Coinfecção TB-HIV: uma análise espacial de áreas críticas no estado do Mato Grosso

Abstract

INTRODUCTION: Tuberculosis (TB) is a preventable and curable disease, TB was the second leading cause of death worldwide and the leading cause of death among people living with human immunodeficiency virus (HIV). Brazil belongs to the priority countries with a high burden of TB-HIV co-infection that were included in a global list and the state of Mato Grosso has faced many challenges in relation to controlling this co-infection. OBJECTIVE: To evaluate the spatial pattern and identify municipalities with greater vulnerability to the occurrence of TB-HIV co-infection in the state of Mato Grosso. METHODS: Cases registered in the municipalities of Mato Grosso between 2012 and 2021 were evaluated. The data was collected by the Notifiable Diseases Information System (SINAN), through the Data Repository of the Information Systems of the State Secretariat of Health of Mato Grosso (DwWeb/SESMT). A descriptive analysis of the sociodemographic and clinical data of reported cases of TBHIV co-infection was carried out and the incidence rate was calculated for each municipality and for each year. The spatial distribution of the incidence obtained was carried out followed by the Getis-Ord Gi* analysis, which was used to identify areas of spatial association. Thematic maps were created, the most evident colors of which represent the most critical areas for the occurrence of TB-HIV co-infection. RESULTS: In the period from 2012 to 2021, 16,683 cases of TB were reported in Mato Grosso, 1,407 of which were TB-HIV co-infection. Regarding sociodemographic data, the majority of cases were male (n=1018, 72.35%), brown (n=887, 63.04%) and aged between 20 and 39 years old (n=711 , 50.53%). In terms of education (n=507, 36.03%) they had Ens. Incomplete fundamental. The spatial analysis made it possible to identify the municipalities most susceptible to TB-HIV co-infection, presenting incidence rates that reached 10.93 cases per 100 thousand inhabitants, and the presence of hot spots that indicate higher risk territories with reliability between 90 and 99%. The main municipalities that belonged to the host spots were Cuiabá, Nova Brasilândia, Jaciara, Rosario do Oeste, Chapada dos Guimaraes, Campo Verde, Santo Antônio do Leverger and Dom Aquino. CONCLUSION: The findings obtained in relation to sociodemographic profiles and clinical aspects, together with spatial analyses, can collaborate as an alert to identify populations more vulnerable to TBHIV co-infection, in addition to supporting the implementation of public policies aimed at strategies to control the TB cases mainly among people living with HIV in the state of Mato Grosso.