Analysis and Prediction of Recorded COVID-19 Infections in the Constitutional Departments of Peru using Specialized Machine Learning Techniques

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The COVID-19 pandemic in Peru caused thousands of losses where it can be seen that until the year 2021 there are more than 200,000 deaths among men and women throughout the country. This figure is alarming and could have been avoided in time if the necessary care had been taken and the norms imposed by the Peruvian government had been followed. In the last months of the year 2020, we began to see a decrease in deaths and infected by COVID-19, which caused the public to calm down, which led to some citizens not following the biosecurity protocols, consequently causing a second wave of infected people. Therefore, it is necessary to be able to prevent a third wave since in 2021 a reduction was again visualized, which meant a reduction of deaths and infected by COVID-19, so one option to be alert to a possible third wave is to use machine learning techniques with a data set with the ministry of health to predict in which parts of the country there is the possibility of new contagions and identify which gender will be more prone to be infected in this way be aware of which parts of the country should be prioritized and thus contribute to the stability and harmony of the country. Keywords— Covid-19; Machine Learning; Software prototype; Prediction models