Incidence Rate Prediction Model for Keratitis, Conjunctivitis, and Dry Eye Syndrome Using Air Pollutants and Meteorological Factors

The eye is a sensory organ with a large area exposed to the atmosphere and, thus, substantially affected by air quality. In this study, we developed a prediction model for keratitis, conjunctivitis, and dry eye syndrome (DES) based on the air quality, using hospital visit records and data for air pollution, weather, and population. Male and female populations were used as independent variables to improve the accuracy of the model. Moreover, developed model was applied to air pollutants and meteorological data using nonlinear regression. The results of the incidence rate prediction model for keratitis, conjunctivitis, and DES were compared with actual data. Each model is statistically significant (p < 0.05). Based on the nationwide prediction model, regional prediction models for 16 administrative districts were analyzed. In the cases of Incheon and Daegu, the model showed high accuracy. However, in the cases of Chungnam and Jeju, the model showed lowest accuracy. Further research is necessary for the optimization of regional predictive models for keratitis, conjunctivitis, and DES.