Active case-finding for TB in India: Assessment of scale and quality benchmarks, time taken and use of rapid...

Since 2017, tuberculosis active case-finding (TB ACF) has been implemented within the routine framework of India's national TB elimination program. Symptom screen of high-risk population followed by confirmation of TB among symptom-screen positive is the algorithm. ACF scale and quality assessments hitherto were predominantly local or based on aggregate program data with limited details on all the scale and quality indicators, the time taken and the extent of use of rapid molecular diagnostic tests in ACF care cascade. In this cohort study from high-risk populations in 30 randomly sampled districts (nine states), we assessed one ACF cycle (intention to screen the high-risk population once) during January-September 2023 using prospectively collected individual level data. 581 633 high-risk individuals were screened by the program utilizing existing workforce and resources. The two scale indicators (target, observed) were: percentage of i) population mapped as high-risk (≥11%, 18.3%) and ii) mapped population screened (≥90%, 7.4%). The four quality indicators (target, observed) were: percentage of i) screened identified as presumptive TB (≥5%, 2%) ii) presumptive TB tested (≥95%, 66.3%) iii) tested diagnosed as TB (≥5%, 1.6%) and iv) diagnosed put on treatment (≥95%, 100%). The number needed to screen (target ≤1538 considering the algorithm) to detect one person with TB was 4971. The same was observed across most of the high-risk groups, with few exceptions. The extent of using rapid molecular diagnostic tests was 26.4% and the median time taken from screening to sputum collection and testing was one day. To conclude, ACF scale and quality in 2023, assessed using prospectively collected individual level data, were grossly below the benchmark and lower than previously reported (2021) based on retrospective aggregate program data. Effective planning, resource allocation including use of rapid molecular diagnostic tests and individual data recording among those screened to facilitate implementation monitoring are recommended.