Emerging infectious diseases have risen sharply due to population growth, urbanization, travel, trade, and environmental changes, with outbreaks like severe acute respiratory syndrome, Middle East respiratory syndrome, and coronavirus disease 2019 highlighting the global need for effective surveillance systems. Various infectious disease surveillance systems are applied depending on the surveillance objectives, target populations, and geographical scope. While Korea has a robust surveillance system, challenges remain in integrating data, enhancing coordination, and improving response efficiency. This article reviews the types and roles of infectious disease surveillance systems through a literature review and proposes strategies for improving Korea’s surveillance system by comparing it with those of other countries, including the World Health Organization (WHO). To strengthen Korea’s surveillance framework, a comprehensive strategy should be implemented to interconnect multiple surveillance mechanisms and enhance real-time data sharing. A centralized data platform must integrate these systems, leveraging artificial intelligence and big data analytics for faster outbreak analysis. International collaboration through data-sharing networks with the WHO, European Center for Disease Prevention and Control, and U.S Centers for Disease Control and Prevention is essential, along with standardized reporting formats to improve interoperability.

Emerging infectious diseases have risen sharply due to population growth, urbanization, travel, trade, and environmental changes, with outbreaks like severe acute respiratory syndrome, Middle East respiratory syndrome, and coronavirus disease 2019 highlighting the global need for effective surveillance systems. Various infectious disease surveillance systems are applied depending on the surveillance objectives, target populations, and geographical scope. While Korea has a robust surveillance system, challenges remain in integrating data, enhancing coordination, and improving response efficiency. This article reviews the types and roles of infectious disease surveillance systems through a literature review and proposes strategies for improving Korea’s surveillance system by comparing it with those of other countries, including the World Health Organization (WHO). To strengthen Korea’s surveillance framework, a comprehensive strategy should be implemented to interconnect multiple surveillance mechanisms and enhance real-time data sharing. A centralized data platform must integrate these systems, leveraging artificial intelligence and big data analytics for faster outbreak analysis. International collaboration through data-sharing networks with the WHO, European Center for Disease Prevention and Control, and U.S Centers for Disease Control and Prevention is essential, along with standardized reporting formats to improve interoperability.

Emerging infectious diseases have risen sharply due to population growth, urbanization, travel, trade, and environmental changes, with outbreaks like severe acute respiratory syndrome, Middle East respiratory syndrome, and coronavirus disease 2019 highlighting the global need for effective surveillance systems. Various infectious disease surveillance systems are applied depending on the surveillance objectives, target populations, and geographical scope. While Korea has a robust surveillance system, challenges remain in integrating data, enhancing coordination, and improving response efficiency. This article reviews the types and roles of infectious disease surveillance systems through a literature review and proposes strategies for improving Korea’s surveillance system by comparing it with those of other countries, including the World Health Organization (WHO). To strengthen Korea’s surveillance framework, a comprehensive strategy should be implemented to interconnect multiple surveillance mechanisms and enhance real-time data sharing. A centralized data platform must integrate these systems, leveraging artificial intelligence and big data analytics for faster outbreak analysis. International collaboration through data-sharing networks with the WHO, European Center for Disease Prevention and Control, and U.S Centers for Disease Control and Prevention is essential, along with standardized reporting formats to improve interoperability.

Emerging infectious diseases have risen sharply due to population growth, urbanization, travel, trade, and environmental changes, with outbreaks like severe acute respiratory syndrome, Middle East respiratory syndrome, and coronavirus disease 2019 highlighting the global need for effective surveillance systems. Various infectious disease surveillance systems are applied depending on the surveillance objectives, target populations, and geographical scope. While Korea has a robust surveillance system, challenges remain in integrating data, enhancing coordination, and improving response efficiency. This article reviews the types and roles of infectious disease surveillance systems through a literature review and proposes strategies for improving Korea’s surveillance system by comparing it with those of other countries, including the World Health Organization (WHO). To strengthen Korea’s surveillance framework, a comprehensive strategy should be implemented to interconnect multiple surveillance mechanisms and enhance real-time data sharing. A centralized data platform must integrate these systems, leveraging artificial intelligence and big data analytics for faster outbreak analysis. International collaboration through data-sharing networks with the WHO, European Center for Disease Prevention and Control, and U.S Centers for Disease Control and Prevention is essential, along with standardized reporting formats to improve interoperability.

The definition of faculty development has been refined and expanded over the past few decades, and various definitions have been used in higher education. Initially, faculty development was defined as activities that help teachers improve teaching skills, design better curricula, and improve the organizational environment for education. Since then, as the focus of faculty development has shifted from individual professors to institutional needs, faculty development is now defined as the personal and professional development of professors, clinicians, researchers, and managers to meet institutional goals, visions, and missions in social terms and moral responsibility to the community. Faculty development in medical education is universally needed to recognize and cope with widespread changes in education, including the traditional role of professors, advances in pedagogical theory, changes in learning styles, innovative curriculum models, and evaluation philosophy. However, critics have pointed out that most universities could not actively implement faculty development or accept professors’ various demands. In this paper, various reports related to faculty development are reviewed to summarize how faculty development has progressed and present future directions for accepting various opinions to improve educational excellence and the quality of health care.

Purpose: The expertise of medicians in clinical decision-making is very important since it improves the quality of medical services provided to patients. This study analyzed the characteristics of the decision-making process and confirmed clinicians’ electroencephalography (EEG) characteristics by measuring their cerebral activity during clinical decision-making. This study aims to present learning directions for brain-based clinical decision-making to develop medical experts. Methods: This study was performed in the following two projects: (1) a qualitative study of clinical decision-making in a clinical scenario and (2) an analysis of differences in cortical activity of experts and novices through EEG. Results: In the 1st study, this study found that “confirmation of the patient’s chief complaints,” “physical examination,” and “radiography reading” steps, which showed the most prominent differences in the experts’ and novices’ decision making, were set as the significant steps of dentists’ clinical decision making. In the 2nd study, the experts’ and novices’ cortical activities were measured through a 32-channel EEG. In task 6, which had the lowest accuracy of diagnoses made by the experts, the brain activities in both groups were higher than in other tasks. Conclusion This study developed and suggested a model of the decision-making process for experts and novices and suggested the basic directions for brain-based learning needed to raise experts based on brain activity.

This study evaluated the consistency between two quantitative fit test devices with different methods of ambient aerosol counting. Three types of respirators (N95, half mask, and full facepiece) were worn by 50 participants (male, n = 25; female, n = 25), PortaCount (Pro+ 8038) and MT (05U) were connected to one probe to one mask, and fit factors (FFs) were measured simultaneously with the original and modified protocols. As a result of comparing MT FFs with PortaCount FFs as references and by applying for the pass/fail criteria (FF = 100), the consistency between the two devices for half masks and full facepieces was very high. N95 was somewhat weaker than the two type of respirators in the consistency; however, the correlation between the two devices was very strong (p < 0.0001). The results showed that an FF of 100 as measured by PortaCount was likely to be measured as 75 by the MT. Therefore, when performing the fit test for N95 using the MT and pass level of FF 100, a certain level of adjustment is necessary, whether end-user or putting a scaling factor by manufacturer.

Objectives: We investigated the impact of the coronavirus disease 2019 (COVID-19) pandemic on tuberculosis (TB) management in the Republic of Korea (ROK). Methods: This retrospective cross-sectional study used nationwide ROK TB notification data (98,346 cases) from 2017 to 2020. The median time from the onset of TB symptoms to treatment initiation and the compliance rates with the required timing for notification and individual case investigations were measured and compared across periods and regions affected by the COVID-19 epidemic. Results: TB diagnosis during the COVID-19 pandemic was delayed. The median time to TB treatment initiation (25 days) in 2020 increased by 3 days compared to that of the previous 3 years (22 days) (p<0.0001). In the outbreak in Seoul, Incheon, and Gyeonggi province during August, the time to TB diagnosis was 4 days longer than in the previous 3 years (p=0.0303). In the outbreak in Daegu and Gyeongbuk province from February to March 2020, the compliance rate with the required timing for individual case investigations was 2.2%p points lower than in other areas in 2020 (p=0.0148). For public health centers, the rate was 13%p lower than in other areas (80.3% vs. 93.3%, p=0.0003). Conclusion TB diagnoses during the COVID-19 pandemic in the ROK were delayed nationwide, especially for patients notified by public-private mix TB control hospitals. TB individual case investigations were delayed in regional COVID-19 outbreak areas (Daegu and Gyeongbuk province), especially in public health centers. Developing strategies to address this issue will be helpful for sustainable TB management during future outbreaks.

In 2017, the Korean government launched an unprecedentedly large-scaled latent tuberculosis infection (LTBI) screening project which covered more than a million individuals in congregate settings. A total of 1,047,689 participants of source population (n = 2,336,157) underwent LTBI testing from 2017 to 2018. The overall LTBI test uptake rate during this project was 44.8%. Workers in daycare centers (83.5%) and kindergartens (78.9%) showed high participation rate. A total of 1,012,206 individuals with valid results of interferongamma release assay (IGRA) were selected to constitute the IGRA cohort. Most of the enrolled participants in the IGRA cohort were in their working age. Approximately, threequarters of total enrolled population were female. Investigating the LTBI prevalence, stages of LTBI care cascade, natural history of LTBI, efficacy of LTBI treatment and cost-effectiveness of LTBI screening are feasible within this IGRA cohort.

In 2017, the Korean government launched an unprecedentedly large-scaled latent tuberculosis infection (LTBI) screening project which covered more than a million individuals in congregate settings. A total of 1,047,689 participants of source population (n = 2,336,157) underwent LTBI testing from 2017 to 2018. The overall LTBI test uptake rate during this project was 44.8%. Workers in daycare centers (83.5%) and kindergartens (78.9%) showed high participation rate. A total of 1,012,206 individuals with valid results of interferongamma release assay (IGRA) were selected to constitute the IGRA cohort. Most of the enrolled participants in the IGRA cohort were in their working age. Approximately, threequarters of total enrolled population were female. Investigating the LTBI prevalence, stages of LTBI care cascade, natural history of LTBI, efficacy of LTBI treatment and cost-effectiveness of LTBI screening are feasible within this IGRA cohort.