The important role of computer-assisted digital chest x-ray screening as a triage tool for identifying people who would benefit from molecular TB diagnostic testing is well documented.[1–3] Although the prospects for a biomarker test in the medium term are good, at present there are no robust triage alternatives to x-ray for most settings.[4–6] While there is now consensus that digital chest x-ray followed by rapid PCR-based testing is the only option in many settings, there are still uncertainties about how best to operationalize this algorithm in low resource settings. Many high burden settings lack enough radiology personnel in the public sector to rapidly interpret the high volumes of chest x-rays.[7, 8] Most images in TB screening show no anomalies or very early disease and are thus time-consuming to read and rule-out. Computer-assisted digital chest x-ray is a technology with potential to rapidly identify those with a high pre-test probability of TB from among a large volume of healthy persons so that a feasible sub-set can be tested.
We report the results of an iterative process to develop and refine TB triage, testing, and treatment algorithm for urban residents of four Nigerian states, in both the southern (Ogun, Lagos) and northern (Kano and Nasarawa) regions, using computer-aided detection (CAD) software program. We describe the operational steps to engage community leaders, define beneficiary groups and participant risk mix, and identify acceptable, feasible, and high transmission settings for high-volume active case finding. Planning processes to ensure yield, flow, confidentiality, and quality of care are summarized. The challenges, miscalculations, and debates during the pilot phase are included to highlight operational lessons useful to implementers elsewhere.
Policy makers, donors, and community advocates are hesitant to invest in the steep infrastructure costs for mobile chest x-ray and GeneXpert MTB/RIF laboratories without a better understanding of how to maximize their impact. A precise assessment of the contribution of mobile TB screening has been challenging because publication bias has limited access to many active case finding projects with poor risk group targeting, scant community engagement, mediocre results, or initial missteps [10–13]. Few authors fully disclose losses along the diagnostic cascade, or report TB treatment outcomes. Finally, few studies have been conducted independently from CAD software developers. To move the field forward it is essential to have a fuller understanding of the demands, constraints, and choices facing implementers and guidance on continuous quality assurance.
Nigeria is a high TB, TB/HIV, and MDR-TB burden country with an estimated TB treatment coverage of 24%. Home to 9% of the world’s missing TB patients, Nigeria has experimented with many models of TB active case-finding (ACF) and results have varied widely.[12, 15–20] Urban Nigeria has an estimated prevalence of bacteriologically-confirmed pulmonary TB between 441-884 cases per 100,000 persons 15 years or older. Prior screening suggested considerable heterogeneity, with high TB yields obtained only with accurate tools and careful attention to participant mix.[16–18, 22, 23]
Nigeria has tried to increase the effectiveness of screening efforts, moving from a three-week chronic cough threshold policy to a two-week cough threshold in 2014, but pulmonary TB (PTB) case notification did not increase significantly. Community referral of chronic coughers is often feasible due to low frequency and high specificity (94%)of chronic cough for TB, the sensitivity of the classical chronic cough screen has recently been downgraded from 56 to 38%.
The Wellness on Wheels (WoW) Intervention
Infrastructure & Staff development
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.
Computer-aided detection for tuberculosis (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.[1–3] The software generates a 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. To determine the threshold, the software is calibrated in each population.
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 CXR TB screening programs. Experts in social mobilization crafted logos and messaging. Staff exposure to radiation was measured through dosimetry as mandated by the Nuclear Regulatory Agency of Nigeria.
Prior to TB screening activity, preparatory visits were made to engage TB stakeholders; sensitize and seek the cooperation of local authorities; assess the feasibility of conducting an effective screening; ensure that all necessary logistics were put in place. The community is mobilized using locally appropriate means such as town announcers, handbills, posters, leaflets, community drama and radio.
Local government TB supervisors, State TB program managers, international and local partners and civil society organizations (CSOs) participated in the inaugural events. Advocacy visits were paid by KNCV active-case finding teams to key stakeholders in Nasarawa state including the governor, local government chairmen and the traditional chiefs particularly the Emir of Lafia detailing the intervention, its objectives and benefits as well as expectations from the selected communities. The initiative was flagged off at the national level in one of the four pilot states, Ogun by the governor supported by the Minister of Health. The flag off brought together different stakeholders including community and religious leaders, community-based organizations, ex-TB patients, different cadre of health workers, security agencies, and political leaders to pledge their support for the intervention. Community leaders, TB program staff, policy makers, and technical experts helped to select the locations for mobile outreach through a participatory mapping process (Table 1).
Strategy and Prioritization
Two week-long planning workshops were held involving state, national, community leadership to plan risk group mix, hot spots, testing algorithms, participant flows and crowd management including retention before screening, performance monitoring and targets. Stakeholders voiced diverse assumptions about the effectiveness of computer-assisted chest x-ray interpretation versus cough screening. To reach consensus on a viable and sustainable approach, sensitivity versus specificity of the screening algorithm and screening quality vs quantity trade-offs were debated. Equity concerns were raised when epidemiologists urged a narrow focus on adult men, older adults, alcohol users, urban poor, prisoners and groups with a higher pre-test probability of TB. Debates ensued about the competing demands of reaching high daily screening volumes versus screening those at highest risk, who would be fewer in number. Modelling diverse yield scenarios helped to make strategic choices and manage expectations of donors, TB program managers, and community leaders (See Supplemental data). The mapping process entailed the identification of groups at higher risk of developing TB disease. These factors included persons sharing similar risk factors for TB such as persons living with HIV and close contacts of pulmonary TB patients or a group of persons living in a specific geographical location associated with high burden of TB e.g. people living in an urban slum or a prison. For each risk group, an estimate of the population and the proportion that could be reached with the screening service was calculated and the number needed to screen (NNS), which itself is a function of the prevalence of TB in the risk group and the screening & diagnostic algorithm, was also estimated. 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.[5, 6] 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. Findings from each phase informed the design of the subsequent phase. Iterative modification of procedures, strategies, test thresholds and targets occurred after review of the results of each phase.
First, a “Calibration phase” was undertaken to assess the viability of the case finding strategy and to identify a feasible TB testing threshold that would ensure a reasonable TB yield given specific micro-epidemic conditions and equipment. It was not possible to conduct the type of calibration that includes precision measurement of algorithm accuracy study via universal testing with a reference standard due to stakeholder opposition and resource limitations. 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.