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. Participants with high likelihood on CAD4TB (≥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%). 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 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.

Policy makers, donors, and community advocates are hesitant to invest in the steep infrastructure costs for mobile digital chest x-ray and GeneXpert MTB/RIF (dCXR/GXP) laboratories without a better understanding of how to maximize and sustain their impact. It is rarely possible to conduct the months of local CAD calibration recommended by experts via costly universal testing with a reference standard.4,9 Stakeholder needs and resource limitations require a more rapid and cost-conscious means of setting a sustainable algorithm. Viable, field-robust methodologies are needed, and optimization strategies informed by routine field findings were lacking. A precise assessment of the contribution of routine mobile TB screening has been challenging because few authors fully disaggregate losses along the diagnostic cascade or track TB treatment outcomes. Publication bias has limited access to results of active case finding pilots with suboptimal risk group targeting, community engagement, yield, or treatment outcomes.10–14 Evaluations (and scrutiny) of routine data are needed that make the demands, constraints, costs and choices facing implementers more explicit.

These are data from digital LP chest x-ray images read by CAD4TB version 5 merged with data from 2 G4 Genexpert machines, with a data variable to indicate screening date, cough status, as well as age and sex. 

Two large container trucks housing a lead-lined chest-x-ray suite, reading area, and mobile GeneXpert laboratory were sourced via competitive tendering. Solar panels, shade canopies, anti-theft features were added.

CAD4TB version 4 by Delft Imaging interprets a digital image in less than a minute and can do so consistently during day-long screening events.24–26 The software generates a TB likelihood score between 0 and 100, indicating the extent of lung abnormalities. CAD4TB displays a heatmap pinpointing the size and location affected. The scores are used to set a threshold above which persons are invited for TB testing. Each team had a radiology technologist, laboratory technologists, data clerks, truck driver, and a clinical supervisor. Training was conducted on standard operating procedures (SOPs) drawn from procedural manuals of successful digital chest X-ray (CXR) TB screening programs.27 Experts in social mobilization crafted logos and messaging. The intervention was implemented by KNCV TB Foundation (KNCV) under a cooperative agreement, Challenge TB Project, funded by the United States Agency for International Development (USAID) from 2016 to 2019. 

The community mobilization strategy was geared toward recruitment of men and persons over 30 years of age, because of their elevated vulnerability. Men tend to be less likely to participate in community TB screening, so dedicated efforts are often required to attain a high risk participant mix.20,28 Aiming for a high-risk pool with a pulmonary TB prevalence of 1,000/100,000 per population with an estimated 85% sensitivity of the algorithm, we expected an average daily yield of 1.7 persons with bacteriologically-confirmed TB.

The intervention was carried out in three phases across four states (See Figure 2 of Eneogu et al. in PLOSGH).  First, a “Calibration phase” was undertaken to identify a feasible CAD4TB score threshold for GeneXpert test eligibility that would ensure a reasonable TB yield given varying micro-epidemic conditions and to ensure value for money.. Rigorous calibration would have required TB testing of approximately 30,000 people at low risk over a six-month period, at cartridge cost of 300,000 USD.  Instead, a sensitive algorithm comprised of a low testing threshold (CAD4TB score ≥ 40) and a classic symptom screen (cough of ≥two weeks) were trialed over 8 days (n=1875).  Persons with CAD4TB scores ≥ 80 and negative spot TB test results were followed up three to six months later to identify missed TB from GeneXpert MTB/RIF testing on a single spot sample. Emphasis was placed on implementation of a simple algorithm to facilitate the highest volume screening of highest risk adults while minimizing the participation burden and risk/benefit balance. Pilots were executed in two regions (North, South), to field test the approach. The third phase (“Scale-up”) leveraged learning from the calibration and pilots to refine strategy. Persons classified as presumptive for TB followed the national guidelines.  Before treatment initiation, a risk factor and clinical interview of bacteriologically confirmed PTB was added to preclude over-diagnosis.Findings from each phase informed the design of the subsequent phase.  Iterative modification of procedures, strategies, CAD test thresholds and targets occurred after review of prior phase results.