Cost-per-diagnosis as a metric for monitoring cost-effectiveness of HIV testing programmes in low-income settings in southern Africa: health economic and modelling analysis.

Andrew N Phillips ORCID logo; Valentina Cambiano ORCID logo; FumiyoNakagawa; Loveleen Bansi-Matharu ORCID logo; David Wilson ORCID logo; IleshJani; TsitsiApollo; MarkSculpher; TimothyHallett; CliffKerr; +18 more... Joep Jvan Oosterhout; Jeffrey W Eaton ORCID logo; JanneEstill; BrianWilliams; NaokoDoi; Frances Cowan ORCID logo; OliviaKeiser; DeborahFord; Karin Hatzold ORCID logo; RuanneBarnabas; Helen Ayles ORCID logo; GesineMeyer-Rath; LisaNelson; Cheryl Johnson ORCID logo; RachelBaggaley; AdeFakoya; AndreasJahn; PaulRevill; (2019) Cost-per-diagnosis as a metric for monitoring cost-effectiveness of HIV testing programmes in low-income settings in southern Africa: health economic and modelling analysis. Journal of the International AIDS Society, 22 (7). e25325-. ISSN 1758-2652 DOI: 10.1002/jia2.25325
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INTRODUCTION: As prevalence of undiagnosed HIV declines, it is unclear whether testing programmes will be cost-effective. To guide their HIV testing programmes, countries require appropriate metrics that can be measured. The cost-per-diagnosis is potentially a useful metric. METHODS: We simulated a series of setting-scenarios for adult HIV epidemics and ART programmes typical of settings in southern Africa using an individual-based model and projected forward from 2018 under two policies: (i) a minimum package of "core" testing (i.e. testing in pregnant women, for diagnosis of symptoms, in sex workers, and in men coming forward for circumcision) is conducted, and (ii) core-testing as above plus additional testing beyond this ("additional-testing"), for which we specify different rates of testing and various degrees to which those with HIV are more likely to test than those without HIV. We also considered a plausible range of unit test costs. The aim was to assess the relationship between cost-per-diagnosis and the incremental cost-effectiveness ratio (ICER) of the additional-testing policy. The discount rate used in the base case was 3% per annum (costs in 2018 U.S. dollars). RESULTS: There was a strong graded relationship between the cost-per-diagnosis and the ICER. Overall, the ICER was below $500 per-DALY-averted (the cost-effectiveness threshold used in primary analysis) so long as the cost-per-diagnosis was below $315. This threshold cost-per-diagnosis was similar according to epidemic and programmatic features including the prevalence of undiagnosed HIV, the HIV incidence and a measure of HIV programme quality (the proportion of HIV diagnosed people having a viral load <1000 copies/mL). However, restricting to women, additional-testing did not appear cost-effective even at a cost-per-diagnosis of below $50, while restricting to men additional-testing was cost-effective up to a cost-per-diagnosis of $585. The threshold cost per diagnosis for testing in men to be cost-effective fell to $256 when the cost-effectiveness threshold was $300 instead of $500, and to $81 when considering a discount rate of 10% per annum. CONCLUSIONS: For testing programmes in low-income settings in southern African there is an extremely strong relationship between the cost-per-diagnosis and the cost-per-DALY averted, indicating that the cost-per-diagnosis can be used to monitor the cost-effectiveness of testing programmes.



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