Benefit incidence analysis of decentralized Truenat MTB Plus and MTB-RIF Dx compared to hub-and-spoke Xpert MTB/RIF in Mozambique and Tanzania (TB-CAPT CORE trial)
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Introduction
Tuberculosis (TB) is a major public health threat worldwide and about one-third of cases go undiagnosed or unreported, leading to continued transmission of the disease. While point-of-care diagnostics are crucial to improve case detection, their distributional financial impact remains underexplored. Understanding how the costs and benefits of these tools are distributed across socio-economic groups is critical to ensure equitable access. This study aims to estimate the benefit incidence of implementing Truenat MTB Plus and Truenat MTB-RIF Dx at point-of-care (intervention arm), compared to the hub-and-spoke Cepheid Xpert MTB/RIF (‘Xpert‘) system or onsite sputum-smear microscopy test (control arm), considering utilisation across the wealth quintiles in Mozambique and Tanzania.
Methods
We conduct a benefit incidence analysis (BIA) using data derived from the TB-CAPT CORE multi-center, cluster randomized controlled trial with a sub-study on patient and provider costs. Our main outcome measure was diagnosis and TB treatment initiation within 7 days of diagnosis. Both patient and health system costs were included in our analysis. We estimated the benefit incidence from health system or societal perspective (combining both patient and health system) for each TB diagnostic strategy reported across wealth quintiles. We constructed concentration curves to visualize the cumulative share of benefit incidence distribution and estimate indices to quantity the magnitude of inequality in benefit for the trial arm and country.
Result
The proportion of people diagnosed with TB and started on treatment was significantly higher among the poorest quintiles (28 patients (25%) in Mozambique and 35 patients (27%) in Tanzania) compared to the least poor quintiles (20 patients (18%) in Mozambique and 15 patients (12%) in Tanzania). A total of 147 individuals in the intervention group initiated TB treatment within 7 days, compared to 95 in the control group. This reflects the intervention arm had more than 1.5 times higher rates of TB treatment initiation compared to control arm. This difference was especially notable in Mozambique. While the societal cost of TB treatment initiation was higher in the intervention arm as compared to the control arm, the public benefit for treatment initiation was more beneficial to poorer populations, with the benefit incidence slightly skewed towards the poor (concentration index of –0.0816 (confidence interval: – 0.0829: – 0.0804)).
Conclusion
The decentralized Point-of-care (POC) testing substantially improved TB treatment initiation within 7 days compared to standard care, ensuring that the investment reached those who need it most, particularly the poorest population subgroups. These finding showed a pro-poor distribution of benefit incidence emphasizing the importance of decentralized POC to improve diagnostic access and promote equity.
