Análises epidemiológica e espacial da Covid-19 no Estado do Piauí

Abstract

The emergence of a new coronavirus in humans, first diagnosed in 2019, has many deaths and serious survival and psychosocial consequences. Through statistical tools and techniques associated with geographic technologies, this ecological, analytical and exploratory study is being developed, whose general objective is to carry out epidemiological and spatial analyzes of the distribution of confirmed cases and deaths from Coronavirus 2019 disease (Coronavirus Disease 2019 - COVID-19), in the year 2020, in the state of Piauí, Brazil. The variables listed are being assigned via the IBGE and SESAPI database. All confirmed cases and deaths with COVID-19 infection that were reported in 2020 in that state were included in the study. In the epidemiological analyzes descriptive statistics were carried out and in the spatial analyses, maps are being constructed using geoprocessing techniques, through the statistical analysis of Moran Global and Local. Preliminary results showed that, in 2020, 143,179 confirmed cases and 2,840 deaths caused by COVID-19 were reported in Piauí. A higher percentage of cases was observed in relation to females, young adults, and deaths in elderly, males, with chronic diseases. The capital Piauiense led the number of cases and deaths from the disease, probably due to the high population density. However, when considering the incidence and mortality coefficients of COVID-19, the highest rates in the state were considered in the municipalities of União and Água Branca, respectively. The spatial analysis of the cases showed clusters of high-high pattern of cases of the disease in the metropolitan region of Teresina, the region between Rios and the region of Tabuleiros do Alto do Parnaíba. A high-high cluster for mortality was verified in fillings in the region of Entre Rios and Vale do Sambito. The analyzes performed provided the visualization of spatial clusters and an identification of vulnerable areas, resulting in information that was not visualized working only with tabular data.