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Analysis of 18FDG PET/CT Imaging as a Tool for Studying Mycobacterium tuberculosis Infection and Treatment in Non-human Primates

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Spatial analysis of drug resistant tuberculosis (DRTB) incidence and relationships with determinants in Rio de

Paula Cristina Pungartnik¹, Paulo Victor de Souza Viana², Jefferson Pereira Caldas Dos Santos³

¹Institute of Collective Health Studies, Federal University of Rio de Janeiro (UFRJ), Rio de Janeiro, Brazil.

|May 2, 2025

Abstract

Background:

The aim of this study was to assess the spatial distribution of drug-resistant tuberculosis (DRTB) cases in Rio de Janeiro state and its association with demographics, socioeconomic and health determinants.

Methods:

An ecological study based on real-world DRTB data from 2010 to 2022, in the Rio de Janeiro state, using data from the Special Tuberculosis Treatment Information System (SITE-TB) and demographic census. Crude incidence rates (CIR) of DRTB per 100,000 inhabitants and smoothed rates through the Global and Local Empirical Bayesian (BEG and BEL) methods were calculated. Spatial autocorrelation was explored using Moran's I statistic, Local Indicators of Spatial Association (LISA), and the Getis-Ord statistics. The SCAN method was also used to identify spatial-time clusters. To analyze the association of DRTB and determinants, we used LISA bivariate for spatial correlation and four explanatory statistical models were listed.

Results:

From 2010 to 2022, 2,709 new cases of DRTB were reported (CIR 16.9/100,000 inhabitants). The municipalities in the metropolitan region of Rio de Janeiro state had the highest rates. Despite 41% of municipalities reporting no new cases, BEG and BEL suggested higher rates than CIR, indicating underreporting. Spatial heterogeneity was observed, and spatial and spatial-temporal clusters and hotspots were detected in metropolitan region. Family health strategy coverage was identified as protection factor, however a not expected negative spatial autocorrelation between CIR and health strategy coverage, primary care and healthcare agent coverage was found. The variables identified as risk factors were population aged ≥18 years old with Elementary School completed (OR:1.10; CI95%:1.04-1.16), demographic density (OR: 1.00; CI95%:1.00-1.01), HIV-TB coinfection (OR: 1.18; CI95%:1.06-1.31).

Conclusion:

The identification of areas of risk for DRTB, spatial correlation and association between incidence and determinants, demonstrates that the DRTB transmission dynamics is related to the perpetuation of social inequality and urban spatial organization.

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