Air pollution effects on clinic visits in small areas of Taiwan revisited

We revisit the complete daily clinic visit records and environmental monitoring data at 50 townships and city districts of Taiwan, considered by Angers et al. (Commun Stat Simul Comput 38:1535–1550, 2009). Extending the earlier analysis, we consider a Bayesian analysis using regression spline model where instead of principal components we consider all the seven covariates for all 50 monitoring stations. We find that NO$$_2$$2, SO$$_2$$2, O$$_3$$3, PM$$_{10}$$10 and temperature are the important pollutants in different areas following some spatial pattern.