Análise de similaridades e padrões estatísticos em séries temporais de casos de suicídio no Brasil

Suicide is a serious global public health problem and is among the leading causes of death in the world. In Brazil, suicide rates have seen alarming increases and continue to rise. Some public policies have been implemented to prevent the rise in suicide cases. Despite this, studies in the field indicate that such measures are not enough to cause a reduction in cases. The collection and analysis of suicide data are important for creating and reevaluating monitoring and prevention processes for suicide attempts. The goal of this master’s project is to contribute to the recognition of temporal patterns of suicide cases in Brazil from suicide deaths data published by DATASUS, using a time series-based approach. The main steps of this work are the collection of data and modeling of time series, provision of a pre-processed database containing daily suicide cases data from Brazil, exploratory analysis of the time series, similarity search between time series and application of clustering; mining of time series subsequence patterns, integration of multimodal data, and finally, the evaluation of the results obtained. It is expected to identify inherent temporal patterns in the time series to assist in understanding the behavior of suicide cases in the states and regions of Brazil.