Epidemic Analysis of COVID-19 in South Korea Based On Spatiotemporal Geographic Information and Graph Databases

Since the first coronavirus case was identified in January of 2020, the COVID-19 outbreak seriously threatens the public health of South Korea. Based on the officially notified case data, this paper explored the spatial and temporal evolution of the epidemic in South Korea. Simultaneously, kernel density estimation, standard deviational ellipse and spatial autocorrelation analysis were also applied to analyse the spatial clustering of COVID-19 at the macro level. The results showed that the epidemic in South Korea has spatial aggregation and directional distribution. The coronavirus is concentrated in the Seoul metropolitan area and spreading to Daegu. At the same time, in order to analyze the transmission characteristics of the coronavirus at the micro level, we use graph database for structuring the coronavirus infection relationship network. Through knowledge mining, we can find the path of coronavirus infection, discover the super spreaders and the evolution process of the epidemic. Finally, according to the characteristics of epidemic evolution and infection, a three-stage epidemic control strategy was proposed.