The quest for better machine learning models to forecast COVID-19-related infections: A case study in the state of Pará-Brazil

COVID-19 disease has become an unprecedented public health crisis. Although a relatively small percentage of people require intensive care, due to the high degree of contagion of the disease, the public system quickly collapses. Due to the highly complex nature of this disease and variation in its behavior depending on the characteristics of each geographic region, in this work, we analyze data from the Amazon region in Brazil (Pará). We applied several machine learning models to forecast the contagious curve to up 10 days. The Linear SVM and Multilayer Perceptron presented the best overall performances. Until the discovery of a vaccine, every effort is needed to understand and anticipate this disease.