Análise preditiva baseada em dados para criação de perfil de grupos de risco no SUS: um estudo de caso aplicado a sífilis no Brasil

Abstract

For many decades, society understood that it was necessary to monitor its population. Several initiatives emerged, were perfected and today, in the era of the digital society, they have become even more incisive. The adoption of monitoring has allowed us to live longer, understand certain diseases and control pandemics. With the life of society permeated with digital “being”, the needs were broader. When before the lack was restricted to the fact of collecting data, at present we experience the excess of data from different sources. This paper explores public data on compulsory syphilis registrations in Brazil, as part of the efforts contained in the “No Syphilis!” Project. to understand andidentify how the different social groups of syphilis patients are constituted. It is understood in the literature specific groups of key population for sexually transmitted infections, however, it is also understood that the loco-regional characteristics of the population may also have influences. For that, it was necessary to build tools capable of analyzing the large volume of data, such as a cluster server architecture associated with big data platform as well as data analysis and science strategies. Grouping techniques were applied to the data, after a data curation process. The results showed that it is possible to observe that there are multiple groups of populations that are united by social characteristics. Such observation and verification allows to specialize public health policies in addition to the macro groups of key population, it also allows the development of other technological solutions to induce the training of health professionals, for example. During development, the study included international cooperation with the University of Athabasca (Canada) and the University of Lorraine (France) whose aim was to exchange experiences and adopt the results as a basis for further research