Improving rifampicin-resistant tuberculosis diagnosis using Xpert® MTB/RIF: modelling interventions and costs

Setting Cape Town, South Africa Objective To model RMP-R diagnosis and laboratory costs in smear/culture and Xpert-based algorithms and the effect of varying adherence and HIV testing in the Xpert-based algorithm. Methods We used a validated operational model (100,000 population) and published laboratory cost data. We estimated the number and cost of RMP-R TB cases identified between a smear/culture and Xpert-based algorithm. We modelled varying adherence and different levels of known HIV-status to the Xpert-based algorithm. Results RMP-R TB cases identified increased from 603 with smear/culture to 1,178 with the Xpert-based algorithm (100% adherence - 60% knew their HIV status). The overall laboratory cost increased from U$1,073,858 to U$2,430,050 and the cost per RMP-TB case identified increased from U$1,781 to U$2,063 in respective algorithms. When adherence to the Xpert-based algorithm was increased from 50% to 100% (60% knew their HIV-status), the number of RMP-R TB cases identified increased from 721 to 1,178. Conclusion The Xpert-based algorithm is efficient in identifying RMP-R TB as the increase in costs is offset by the increase in the number of cases identified. Adherence to the Xpert-based algorithm is important to ensure all presumptive TB cases receive the benefit of simultaneous TB and RMP-R testing.