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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 government's 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 government's intervention policies as a difference between the data-fitted and uncontrolled transmission rate that is derived from the basic reproductive number, R 0 , 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. [ABSTRACT FROM AUTHOR]

In this paper, we developed a dynamic model of smoking-tuberculosis (TB) transmission in South Korea, and investigated the effects of control strategies on the number of incidence of TB using optimal control theory. Model parameters regarding TB and smoking are estimated through least-squares fitting to real data. We considered three TB controls (distancing, case-finding, and case-holding) and two smoking controls (distancing and quitting), in order to minimize the number of exposed and infectious individuals and the cost of control. Numerical simulations for the various control strategies highlight that implementing the smoking controls, not with TB controls, can effectively reduce the incidence of TB transmission. [ABSTRACT FROM AUTHOR]

Abstract: We have developed a dynamic model for tuberculosis (TB) transmission in South Korea using a SEIR model with the time-dependent parameters. South Korea ranked the highest TB incidence among members of the Organization for Economic Cooperation and Development (OECD) in 2005yr. The observed data from the Korea Center for Disease Control and Prevention (KCDC) shows a certain rise of active-TB incidence individuals after 2001yr. Because of this sudden jump, we have considered two different periods for best fitting the model: prior to 2001yr and posterior to 2001yr. The least-squares fitting has been used for estimating model parameters to the observed data of active-TB incidence. Our model agrees well with the observed data. In this work, we also propose optimal treatment strategies of TB model in South Korea for the future. We have considered three control mechanisms representing distancing, case finding and case holding efforts. Optimal control programs have been proposed in various scenarios, in order to minimize the number of exposed and infectious individuals and the cost of implementing the control treatment. [Copyright &y& Elsevier]

The approved coronavirus disease (COVID-19) vaccines reduce the risk of disease by 70–95%; however, their efficacy in preventing COVID-19 is unclear. Moreover, the limited vaccine supply raises questions on how they can be used effectively. To examine the optimal allocation of COVID-19 vaccines in South Korea, we constructed an age-structured mathematical model, calibrated using country-specific demographic and epidemiological data. The optimal control problem was formulated with the aim of finding time-dependent age-specific optimal vaccination strategies to minimize costs related to COVID-19 infections and vaccination, considering a limited vaccine supply and various vaccine effects on susceptibility and symptomatology. Our results suggest that "susceptibility-reducing" vaccines should be relatively evenly distributed among all age groups, resulting in more than 40% of eligible age groups being vaccinated. In contrast, "symptom-reducing" vaccines should be administered mainly to individuals aged 20–29 and ≥60 years. Thus, our study suggests that the vaccine profile should determine the optimal vaccination strategy. Our findings highlight the importance of understanding vaccine's effects on susceptibility and symptomatology for effective public health interventions. [ABSTRACT FROM AUTHOR]

Green Credit Policy (GCP) in South Korea is an environmentally friendly regulation that enables manufacturers to reduce pollution by cooperating with suppliers. The main objective of this study is to investigate the impact of the GCP on manufacturers' efforts to reduce pollution in the supply chain. This study adopts an optimal control model that reflects the GCP's incentive scheme as well as consumers' environmental awareness. A numerical analysis is illustrated to demonstrate the applicability of our model. We find that manufacturers can create additional value by reducing their suppliers' pollution at the desirable levels. Furthermore, our finding suggests that manufacturers should strengthen their capability to reduce pollution to obtain more incentives under the GCP. [ABSTRACT FROM AUTHOR]