Vulnerable territories to tuberculosis-diabetes mellitus comorbidity in a northeastern Brazilian scenario.

INTRODUCTION: Epidemiological investigations on tuberculosis-diabetes comorbidity using spatial analysis should be encouraged towards a more comprehensive view of the health of individuals affected by such comorbidity in different contexts. This study analyzes the territories vulnerable to tuberculosis-diabetes comorbidity in a municipality in northeastern Brazil using spatial analysis techniques. METHODS: An ecological study was carried out in Imperatriz, Maranhão, Brazil. Tuberculosis-diabetes cases reported in the Brazilian Notifiable Diseases Information System between 2009 and 2018 were analyzed. Kernel density estimation and spatial scanning techniques were used to identify the areas with the greatest occurrence of spatial clusters. RESULTS: A heterogeneous spatial distribution was found, ranging from 0.00 to 4.12 cases/km2. The spatial scanning analysis revealed three high-risk spatial clusters with statistical significance (p < 0.05), involving eleven strictly urban sectors with a relative risk of 4.00 (95% CI: 2.60-6.80), 5.10 (95% CI: 2.75-7.30), and 6.10 (95% CI: 3.21-8.92), indicating that the population living in these areas had a high risk of tuberculosis-diabetes comorbidity. CONCLUSIONS: The highest concentration of cases/km2, as well as risk clusters, were found in areas with high circulation of people and socio-economic and environmental vulnerabilities. Such findings reinforce the need for public health interventions to reduce social inequalities.

Tuberculosis/HIV co-infection in Northeastern Brazil: Prevalence trends, spatial distribution, and associated factors.

INTRODUCTION: The objective was to analyze the prevalence trend, spatial distribution, and TB-HIV co-infection-associated factors in an endemic scenario for TB in Northeastern Brazil. METHODS: An ecological and temporal series study was conducted based on secondary data obtained from the Brazilian Notifiable Diseases Information System between January 2008 and December 2019. The prevalence rates were determined for each year and the average for the period. Prais-Winsten regressions were used for temporal variation analysis, scanning techniques were used to detect spatial clusters, and the Poisson regression model was used to explore the factors associated with the outcome. RESULTS: A total of 947 TB cases were reported, of which 501 (52.9%) underwent HIV testing, and of these, 73 were positive. The average prevalence was 20.0%, ranging from 1.5% in 2018 to 44.4% in 2009. A decreasing trend was found. Sixty-seven cases (92%) were geocoded, and two statistically significant (p < 0.005) high relative risk (RR) spatial clusters were detected. Statistically significant associations (p < 0.05) between the co-infection and variables such as male gender, living in the urban area, entry due to relapse, and case closure due to loss to follow-up were evidenced, and these variables constituted risk factors. CONCLUSIONS: A decreasing prevalence of TB-HIV co-infection has been found, as well as a heterogeneous spatial distribution with the formation of spatial clusters in urban areas characterized by socio-spatial inequalities associated with clinical-epidemiological factors. Such findings provide subsidies for rethinking health care activities and improving public policies for vulnerable populations.