Seo Haram, Choi Minchan, Chowell Gerardo, Lee Hyosun, Kim Byul Nim, Lee Sunmi
Applied Mathematics, Kyung Hee University, Deogyeong-daero, 17104, Yongin, Gyeonggi, Korea.
Population Health Sciences, Georgia State University, Street, GA 30303, Atlanta, Georgia, USA.
BMC Infect Dis. 2025 Jul 1;25(1):820. doi: 10.1186/s12879-025-11260-3.
The global spread of infectious diseases like COVID-19, accelerated by globalization and frequent international interactions, poses a serious threat to public health. Robust epidemiological data on imported cases is essential for managing cross-border disease transmission, enabling targeted public health responses through international cooperation and enhanced surveillance. This study investigates the impact of imported COVID-19 cases on South Korea's pandemic response from January 2020 to May 2023.
We analyzed 78,495 imported COVID-19 cases reported by the Korea Disease Control and Prevention Agency (KDCA) from January 2020 to May 2023. The dataset included demographic information, countries of origin, entry points, and information on dominant viral variants during the specified period. Temporal and spatial analyses examined how variant transitions, particularly from Delta to Omicron, and quarantine policy changes influenced imported case patterns. We calculated the "confirmation lag," the time between entry and confirmation, and applied Kernel Density Estimation (KDE) to evaluate how detection speed was affected by policy shifts and variant changes. In addition, least squares regression was used to explore the relationship between regional population size and the number of imported cases.
The findings reveal a significant increase in imported cases during the transition from the Delta to Omicron variants, highlighting the increased transmissibility of Omicron and its impact on imported case numbers. Consequently, testing strategies were improved for faster detection and quarantine adaptability, which was confirmed by the observed reduction in confirmation lag. Regions with major entry points, such as Incheon, had higher imported case ratios. Population size was the strongest predictor, followed by first importation timing. This trend underscores the importance of tailored measures, such as region-based surveillance and country-targeted entry policies, to effectively manage virus importation.
By systematically analyzing a large-scale dataset of imported COVID-19 cases, we demonstrate that targeted border measures-accounting for travelers' countries of origin and regional vulnerabilities-are essential for effective containment. Our findings underscore the value of variant-specific strategies, reinforced by real-time surveillance of imported cases, as a critical component of South Korea's public health infrastructure. This approach not only enhances current response capacity but also strengthens preparedness for future cross-border infectious disease threats.
全球化和频繁的国际交流加速了COVID-19等传染病在全球的传播，对公共卫生构成严重威胁。关于输入病例的可靠流行病学数据对于管理跨境疾病传播至关重要，有助于通过国际合作和加强监测实现有针对性的公共卫生应对。本研究调查了2020年1月至2023年5月输入性COVID-19病例对韩国疫情应对的影响。
我们分析了韩国疾病控制与预防机构（KDCA）报告的2020年1月至2023年5月期间的78495例输入性COVID-19病例。数据集包括人口统计信息、原籍国、入境点以及特定时期内主要病毒变种的信息。时间和空间分析考察了变种转变，特别是从德尔塔到奥密克戎的转变，以及检疫政策变化如何影响输入病例模式。我们计算了“确诊滞后时间”，即入境与确诊之间的时间，并应用核密度估计（KDE）来评估检测速度如何受到政策转变和变种变化的影响。此外，使用最小二乘法回归来探索区域人口规模与输入病例数之间的关系。
研究结果显示，在从德尔塔变种向奥密克戎变种转变期间，输入病例显著增加，凸显了奥密克戎的更高传播性及其对输入病例数的影响。因此，改进了检测策略以实现更快检测和检疫适应性，确诊滞后时间的减少证实了这一点。仁川等主要入境点所在地区的输入病例比率较高。人口规模是最强的预测因素，其次是首次输入时间。这一趋势强调了采取针对性措施的重要性，如基于地区的监测和针对国家的入境政策，以有效管理病毒输入。
通过系统分析大规模的输入性COVID-19病例数据集，我们证明了考虑旅行者原籍国和地区脆弱性的针对性边境措施对于有效遏制至关重要。我们的研究结果强调了针对变种的策略的价值，通过对输入病例的实时监测加以强化，这是韩国公共卫生基础设施的关键组成部分。这种方法不仅提高了当前的应对能力，还加强了对未来跨境传染病威胁的防范。
