article
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
  • 20,528 View
  • 1,293 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

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Original Article
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
  • 11,153 View
  • 208 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
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