• The Journal of the Convergence on Culture Technology
• /
• v.7 no.4
• /
• pp.613-621
• /
• 2021

This study conducted a network analysis to determine how COVID-19 vaccine-related issue spread on Twitter during the introduction stage of the COVID-19. Issue diffusion tendency is analyzed according to the time period: phase 1 (initiation of vaccine introduction: March 7 - April 3, 2021), phase 2 (stagnant period of vaccination: April 4 - April 22, 2021), and phase 3 (increase of vaccination: April 23 - May 5, 2021). NodeXL was used for data collection and analysis. Daily Twitter network data were collected by entering search terms highly related to the COVID-19 vaccine. This study found that side effects-related opinions were repeatedly formed throughout the analysis period. As the vaccination rate increased and death cases were reported on media, death-related issues also emerged on Twitter. On the other hand, vaccine safety did not receive much attention on Twitter. The results of this study highlight the role of social media as a channel of issue diffusion when a national disaster strikes. We emphasize the need for the government to monitor public opinions on social media and reflect them in crisis communication strategies.

• Journal of Industrial Convergence
• /
• v.21 no.1
• /
• pp.175-185
• /
• 2023

Recently, novel viral infections such as COVID-19 have spread and pose a serious public health problem. In particular, these diseases have a fatal effect on the elderly, threatening life and causing serious social and economic losses. Accordingly, applications such as telemedicine, healthcare, and disease prevention using the Internet of Things (IoT) and artificial intelligence (AI) have been introduced in many industries to improve disease detection, monitoring, and quarantine performance. However, since existing technologies are not applied quickly and comprehensively to the sudden emergence of infectious diseases, they have not been able to prevent large-scale infection and the nationwide spread of infectious diseases in society. Therefore, in this paper, we try to predict the spread of infection by collecting various infection information with regional limitations through a virus disease information collector and performing AI analysis and severity matching through an AI broker. Finally, through the Korea Centers for Disease Control and Prevention, danger alerts are issued to the elderly, messages are sent to block the spread, and information on evacuation from infected areas is quickly provided. A realistic elderly support system compares the location information of the elderly with the information of the infected area and provides an intuitive danger area (infected area) avoidance function with an augmented reality-based smartphone application. When the elderly visit an infected area is confirmed, quarantine management services are provided automatically. In the future, the proposed system can be used as a method of preventing a crushing accident due to sudden crowd concentration in advance by identifying the location-based user density.

• Korean Journal of Clinical Laboratory Science
• /
• v.54 no.4
• /
• pp.265-272
• /
• 2022

The emergence and dissemination of carbapenemase-producing Enterobacteriaceae (CPE), particularly the Klebsiella pneumoniae carbapenemase-2 (KPC-2) producing Klebsiella pneumoniae, has been rapidly increasing worldwide and is becoming a serious public health threat. Since the epidemiology and characteristics of these KPC-2-producing K. pneumoniae vary according to the region and period under consideration, this study investigated the prevalence of carbapenemases and the epidemiological relationship of 78 carbapenem-resistant K. pneumoniae (CRKP) isolated from a tertiary hospital in Daejeon, from March 2017 to December 2020. The antimicrobial susceptibility tests were identified using the disk-diffusion method. PCR and DNA sequencing were used to determine the carbapenemase genes. In addition, molecular epidemiology was performed by multilocus sequence typing (MLST). Among the 78 CRKP isolates, 35 isolates (44.9%) were carbapenemase-producing K. pneumoniae (CPKP) and the major carbapenemase type was KPC-2 (30 isolates, 85.7%). The New Delhi metallo-enzyme-1 (NDM-1) and NDM-5 were identified in 4 isolates (11.4%) and 1 isolate (2.9%), respectively. Multilocus sequence typing (MLST) analysis showed 10 sequence types (STs) and the most prevalent ST was ST307 (51.4%, 18/35). All the ST307 isolates were KPC-2-producing K. pneumoniae and were multidrug-resistant (MDR). In addition, ST307 has gradually emerged during a four-year period. These findings indicate that continuous monitoring and proper infection control are needed to prevent the spread of KPC-2-producing K. pneumoniae ST307.

• Korean Journal of Clinical Laboratory Science
• /
• v.54 no.4
• /
• pp.249-255
• /
• 2022

Alzheimer's disease (AD) represents a major public health concern and has been identified as a research priority. Clinical research evidence supports that the core cerebrospinal fluid (CSF) biomarkers for AD, including amyloid-β (Aβ42), total tau (T-tau), and phosphorylated tau (P-tau), reflect key elements of AD pathophysiology. Nevertheless, advances in the clinical identification of new indicators will be critical not only for the discovery of sensitive, specific, and reliable biomarkers of preclinical AD pathology, but also for the development of tests that facilitate the early detection and differential diagnosis of dementia and disease progression monitoring. The early detection of AD in its presymptomatic stages would represent a great opportunity for earlier therapeutic intervention. The chance of successful treatment would be increased since interventions would be performed before extensive synaptic damage and neuronal loss would have occurred. In this study, the importance of developing an early diagnostic method using cognitive decline biomarkers that can discriminate between normal, mild cognitive impairment (MCI), and AD preclinical stages has been emphasized.