Utilização de matrizes de vizinhança socioeconômicas em modelos da classe STARMA aplicados a dados epidemiológicos

Abstract

In this work the use of socioeconomic neighborhood matrices was studied in space-time models of the autoregressive and moving averages class (STARMA). The selected data set is composed of nine time series that quantify the incidence rate of Tuberculosis observed between 2002 and 2017 in the following cities: Belo Horizonte, Betim, Contagem, Governador Valadares, Juiz de Fora, Lavras, Montes Claros, Pouso Alegre and Uberlândia. Since most cities are geographically distant, the use of socioeconomic neighborhood matrices was necessary. The matrices were obtained through two socioeconomic variables: the municipal IDH and the average annual investment in basic health. STARMA class models were adjusted considering the data set and the two neighborhood matrices obtained. The model was obtained computationally and consisted of three stages: Identification, estimation and diagnosis of the model. It was concluded that the socioeconomic neighborhood matrices in STARMA models applied to the data set chosen were appropriate since these matrices can be used in space-time series in which the places of interest are geographically distant.