Epidemiologist | Health Data Scientist
📇 ORCID: 0000-0002-9745-3887
🖇️ LinkedIn: /jeehyun-kim-473269321
Researcher with extensive experience in large-scale health data analysis and spatial epidemiology, applying statistical and machine learning methods to national surveillance and clinical datasets to understand disease patterns and support data-driven healthcare and clinical decision-making.
We investigated health behaviors as potential factors of COVID-19 incidence in the early phase of transmission in the spatial context*,* using COVID-19 cumulative case data as of February 25, 2021—one day prior to nationwide COVID-19 vaccination commencement. Besag–York–Mollie models highlighted that the municipalities with lower COVID-19 incidence were likely to have more people who previously received influenza vaccination, even after adjusting for covariates and spatial autocorrelation.
We examined spatiotemporal patterns of Kawasaki disease (KD) by sex in South Korea using 2008—2017 data of KD cases under 5 years (ICD-10-CM code, M303) at municipal level. Spatial analyses, including mapping, Getis-Ord Gi*, and Emerging Hot Spot analyses, consistently identified hotspots in northern regions over 9 years, with emerging hotspots on the northwestern and eastern coasts. However, the distribution and proportion of hot- or cold-spot types varied by sex, suggesting KD's features extend beyond infectious triggers, involving multiple factors like genetics and environment, with distinct associations for different sexes.