title: A dynamic compartmental model for the Middle East respiratory syndrome outbreak in the Republic of Korea: A retrospective analysis on control interventions and superspreading events.
abstract: The 2015 Middle East respiratory syndrome (MERS) outbreak in the Republic of Korea has provided an opportunity to improve our understanding of the spread of MERS linked to healthcare settings. Here we designed a dynamic transmission model to analyze the MERS outbreak in the Republic of Korea based on confirmed cases reported during the period May 20-July 4, 2015. Our model explicitly incorporates superspreading events and time-dependent transmission and isolation rates. Our model was able to provide a good fit to the trajectory of the outbreak and was useful to analyze the role of hypothetical control scenarios. Specifically, we assessed the impact of the timing of control measures, especially associated with a reduction of the transmission rate and diagnostic delays on outbreak size and duration. Early interventions within 1week after the epidemic onset, for instance, including the initial government announcement to the public about the list of hospitals exposed to MERS coronavirus (MERS-CoV), show a promising means to reduce the size (>71%) and duration (>35%) of the MERS epidemic. Finally, we also present results of an uncertainty analysis focused on the role of superspreading events.
authors: Department of Mathematics, Konkuk University, Seoul 05029, Republic of Korea. Electronic address: jack9872@konkuk.ac.kr.
authors: Jonggul
authors: J
authors: Lee
authors: School of Public Health, Georgia State University, Atlanta, GA, USA; Division of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, MD, USA. Electronic address: gchowell@gsu.edu.
authors: Gerardo
authors: G
authors: Chowell
authors: Department of Mathematics, Konkuk University, Seoul 05029, Republic of Korea. Electronic address: junge@konkuk.ac.kr.
authors: Eunok
authors: E
authors: Jung
mesh_terms: D018352:Coronavirus Infections / Q000453:epidemiology* / Q000517:prevention & control; D004196:Disease Outbreaks / Q000517:prevention & control / Q000706:statistics & numerical data*; D006801:Humans; D008954:Models, Biological; D056910:Republic of Korea; D012189:Retrospective Studies; D013997:Time Factors
keywords: Infectious diseases; MERS; Mathematical modeling; Nosocomial infections; Republic of Korea; Superspreader