Descriptive statistics of the subdistricts.

Climate change and urbanization are contributing to the expansion of Aedes mosquito populations in subtropical metropolitan areas, thereby increasing the potential for human–vector contact and associated transmission risk. As vectors of multiple pathogenic viruses, Aedes mosquitoes not only elevate public health risks but also impose considerable burdens on urban health systems. Beyond vector distribution, demographic characteristics and the associated spatial patterns also influence the transmission risk of diseases such as dengue fever. However, a comprehensive framework for spatially assessing Aedes mosquito bite risk from multiple dimensions is still lacking in subtropical regions, which hinders the formulation of targeted public health strategies. Based on the hazard-exposure-vulnerability risk assessment framework, this study systematically evaluated the Aedes mosquito bite risk in Shenzhen. The hazard layer was generated using the Optimal Parameters-based Geographical Detector (OPGD) and the Geographically Weighted Random Forest (GWRF) model to predict spatial patterns of Aedes mosquito density from surveillance data. The exposure layer was derived from population density data, while the vulnerability layer was constructed by applying Geographically Weighted Principal Component Analysis (GWPCA) to multiple demographic and socioeconomic variables. By combining hazard, exposure, and vulnerability layers, we generated a comprehensive Aedes mosquito bite risk map and identified high risk subdistricts in Shenzhen. Further analysis revealed the underlying drivers of each risk hotspot, enabling the proposal of tailored recommendations for Aedes mosquito bite risk prevention. These findings provided valuable insights for the development of preventive measures against vector-borne disease spread and offer a method that can be easily applied to other subtropical megacities.