Prediction System to Control the Spread of COVID-19 in People Who Work in Person in the Los Olivos District (#874)

Authors

Paredes Reyes, Iván Wilber

Abstract

In Peru, the COVID-19 pandemic affects various private and state sectors, due to the spread of the virus. The current government decreed quarantines to reduce infections, which implied that part of the population would have to stay at home , but a group of people carry out face-to-face activities and also cause contagion to younger people or older adults.The objective of this research work is to create a prediction mobile application that allows to identify if a person who carries out economic activities in person is exposed to contagion, depending on the transport chosen and the time to reach their destination.In order to develop the solution, data was collected from pages of the Peruvian government in charge of controlling the spread of the epidemic and when analyzing the data, the variables for prediction were identified through decision trees. Azure machine learning, SQL language, was used for the development of the project. The Kanban methodology was used to develop the project and the CRIPS-DM methodology for data analysis.The result was a mobile application to carry out a test on possible COVID-19 contagion.