A model to predict the incidence of allergic rhinitis based on meteorological factors.

Meteorological factors have been shown to affect the physiology, distribution, and amounts of inhaled allergens. The aim of this study was to develop a model to predict the trends for onset of allergic rhinitis (AR) patients. A total of 10,914 consecutive AR outpatients were assessed for the number of daily patient visits over a period of 4 years. Meteorological data were used to assess the relationship between meteorological factors and AR incidence by time-series data and regression analysis. Predictive models for incidence of AR were established in pollen-, dust mite- and mould-sensitive groups of patients, and the predictive performances of meteorological factors on the incidence of AR were estimated using root mean squared errors (RMSEs). The incidence of pollen-, dust mites- and mould-sensitive AR patients was significantly correlated with minimum temperature, vapour pressure, and sea-level pressure, respectively. The correlation between comprehensive meteorological parametric (CMP) and incidence of AR was higher than the correlation between the individual meteorological parameters and AR incidence. CMP had higher performance than individual meteorological parameters for predicting the incidence of AR patients. These findings suggest that the incidence of pollen-, dust mites- and mould-sensitive AR can be predicted employing models based on prevailing meteorological conditions.