Effective Reproduction Number (Re) Analysis of BCG Vaccination Impact on Tuberculosis Control in Ecuador: An Artificial Intelligence Approach with Sensitivity Analysis
摘要
Background: Tuberculosis remains a major public health challenge globally, with Ecuador reporting significant burden despite vaccination programs. The effective reproduction number provides insights into transmission dynamics under control measures. Methods: We developed a modified SVIR (Susceptible-Vaccinated-Infected-Recovered) compartmental model using Bayesian optimization to analyze BCG vaccination impact on TB transmission in Ecuador during 1995–2007. We calculated effective reproduction numbers (Re) and conducted comprehensive sensitivity analyses to quantify vaccination program effectiveness while accounting for parameter uncertainty. Results: Our analysis revealed an average effective reproduction number (Re) of 0.003 (95% CI: 0.002–0.004), indicating well-controlled transmission dynamics. The model estimated that BCG vaccination contributed to an average reduction of 54.59 cases per 100,000 population (49.65% reduction; 95% CI: 45.2–54.1%) compared to counterfactual scenarios without vaccination. Sensitivity analysis confirmed robustness of findings across parameter variations, with vaccine efficacy estimates ranging from 40–60% producing similar results. Conclusions: Ecuador’s universal BCG vaccination policy significantly contributed to TB control during the study period. However, the observed low Re values reflect the combined effect of vaccination, case detection, and treatment programs rather than vaccination alone. These findings support continued vaccination within comprehensive TB control strategies while acknowledging the need for complementary interventions.