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Jin Lee 2 Articles
2019 Tabletop Exercise for Laboratory Diagnosis and Analyses of Unknown Disease Outbreaks by the Korea Centers for Disease Control and Prevention
Il-Hwan Kim, Jun Hyeong Jang, Su-Kyoung Jo, Jin Sun No, Seung-Hee Seo, Jun-Young Kim, Sang-Oun Jung, Jeong-Min Kim, Sang-Eun Lee, Hye-Kyung Park, Eun-Jin Kim, Jun Ho Jeon, Myung-Min Choi, Boyeong Ryu, Yoon Suk Jang, Hwami Kim, Jin Lee, Seung-Hwan Shin, Hee Kyoung Kim, Eun-Kyoung Kim, Ye Eun Park, Cheon-Kwon Yoo, Sang-Won Lee, Myung-Guk Han, Gi-Eun Rhie, Byung Hak Kang
Osong Public Health Res Perspect. 2020;11(5):280-285.   Published online October 22, 2020
DOI: https://doi.org/10.24171/j.phrp.2020.11.5.03
  • 4,399 View
  • 97 Download
AbstractAbstract PDF
Objectives

The Korea Centers for Disease Control and Prevention has published “A Guideline for Unknown Disease Outbreaks (UDO).” The aim of this report was to introduce tabletop exercises (TTX) to prepare for UDO in the future.

Methods

The UDO Laboratory Analyses Task Force in Korea Centers for Disease Control and Prevention in April 2018, assigned unknown diseases into 5 syndromes, designed an algorithm for diagnosis, and made a panel list for diagnosis by exclusion. Using the guidelines and laboratory analyses for UDO, TTX were introduced.

Results

Since September 9th, 2018, the UDO Laboratory Analyses Task Force has been preparing TTX based on a scenario of an outbreak caused by a novel coronavirus. In December 2019, through TTX, individual missions, epidemiological investigations, sample treatments, diagnosis by exclusions, and next generation sequencing analysis were discussed, and a novel coronavirus was identified as the causal pathogen.

Conclusion

Guideline and laboratory analyses for UDO successfully applied in TTX. Conclusions drawn from TTX could be applied effectively in the analyses for the initial response to COVID-19, an ongoing epidemic of 2019 – 2020. Therefore, TTX should continuously be conducted for the response and preparation against UDO.

Development and Utilization of a Rapid and Accurate Epidemic Investigation Support System for COVID-19
Young Joon Park, Sang Yun Cho, Jin Lee, Ikjin Lee, Won-Ho Park, Seungmyeong Jeong, Seongyun Kim, Seokjun Lee, Jaeho Kim, Ok Park
Osong Public Health Res Perspect. 2020;11(3):118-127.   Published online May 20, 2020
DOI: https://doi.org/10.24171/j.phrp.2020.11.3.06
  • 10,164 View
  • 286 Download
  • 15 Citations
AbstractAbstract PDF
Objectives

In this pandemic situation caused by a novel coronavirus disease in 2019 (COVID-19), an electronic support system that can rapidly and accurately perform epidemic investigations, is needed. It would systematically secure and analyze patients’ data (who have been confirmed to have the infection), location information, and credit card usage.

Methods

The “Infectious Disease Prevention and Control Act” in South Korea, established a legal basis for the securement, handling procedure, and disclosure of information required for epidemic investigations. The Epidemic Investigation Support System (EISS) was developed as an application platform on the Smart City data platform.

Results

The EISS performed the function of inter-institutional communication which reduced the processing period of patients’ data in comparison to other methods. This system automatically marked confirmed cases’ tracking data on a map and hot-spot analysis which lead to the prediction of areas where people may be vulnerable to infection.

Conclusion

The EISS was designed and implemented for use during an epidemic investigation to prevent the spread of an infectious disease, by specifically tracking confirmed cases of infection.

Citations

Citations to this article as recorded by  
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    Journal of Primary Health Care.2021; 13(2): 116.     CrossRef
  • Contributions of Smart City Solutions and Technologies to Resilience against the COVID-19 Pandemic: A Literature Review
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    Sustainability.2021; 13(14): 8018.     CrossRef
  • Harnessing the Power of Smart and Connected Health to Tackle COVID-19: IoT, AI, Robotics, and Blockchain for a Better World
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    IEEE Internet of Things Journal.2021; 8(16): 12826.     CrossRef
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    New Generation Computing.2021; 39(3-4): 541.     CrossRef
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    International Journal of Environmental Research an.2020; 17(18): 6691.     CrossRef
  • Evidence of Long-Distance Droplet Transmission of SARS-CoV-2 by Direct Air Flow in a Restaurant in Korea
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    Journal of Korean Medical Science.2020;[Epub]     CrossRef

PHRP : Osong Public Health and Research Perspectives