Spatial Epidemiological Approach to Tuberculosis Treatment Outcomes in a Tertiary-Level Hospital: A Retrospective Analysis

Tuberculosis (TB) remains a persistent public health challenge in Mexico, particularly in large urban settings marked by social heterogeneity. We conducted a retrospective cohort study of patients diagnosed with tuberculosis and treated at a tertiary-level hospital in Guadalajara, Mexico, between 2020 and 2023. Unfavorable treatment outcomes were defined as treatment failure, loss to follow-up, or death. Multivariable logistic regression was used to identify factors independently associated with unfavorable outcomes. Spatial analyses, including Kernel Density Estimation, Global Moran’s I, Local Indicators of Spatial Association (LISA), and Getis–Ord Gi*, were applied to explore the geographic distribution of unfavorable outcomes. Unfavorable tuberculosis treatment outcomes among patients treated at a tertiary-level hospital were not randomly distributed in space. Spatial epidemiological methods provided complementary, exploratory insights beyond individual-level clinical factors, highlighting geographic patterns that may inform place-sensitive public health interventions and strengthen routine tuberculosis surveillance, without implying causal inference.