• 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.

• Genomics & Informatics
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• v.19 no.3
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• pp.21.1-21.5
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• 2021

The use of social media data, like Twitter, for biomedical research has been gradually increasing over the years. With the coronavirus disease 2019 (COVID-19) pandemic, researchers have turned to more non-traditional sources of clinical data to characterize the disease in near-real time, study the societal implications of interventions, as well as the sequelae that recovered COVID-19 cases present. However, manually curated social media datasets are difficult to come by due to the expensive costs of manual annotation and the efforts needed to identify the correct texts. When datasets are available, they are usually very small and their annotations don't generalize well over time or to larger sets of documents. As part of the 2021 Biomedical Linked Annotation Hackathon, we release our dataset of over 120 million automatically annotated tweets for biomedical research purposes. Incorporating best-practices, we identify tweets with potentially high clinical relevance. We evaluated our work by comparing several SpaCy-based annotation frameworks against a manually annotated gold-standard dataset. Selecting the best method to use for automatic annotation, we then annotated 120 million tweets and released them publicly for future downstream usage within the biomedical domain.

• Journal of the Korean Regional Science Association
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• v.38 no.3
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• pp.41-49
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• 2022

This paper aimed at understanding the effect of infectious disease conditions on willingness to pay for the green roof implemented to reduce the urban heat island. For this purpose, the willingness to pay for the green roof under infectious disease and non-infectious disease conditions was calculated and comparatively analyzed using the contingent valuation method. As a result, there was a statistically significant difference in the willingness to pay according to the infectious disease condition, and it was confirmed that the willingness to pay for the infectious disease condition was lower than the non-infectious disease condition.

• Journal of Distribution Science
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• v.21 no.2
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• pp.111-118
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• 2023

After the outbreak of the COVID-19 in the early 2020, Korea has attempted to reinforce the existing rent controls to help the low-income households. From July 2000, the tenants' right of lease renewal came into effect, as a policy tool to enforce the upper bound percentage of rent increases within Korea. Purpose: This study aims to examine the impact of rent control on the uncontrolled rents in Seoul Metropolitan Area (SMA). Research design, data and methodology: The study regresses the monthly panel data from 58 municipalities in SMA from January 2020 to March 2022, during the COVID-19 pandemic. Results: The data indicates that the policy had the effect of lowering rents for a period of two months, and subsequently monetary policy including quantitative easing and low interest rates, coupled with asset market bubbles lead to rent increases. During the sample data period, the quantity of money supply increased by 12.6% and CPI rose by 3.0%, these phenomena collectively increased the rents by up to 14.7%. Conclusions: The results of the present study support the findings of earlier studies in part: namely, that rent control without the government's steps to stabilize the property price may have an undesirable effect on rental tenants.

• Korean journal of aerospace and environmental medicine
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• v.31 no.3
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• pp.61-63
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• 2021

In Vol. 31, No. 3, our journal prepared three review articles, an original paper, and two case reports. First, as COVID-19 continues for a long time, aviation workers, including pilots, are also experiencing mental problems such as depression. Therefore, we have compiled the basic principles for improving the mental health of pilots. Next, it is difficult to properly perform cardio-pulmonary resuscitation (CPR) when a cardiac arrest situation occurs in an aircraft. Moreover, in the context of the COVID-19 pandemic, CPR is more difficult because medical staff and other passengers may also be exposed to infections. Therefore, we have summarized the principles of CPR on board and ways to perform CPR while keeping the safety of medical staff and other passengers in the COVID-19 situation. The sudden change of gravity caused by space travel has various effects on the human body, and among them, the effect on the immune system is profound. Therefore, we reviewed the research methods to study the effect of gravity on the immune system and the results. In addition, we analyzed the demographic characteristics and health status of immigrant visa applicants who intended to immigrate to the United States over the past five years. Next, through two case reports, we reported cases of determining physical fitness for aviation service in patients who recovered after receiving appropriate treatment for chronic myeloid leukemia or renal cell carcinoma.

• Annual Conference of KIPS
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• 2021.11a
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• pp.823-826
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• 2021

The recent COVID-19 pandemic has accentuated the need for faster and more accurate ways of diagnosing certain diseases for there to be safer and more effective early responses that help to prevent a total outbreak. In this work, we would like to approach this issue through machine learning algorithms to investigate whether or not they could serve as a viable replacement for conventional diagnosis. Through a process of training and testing various algorithms, we analyzed how successfully they can predict a patient's COVID-19 diagnosis based on a list of symptoms and also identified which algorithm is the most effective at doing so. If the necessary data, containing the symptoms and diagnoses of different cases, is provided, this method can be utilized to make a probable diagnosis of any disease besides COVID-19. This method can be used in conjunction with or in lieu of conventional diagnosis depending on the situation: if there is a lack of testing facilities or test kits, this method can be employed as it is inexhaustible and it could also be used in situations where a conventional diagnosis is proven to be inaccurate.

• Journal of Korean Academy of Rural Health Nursing
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• v.18 no.2
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• pp.125-133
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• 2023

Purpose: This study aimed to understand and explore the experiences and meanings of life changes and loneliness caused by the coronavirus disease (COVID-19) among older people living in rural areas. Methods: This study adopted an individual interview approach. A total of 33 older adults were interviewed using semi-structured questions between October and December; 2020. The collected data were analyzed using thematic analysis. Results: Four main themes and ten sub-themes emerged. One main theme was "the never-ending anxiety of a changed world", the second theme was "disconnecting from the world through social distancing", the third theme was "working to overcome COVID-19", and forth "health is the most important thing in life." Conclusion: Based on the results of this study, we confirmed the urgent need for psycho-social support to relieve loneliness and social isolation of older people in rural areas during the spread of infectious diseases.

• Journal of Contemporary Eastern Asia
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• v.22 no.2
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• pp.18-38
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• 2023

This paper examines the Chinese government's response to four epidemic crises, including COVID-19, and analyzes the similarities and differences in these responses. It argues that while the Chinese government learned from previous epidemics and improved its handling of subsequent outbreaks, a significant variation occurred during the COVID-19 pandemic, which had a detrimental impact globally. Existing scholarly research on China's epidemic responses has often been limited in scope, focusing on individual crises and neglecting the central-local government relationship in crisis decision-making. By adopting a comprehensive approach, this paper delves into the nuanced dynamics of China's responses to these epidemics. It highlights the variations in responses, attributing them to the Chinese government's fear of undermined legitimacy and its consideration of its international image. The government's recognition of the importance of public perception and trust, both domestically and globally, has shaped its crisis management strategies. Through a detailed analysis of these factors, this paper contributes to a deeper understanding of the variations observed in China's epidemic responses. It emphasizes the significance of the central-local government relationship and the government's international image in determining its actions during epidemics. Recognizing these factors can provide policymakers and researchers with insights to shape future epidemic response strategies and foster effective global health governance.

• Asia pacific journal of information systems
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• v.32 no.4
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• pp.945-963
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• 2022

With the widespread use of social media, online social platforms like Twitter have become a place of rapid dissemination of information-both accurate and inaccurate. After the COVID-19 outbreak, the overabundance of fake information and rumours on online social platforms about the COVID-19 pandemic has spread over society as quickly as the virus itself. As a result, fake news poses a significant threat to effective virus response by negatively affecting people's willingness to follow the proper public health guidelines and protocols, which makes it important to identify fake information from online platforms for the public interest. In this research, we introduce an approach to detect fake news using deep learning techniques, which outperform traditional machine learning techniques with a 93.1% accuracy. We then investigate the content differences between real and fake news by applying topic modeling and linguistic analysis. Our results show that topics on Politics and Government services are most common in fake news. In addition, we found that fake news has lower analytic and authenticity scores than real news. With the findings, we discuss important academic and practical implications of the study.

• IMMUNE NETWORK
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• v.21 no.1
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• pp.10.1-10.13
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• 2021

The coronavirus disease 2019 (COVID-19) pandemic (severe acute respiratory syndrome coronavirus 2) is a global infectious disease with rapid spread. Some patients have severe symptoms and clinical signs caused by an excessive inflammatory response, which increases the risk of mortality. In this study, we reanalyzed scRNA-seq data of cells from bronchoalveolar lavage fluids of patients with COVID-19 with mild and severe symptoms, focusing on Ab-producing cells. In patients with severe disease, B cells seemed to be more activated and expressed more immunoglobulin genes compared with cells from patients with mild disease, and macrophages expressed higher levels of the TNF superfamily member B-cell activating factor but not of APRIL (a proliferation-inducing ligand). In addition, macrophages from patients with severe disease had increased pro-inflammatory features and pathways associated with Fc receptor-mediated signaling, compared with patients with mild disease. CCR2-positive plasma cells accumulated in patients with severe disease, probably because of increased CCL2 expression on macrophages from patients with severe disease. Together, these results support the hypothesis that different characteristics of B cells might be associated with the severity of COVID-19 infection.