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.
Journal of the Korea Society of Computer and Information
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v.26
no.5
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pp.1-8
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2021
Coronavirus disease 2019 (COVID-19) has affected the world seriously. Every person is required for wearing a mask properly in a public area to prevent spreading the virus. However, many people are not wearing a mask properly. In this paper, we propose an efficient mask detection system. In our proposed system, we first detect the faces of input images using YOLOv5 and classify them as the one of three scene complexity classes (Simple, Moderate, and Complex) based on the number of detected faces. After that, the image is fed into the Faster-RCNN with the one of three ResNet (ResNet-18, 50, and 101) as backbone network depending on the scene complexity for detecting the face area and identifying whether the person is wearing the mask properly or not. We evaluated our proposed system using public mask detection datasets. The results show that our proposed system outperforms other models.
International Journal of Computer Science & Network Security
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v.24
no.3
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pp.59-70
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2024
Background: The COVID-19 pandemic (the form of coronaviruses) developed at the end of 2019 and spread rapidly to almost every corner of the world. It has infected around 25,334,339 of the world population by the end of September 1, 2020 [1] . It has been spreading ever since, and the peak specific to every country has been rising and falling and does not seem to be over yet. Currently, the conventional RT-PCR testing is required to detect COVID-19, but the alternative method for data archiving purposes is certainly another choice for public departments to make. Researchers are trying to use medical images such as X-ray and Computed Tomography (CT) to easily diagnose the virus with the aid of Artificial Intelligence (AI)-based software. Method: This review paper provides an investigation of a newly emerging machine-learning method used to detect COVID-19 from X-ray images instead of using other methods of tests performed by medical experts. The facilities of computer vision enable us to develop an automated model that has clinical abilities of early detection of the disease. We have explored the researchers' focus on the modalities, images of datasets for use by the machine learning methods, and output metrics used to test the research in this field. Finally, the paper concludes by referring to the key problems posed by identifying COVID-19 using machine learning and future work studies. Result: This review's findings can be useful for public and private sectors to utilize the X-ray images and deployment of resources before the pandemic can reach its peaks, enabling the healthcare system with cushion time to bear the impact of the unfavorable circumstances of the pandemic is sure to cause
It has been reported that some exercise could enhance the anti-viral antibody titers after vaccination including influenza and coronavirus disease 2019 vaccines. We developed SAT-008, a novel digital device, consists of physical activities and activities related to the autonomic nervous system. We assessed the feasibility of SAT-008 to boost host immunity after an influenza vaccination by a randomized, open-label, and controlled study on adults administered influenza vaccines in the previous year. Among 32 participants, the SAT-008 showed a significant increase in the anti-influenza antibody titers assessed by hemagglutination-inhibition test against antigen subtype B Yamagata lineage after 4 wk of vaccination and subtype B Victoria lineage after 12 wk (p<0.05). There was no difference in the antibody titers against subtype "A." The SAT-008 also showed significant increase in the plasma cytokine levels of IL-10, IL-1β, and IL-6 at weeks 4 and 12 after the vaccination (p<0.05). A new approach using the digital device may boost host immunity against virus via vaccine adjuvant-like effects.
The proliferation of health misinformation gained momentum amidst the outbreak of the novel coronavirus disease 2019 (COVID-19). People stuck in their homes, without work pressure, regardless of health concerns towards personal, family, or peer groups, consistently demanded information. People became engaged with misinformation while attempting to find health information content. This study used the content analysis method and analyzed 1,154 misinformation stories from four prominent signatories of the International Fact-Checking Network during the pandemic. The study finds the five main categories of misinformation related to the COVID-19 pandemic. These are 1) the severity of the virus, 2) cure, prevention, and treatment, 3) myths and rumors about vaccines, 4) health authorities' guidelines, and 5) personal and social impacts. Various sub-categories supported the content characteristics of these categories. The study also analyzed the emotional valence of health misinformation. It was found that misinformation containing negative sentiments got higher engagement during the pandemic. Positive and neutral sentiment misinformation has less reach. Surprise, fear, and anger/aggressive emotions highly affected people during the pandemic; in general, people and social media users warning people to safeguard themselves from COVID-19 and creating a confusing state were found as the primary motivation behind the propagation of misinformation. The present study offers valuable perspectives on the mechanisms underlying the spread of health-related misinformation amidst the COVID-19 outbreak. It highlights the significance of discerning the accuracy of information and the feelings it conveys in minimizing the adverse effects on the well-being of public health.
Objectives: This study investigated the impact of socioeconomic factors and sexual orientation-related attributes on the rates of coronavirus disease 2019 (COVID-19) vaccination and infection among men who have sex with men (MSM). Methods: A web-based survey, supported by the National Research Foundation of Korea, was conducted among paying members of the leading online portal for the lesbian, gay, bisexual, transgender, or queer and questioning (LGBTQ+) community in Korea. The study participants were MSM living in Korea (n=942). COVID-19 vaccination and infection were considered dependent variables, while sexual orientation-related characteristics and adherence to non-pharmacological intervention (NPI) practices served as primary independent variables. To ensure analytical precision, nested logistic regression analyses were employed. These were further refined by dividing respondents into 4 categories based on sexual orientation and disclosure (or "coming-out") status. Results: Among MSM, no definitive association was found between COVID-19 vaccination status and factors such as socioeconomic or sexual orientation-related attributes (with the latter including human immunodeficiency virus [HIV] status, sexual orientation, and disclosure experience). However, key determinants influencing COVID-19 infection were identified. Notably, people living with HIV (PLWH) exhibited a statistically significant predisposition towards COVID-19 infection. Furthermore, greater adherence to NPI practices among MSM corresponded to a lower likelihood of COVID-19 infection. Conclusions: This study underscores the high susceptibility to COVID-19 among PLWH within the LGBTQ+ community relative to their healthy MSM counterparts. Consequently, it is crucial to advocate for tailored preventive strategies, including robust NPIs, to protect these at-risk groups. Such measures are essential in reducing the disparities that may emerge in a post-COVID-19 environment.
Objectives: Comorbidities increase susceptibility to severe coronavirus disease 2019 (COVID-19) infections, but limited information has been published regarding human immunodeficiency virus (HIV) and COVID-19 co-infections. This study explored the relationships among socioeconomic characteristics, sexual behaviors, and COVID-19 infection rates among Korean men who have sex with men (MSM) who are also living with HIV. Methods: Data were collected through a web survey aimed at members of the largest gay portal site in Korea, supported by the National Research Foundation of Korea (n=1005). The primary independent variables included COVID-19-related vaccinations and sexual behaviors. The dependent variable was the incidence of COVID-19 infection among respondents during the pandemic. For statistical analysis, hierarchical multiple logistic regression was performed, controlling for potential confounding variables. Results: Model I indicated that older MSM were less likely to contract COVID-19 (adjusted odds ratio [aOR], 0.98; 95% confidence interval [CI], 0.96 to 0.99). Model II demonstrated that HIV-positive MSM were nearly twice as likely to be infected with COVID-19 compared to their HIV-negative counterparts (aOR, 1.97; 95% CI, 1.14 to 3.41). Furthermore, even after accounting for COVID-19 vaccination status in model III, HIV-positive MSM continued to show a higher risk of infection (aOR, 1.93; 95% CI, 1.12 to 3.35). Conclusions: The findings of this study indicate that HIV-positive MSM are at an increased risk of contracting COVID-19, even when their vaccination status is considered. Therefore, it is essential to prioritize the prevention of COVID-19 infections in HIV-positive individuals by administering appropriate antiretroviral therapy and ensuring adherence to public health guidelines.
It is analyzed that the energy pattern is affected by the social matters of the disease trend where the energy consumption has been reduced following the depression of the national economy. The campaign of social distance for the people has been done by voluntary or legally due to the epidemic of the Coronavirus Disease 2019 (COVID-19). Some economic stimulus policies have been done in some countries including the United States, South Korea, and some others. It is shown the susceptible, infectious, and recovered (SIR) modeling applied by system dynamics (SD) where the logical modeling is constructed with S, I, and R. Especially, the I is connected with Society including Population, Race, and Maturity. In addition, Economy and Politics are connected to Income, GDP, Resources, President, Popularity, Ruling Government, and Leadership. The graph shows the big jump on 2020 April when is the starting month of the S value multiplication. This shows the effect of the COVID-19 and its related post-pandemic trend. The trends of OECD and non-OECD are very similar and the effect of the virus hazards causes significantly to the economic depressions.
Ye Ji Kim;Hyun Mi Kang;In Young Yoo;Jae Won Yoo;Seong Koo Kim;Jae Wook Lee;Dong Gun Lee;Nack-Gyun Chung;Yeon-Joon Park;Dae Chul Jeong;Bin Cho
Pediatric Infection and Vaccine
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v.30
no.2
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pp.73-83
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2023
Purpose: This study aimed to investigate the viral load dynamics in children with underlying malignancies diagnosed with symptomatic coronavirus disease 2019 (COVID-19). Methods: This was a retrospective longitudinal cohort study of patients <19 years old with underlying hemato-oncologic malignancies that were diagnosed with their first symptomatic severe acute respiratory syndrome coronavirus 2 polymerase chain reaction (PCR)-confirmed COVID-19 infection during March 1 to August 30, 2022. Review of electronic medical records and telephone surveys were undertaken to assess the clinical presentations and transmission route of the patients. Thresholds of negligible likelihood of infectious virus was defined as E gene reverse transcription (RT)-PCR cycle threshold (Ct) value ≥25. Results: During the 6-month study period, a total of 43 children with 44 episodes of COVID-19 were included. Of the 44 episodes, the median age of the patients included was 8 years old (interquartile range [IQR], 4.9-10.5), and the most common underlying disease was acute lymphoid leukemia (n=30, 68.2%), followed by patients post-hematopoietic stem cell transplantation (n=8, 18.2%). Majority of the patients had mild COVID-19 (n=32, 72.7%), and three patients (7.0%) had severe/critical COVID-19. Furthermore, 2.3% (n=1) died of COVID-19 associated acute respiratory distress syndrome. The largest percentage of the patients showed E gene RT-PCR Ct value ≥25 between 15-21 days (n=13, 39.4%), followed by 22-28 days (n=10, 30.3%). In 15.2% (n=5), E gene RT-PCR Ct value remained <25 beyond 28 days after initial positive PCR. Refractory malignancy status (β, 67.0; 95% confidence interval, 7.0-17.0; P=0.030) was significantly associated with prolonged duration of E gene RT-PCR <25. A patient with prolonged duration of E gene RT-PCR Ct value <25 was suspected to have infectivity shown by the transmission of the virus to his mother at day 86 after his initial positive test. Conclusions: Children that acquire symptomatic COVID-19 during refractory malignancy state are at a high risk for prolonged shedding warranting PCR-based transmission precautions in this cohort of patients.
Rudi Alberts;Sze Chun Chan;Qian-Fang Meng;Shan He;Lang Rao;Xindong Liu;Yongliang Zhang
IMMUNE NETWORK
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v.22
no.3
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pp.22.1-22.25
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2022
Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndromecoronavirus-2 (SARS-CoV-2), has spread over the world causing a pandemic which is still ongoing since its emergence in late 2019. A great amount of effort has been devoted to understanding the pathogenesis of COVID-19 with the hope of developing better therapeutic strategies. Transcriptome analysis using technologies such as RNA sequencing became a commonly used approach in study of host immune responses to SARS-CoV-2. Although substantial amount of information can be gathered from transcriptome analysis, different analysis tools used in these studies may lead to conclusions that differ dramatically from each other. Here, we re-analyzed four RNA-sequencing datasets of COVID-19 samples including human bronchoalveolar lavage fluid, nasopharyngeal swabs, lung biopsy and hACE2 transgenic mice using the same standardized method. The results showed that common features of COVID-19 include upregulation of chemokines including CCL2, CXCL1, and CXCL10, inflammatory cytokine IL-1β and alarmin S100A8/S100A9, which are associated with dysregulated innate immunity marked by abundant neutrophil and mast cell accumulation. Downregulation of chemokine receptor genes that are associated with impaired adaptive immunity such as lymphopenia is another common feather of COVID-19 observed. In addition, a few interferon-stimulated genes but no type I IFN genes were identified to be enriched in COVID-19 samples compared to their respective control in these datasets. These features are in line with results from single-cell RNA sequencing studies in the field. Therefore, our re-analysis of the RNA-seq datasets revealed common features of dysregulated immune responses to SARS-CoV-2 and shed light to the pathogenesis of COVID-19.
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