Impact of the Stool-Based Xpert Test on Childhood Tuberculosis Diagnosis in Selected States in Nigeria.

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.

Iterative evaluation of mobile computer-assisted digital chest x-ray screening for TB improves efficiency, yield, and outcomes in Nigeria.

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.

Identifying Hot Spots of Tuberculosis in Nigeria Using an Early Warning Outbreak Recognition System: Retrospective Analysis of Implications for Active Case Finding Interventions.

BACKGROUND: Undiagnosed tuberculosis (TB) cases are the major challenge to TB control in Nigeria. An early warning outbreak recognition system (EWORS) is a system that is primarily used to detect infectious disease outbreaks; this system can be used as a case-based geospatial tool for the real-time identification of hot spot areas with clusters of TB patients. TB screening targeted at such hot spots should yield more TB cases than screening targeted at non-hot spots. OBJECTIVE: We aimed to demonstrate the effectiveness of an EWORS for TB hot spot mapping as a tool for detecting areas with increased TB case yields in high TB-burden states of Nigeria. METHODS: KNCV Tuberculosis Foundation Nigeria deployed an EWORS to 14 high-burden states in Nigeria. The system used an advanced surveillance mechanism to identify TB patients' residences in clusters, enabling it to predict areas with elevated disease spread (ie, hot spots) at the ward level. TB screening outreach using the World Health Organization 4-symptom screening method was conducted in 121 hot spot wards and 213 non-hot spot wards selected from the same communities. Presumptive cases identified were evaluated for TB using the GeneXpert instrument or chest X-ray. Confirmed TB cases from both areas were linked to treatment. Data from the hot spot and non-hot spot wards were analyzed retrospectively for this study. RESULTS: During the 16-month intervention, a total of 1,962,042 persons (n=734,384, 37.4% male, n=1,227,658, 62.6% female) and 2,025,286 persons (n=701,103, 34.6% male, n=1,324,183, 65.4% female) participated in the community TB screening outreaches in the hot spot and non-hot spot areas, respectively. Presumptive cases among all patients screened were 268,264 (N=3,987,328, 6.7%) and confirmed TB cases were 22,618 (N=222,270, 10.1%). The number needed to screen to diagnose a TB case in the hot spot and non-hot spot areas was 146 and 193 per 10,000 people, respectively. CONCLUSIONS: Active TB case finding in EWORS-mapped hot spot areas yielded higher TB cases than the non-hot spot areas in the 14 high-burden states of Nigeria. With the application of EWORS, the precision of diagnosing TB among presumptive cases increased from 0.077 to 0.103, and the number of presumptive cases needed to diagnose a TB case decreased from 14.047 to 10.255 per 10,000 people.

Budgetary impact of using BPaL for treating extensively drug-resistant tuberculosis.

INTRODUCTION: Bedaquiline, pretomanid and linezolid (BPaL) is a new all oral, 6-month regimen comprised of bedaquiline, the new drug pretomanid and linezolid, endorsed by the WHO for use under operational research conditions in patients with extensively drug-resistant tuberculosis (XDR-TB). We quantified per-patient treatment costs and the 5-year budgetary impact of introducing BPaL in Indonesia, Kyrgyzstan and Nigeria. METHODS: Per-patient treatment cost of BPaL regimen was compared head-to-head with the conventional XDR-TB treatment regimen for respective countries based on cost estimates primarily assessed using microcosting method and expected frequency of each TB service. The 5-year budget impact of gradual introduction of BPaL against the status quo was assessed using a Markov model that represented patient's treatment management and outcome pathways. RESULTS: The cost per patient completing treatment with BPaL was US$7142 in Indonesia, US$4782 in Kyrgyzstan and US$7152 in Nigeria - 57%, 78% and 68% lower than the conventional regimens in the respective countries. A gradual adoption of the BPaL regimen over 5 years would result in an 5-year average national TB service budget reduction of 17% (US$128 780) in XDR-TB treatment-related expenditure in Indonesia, 15% (US$700 247) in Kyrgyzstan and 32% (US$1 543 047) in Nigeria. CONCLUSION: Our study demonstrates that the BPaL regimen can be highly cost-saving compared with the conventional regimens to treat patients with XDR-TB in high drug-resistant TB burden settings. This supports the rapid adoption of the BPaL regimen to address the significant programmatic and clinical challenges in managing patients with XDR-TB in high DR-TB burden countries.

Assessment of GeneXpert MTB/RIF Performance by Type and Level of Health-Care Facilities in Nigeria.

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.