• Korean Journal of Clinical Laboratory Science
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• v.55 no.3
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• pp.143-150
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• 2023

The global outbreak of COVID-19 has underscored the pressing need for robust infection control practices in pulmonary function laboratories (PFL). However, the existing guidelines and regulatory frameworks provided by relevant authorities in the country have revealed certain deficiencies in effectively addressing this significant public health crisis. This study surveyed the infection control regulations, disposable item usage, ventilation facilities, spatial separation, and the configuration of entrance doors in 51 domestic hospital facilities from Oct 1, 2021, to Nov 2, 2021. The survey findings revealed that while there was a relatively satisfactory adherence to airborne, droplet, and contact precautions with adequate awareness and utilization of personal protective equipment, the environmental disinfection practices exhibited a suboptimal performance rate of 39.22% per patient. Depending on the specific survey domains, substantial variations were observed in the utilization of disposable items (81.05%), ventilation systems (45.75%), dedicated testing spaces (80.39%), separation of administrative areas (15.69%), and the installation of automated doors (19.61%). This study not only highlights the paramount importance of infection control in PFLs within domestic medical institutions but also provides foundational data for developing and enhancing standardized guidelines that align with international benchmarks for infection control in these settings.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.32 no.2
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• pp.111-115
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• 2022

Objectives: The purpose of this study is to verify whether droplet-induced propagation, the main route of infectious diseases such as COVID-19, can occur in semiconductor FAB (Fabrication), based on research results on general droplet propagation. Methods: Through data surveys droplet propagation was modeled through simulation and experimental case analysis according to general (without mask) and mask-wearing conditions, and the risk of droplet propagation was inferred by reflecting semiconductor FAB operation conditions (air current, air conditioning system, humidity, filter conditions). Results: Based on the results investigated to predict the possibility of spreading infectious diseases in semiconductor FAB, the total amount of droplet propagation (concentration), propagation distance, and virus life in FAB were inferred by reflecting the management parameter of semiconductor FAB. Conclusions: The total amount(concentration) of droplet propagation in the semiconductor fab is most affected by the presence or absence of wearing a mask and the line air dilution rate has some influence. when worn it spreads within 0.35~1m, and since the humidity is constant the virus can survive in the air for up to 3 hours. as a result the semiconductor fab is judged to be and effective space to block virus propagation due to the special environmental condition of a clean room.

• Pediatric Infection and Vaccine
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• v.14 no.1
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• pp.47-54
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• 2007

Purpose : Viral respiratory tract infection is most common cause for admission to hospital in children. There are many cases with elevated transaminase level in patients with viral lower respiratory tract infection (LRTI). The aim of this study was to compare indexes of disease severity such as duration of assisted ventilation, length of hospital stay and Respiratory Distress Assessment Instrument (RDAI) score in children with viral LRTI with and without elevated transaminase levels and to determine the etiology related to elevated transaminase levels in this patients group. Methods : Virological analysis was done from respiratory specimens obtained from patients with LRTI admitted to Kangnam Sacred Heart Hospital from Jan. 2003 to Jun. 2005. Viral diagnosis was made by isolation of viruses employing HEp-2 cell culture from nasopharyngeal aspiration. Medical records of children were reviewed retrospectively. We compared age, sex, RDAI score, Respiratory Rate (RR) score and mean duration of hospital stay between patients with elevated transaminase levels (Patient Group) and patients with normal transaminase levels (Control Group). Results : Viruses were isolated from 181 children with LRTI. 16 cases were excluded according to criteria. 28 cases (17.0%) had elevated transaminase levels (Patient group) and 137 cases (83.0%) had normal transaminase levels (Control group). There were no significant difference in duration of fever, RR score, RDAI score, incidence of $O_2$ inhalation and duration of hospital stay between patient group and control group. We found 17 (60.7%) cases of RSV, 4 cases (14.3%) of parainfluenza, 4 cases (14.3%) of influenza B virus, 3 cases (10.7%) of adenovirus and 1 case (3.6%) of influenza A virus infection in patient group and 78 cases (56.9%) of RSV, 28 cases (20.4%) of parainfluenza virus, 13 cases (9.5%) of influenza A virus, 9 cases (6.6%) of influenza B virus, 6 cases (4.4%) of adenovirus and 3 cases (2.2%) of coxsackie virus infection in control group. Conclusion : There were 28 cases (17.0%) with elevated transaminase level among patients with virus isolated LRTI. There was no relation between elevated transaminase level and severity of disease. The viral etiologies in two groups were not significantly different. There was no significant difference of age distribution between two groups.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.9
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• pp.387-398
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• 2023

The COVID-19 outbreak has significantly impacted human lifestyles and patterns. It was recommended to avoid face-to-face contact and over-crowded indoor places as much as possible as COVID-19 spreads through air, as well as through droplets or aerosols. Therefore, if a person who has contacted a COVID-19 patient or was at the place where the COVID-19 patient occurred is concerned that he/she may have been infected with COVID-19, it can be fully expected that he/she will search for COVID-19 symptoms on Google. In this study, an exploratory data analysis using deep learning models(DNN & LSTM) was conducted to see if we could predict the number of confirmed COVID-19 cases by summoning Google Trends, which played a major role in surveillance and management of influenza, again and combining it with data on the number of confirmed COVID-19 cases. In particular, search term frequency data used in this study are available publicly and do not invade privacy. When the deep neural network model was applied, Seoul (9.6 million) with the largest population in South Korea and Busan (3.4 million) with the second largest population recorded lower error rates when forecasting including search term frequency data. These analysis results demonstrate that search term frequency data plays an important role in cities with a population above a certain size. We also hope that these predictions can be used as evidentiary materials to decide policies, such as the deregulation or implementation of stronger preventive measures.