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Prediction of COVID-19 transmission dynamics using a mathematical model considering behavior changes in Korea

Epidemiology and Health 2020년 42권 1호 p.26 ~ 26
김소영, 서유빈, Jung Eun-Ok,
소속 상세정보
김소영 ( Kim So-Young ) - Konkuk University Department of Mathematics
서유빈 ( Seo Yu-Bin ) - Hallym University College of Medicine Department of Internal Medicine
 ( Jung Eun-Ok ) - Konkuk University Department of Mathematics

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.

키워드

COVID-19; Mathematical model; Behavior changes; Parameter estimation; Model prediction

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