• International Journal of Advanced Culture Technology
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• v.10 no.1
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• pp.204-210
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• 2022

From the 1970s to the present, the number of new infectious diseases such as SARS, Ebola virus, and MERS has steadily increased. The new infectious disease, COVID-19, which began in Wuhan, Hubei Province, China, has pushed the world into a pandemic era. As a result, Countries imposed restrictions on entry to foreign countries due to concerns over the spread of COVID-19, which led to a decrease in the movement of tourists. Due to the restriction of travel, keywords such as "Corona blue" have soared and depression has increased. Therefore, this study aims to analyze the stress meaning network of the COVID-19 era to derive keywords and come up with a plan for a travel-related platform of the Post-COVID 19 era. This study conducted analysis of travel and stress caused by COVID-19 using TEXTOM, a big data analysis tool, and conducted semantic network analysis using UCINET6. We also conducted a CONCOR analysis to classify keywords for clustering of words with similarities. However, since we have collected travel and stress-oriented data from the start to the present, we need to increase the number of analysis data and analyze more data in the future.

• Atmosphere
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• v.32 no.1
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• pp.51-60
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• 2022

Corona Virus Disease 19 pandemic (COVID-19) causes many deaths worldwide, and has enormous impacts on society and economy. The COVID-19 was caused by a new type of coronavirus (Severe Acute Respiratory Syndrome Cornonavirus 2; SARS-CoV-2), which has been found that these viruses can be effectively inactivated by ultraviolet (UV) radiation of 290~315 nm. In this study, 90% inactivation time of the SARS-CoV-2 virus was analyzed using ground observation data from Brewer spectrophotometer at Yonsei University, Seoul and simulation data from UVSPEC for the period of 2015~2017 and 2020. Based on 12:00-13:00 noon time, the shortest virus inactivation time were estimated as 13.5 minutes in June and 4.8 minutes in July/August, respectively, under all sky and clear sky conditions. In the diurnal and seasonal variations, SARS-CoV-2 could be inactivated by 90% when exposed to UV radiation within 60 minutes from 10:00 to 14:00, for the period of spring to autumn. However, in winter season, the natural prevention effect was meaningless because the intensity of UV radiation weakened, and the time required for virus inactivation increased. The spread of infectious diseases such as COVID-19 is related to various and complex interactions of several variables, but the natural inactivation of viruses by UV radiation presented in this study, especially seasonal differences, need to be considered as major variables.

• Clinical and Experimental Pediatrics
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• v.64 no.5
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• pp.239-246
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• 2021

Background: The consequences of severe acute respiratory syndrome corona virus 2 on mother and fetus remain unknown due to a lack of robust evidence from prospective studies. Purpose: This study evaluated the effect of coronavirus disease 2019 (COVID-19) on neonatal outcomes and the scope of vertical transmission. Methods: This ambispective observational study enrolled pregnant women with COVID-19 in North India from April 1 to August 31, 2020 to evaluate neonatal outcomes and the risk of vertical transmission. Results: A total of 44 neonates born to 41 COVID-19-positive mothers were evaluated. Among them, 28 patients (68.3%) (2 sets of twins) were delivered within 7 days of testing positive for COVID-19, 23 patients (56%) (2 sets of twins) were delivered by cesarean section; 13 newborns (29.5%) had low birth weight; 7 (15.9%) were preterm; and 6 (13.6%) required neonatal intensive care unit admission, reflecting an increased incidence of cesarean delivery and low birth weight but zero neonatal mortality. Samples of cord blood, placental membrane, vaginal fluid, amniotic fluid, peritoneal fluid (in case of cesarean section), and breast milk for COVID-19 reverse transcription-polymerase chain reaction tested negative in 22 prospective delivery cases. Nasopharyngeal swabs of 2 newborns tested positive for COVID-19: one at 24 hours and the other on day 4 of life. In the former case, biological samples were not collected as the mother was asymptomatic and her COVID-19 report was available postdelivery; hence, the source of infection remained inconclusive. In the latter case, all samples tested negative, ruling out the possibility of vertical transmission. All neonates remained asymptomatic on follow-up. Conclusion: COVID-19 does not have direct adverse effects on the fetus per se. The possibility of vertical transmission is almost negligible, although results from larger trials are required to confirm our findings.

• Journal of Convergence for Information Technology
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• v.12 no.3
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• pp.66-74
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• 2022

This study identified the impact of information literacy, risk perception, crisis communication on preventive behaviors related to COVID-19 among nursing students. Data were collected from 187 nursing students from 25 June 2020 to 3 July 2020, and analyzed using the SPSS/WIN 26.0 program. As a result of regression analysis, the factors influencing prevention behaviors were crisis communication(β=0.30, p<.001), information literacy(β=0.29, p<.001), and risk perception(β=0.19, p=.004). The explanatory power of the model was 27%. This study suggests that the focus should be on improving the activating crisis communication process among individual, family and society, increasing information literacy and risk perception on crisis when developing program to improve COVID-19 preventive behaviors of nursing students experiencing clinical practice.

• Journal of Medicine and Life Science
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• v.19 no.2
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• pp.74-77
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• 2022

We present a fatal case of cerebral arterial thrombosis after corona virus disease 19 (COVID-19) vaccination with ChAdOx1 nCOV-19. The deceased was a 63-year-old woman with no relevant medical history. She presented symptoms of nausea, fatigue, and headache immediately after vaccination. Ten days after vaccination, she suddenly started vomiting and developed high blood pressure. The patient eventually died 23 days after vaccination. Autopsy findings showed that the cerebral arteries and internal carotid arteries were fully enlarged and were compacted with thrombi. The brain stem showed ischemic necrosis, and extravasation from this necrotic lesion led to focal subarachnoid hemorrhage around the brain stem where large blood clots still remained. No aneurysms or atherosclerotic changes were found in these arteries. We note the following three facts. Firstly, all symptoms occurred immediately after vaccination; secondly, the main cause of death was consistent with known side effects of the vaccine; and lastly, the mechanism of thrombus formation in this case goes beyond the general category of thrombogenesis known so far. While the authors know that this case does not fall into known categories of vaccine side effects, we presenting this case to demonstrate that a comprehensive review of various possibilities related to vaccine side effects is needed to establish a COVID-19 defense system.

• International journal of advanced smart convergence
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• v.9 no.4
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• pp.132-138
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• 2020

Worldwide, the number of corona virus disease 2019 (COVID-19) confirmed cases is rapidly increasing. Although vaccines and treatments for COVID-19 are being developed, the disease is unlikely to disappear completely. By attaching a smart sensor to the respirator worn by medical staff, Internet of Things (IoT) technology and artificial intelligence (AI) technology can be used to automatically detect the medical staff's infection symptoms. In the case of medical staff showing symptoms of the disease, appropriate medical treatment can be provided to protect the staff from the greater risk. In this study, we design and develop a system that detects cough, a typical symptom of respiratory infectious diseases, by applying IoT technology and artificial technology to respiratory protection. Because the cough sound is distorted within the respirator, it is difficult to guarantee accuracy in the AI model learned from the general cough sound. Therefore, coughing and non-coughing sounds were recorded using a sensor attached to a respirator, and AI models were trained and performance evaluated with this data. Mel-spectrogram conversion method was used to efficiently classify sound data, and the developed cough recognition system had a sensitivity of 95.12% and a specificity of 100%, and an overall accuracy of 97.94%.

• Journal of Industrial Convergence
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• v.19 no.3
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• pp.35-40
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• 2021

This study attempted to derive important factors of emerging infectious diseases by collecting and analyzing text data onto emerging infectious diseases. For this purpose, articles in the Naver News database were directly crawled, pre-processed, and used for data analysis. In addition, additional analysis was performed using Big Kinds. As a result of the priority analysis, the importance was shown in the order of corona, infectious disease, quarantine, vaccine, outbreak, virus, infection, and development. As a result of the proximity centrality analysis, the importance was shown in the order of government, death, and plan, and the analysis result of Big Kinds showed that Covid-19 and the Korea Centers for Disease Control and Prevention were important. Based on the results of this study, it can be said that the government's policy support is needed to raise public awareness of new infectious diseases, prevent disease, and develop vaccines and treatments.

• The Journal of Information Systems
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• v.29 no.4
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• pp.123-135
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• 2020

Purpose The purpose of this study is to investigate the development process and the effectiveness of the EISS (epidemiological investigation support system), which prevents the spread of infectious diseases like a novel corona virus disease, COVID-19. Design/methodology/approach This study identified the existing epidemiological support system for MERS through prior research and studied the case of the development of a newly developed epidemiological support system based on cloud computing infrastructure for COVID-19 through inter-ministerial collaboration in 2020. Findings The outbreak of COVID-19 drove the Korean Government began the development of the EISS with private companies. This system played a significant role in flattening the spread of infection during several waves in which the number of confirmed cases increased rapidly in Korea, However, we need to be careful in handling confirmed patients' private data affecting their privacy.

• Journal of Physiology & Pathology in Korean Medicine
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• v.36 no.5
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• pp.147-154
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• 2022

In order to secure practising rapid pattern(證, zheng) differentiation against acute infectious diseases like corona virus disease-19(COVID-19) showing rapid variation and contagion, a simplified classification of stages centering on the exterior-interior pattern identification with 2 step-subdivision by cold, heat, deficiency, excess pattern and pathogens is proposed. Pattern differentiation by compound patterns of 8 principles is made for the non-severe stage of general cold and the early mild stage of epidemic disease. Compound pattern's names of 8 principles about external infectious diseases are composed of three stages, that is disease site-characters-etiology. Based on early stage symptoms of fever or chilling etc., exterior, interior and half exterior and half interior patterns are determined first, and then cold, heat, deficiency, excess patterns of exterior and interior pattern respectively are determined, and then more concrete differentiation on pathogens of wind, dryness, dampness and dearth of qi, blood, yin, yang accompanied with constitutional and personal illness factors. Summarizing above descriptions, 4 patterns of exterior cold, exterior heat, exterior deficiency, exterior excess and their secondary compound patterns of exterior cold deficiency and exterior cold excess and so on are classified together with treatment method and available decoction for a standard measure of eight principle pattern differentiation.

• Safety and Health at Work
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• v.13 no.3
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• pp.269-278
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• 2022

Background: PTSD (Post-traumatic stress disorder, PTSD) had a great impact on health care workers during the COVID-19 (Corona Virus Disease 2019, COVID-19). Better knowledge of the prevalence of PTSD and its risk factors is a major public health problem. This study was conducted to assess the prevalence and important risk factors of PTSD among medical staff during the COVID-19. Methods: The databases were searched for studies published during the COVID-19, and a PRISMA (preferred reporting items for systematic review and meta-analysis) compliant systematic review (PROSPERO-CRD 42021278970) was carried out to identify articles from multiple databases reporting the prevalence of PTSD outcomes among medical staff. Proportion random effect analysis, I² statistic, quality assessment, subgroup analysis, and sensitivity analysis were carried out. Results: A total of 28 cross-sectional studies and the PTSD results of doctors and nurses were summarized from 14 and 27 studies: the prevalences were 31% (95% CI [confidence interval, CI]: 21%-40%) and 38% (95% CI: 30%-45%) in doctors and nurses, respectively. The results also showed seven risks (p < 0.05): long working hours, isolation wards, COVID-19 symptoms, nurses, women, fear of infection, and pre-existing mental illness. Two factors were of borderline significance: higher professional titles and married. Conclusion: Health care workers have a higher prevalence of PTSD during COVID-19. Health departments should provide targeted preventive measures for medical staff away from PTSD.