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

Abstract

Setting: Cape Town, South Africa.

Objective: To model the diagnosis of rifampicin-resistant tuberculosis (RR-TB) and laboratory costs of smear/culture and Xpert-based algorithms and the effect of varying adherence and human immunodeficiency virus (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 RR-TB cases identified using the smear/culture- and Xpert-based algorithms. We modelled varying adherence and different levels of known HIV status against the Xpert-based algorithm.

Results: The number of RR-TB cases identified increased from 603 with smear/culture to 1178 with the Xpert-based algorithm (100% adherence; 60% knew their HIV status). The overall laboratory cost increased from US$1 073 858 to US$2 430 050 and the cost per RR-TB case identified increased from US$1781 to US$2063 in the respective algorithms. When adherence to the Xpert-based algorithm was increased from 50% to 100% (60% knew their HIV status), the number of RR-TB cases identified increased from 721 to 1178.

Conclusion: The Xpert-based algorithm is efficient in identifying RR-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 that all presumptive TB cases receive the benefit of simultaneous TB and RR-TB testing.