Background

Evidence favoring earlier HIV ART initiation at high CD4+ T-cell counts (CD4>350/uL) has grown, and guidelines now recommend earlier HIV treatment. However, the cost of providing ART to individuals with CD4>350 in Sub-Saharan Africa has not been well estimated. This remains a major barrier to optimal global cost projections for accelerating the scale-up of ART. Our objective was to compute costs of ART delivery to high CD4+count individuals in a typical rural Ugandan health center-based HIV clinic, and use these data to construct scenarios of efficient ART scale-up.

Methods

Within a clinical study evaluating streamlined ART delivery to 197 individuals with CD4+ cell counts >350 cells/uL (EARLI Study: NCT01479634) in Mbarara, Uganda, we performed a micro-costing analysis of administrative records, ART prices, and time-and-motion analysis of staff work patterns. We computed observed per-person-per-year (ppy) costs, and constructed models estimating costs under several increasingly efficient ART scale-up scenarios using local salaries, lowest drug prices, optimized patient loads, and inclusion of viral load (VL) testing.

Findings

Among 197 individuals enrolled in the EARLI Study, median pre-ART CD4+ cell count was 569/uL (IQR 451-716). Observed ART delivery cost was $628 ppy at steady state. Models using local salaries and only core laboratory tests estimated costs of $529/$445 ppy (+/-VL testing, respectively). Models with lower salaries, lowest ART prices, and optimized healthcare worker schedules reduced costs by $100-200 ppy. Costs in a maximally efficient scale-up model were $320/$236 ppy (+/- VL testing). This included $39 for personnel, $106 for ART, $130/$46 for laboratory tests, and $46 for administrative/other costs. A key limitation of this study is its derivation and extrapolation of costs from one large rural treatment program of high CD4+ count individuals.

Conclusions

In a Ugandan HIV clinic, ART delivery costs--including VL testing--for individuals with CD4>350 were similar to estimates from high-efficiency programs. In higher efficiency scale-up models, costs were substantially lower. These favorable costs may be achieved because high CD4+ count patients are often asymptomatic, facilitating more efficient streamlined ART delivery. Our work provides a framework for calculating costs of efficient ART scale-up models using accessible data from specific programs and regions.