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Individual-based simulation model for COVID-19 transmission in Daegu,Korea
Author(s) -
Woo-Sik Son
Publication year - 2020
Publication title -
epidemiology and health
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.109
H-Index - 19
ISSN - 2092-7193
DOI - 10.4178/epih.e2020042
Subject(s) - census , covid-19 , geography , demography , population , hotspot (geology) , socioeconomics , medicine , infectious disease (medical specialty) , disease , sociology , pathology , geophysics , geology
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.

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