• Journal of the Korean Data and Information Science Society
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• v.28 no.1
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• pp.57-66
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• 2017

SIR model (Kermack and McKendrik, 1927) is one of the most popular method to explain the spread of disease, In order to construct SIR model, we need to estimate transition rate parameter and recovery rate parameter. If we don't have any information of the two rate parameters, we should estimate using observed whole trajectory of pandemic of disease. Thus, with restricted observed data, we can't estimate rate parameters. In this research, we introduced Reed-Frost model (Andersson and Britton, 2000) to calculate the probability of infection in the early stage of pandemic with the restriction of data. When we have an initial number of susceptible and infected, and a final number of infected, we can apply Reed - Frost model and we can get the probability of infection. We applied the Reed - Frost model to the Vibrio cholerae pandemic data from Republic of the Cameroon and calculated the probability of infection at the early stage. We also construct SIR model using the result of Reed - Frost model.

• Journal of the Korea Society for Simulation
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• v.23 no.4
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• pp.31-39
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• 2014

Seasonal influenza epidemics cause 3 to 5 millions severe illness and 250,000 to 500,000 deaths worldwide each year. To prepare better controls on severe influenza epidemics, many studies have been proposed to achieve near real-time surveillance of the spread of influenza. Korea CDC publishes clinical data of influenza epidemics on a weekly basis typically with a 1-2-week reporting lag. To provide faster detection of epidemics, recently approaches using unofficial data such as news reports, social media, and search queries are suggested. Collection of such data is cheap in cost and is realized in near real-time. This research aims to develop regression models for early detecting the outbreak of the seasonal influenza epidemics in Korea with keyword query information provided from the Naver (Korean representative portal site) trend services for PC and mobile device. We selected 20 key words likely to have strong correlations with influenza-like illness (ILI) based on literature review and proposed a logistic regression model and a multiple regression model to predict the outbreak of ILI. With respect of model fitness, the multiple regression model shows better results than logistic regression model. Also we find that a mobile-based regression model is better than PC-based regression model in estimating ILI percentages.

• Journal of the Korean Dietetic Association
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• v.21 no.3
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• pp.215-226
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• 2015

The prevalence of obesity is increasing worldwide and has become a serious epidemic health problem. We developed the 'Change 10 Habits' educational program based on obesity treatment and dietary guidelines and examined its effects on customized nutrition education in mildly obese adults. The study was approved by the Institutional Review Board. Study subjects were excluded if they had several major diseases, if had consumed an anti-obesity drug, or if they practiced an obesity-related program within 30 days. The subjects (n=87, $25{\leq}BMI$ <30) were each exposed to the customized nutrition education program with four lessons according to the stage of the transtheoretical model (TTM). The stage-matched program was administered for 12 weeks and was run by a clinical dietitian. Overall, subjects who were in the precontemplation/contemplation stage at baseline made progress in the preparation and action/maintenance stage after 12 weeks (P<0.05). For 'Alcohol is consumed, up to 2 drinks per day', the proportion of subjects who belonged in the action/maintenance stage increased from 34.5% to 49.4% at 12 weeks. In addition, scores of all items significantly increased after the program (P<0.05). 'Chew more than 10 times and eat slowly' score significantly increased from $3.9{\pm}2.4$ to $5.8{\pm}2.3$ (P<0.05). In conclusion, behavioral stage-matched nutrition education using the 'Change 10 Habits' program was effective in improving eating behaviors and enhancing healthy lifestyles in mildly obese adults.

• Nutrition Research and Practice
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• v.8 no.2
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• pp.172-176
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• 2014

BACKGROUND/OBJECTIVES: Non-alcoholic fatty liver disease (NAFLD) is becoming an important public health problem as metabolic syndrome and type 2 diabetes have become epidemic. In this study we investigated the protective effect of Cordyceps militaris (C. militaris) against NAFLD in an obese mouse model. MATERIALS/METHODS: Four-week-old male ob/ob mice were fed an AIN-93G diet or a diet containing 1% C. militaris water extract for 10 weeks after 1 week of adaptation. Serum glucose, insulin, free fatty acid (FFA), alanine transaminase (ALT), and proinflammatory cytokines were measured. Hepatic levels of lipids, glutathione (GSH), and lipid peroxide were determined. RESULTS: Consumption of C. militaris significantly decreased serum glucose, as well as homeostasis model assessment for insulin resistance (HOMA-IR), in ob/ob mice. In addition to lowering serum FFA levels, C. militaris also significantly decreased hepatic total lipids and triglyceride contents. Serum ALT activities and tumor necrosis factor-${\alpha}$ (TNF-${\alpha}$) and interleukin-6 (IL-6) levels were reduced by C. militaris. Consumption of C. militaris increased hepatic GSH and reduced lipid peroxide levels. CONCLUSIONS: These results indicate that C. militaris can exert protective effects against development of NAFLD, partly by reducing inflammatory cytokines and improving hepatic antioxidant status in ob/ob mice.

• Journal of Preventive Medicine and Public Health
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• v.53 no.3
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• pp.158-163
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• 2020

Objectives: In the current early phase of the coronavirus disease 2019 (COVID-19) outbreak, Bali needs to prepare to face the escalation of cases, with a particular focus on the readiness of healthcare services. We simulated the future trajectory of the epidemic under current conditions, projected the impact of policy interventions, and analyzed the implications for healthcare capacity. Methods: Our study was based on the first month of publicly accessible data on new confirmed daily cases. A susceptible, exposed, infected, recovered (SEIR) model for COVID-19 was employed to compare the current dynamics of the disease with those predicted under various scenarios. Results: The fitted model for the cumulative number of confirmed cases in Bali indicated an effective reproduction number of 1.4. Interventions have decreased the possible maximum number of cases from 71 125 on day 86 to 22 340 on day 119, and have prolonged the doubling time from about 9 days to 21 days. This corresponds to an approximately 30% reduction in transmissions from cases of mild infections. There will be 2780 available hospital beds, and at the peak (on day 132), the number of severe cases is estimated to be roughly 6105. Of these cases, 1831 will need intensive care unit (ICU) beds, whereas the number of currently available ICU beds is roughly 446. Conclusions: The healthcare system in Bali is in danger of collapse; thus, serious efforts are needed to improve COVID-19 interventions and to prepare the healthcare system in Bali to the greatest extent possible.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.21 no.4
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• pp.77-89
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• 2013

The purpose of this study is to anticipate the air travel demands over the period of 164 months, from January 1997 to August 2010 using ARIMA-Intervention modeling on the selected sample data. The sample data is composed of the number of the passengers who in the domestic route for Jeju route. In the analysis work of this study, the past events which are assumed to have affected the demands for the air travel routes to Jeju in different periods were used as the intervention variables. The impacts of such variables were reflected in the presupposed demand. The intervention variables used in this study are, respectively, the World Cup event in 2002 (from May to June), 2003 SARS outbreak (from April to May), Tsunami in January 2005, and the influenza outbreak from October to December 2009. The result of the above mentioned analysis revealed that the negative intervention events, like a global outbreak of an epidemic did have negative impact on the air travel demands in a risk aversion by the users of the aviation services. However, in case of the negative intervention events in limited area, where there are possible substituting destinations for the tourists, the impact was positive in terms of the air travel demands for substituting destinations due to the rational expectation of the users as they searched for other options. Also in this study, it was discovered that there is not a binding correlation between a nation wide mega-event, such as the World Cup games in 2002, and the increased air travel demands over a short-term period.

• Journal of the Korea Society of Computer and Information
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• v.25 no.8
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• pp.189-196
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• 2020

In this paper, we propose a study on the purchasing intent of the new e-commerce consumer, the coronavirus may once again drive the structural change of China's economy, and the new online marketing model will be noticed during the epidemic. Through 438 questionnaires collected on the Internet, frequency analysis, element analysis, reliability analysis and structural equation analysis were performed using SPSS V22.0 and AMOS V22.0 methods. Study the validation of hypotheses in the model to reveal the reasons why consumers in the new e-business are exposed. The results show that e-commerce features of Internet celebrities and individual characteristics of Internet celebrities can only enhance consumers' satisfaction. Quasi social relationships only increase consumer satisfaction without generating the will to purchase directly. Consumer satisfaction is the core foundation that dominates long-term consumption. E-commerce should focus on the ability of online celebrities to sell their expertise and the adaptability of value and product characteristics when conducting online celebrity marketing.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.24 no.5
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• pp.443-454
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• 2021

Purpose: Due to the increasing prevalence of obesity worldwide, non-alcoholic fatty liver disease (NAFLD) has reached epidemic dimensions over time. NAFLD is the most common cause of childhood chronic liver disease. There is a relationship between NAFLD and oxidative stress. This study aims to investigate the changes in thiol/disulfide homeostasis parameters to determine the oxidant/antioxidant balance in obese rats with diet-induced NAFLD and healthy rats. Methods: Twelve Wistar albino rats were used in this study. Experimentally produced NAFLD obese rats (n=6) and healthy rats were compared. Experimental NAFLD model was created with a special fatty liver diet (Altromin^® C1063, Fatty Liver Diet, Exclusivet, Lage, Germany). The biochemical and histopathological features of the groups, as well as serum thiol/disulfide homeostasis parameters, were analyzed and compared. Results: In the experimentally induced NAFLD rat model, they gained more weight than the control group. Steatosis (at least grade 2) occurred in all rats fed with special fatty liver diet for 12 weeks. Histopathologically, no high-grade inflammation was observed in rats with experimental NAFLD after feeding a diet for 12 weeks. Results revealed that aspartate transaminase and alanine transaminase levels were high, albumin levels were low, oxidant stress parameters increased, and antioxidant thiol groups decreased. Conclusion: Experimental NAFLD is characterized by increased oxidant stress accompanying fatty tissue in the liver. Analysis of thiol/disulfide homeostasis parameters in NAFLD can be used in further studies to develop effective treatment options.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.154-168
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• 2021

COVID-19 has been spreading all around the world, and threatening global health. In this situation, identifying and isolating infected individuals rapidly has been one of the most important measures to contain the epidemic. However, the standard diagnosis procedure with RT-PCR (Reverse Transcriptase Polymerase Chain Reaction) is costly and time-consuming. For this reason, pooled testing for COVID-19 has been proposed from the early stage of the COVID-19 pandemic to reduce the cost and time of identifying the COVID-19 infection. For pooled testing, how many samples are tested in group is the most significant factor to the performance of the test system. When the arrivals of test requirements and the test time are stochastic, batch-service queueing models have been utilized for the analysis of pooled-testing systems. However, most of them do not consider the false-negative test results of pooled testing in their performance analysis. For the COVID-19 RT-PCR test, there is a small but certain possibility of false-negative test results, and the group-test size affects not only the time and cost of pooled testing, but also the false-negative rate of pooled testing, which is a significant concern to public health authorities. In this study, we analyze the performance of COVID-19 pooled-testing systems with false-negative test results. To do this, we first formulate the COVID-19 pooled-testing systems with false negatives as a batch-service queuing model, and then obtain the performance measures such as the expected number of test requirements in the system, the expected number of RP-PCR tests for a test sample, the false-negative group-test rate, and the total cost per unit time, using the queueing analysis. We also present a numerical example to demonstrate the applicability of our analysis, and draw a couple of implications for COVID-19 pooled testing.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.4
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• pp.29-38
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• 2022

The enormous sway of COVID-19 on the international financial market has been felt across the globe. The financial markets of Bangladesh have also been similarly affected by the global epidemic and experienced a significant increase in volatility. To scrutinise the connection between COVID-19 and the Dhaka Stock Exchange (DSE) indices' return and instability, this study uses data of the DSE from February 2014 to September 2021. A comparative examination of the return and instability of the stock indices of the DSE has also been done considering the outbreak of the current COVID-19 situation. After using the GJR-GARCH (1,1) model, this review uncovers that the outbreak of COVID-19 has a statistically positive noteworthy association with the DSE stock indices' instability, which increases the market's volatility. Traders' fear and the rising frequency of COVID-19 reported patients could cause this. Besides, according to this study, COVID-19 shows a substantial positive linkage with stock market returns that increases the market's return. An appealing valuation, lower interest rates in the banking channel, economic rebound following the closure to prevent coronavirus transmission, improved remittance inflows, and a return of export revenues could all have contributed to this outcome. In addition, the findings also reveal that all market indices are in a mean-reverting phase.