National Implementation of a Tuberculosis Sample Referral Network to Expand Access to Molecular Diagnosis in the Republic of Congo: Pilot Evaluation and Programmatic Analysis (2023–2025)

Abstract

Background: Limited access to rapid molecular diagnostics remains a major barrier to timely tuberculosis (TB) detection and drug-resistance surveillance in resource-constrained settings. In the Republic of Congo, GeneXpert MTB/RIF platforms remain concentrated in a few laboratories, while peripheral facilities rely predominantly on smear microscopy, highlighting the need for a structured sample referral system. Methods: We conducted a three-year mixed-methods operational study comprising a six-month pilot phase (January–June 2023), initially enrolling 29 TB diagnostic and treatment centers in urban and rural settings followed by a 30-month national roll-out phase (July 2023–December 2025), evaluated retrospectively using routine programmatic surveillance data. Results: During the pilot phase, 962 sputum samples were transported. 294 (30.6%) were TB cases, including 12 (4.1%) RR-TB. Median total turnaround time was 53 h (19–168) in urban and 62 h (26–204) in rural, with 86% overall site participation (92% urban vs. 60% rural). During scale-up, samples increased from 2154 (2023) to 5160 (2024), achieving full national coverage (12/12 departments). Over three years, 2587 TB and 84 RR-TB cases were detected. The system’s contribution to national TB detection grew from 9.2% to 16.0%, and RR-TB detection from 10.4% to 18.7%. Conclusions: Implementation of the structured sample referral system was associated with improved equitable access to molecular TB diagnosis, turnaround times within national targets, and strengthened the RR-TB surveillance. Scalable transport networks integrated into national guidelines may enhance diagnostic equity and drug-resistance detection in centralized laboratory systems.