Designing an optimal HIV programme for South Africa: Does the optimal package change when diminishing returns are considered?

Calvin Chiu,Lise Jamieson,Leigh F Johnson,Gesine Meyer-Rath,Bruce A Larson

doi:10.1186/s12889-017-4023-3

Abstract

BackgroundSouth Africa has a large domestically funded HIV programme with highly saturated coverage levels for most prevention and treatment interventions. To further optimise its allocative efficiency, we designed a novel optimisation method and examined whether the optimal package of interventions changes when interaction and non-linear scale-up effects are incorporated into cost-effectiveness analysis.MethodsThe conventional league table method in cost-effectiveness analysis relies on the assumption of independence between interventions. We added methodology that allowed the simultaneous consideration of a large number of HIV interventions and their potentially diminishing marginal returns to scale. We analysed the incremental cost effectiveness ratio (ICER) of 16 HIV interventions based on a well-calibrated epidemiological model that accounted for interaction and non-linear scale-up effects, a custom cost model, and an optimisation routine that iteratively added the most cost-effective intervention onto a rolling baseline before evaluating all remaining options. We compared our results with those based on a league table.ResultsThe rank order of interventions did not differ substantially between the two methods- in each, increasing condom availability and male medical circumcision were found to be most cost-effective, followed by anti-retroviral therapy at current guidelines. However, interventions were less cost-effective throughout when evaluated under the optimisation method, indicating substantial diminishing marginal returns, with ICERs being on average 437% higher under our optimisation routine.ConclusionsConventional league tables may exaggerate the cost-effectiveness of interventions when programmes are implemented at scale. Accounting for interaction and non-linear scale-up effects provides more realistic estimates in highly saturated real-world settings.

Highlights

South Africa has a large domestically funded Human immunodeficiency virus (HIV) programme with highly saturated coverage levels for most prevention and treatment interventions
South Africa is in the unique position of having a preexisting, well-calibrated HIV transmission model that already takes into account those non-linear effects as well as interaction effects between interventions, the Thembisa model [16], which we extended with a custom cost model and optimisation routine
Comparing our novel optimisation routine against conventional cost-effectiveness analysis methods using interventions included in the South African Investment Case as a case study, we found substantial gains in analytical precision from our methodology

Summary

Introduction

South Africa has a large domestically funded HIV programme with highly saturated coverage levels for most prevention and treatment interventions. A. Chiu et al BMC Public Health (2017) 17:143 recent combined analysis of 12 mathematical models examined the cost and cost-effectiveness of expanded treatment coverage and/or eligibility criteria for antiretroviral therapy (ART) [5]. The Bärnighausen, Bloom and Humair model compared medical male circumcision (MMC) against the provision of ART at current guidelines vs universal testing and treatment and applied it to several countries in sub-Saharan Africa [6]. Focusing on South Africa, Long et al evaluated the cost-effectiveness of a range of interventions (ART, MMC, pre-exposure prophylaxis (PrEP), microbicides) both singularly and in combination [7]. Anderson et al evaluated the impact at a subnational level of a similar package of interventions on the Kenyan HIV epidemic, targeting specific geographic locations that had high concentrations of female sex workers and men who have sex with men [8]

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