Remote Sensing Applied to the Study of Chronic Diseases in the Environment Through Analysis of Atmospheric Pollutants Case Studies Quito Ecuador

General objective To estimate by remote sensing air pollutants and their relationship with chronic respiratory diseases in Quito, Ecuador. Justification The availability of this information will be crucial to the success of this work. Several methods such as artificial neural network, logistic regression, Maxent, or Bayesian Model Averaging (BMA) are applied to assess the relationship between environmental variables and health data. Partial hazard models and an ensemble mean model calculated from all tested methods are calculated. Finally, an integrated model is proposed.