Observational studyTropical medicine & international health : TM & IH2026
Epidemiological, Spatial and Predictive Analysis of Tuberculosis-Related Mortality in the Department of Risaralda (Colombia), 2020-2024.
Observational study in Tropical medicine & international health : TM & IH, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Epidemiological, Spatial and Predictive Analysis of Tuberculosis-Related Mortality in the Department of Risaralda (Colombia), 2020-2024.Tropical medicine & international health : TM & IH · 2026Observational
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3 authors.
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Abstract
objectiveTo analyse the epidemiological characteristics, spatial distribution and predictors of TB-related mortality in Risaralda from 2020 to 2024.
methodsA retrospective observational study was conducted using secondary data from the National Public Health Surveillance System (SIVIGILA). Descriptive statistics, spatial analysis (choropleth maps) and binary logistic regression were used to identify sociodemographic and clinical factors associated with TB case fatality. Model performance was evaluated using ROC curves, sensitivity, specificity and 5-fold cross-validation.
resultsA total of 2081 confirmed TB cases were analysed, with a case fatality rate of 13.2%. Mortality was higher among individuals ≥ 65 years (OR: 3.87), hospitalized patients (OR: 7.33), HIV-positive individuals (OR: 3.49), those with undernutrition (OR: 1.89), males (OR: 1.45) and Indigenous persons (OR: 1.67). The logistic model showed good discrimination (AUC: 0.82), with sensitivity of 79.2% and specificity of 73.8%. Cross-validation confirmed model stability (AUC: 0.81). Spatial analysis revealed high mortality in rural municipalities with low case burden, suggesting health inequities.
conclusionTB mortality in Risaralda is influenced by age, comorbidities and social determinants, with pronounced territorial disparities. These findings support the integration of spatial and predictive tools in TB surveillance to strengthen targeted interventions and reduce mortality in high-risk populations.
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