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BACKGROUND: In Nigeria, most children with tuberculosis (TB) present at primary health clinics where there are limited personnel skilled in collecting appropriate respiratory specimens from those who cannot produce sputum. KNCV Nigeria, in collaboration with the National Tuberculosis Control Program, implemented a modified simple, one-step (SOS), stool-based Xpert MTB/RIF method for diagnosis of TB in children who cannot expectorate sputum. We evaluated the impact of its implementation on childhood TB diagnosis. METHOD: A cross-sectional study was conducted across 14 selected states using secondary data of children presumed to have TB. Stool was collected from children presumed to have TB and processed using Xpert. RESULT: Out of 52,117 presumptive TB cases, 52% were male and 59.7% were under 5 years old. A total of 2440 (5%) cases were diagnosed with TB, and 2307 (95%) were placed on treatment. Annual TB notifications increased significantly after the introduction of the stool-based Xpert test when compared to those in the pre-implementation period. Increasing contributions from stool testing were observed throughout the implementation period, except in 2020 during the COVID-19 era. Overall, stool Xpert testing improved childhood TB notification in the studied states. Interventions aimed at awareness creation, capacity building, and active case finding improved the performance of the test.
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Wellness on Wheels (WoW) is a model of mobile systematic tuberculosis (TB) screening of high-risk populations combining digital chest radiography with computer-aided automated detection (CAD) and chronic cough screening to identify presumptive TB clients in communities, health facilities, and prisons in Nigeria. The model evolves to address technical, political, and sustainability challenges. Screening methods were iteratively refined to balance TB yield and feasibility across heterogeneous populations. Performance metrics were compared over time. Screening volumes, risk mix, number needed to screen (NNS), number needed to test (NNT), sample loss, TB treatment initiation and outcomes. Efforts to mitigate losses along the diagnostic cascade were tracked. Persons with high CAD4TB score (≥80), who tested negative on a single spot GeneXpert were followed-up to assess TB status at six months. An experimental calibration method achieved a viable CAD threshold for testing. High risk groups and key stakeholders were engaged. Operations evolved in real time to fix problems. Incremental improvements in mean client volumes (128 to 140/day), target group inclusion (92% to 93%), on-site testing (84% to 86%), TB treatment initiation (87% to 91%), and TB treatment success (71% to 85%) were recorded. Attention to those as highest risk boosted efficiency (the NNT declined from 8.2 ± SD8.2 to 7.6 ± SD7.7). Clinical diagnosis was added after follow-up among those with ≥ 80 CAD scores and initially spot -sputum negative found 11 additional TB cases (6.3%) after 121 person-years of follow-up. Iterative adaptation in response to performance metrics foster feasible, acceptable, and efficient TB case-finding in Nigeria. High CAD scores can identify subclinical TB and those at risk of progression to bacteriologically-confirmed TB disease in the near term.
RESUMEN
SETTING: Nigeria adopted GeneXpert MTB Rif as a primary diagnostic tool were available and accessible since 2016. The current geographical coverage of GeneXpert machines by LGAs stands at 48%, with a varied access and utilization. OBJECTIVES: To assess the association between the type and level of health facilities implementing GeneXpert MTB/Rif and performance outcome of the machines in Nigeria. STUDY DESIGN: Retrospective secondary data analysis of GeneXpert performance for 2017 from GXAlert database. The independent variables were type and levels of health care facilities, and dependent variables were GeneXpert performance (utilization, successful test, error rates, MTB detected, and Rifampicin resistance detected). RESULTS: Only 366 health care facilities are currently implementing and reporting GeneXpert performance, the distribution is 86.9% and 13.1% public and private health care facilities respectively, and only 6.3% of the facilities are primary health care. Of 354,321 test conducted in 2017, 91.5% were successful, and among unsuccessful test 6.8% were errors. The yield was 16.8% MTB detected (54,713) among which 6.8% had Rif resistance. The GeneXpert utilization rate was higher among private health care facilities (55.8%) compared to 33.3% among public health care facilities. There was a statistically significant difference in the number of successful test between public and private health facility-based machines as determined by one-way ANOVA (F(1,2) = 21.81, P = 0.02) and between primary, secondary and tertiary level health facility-based machines (F(1,2) = 41.24, P < 0.01). CONCLUSION: Nigeria with very low TB coverage should rapidly scale-up and decentralize GeneXpert services to the private sector.