Risk factor identification and spatiotemporal diffusion path during the dengue outbreak

Abstract

This study analyzed the spatiotemporal diffusion path and main risk factors of dengue outbreak through microscopic spatiotemporal data mining. Firstly, the life cycle and variation trend of dengue fever were investigated by using the least-squares trend fitting and derivative methods. Then, by regarding day and week, the spatiotemporal mapping and spatial analysis methods were employed to investigate the spatiotemporal hotspots and diffusion path and the outbreak phase of dengue fever. Finally, this study analyzed the relationship between dengue fever and the comprehensive meteorology, population, Breteau index (BI), and other factors during dengue outbreaks through Spearman relevance, spatial regression, and spatial autocorrelation analyses to identify and quantify risk factors. The results showed that the life cycle of dengue outbreaks can be divided into different stages: initial, beginning, outbreak, and extinction. Meanwhile, the results indicated that the most significant risk factors for dengue outbreaks are population density and the BI from microscopic spatiotemporal view. In addition, a spatiotemporal diffusion path study demonstrated that dengue fever spread around hotspots and presented a significant axial propagation effect in outbreak stage. Microscopic spatiotemporal data mining can effectively identify risk factors and spatiotemporal diffusion paths during dengue outbreaks, thereby providing a quantized reference for decisions on preventing and controlling the disease.