Objective: Evaluation of the association between air pollution and mortality and morbidity is becoming ever more complex owing to changes in inner-city air pollution, marked by decreasing values for all main pollutants save those associated with traffic. This has led to the need for the study of new epidemiological scenarios in which most pollutants are below guideline values. Nonetheless, the health effects are significant.
Methods: This report presents the results of a statistically based model for real-time forecasting of mortality and morbidity in Madrid, with meteorological and pollution series serving as inputs.
Results and conclusions: Not only did the models perform well with correlation coefficients between predicted and observed values (r = 0.683 for mortality, r = 0.681 for morbidity), but they enabled quantification of the impact of air pollution on mortality and morbidity (with increases ranging from 1. 8% to 12% for mortality and from 2.3% to 18% for morbidity for a 25-microg/m(3) increase in pollutants). Moreover, attention should be drawn to the observation that the model proved to be easy to implement and operate on a routine basis.