The Association Between Tuberculosis/HIV Incidence and Mortality in Nigeria: A Retrospective Analysis from 2000 to 2023

Background: Tuberculosis and Human Immunodeficiency Virus (HIV) co-infection remains a major public health challenge, particularly in high-burden countries like Nigeria. Understanding incidence–mortality dynamics is essential for guiding control strategies. Objective: To analyze the association between TB/HIV incidence and TB/HIV-related mortality in Nigeria from 2000 to 2023, accounting for temporal trends. Methods: A retrospective secondary data analysis was conducted using UNAIDS estimates. Correlation, linear regression, and segmented time-series regression were applied to quantify associations and detect mortality trend changes. Analyses were performed in R version 4.4.2. Results: TB/HIV incidence and deaths were strongly correlated (r = 0.991, p < 0.001). Linear regression confirmed a significant association, with each additional case of TB/HIV incidence linked to ~0.67 deaths (95% CI: 0.63–0.70, p < 0.001). The model explained 98.2% of mortality variance (adjusted R² = 0.982), though the negative intercept reflected a model limitation. Segmented regression identified two breakpoints (2003 and 2011), marking shifts in mortality: declines (–2800 deaths/year, 2000–2003), sharp increases (+3250 deaths/year, 2003–2011), and subsequent steep declines (–4484 deaths/year, 2011–2023). These transitions coincided with programmatic changes, including ART scale-up and strengthened TB/HIV collaboration. Conclusion: TB/HIV incidence strongly predicts mortality in Nigeria, but the very high R² should be interpreted cautiously given shared UNAIDS modeling assumptions. Combining linear and time-series approaches provides a more nuanced understanding of Nigeria’s TB/HIV epidemic and underscores the need for adaptive, evidence-based control strategies. A key limitation is reliance on secondary UNAIDS estimates, which may introduce modeling biases and restrict causal inference.