Yield, Efficiency, and Costs of Mass Screening Algorithms for Tuberculosis in Brazilian Prisons

Abstract

Abstract Background Tuberculosis (TB) is a major cause of morbidity and mortality among incarcerated populations globally. We performed mass TB screening in 3 prisons and assessed yield, efficiency, and costs associated with various screening algorithms. Methods Between 2017 and 2018, inmates from 3 prisons in Brazil were screened for TB by symptom assessment, chest radiography, sputum testing by Xpert MTB/RIF fourth-generation assay, and culture. Chest radiographs were scored by an automated interpretation algorithm (Computer-Aided Detection for Tuberculosis [CAD4TB]) that was locally calibrated to establish a positivity threshold. Four diagnostic algorithms were evaluated. We assessed the yield (percentage of total cases found) and efficiency (prevalence among those screened) for each algorithm. We performed unit costing to estimate the costs of each screening or diagnostic test and calculated the cost per case detected for each algorithm. Results We screened 5387 prisoners, of whom 214 (3.9%) were diagnosed with TB. Compared to other screening strategies initiated with chest radiography or symptoms, the trial of all participants with a single Xpert MTB/RIF sputum test detected 74% of all TB cases at a cost of US$249 per case diagnosed. Performing Xpert MTB/RIF screening tests only on those with symptoms had a similar cost per case diagnosed (US$255) but missed 35% more cases (73 vs 54) as screening all inmates. Conclusions In this prospective study in 3 prisons in a high TB burden country, we found that testing all inmates with sputum Xpert MTB/RIF was a sensitive approach, while remaining cost-efficient. These results support use of Xpert MTB/RIF for mass screening in TB-endemic prisons.