Transformative Innovations in Tuberculosis Control: Advancing Diagnostics, Treatment, and Prevention for Global Elimination - Abdulhakeem, Abdulsalam Oladipupo; Sununu, Amina Tanko; Alshabrawi, Faisal (Journal of Multidisciplinary Science: MIKAILALSYS, 2026)
Tuberculosis (TB) remains a major global public health threat, driven by undiagnosed infections, the emergence of multidrug-resistant strains, and persistent weaknesses in health-care delivery systems, particularly in high-burden regions, thereby undermining progress toward the World Health Organization 2030 TB elimination targets. This study aimed to synthesize recent transformative innovations in TB diagnosis, treatment, and prevention and to evaluate their collective potential to accelerate global TB control. Using a narrative synthesis approach, the study reviewed evidence from late-stage clinical trials, implementation studies, and policy-relevant literature, with a focus on novel molecular diagnostics, artificial intelligence-assisted imaging, shortened drug regimens, genomic surveillance, and emerging TB vaccines. The synthesis indicates that rapid molecular tools, including Xpert MTB/XDR, enable genotypic drug-resistance profiling within 90 minutes, while CRISPR-based non-sputum assays improve detection in low-bacterial-load cases. Artificial intelligence-enabled radiology systems show diagnostic accuracy comparable to expert readers, supporting scalable screening in resource-limited settings. In treatment, the 6-month all-oral BPaLM/BPaL regimen demonstrates higher treatment success and adherence than conventional regimens, further strengthened by genomic surveillance for real-time resistance monitoring. In prevention, the M72/AS01E vaccine shows approximately 50% efficacy in preventing active TB, representing a substantial advance for high-risk populations. Overall, the convergence of advanced diagnostics, simplified treatment, and effective vaccination provides a realistic pathway toward TB elimination; however, equitable access, health-system readiness, and effective implementation across diverse epidemiological settings remain essential to achieving population-level impact.