SUPPORT SYSTEM FOR EARLY ALERTS OF POSSIBLE CONTAGES THROUGH DATA ANALYSIS TECHNIQUES

The rapid and silent contagion is one of the great reasons that has led the world to the current state of Covid-19. The study on how to deal with infections from people without symptoms takes on special relevance, seeking to control the spread of the virus as much as possible. Taking advantage of the social network approach and other data analysis techniques, this project aims to develop algorithms to model the social network of infected people, the determination of places with a high probability of contagion with SARS-CoV-2 and the identification of other social interactions, as support for early warnings of possible infections. The potential impacts expected with the implementation of the proposed system and with the dissemination by the entities facing the pandemic in our country, will allow the possible infected to find out about their situation, both due to the recent relationship with those infected or due to the permanence in sites. where were the infected. It would be expected that given this information they take the necessary measures not to become another link in the chain of infections. It would serve the entities to monitor nodes and arcs in the propagation process.