Tuberculosis deaths after initiation of treatment and underreporting of cases in the frontier triple Paraguay, Argentina and Brazil

Abstract

Death due to tuberculosis (TB) represents an important health indicator capable of expressing fragility in the access and use of health services, as well as a precarious social and economic conditions of groups and geographic areas. The treatment has not been able to eliminate the death due to TB, considering that in Brazil a death rate per TB is 2.2 to 100 thousand inhabitants and still in this group that died by TB obtaining the diagnosis after death. In this sense, the general objective of the proposal is to analyze the occurrence of TB deaths after the beginning of the treatment of the disease and to identify an underreporting of the deaths in two health information systems of the municipality of Foz do Iguaçu (PR) in the period from 2004 to 2015. This is an ecological study, whose data are obtained in the SIM and SINAN. In the exploratory phase of the data based on calculations of absolute and relative frequencies, subsequent were performed or confronted with the initially identified data identified cases common in both banks, cases that started treatment and died from TB were identified. At the opportunity we also identified an underreporting. The spatial analysis of the cases that initiated the treatment and failure of initialization procedures of a geocoding of the data in the cartographic base, using TerraView software version 4.2.2. Next, we will use the technique of point density analysis - Kernel Intensity Estimation - for an identification and representation of the areas with the highest death rates by TB. It will be used as a unit of analysis of the census tracts defined by the Demographic Census of 2010, of the Brazilian Institute of Geography and Statistics (IBGE). Information management and thematic mapping are not performed in ArcGis version 10.1. The Kernel estimator is very useful to provide an overview of the distribution of sample points, which suggests spatial dependence. Thus, this technique allows us to observe the clusters in order to raise hypotheses about the spatial pattern of a given event. (AU)