Characterization of the Spatial Distribution and Drivers of the Association of Meteorological Factors and Air Pollution with the Number of First Aiders

Based on the health data from Zhejiang Emergency Command Center, combined with meteorological, air pollution, land use and socio-economic data of Zhejiang Province, distributional lag nonlinear models, grouped weighted quantile and regression and Bayesian spatial models were used to explore the independent and interactive effects of the association between meteorological factors and air pollution and the number of first-aiders, to identify the related characteristics of the vulnerable populations, the types of sensitive diseases and the high-risk areas, and to elucidate the driving factors of the association between meteorological factors and air pollution and the number of first-aiders. It also clarifies the drivers of the association between meteorological factors and air pollution and the number of emergencies, so as to provide a reference for the government to take targeted measures to reduce the burden of related healthcare services.