Descoberta de conhecimento na base de dados do SINAN-TO para os casos de Hanseníase no estado Tocantins

Abstract

Leprosy is an infectious disease and is considered a public health problem because it is a neglected disease, and for that reason there is a big problem in preventing and combating it. In the state of Tocantins, the disease is considered hyperendemic according to the parameters per 100,000 inhabitants, being one of the states with the most new cases in Brazil. In view of this problem, it is sought through data from the Information Notification System (Sinan) that performs the collection of notification of diseases and conditions, the extraction of knowledge about leprosy cases in the state of Tocantins by applying the process of knowledge discovery known as Knowledge Discover in Database (KDD) and through data mining using association rules to characterize people affected by the disease in the state. The methodology used was of the descriptive and exploratory type, in order to seek to describe the facts and try to explore the data, exploratory data analysis was used to explore the relevant attributes of the patient’s characteristics, the disease, the space and the time. In data mining using association rules, he was responsible for associating these attributes to know the profile of patients who were frequent in the database in order to characterize them. The results of the research that were found are that the people most affected by the disease are people who live in urban areas, and the multibacillary forms are more common in total, with the male population being the most affected by them. The education of the population was mostly low, and it was also related to the low income of the people affected. Every year of the study, the number of cases was hyperendemic according to national and international parameters.