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COVID-19: Methods
Individual-based simulation model for COVID-19 transmission in Daegu, Korea
Woo-Sik Son, RISEWIDs Team
Epidemiol Health. 2020;42:e2020042.   Published online June 15, 2020
DOI: https://doi.org/10.4178/epih.e2020042
  • 11,908 View
  • 287 Download
  • 7 Web of Science
  • 5 Crossref
AbstractAbstract AbstractSummary PDFSupplementary Material
Abstract
OBJECTIVES
The aims of this study were to obtain insights into the current coronavirus disease 2019 (COVID-19) epidemic in the city of Daegu, which accounted for 6,482 of the 9,241 confirmed cases in Korea as of March 26, 2020, to predict the future spread, and to analyze the impact of school opening.
METHODS
Using an individual-based model, we simulated the spread of COVID-19 in Daegu. An individual can be infected through close contact with infected people in a household, at work/school, and at religious and social gatherings. We created a synthetic population from census sample data. Then, 9,000 people were randomly selected from the entire population of Daegu and set as members of the Shincheonji Church. We did not take into account population movements to and from other regions in Korea.
RESULTS
Using the individual-based model, the cumulative confirmed cases in Daegu through March 26, 2020, were reproduced, and it was confirmed that the hotspot, i.e., the Shincheonji Church had a different probability of infection than non-hotspot, i.e., the Daegu community. For 3 scenarios (I: school closing, II: school opening after April 6, III: school opening after April 6 and the mean period from symptom onset to hospitalization increasing to 4.3 days), we predicted future changes in the pattern of COVID-19 spread in Daegu.
CONCLUSIONS
Compared to scenario I, it was found that in scenario III, the cumulative number of patients would increase by 107 and the date of occurrence of the last patient would be delayed by 92 days.
Summary
Korean summary
신천지 교인 집단이 hotspot이 되어 지역사회로 전파된 대구의 COVID-19 확산을 시뮬레이션하였다. Individual based model을 이용하여 신천지 교인 집단, 즉 hotspot과 non-hotspot이 서로 다른 감염 확률을 갖고 있음을 확인하였으며, 4월 6일로 예정된 개학이 대구 지역 COVID-19 확산에 어떤 영향을 미칠지 분석하였다.

Citations

Citations to this article as recorded by  
  • Using simulation modelling and systems science to help contain COVID‐19: A systematic review
    Weiwei Zhang, Shiyong Liu, Nathaniel Osgood, Hongli Zhu, Ying Qian, Peng Jia
    Systems Research and Behavioral Science.2023; 40(1): 207.     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
  • Transition from growth to decay of an epidemic due to lockdown
    Hamid Khataee, Jack Kibble, Istvan Scheuring, Andras Czirok, Zoltan Neufeld
    Biophysical Journal.2021; 120(14): 2872.     CrossRef
  • A Full-Scale Agent-Based Model to Hypothetically Explore the Impact of Lockdown, Social Distancing, and Vaccination During the COVID-19 Pandemic in Lombardy, Italy: Model Development
    Giuseppe Giacopelli
    JMIRx Med.2021; 2(3): e24630.     CrossRef
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    Mina Kim, In-Hoo Park, Young-Shin Kang, Honey Kim, Min Jhon, Ju-Wan Kim, Seunghyong Ryu, Ju-Yeon Lee, Jae-Min Kim, Jonghun Lee, Sung-Wan Kim
    Frontiers in Psychiatry.2020;[Epub]     CrossRef
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
  • 20,513 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

Citations to this article as recorded by  
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    Hyojung Lee, Sol Kim, Minyoung Jeong, Eunseo Choi, Hyeonjeong Ahn, Jeehyun Lee
    Yonsei Medical Journal.2023; 64(1): 1.     CrossRef
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    Healthcare.2023; 11(11): 1623.     CrossRef
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