Event-based surveillance in the Republic of Korea: assessment of the effectiveness of Epidemic Intelligence from Open Sources
DOI:
https://doi.org/10.5365/wpsar.2025.16.3.1151Keywords:
epidemiology, epidemic intelligence, event-based surveillance, early warning system, EIOS system, outbreak detection, artificial intelligenceAbstract
In 2023, the Republic of Korea’s Korea Disease Control and Prevention Agency (KDCA) enhanced its event-based surveillance practices by using the World Health Organization’s (WHO) Epidemic Intelligence from Open Sources (EIOS) to actively screen and share information about potential public health threats to the country. This report describes the preliminary assessment of the results of implementing these enhanced event-based surveillance activities from June to October 2023. During this period, 425 (0.4%) events were detected globally by the KDCA from 99 945 media articles, with the highest frequency reported in Asia (185, 43.5%) and North America (81, 19.1%). The most frequently reported diseases or conditions were dengue fever (111, 26.1%) and mpox (32, 7.5%). Eight events were detected early by the KDCA using EIOS before being officially listed on WHO’s Event Information Site (EIS) or in Disease Outbreak News (DON), with an average interval of 20 days (range: 5–41) between the detection date and posting on EIS or DON. Thus, EIOS is efficient in aiding early detection of potential public health threats at the national level. This finding highlights the importance of sustaining international cooperation and support to enhance surveillance capabilities in resource-limited settings and expanding the scope of EIOS, including by incorporating additional sources and sources in additional languages, reducing noise. However, as the current report is based on a descriptive analysis, in the future a systematic evaluation of event-based surveillance using EIOS to identify relevant attributes will need to be conducted.
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