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.