Jonggul Lee

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.

A spatial-temporal transmission model and early intervention policies of 2009 A/H1N1 influenza in South Korea.

We developed a spatial-temporal model of the 2009 A/H1N1 influenza pandemic in the Seoul metropolitan area (SMA), which is located in the north-west of South Korea and is the second-most complex metropolitan area worldwide. This multi-patch influenza model consists of a SEIAR influenza transmission model and flow model between two districts. This model is based on the daily confirmed cases of A/H1N1 influenza collected by the Korea Center for Disease Control and Prevention from April 27 to September 15, 2009 and the daily commuting data from 33 districts of SMA reported in the 2010 Population and Housing Census (PHC). We analyzed the spread patterns of 2009 influenza in the SMA by the reproductive numbers and geographic information systems. During the early period of novel influenza pandemics, when pharmaceutical interventions are lacking, non-pharmaceutical public health interventions will be the most critical strategies for impeding the spread of influenza and delaying an epidemic. Using the spatial-temporal model developed herein, we also investigated the impact of non-pharmaceutical public health interventions, isolation and/or commuting restrictions, on the incidence reduction in various scenarios. Our model provides scientific evidence for predicting the spread of disease and preparedness for a future pandemic.

Mathematical model of transmission dynamics and optimal control strategies for 2009 A/H1N1 influenza in the Republic of Korea

A mathematical model for the transmission dynamics of the 2009 A/H1N1 influenza epidemic in the Republic of Korea is developed. The simulation period is separated into three consecutive periods based on the governments intervention strategies: the nonpharmaceutical strategy is used during Period 1. The nonpharmaceutical and antiviral strategies are executed during Period 2 and the vaccine strategy is added during Period 3. During Period 1, we estimate the reduction in the transmission rate due to the governments intervention policies as a difference between the data-fitted and uncontrolled transmission rate that is derived from the basic reproductive number, R0, of the model without intervention. This quantified reduced transmission rate is used as an upperbound of the nonpharmaceutical control for studying optimal control strategies, which is a new approach for determining the realistic upperbound of control. In this study, we also explore the real-time prediction of incidence using the mathematical model during the early stage of the epidemic. We investigate the impact of vaccination coverage and timing with respect to the cumulative incidence. The result implies that early vaccination plays a significant role for preventing the epidemic.

Metapopulation model using commuting flow for national spread of the 2009 H1N1 influenza virus in the Republic of Korea

We study the spatial-temporal pattern of the spread of the 2009 H1N1 influenza virus using a metapopulation model linked by commuting flow based on the reported influenza cases during the early stages of the epidemic in the Republic of Korea. The spatial heterogeneities, such as the local reproductive number and peak time, are investigated at province level. Furthermore, we discuss the effect of early intervention strategies, isolation and commuting restrictions, on the reduction of incidence at each province level. A major finding of this study is that early intervention at the source area of infection is more effective than interventions at the commuting-hub areas if the cost is limited.

Continuous and discrete SIR-models with spatial distributions.

The SIR-model is a basic epidemic model that classifies a population into three subgroups: susceptible S, infected I and removed R. This model does not take into consideration the spatial distribution of each subgroup, but considers the total number of individuals belonging to each subgroup. There are many variants of the SIR-model. For studying the spatial distribution, stochastic processes have often been introduced to describe the dispersion of individuals. Such assumptions do not seem to be applicable to humans, because almost everyone moves within a small fixed radius in practice. Even if individuals do not disperse, the transmission of disease occurs. In this paper, we do not assume the dispersion of individuals, and instead use the infectious radius. Then, we propose simple continuous and discrete SIR-models that show spatial distributions. The results of our simulations show that the propagation speed and size of an epidemic depend on the population density and the infectious radius.

Evaluating the Number of Sickbeds During Ebola Epidemics Using Optimal Control Theory

Optimal control (OC) theory is a powerful tool to guide the design and implementation of control intervention strategies against epidemics. This technique defined control measures under a predetermined objective while minimizing the costs associated with the implementation of the control strategy. Here we use optimal control and epidemic modeling to explore the uncertainty in hospital bed capacity that would be needed to control an Ebola epidemic under different initial conditions, variation in the basic reproduction number, and associated costs to implement control measures. In particular, we focus on assessing the impact of effective isolation of infectious individuals in the health care setting because one key factor that facilitated the development of the Ebola epidemic in West Africa was the lack of public health surveillance systems to detect new outbreaks and the healthcare capacity that is needed to enforce infection control practices.

MULTIDIMENSIONAL OPEN SYSTEM FOR VALVELESS PUMPING

In this study, we present a multidimensional open system for valveless pumping (VP). This system consists of an elastic tube connected to two open tanks filled with a fluid under gravity. The two-dimensional elastic tube model is constructed based on the immersed boundary method, and the tank model is governed by a system of ordinary differential equations based on the work-energy principle. The flows into and out of the elastic tube are modeled in terms of the source/sink patches inside the tube. The fluid dynamics of this system is generated by the periodic compress-and-release action applied to an asymmetric region of the elastic tube. We have developed an algorithm to couple these partial differential equations and ordinary differential equations using the pressure-flow relationship and the linearity of the discretized Navier-Stokes equations. We have observed the most important feature of VP, namely, the existence of a unidirectional net flow in the system. Our computations are focused on the factors that strongly influence the occurrence of unidirectional flows, for example, the frequency, compression duration, and location of pumping. Based on these investigations, some case studies are performed to observe the details of the ow features.