Browsing by Author "Hallett, Timothy"
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- ItemCost-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(International AIDS Society, 2019) Phillips, Andrew N.; Cambiano, Valentina; Nakagawa, Fumiyo; Bansi-Matharu, Loveleen; Wilson, David; Jani, Ilesh; Apollo, Tsitsi; Sculpher, Mark; Hallett, Timothy; Kerr, Cliff; Van Oosterhout, J.; Eaton, Jeffrey W.; Estill, Janne; Williams, Brian; Doi, Naoko; Cowan, Frances; Keiser, Olivia; Ford, Deborah; Hatzold, Karin; Barnabas, Ruanne; Ayles, Helen; Meyer-Rath, Gesine; Nelson, Lisa; Johnson, Cheryl; Baggaley, Rachel; Fakoya, Ade; Jahn, Andreas; Revill, PaulIntroduction: 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 (“additionaltesting”), 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.
- ItemEstimating HIV incidence among adults in Kenya and Uganda : a systematic comparison of multiple methods(Public Library of Science, 2011-03-07) Kim, Andrea A.; Hallett, Timothy; Stover, John; Gouws, Eleanor; Musinguzi, Joshua; Mureithi, Patrick K.; Bunnell, Rebecca; Hargrove, John; Mermin, Jonathan; Kaiser, Reinhard K.; Barsigo, Anne; Ghys, Peter D.Background: Several approaches have been used for measuring HIV incidence in large areas, yet each presents specific challenges in incidence estimation. Methodology/Principal Findings: We present a comparison of incidence estimates for Kenya and Uganda using multiple methods: 1) Epidemic Projections Package (EPP) and Spectrum models fitted to HIV prevalence from antenatal clinics (ANC) and national population-based surveys (NPS) in Kenya (2003, 2007) and Uganda (2004/2005); 2) a survey-derived model to infer age-specific incidence between two sequential NPS; 3) an assay-derived measurement in NPS using the BED IgG capture enzyme immunoassay, adjusted for misclassification using a locally derived false-recent rate (FRR) for the assay; (4) community cohorts in Uganda; (5) prevalence trends in young ANC attendees. EPP/Spectrum-derived and survey-derived modeled estimates were similar: 0.67 [uncertainty range: 0.60, 0.74] and 0.6 [confidence interval: (CI) 0.4, 0.9], respectively, for Uganda (2005) and 0.72 [uncertainty range: 0.70, 0.74] and 0.7 [CI 0.3, 1.1], respectively, for Kenya (2007). Using a local FRR, assay-derived incidence estimates were 0.3 [CI 0.0, 0.9] for Uganda (2004/2005) and 0.6 [CI 0, 1.3] for Kenya (2007). Incidence trends were similar for all methods for both Uganda and Kenya. Conclusions/Significance: Triangulation of methods is recommended to determine best-supported estimates of incidence to guide programs. Assay-derived incidence estimates are sensitive to the level of the assay's FRR, and uncertainty around high FRRs can significantly impact the validity of the estimate. Systematic evaluations of new and existing incidence assays are needed to the study the level, distribution, and determinants of the FRR to guide whether incidence assays can produce reliable estimates of national HIV incidence.