• 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 Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.2
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• pp.117-123
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• 2022

Currently the number of COVID-19 cases is increasing rapidly around the world. One way to restrict the spread of COVID-19 infection is to find confirmed cases using rapid diagnosis. The previously proposed group testing problem assumed without measurement noise, but recently, false positive and false negative cases have occurred during COVID-19 testing. In this paper, we define the noisy group testing problem and analyze how much measurement noise affects the performance. In this paper, we show that the group testing system should be designed to be less susceptible to measurement noise when conducting group testing with a low positive rate of COVID-19 infection. And compared with other developed reconstruction algorithms, our proposed algorithm shows superior performance in noisy group testing.

• International Journal of Computer Science & Network Security
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• v.21 no.4
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• pp.93-102
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• 2021

The world is facing an unprecedented economic, social and political crisis with the spread of COVID-19. The Corona Virus (COVID-19) and its global spread have resulted in declaring a pandemic by the World Health Organization. The deadly pandemic of 21st century has spread its wings across the globe with an exponential increase in the number of cases in many countries. The developing and underdeveloped countries are struggling hard to counter the rapidly growing and widespread challenge of COVID-19 because it has greatly influenced the global economies whereby the underdeveloped countries are more affected by its devastating impacts, especially the life of the low-income population. Information and Communication Technology (ICT) were particularly useful in spreading key emergency information and helping to maintain extensive social distancing. Updated information and testing results were published on national and local government websites. Mobile devices were used to support early testing and contact tracing. The government provided free smartphone apps that flagged infection hotspots with text alerts on testing and local cases. The purpose of this research work is to provide an in depth overview of emerging technologies and recent ICT developments to combat COVID-19 Pandemic. Finally, the author highlights open challenges in order to give future research directions.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.33 no.1
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• pp.54-57
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• 2022

The coronavirus disease (COVID-19) by severe acute syndrome coronavirus-2 (SARS-CoV-2) occurs the unprecedented pandemic during recent two years and the WHO declared a global pandemic of COVID-19 in March 2020. The most common sampling sites in COVID-19 test are the oropharynx and nasopharynx. We recently encountered a total laryngectomee who had a positivity COVID-19 diagnostic test from the tracheostoma, on the other hand, false negativity from the nasal cavity. The meaning of this case is that accurate screening test could be achieved by performing a test through the tracheostoma as well as nasal cavity or oropharynx. We also would like to discuss the accurate testing methods of patients whose airflow has distorted due to surgery, the management method of these patients, and the need of further research in the COVID-19 pandemic period with relevant literature reviews.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.6
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• pp.445-451
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• 2021

Due to the recent spread and increasing damage of COVID-19, the most important measure to prevent infection is to find infected people early. Group testing which introduced half a century ago, can be used as a diagnostic method for COVID-19 and has become very efficient method. In this paper, we review the fundamental principles of existing group testing algorithms. In addition, the sparse signal reconstruction approach proposed by compressed sensing is improved and presented as a solution to group testing. Compressed sensing and group testing differ in computational methods, but are similar in that they find sparse signals. The our simulation results show the superiority of the proposed sparse signal reconstruction method. It is noteworthy that the proposed method shows performance improvement over other algorithms in the group testing schemes. It also shows performance improvement when finding a large number of defective samples.

• Journal of Medicine and Life Science
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• v.20 no.3
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• pp.107-114
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• 2023

Epidemiological control of coronavirus disease 2019 (COVID-19) is needed to estimate the infection period of confirmed cases and identify potential cases. The present study, targeting confirmed cases for which the time of COVID-19 symptom onset was disclosed, aimed to investigate the relationship between intervals (day) from symptom onset to testing the cycle threshold (CT) values of real-time reverse transcription-polymerase chain reaction. Of the COVID-19 confirmed cases, those for which the date of suspected symptom onset in the epidemiological investigation was specifically disclosed were included in this study. Interval was defined as the number of days from symptom onset (as disclosed by the patient) to specimen collection for testing. A locally weighted regression smoothing (LOWESS) curve was applied, with intervals as explanatory variables and CT values (CTR for RdRp gene and CTE for E gene) as outcome variables. After finding its non-linear relationship, a polynomial regression model was applied to estimate the 95% confidence interval values of CTR and CTE by interval. The application of LOWESS in 331 patients identified a U-shaped curve relationship between the CTR and CTE values according to the number of interval days, and both CTR and CTE satisfied the quadratic model for interval days. Active application of these results to epidemiological investigations would minimize the chance of failing to identify individuals who are in contact with COVID-19 confirmed cases, thereby reducing the potential transmission of the virus to local communities.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.1-9
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• 2022

The influence of information sensitivity during the COVID-19 pandemic on perceived risk and personal preventive behaviors of consumers in China had been investigated. The participants were Chinese individuals experiencing the pandemic as it happened. Participants voluntarily completed an online questionnaire to provide their COVID-19 information sensitivity, their perceived COVID-19 risk, preventive behavior and their respective age. Our study discovered that COVID-19 information sensitivity positively influence perceived risk and preventive behavior. Moreover, young individuals show higher levels of online information sensitivity, which influenced their personal protective behavior when compared to that of middle-aged and elderly participants. Furthermore, Perceived risk significantly affected preventive behaviors. The results of this study may assist the government and marketeers in comprehending information sensitivity which can affect consumers' protective behavior toward reducing COVID-19 infections.

• Journal of Preventive Medicine and Public Health
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• v.56 no.4
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• pp.377-383
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• 2023

Objectives: Korea and Japan have managed the spread of coronavirus disease 2019 (COVID-19) using markedly different policies, referred to as the "3T" and "3C" strategies, respectively. This study examined these differences to assess the roles of active testing and contact tracing as non-pharmaceutical interventions (NPIs). We compared the proportion of unlinked cases (UCs) and test positivity rate (TPR) as indicators of tracing and testing capacities. Methods: We outlined the evolution of NPI policies and investigated temporal trends in their correlations with UCs, confirmed cases, and TPR prior to the Omicron peak. Spearman correlation coefficients were reported between the proportion of UCs, confirmed cases, and TPR. The Fisher r-to-z transformation was employed to examine the significance of differences between correlation coefficients. Results: The proportion of UCs was significantly correlated with confirmed cases (r=0.995, p<0.001) and TPR (r=0.659, p<0.001) in Korea and with confirmed cases (r=0.437, p<0.001) and TPR (r=0.429, p<0.001) in Japan. The Fisher r-to-z test revealed significant differences in correlation coefficients between the proportion of UCs and confirmed cases (z=16.07, p<0.001) and between the proportion of UCs and TPR (z=2.12, p=0.034) in Korea and Japan. Conclusions: Higher UCs were associated with increases in confirmed cases and TPR, indicating the importance of combining testing and contact tracing in controlling COVID-19. The implementation of stricter policies led to stronger correlations between these indicators. The proportion of UCs and TPR effectively indicated the effectiveness of NPIs. If the proportion of UCs shows an upward trend, more testing and contact tracing may be required.

• Journal of Preventive Medicine and Public Health
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• v.53 no.3
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• pp.175-177
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• 2020

Public health doctors of Korea contributed significantly to massive coronavirus disease 2019 (COVID-19) testing. They were immediately dispatched to epicenters of the COVID-19 pandemic, and have run tests at screening centers, airport quarantines and hospitals. However, their expertise from in-field experience has been often neglected. It is time to reorganize public health doctor system to better prepare for future epidemics. Transforming and strengthening their roles as public health experts through systematic training is crucial.

• Journal of Korean Critical Care Nursing
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• v.16 no.2
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• pp.54-66
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• 2023

Purpose : Developing infection control capabilities during the COVID-19 pandemic was critical. This study aimed to develop a simulation program to control patients with COVID-19 in nursing students and examine the effects on COVID-19 knowledge, COVID-19 nursing intention, self-efficacy learning, and clinical performance. Methods : The study used nonequivalent control group pretest-posttest design. Sixty nursing students were recruited from two different colleges using purposive sampling. For the intervention group(n=30), the pretest was administered before the simulation program, involving six sessions of online lectures and simulation practices. Immediately, the posttest was conducted following the program. Results : COVID-19 knowledge (t=9.87, p <.001), COVID-19 nursing intention (t=4.45, p <.001), learning self-efficacy (t=6.49, p <.001), and clinical performance (t=6.77, p <.001) increased significantly after the program, revealing the positive effect of the COVID-19 infection control simulation program in nursing students. Conclusion : The results of the study and the curriculum may be used as practical evidence for COVID-19 infection control in nursing schools and medical institutions.