The recent spread of novel and highly variant pathogenic viruses, including the coronavirus (SARS-CoV-2), has increased the demand for diagnostic testing for rapid confirmation. This has resulted in investigating the functional capability of each space, and preparing facility guidelines to secure the safety of medical technologists. During viral evaluations, there is a requirement of negative pressure facilities along with thread separation, during pre-treatment of samples and before nucleic acid amplification. Space composition therefore needs to be planned by considering unidirectional air flow. This classification of safety management facilities is designated as biosafety level 2, and personal protective equipment is placed accordingly. In case of handling dangerous materials, they need to be carried out of the biosafety cabinet, and sterilizers are required for suitable disposal of infectious agents. A common feature of domestic laboratories is maintenance of the sample pre-treatment space at a negative pressure of -2.5 Pa or less, and arranging separate pre-treatment and reagent preparation spaces during the test process. We believe that the data generated in this study is meaningful, and offers an efficient direction and detailed flow for separation of the inspection process and space functions. Moreover, this study introduces construction of the laboratory by applying the safety management standards.
After the outbreak of the SARS-CoV2 virus that causes COVID-19, it spreads around the world with the number of infections and deaths rising rapidly caused a shortage of medical resources. As a way to solve this problem, chest X-ray diagnosis using Artificial Intelligence(AI) received attention as a primary diagnostic method. The purpose of this study is to comprehensively analyze the detection of COVID-19 via AI. To achieve this purpose, 292 studies were collected through a series of Classification methods. Based on these data, performance measurement information including Accuracy, Precision, Area Under Cover(AUC), Sensitivity, Specificity, F1-score, Recall, K-fold, Architecture and Class were analyzed. As a result, the average Accuracy, Precision, AUC, Sensitivity and Specificity were achieved as 95.2%, 94.81%, 94.01%, 93.5%, and 93.92%, respectively. Although the performance measurement information on a year-on-year basis gradually increased, furthermore, we conducted a study on the rate of change according to the number of Class and image data, the ratio of use of Architecture and about the K-fold. Currently, diagnosis of COVID-19 using AI has several problems to be used independently, however, it is expected that it will be sufficient to be used as a doctor's assistant.
Lee, Mu Ha;Park, Hye Ran;Chang, Jae Chil;Park, Hyung Ki;Lee, Gwang Soo
Journal of Korean Neurosurgical Society
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v.65
no.5
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pp.741-750
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2022
Objective : In March 2020, World Health Organization declared a global pandemic caused by a novel coronavirus (SARS-CoV-2). The disease caused by this virus is called COVID-19. Due to its high contagiousness, many changes have occurred in overall areas of our daily life including hospital use by patients. The aim of this study was to investigate the impact of COVID-19 on volume of spine surgery in South Korea using the National Health Insurance database and compare it with the volume of a homologous period before the pandemic. Methods : Data of related to spine surgery from January 2019 to April 2021 were obtained from the National Health Insurance and Health Insurance Review and Assessment Service database. Primary outcomes were total number of patients, rate of patients per 100000 population, and total number of procedures. The number of patients by hospital size was also analyzed. Results : COVID-19 outbreaks occurred in South Korea in March, August, and December of 2020. Compared to the previous year, the total number of patients who underwent spinal surgery showed a decrease for 2-3 months after the first and second outbreaks. However, it showed an increasing trend after the third outbreak. The same pattern was observed in terms of the ratio of the number of patients per 100000 population. Between 2019 and 2021, the mean number of spine surgeries per month tended to increase. Mean annual medical expenses increased over the years (p=0.001). When the number of spine surgeries was analyzed by hospital size, proportion of tertiary general hospital in 2021 increased compared to those in 2019 and 2020 (vs. 2019, p=0.012; vs. 2020, p=0.016). The proportion of general hospital was significantly decreased in 2020 compared to that in 2019 (p=0.037). Conclusion : After the COVID-19 outbreak, patients tended to postpone spinal surgery temporarily. The number of spinal surgeries decreased for 2-3 months after the first and second outbreaks. However, as the ability to respond to the COVID-19 pandemic at the hospital and society-wide level gradually increased, the number of spine surgeries did not decrease after the third outbreak in December 2020. In addition, the annual number of spine surgeries continued to increase. However, it should be noted that patients tend to be increasingly concentrated in tertiary hospitals for spinal surgery.
KSII Transactions on Internet and Information Systems (TIIS)
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v.16
no.6
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pp.2018-2043
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2022
Nowadays, COVID-19 infections are influencing our daily lives which have spread globally. The major symptoms' of COVID-19 are dry cough, sore throat, and fever which in turn to critical complications like multi organs failure, acute respiratory distress syndrome, etc. Therefore, to hinder the spread of COVID-19, a Computerized Doughty Predictor Framework (CDPF) is developed to yield benefits in monitoring the progression of disease from Chest CT images which will reduce the mortality rates significantly. The proposed framework CDPF employs Convolutional Neural Network (CNN) as a feature extractor to extract the features from CT images. Subsequently, the extracted features are fed into the Adaptive Dragonfly Algorithm (ADA) to extract the most significant features which will smoothly drive the diagnosing of the COVID and Non-COVID cases with the support of Doughty Learners (DL). This paper uses the publicly available SARS-CoV-2 and Github COVID CT dataset which contains 2482 and 812 CT images with two class labels COVID+ and COVI-. The performance of CDPF is evaluated against existing state of art approaches, which shows the superiority of CDPF with the diagnosis accuracy of about 99.76%.
Purpose: As SARS-CoV-2, which was the main cause of the global pandemic, has repeatedly mutated in various forms, the threat of the virus has decreased considerably, and the spread has also subsided. Therefore, the purpose of this study was to explore the change in the role of masks and sustainable mask consumption according to the change in perception of wearing masks during the pandemic. Research design, data and methodology: This study used a descriptive review method as a literature review, and utilized the literature search method in PubMed, Riss, Scopus, and Google Scholar databases. Among them, a total of 46 papers were selected in the final stage. Results: As a result, it can be seen that during the pandemic, masks changed their roles according to social trends as their perceptions changed from general perceptions of protecting from external environments or diseases to fashion items with quarantine functions. Conclusions: Masks will be continuously consumed as one of the fashion items with the function of quarantine that protects the respiratory tract from the external environment that is indispensable in our daily lives. Therefore, measures should be taken on sustainable consumption measures according to consumer demand for disposable masks.
Journal of Information Technology Applications and Management
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v.31
no.1
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pp.1-9
/
2024
Predicting the spread of COVID-19 remains a challenge due to the complexity of the disease and its evolving nature. This study presents an integrated approach using the classic SIR model for infectious diseases, enhanced by the chemical master equation (CME). We employ a Monte Carlo method (SSA) to solve the model, revealing unique aspects of the SARS-CoV-2 virus transmission. The study, a first of its kind in Korea, adopts a step-by-step and complementary approach to model prediction. It starts by analyzing the epidemic's trajectory at local government levels using both basic and stochastic SIR models. These models capture the impact of public health policies on the epidemic's dynamics. Further, the study extends its scope from a single-infected individual model to a more comprehensive model that accounts for multiple infections using the jump SIR prediction model. The practical application of this approach involves applying these layered and complementary SIR models to forecast the course of the COVID-19 epidemic in small to medium-sized local governments, particularly in Gangnam-gu, Seoul. The results from these models are then compared and analyzed.
In December 2019, the coronavirus disease 2019 (COVID-19) caused by the virus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in China and spread rapidly around the world, infecting millions of people. Cases of COVID-19 infection were observed to lead to viral pneumonia. Thirty-five patients admitted to the Gyeonggi Medical Center, South Korea, between November 2020 to January 2021, were found to have been infected with the influenza virus A and B, which cause symptoms similar to COVID-19. The records of these patients and those of COVID-19 patients who visited the hospital for medical examination were compared. The study patients included thirty patients with COVID-19 and/or influenza, five of those with influenza alone. A group of 121 patients without infection was used as control. Patients with COVID-19 and influenza had significantly higher lactate dehydrogenase levels than the patients with COVID-19 alone. The erythrocyte sedimentation rate (ESR) was higher in patients with COVID-19 alone than in other groups. Significant clinical outliers were observed in the COVID-19 and influenza infection group compared with the COVID-19 alone group. These results are expected to play an important role in the analysis of the hematological data of infected patients and the comparison of simultaneous and single infection data to determine clinical symptoms and other signs. These results may also assist in the development of vaccines and treatments for COVID-19.
Journal of Physiology & Pathology in Korean Medicine
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v.34
no.6
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pp.309-318
/
2020
Besides respiratory infection, COVID-19 has many neurological symptoms not only loss of smell and taste but also fatigue and brain fog. But it is a challenge to treat the neurological symptoms especially of anosmia and ageusia. In order to search for the therapeutic methods, the geographical diversity and pathological mechanisms of the COVID-19 and two symptoms were investigated from the latest clinical studies. Because the environmental conditions of the monsoon climate zone of East Asia and the Mediterranean and Oceanic climate zone of Italy, Britain, United States and tropical Brazil are different, each of diverse etiology and internal milieu should be considered differently in the treatment. SARS-CoV-2 exhibits the dampness-like characteristics and the olfactory and gustatory disorders are particularly more common than other flu or cold. and it tends to show features of damaging the lung qi of olfaction and heart-spleen qi of gustation. The mechanisms of olfactory and gustatory loss are various according to precursory, inflammatory, non-inflammatory and sequelar forms, so the therapeutic method should be designed for each period and pathology. If the process of inflammation arises from nasal and respiratory, olfactory epithelium to the central nervous structure by way of blood brain barrier, the treatment should be corresponded with the stage and depth of pathogen place. And if the olfactory loss is asymptomatic or in the initial stage, it can be applied intranasal topical scent therapy to relieve temporary locking of qi movement, but maybe also used in parallel together with herbs of relieving dampness toxin latent in the lung parenchyma.
Song, Gi Seon;Lee, You-Rim;Kim, Sungmin;Kim, Wontae;Choi, Jungwon;Yoo, Dahyeon;Yoo, Jungyoung;Jang, Kyung-Tae;Lee, Jaewang;Jun, Jin Hyun
Korean Journal of Clinical Laboratory Science
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v.52
no.3
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pp.284-295
/
2020
In December 2019, the first coronavirus disease- 2019 (COVID-19) patient was reported in Wuhan, Hubei Province, China. Since then, the number of patients who suffered severe acute respiratory syndrome caused by the novel Coronavirus (SARS-CoV-2 or 2019-nCoV) has increased dramatically in Korea. This new variant virus induces pulmonary diseases, including cough, sore throat, rhinorrhea, dyspnea, and pneumonia. Because SARS-CoV-2 is an RNA virus, real-time reverse-transcriptase PCR has been used widely to diagnose COVID-19. As the Korea Centers for Disease Prevention and Control (KCDC) and Ministry of Food & Drug Safety (MFDS) approved emergency use authorization, clinical specimens collected from COVID-19 patients and even healthy people have been clinically diagnosed by laboratory medicine. Based on a literature search, this paper reviews the epidemiology, symptoms, molecular diagnostics approved by KCDC, a current diagnosis of COVID-19 in the laboratories, the difference between molecular and serological diagnosis, and guidelines for clinical specimens. In addition, the Korean guidelines of biosafety for clinical laboratory scientists are evaluated to prevent healthcare-associated infection. The author's experience and lessons as clinical laboratory scientists will provide valuable insights to protect the domestic and international health community in this COVID-19 pandemic around the world.
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.
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