The need for a scientific approach that can provide subsidies to governments and public health authorities in decision making to face pandemics, epidemics and endemics was one of the aspects recognized worldwide with the first wave of COVID-19. This article presents a methodology for the application of data mining as a support tool for coping with epidemic diseases. The methodological approach was applied in the city of São Paulo, Brazil, with the aim of predicting the evolution of COVID-19 in

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... he metropolis and identifying air quality and meteorological variables correlated with confirmed cases and deaths from the coronavirus. Forecasting public health conditions is useful for preparing health teams in advance for a pandemic to prevent the system from collapsing. The statistical analyzes indicated the most important explanatory environmental variables, while the cluster analyzes showed which are the best input variables for the forecasting models. The forecast models were built by two different algorithms, J48 (C4.5) and CBA, and their results have been compared. The models developed can be used to predict new cases and deaths by COVID-19 in São Paulo. The methodological approach can be applied in other cities and for other epidemic diseases.