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Epidemiology and Health 2019;e2019048.
DOI: https://doi.org/10.4178/epih.e2019048    [Accepted] Published online Nov 24, 2019.
Risk estimation of Ebola virus disease outbreak in the Republic of Korea: using mathematical model and stochastic simulation
Youngsuk Ko1  , Seokmin Lee2  , Soyoung Kim1  , Moran Ki3  , Eunok Jung1 
1Department of Mathematics, Konkuk University, Seoul, Korea
2Department of Liberal Arts, College of Engineering, Hongik University, Seoul, Korea
3Department of Cancer Control and Population Health, Graduate School of Cancer Science and Policy, National Cancer Center, Goyang, Korea
Correspondence  Eunok Jung ,Tel: +82-2-450-4163, Fax: +82-2-458-1952, Email: junge@konkuk.ac.kr
Received: Aug 17, 2019  Accepted after revision: Nov 20, 2019
According to the World Health Organization (WHO), there have been constant reports of Ebola virus disease (EVD) since the 2014 EVD pandemic in West Africa. We aim to estimate the scale of spread when a case of EVD infection arrives in Korea using a mathematical model based on various parameters.
The spread model of Western African EVD derived from deterministic epidemic mathematical models (SEIJR or SEIJQR) has been modified to fit the circumstances in Korea and create a Korean EVD version. The expected number of domestic patients and outbreak duration were projected with probabilistic simulation. Furthermore, the duration of EVD outbreak, maximum number of daily incidences, and total number of patients were predicted by simulating 2 scenarios wherein diagnosis of the first imported case was delayed and EVD cases were missed until multiple secondary infections were found.
The results of 2,000 rounds of probabilistic simulation for each scenario demonstrated that the possible median number of patients is 2 and the estimated maximum number is 11 when an interim policy is adopted immediately with the first domestic case admitted to a health care institution. With a 6-day delay in confirming the diagnosis of the first case imported to Korea, the median number of patients becomes 7, and the maximum, 20. If the first imported case is missed and the government interim policy is not activated until 2 cases of secondary infection are determined, the median number of patients is estimated at 15, and the maximum, at 35.
Timely and rigorous confirmation of the diagnosis is important to reduce the spreading scale of infection when a new communicable disease is imported into Korea. Moreover, it is imperative to strengthen the local surveillance system and diagnostic protocols to avoid missing cases of secondary infection.
Keywords: Ebola virus disease, Mathematical model, Stochastic simulation, Intervention strategy, Republic of Korea
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