Modelling Methods of Economic Evaluations of HIV Testing Strategies in Sub-Saharan Africa: A Systematic Review

Abstract

BackgroundEconomic evaluations (EEs), a decision-support tool for policy makers, will be crucial in planning and tailoring HIV prevention and treatment strategies especially in the wake of stalled and decreasing funding for the global HIV response. As HIV testing and treatment coverage increase, case-identification becomes increasingly difficult and costly. Determining which subset of the population these strategies should be targeted to, becomes of vital importance as well. Generating quality economic evidence begins with the validity of the modelling approach and the model structure employed. This study synthesizes and critiques the reporting around modelling methodology of economic models in the evaluation of HIV testing strategies in sub-Saharan Africa (SSA). MethodsThe following databases were searched from Jan 2000 -Sept 2020: Medline, Embase, Scopus, EconLit and Global Health. Any model-based EE of a unique HIV testing strategy conducted in SSA presenting a costeffectiveness measure published from 2013 onwards was eligible. Data were extracted around three components: general study characteristics; EE design; and quality of model reporting using a novel tool developed for the purposes of this study. ResultsA total of 21 studies were included; 10 cost-effectiveness analysis, 11 cost-utility analysis. All but one study was conducted in Eastern and Southern Africa. Modelling approaches for HIV testing strategies can be broadly characterized as static aggregate models (3/21); static individual models (6/21); dynamic aggregate models (5/21); dynamic individual models (7/21). Adequate reporting around data handling was the highest of the three categories assessed (74%), and model validation, the lowest (45%). Limitations to model structure, justification of chosen time horizon and cycle length, and description of external model validation process, were all adequately reported in less than 40% of studies. The predominant limitation of this review relates to the potential implications of the narrow inclusion criteria. ConclusionsThis review is the first to synthesize EEs of HIV testing strategies in SSA. The majority of models exhibited dynamic, stochastic and individual properties. Model reporting against the 13 criteria in our novel tool was mixed. Future model-based EEs of HIV testing strategies would benefit from transparency around choice of modelling approach, model structure, data handling procedures and model validation techniques.

Cost‐effectiveness analysis of community‐led HIV self‐testing among key populations in Côte d'Ivoire, Mali, and Senegal

“…Although clients and sexual partners of KP are not included within the KP definition, they are important to overall HIV transmission dynamics [ 7 , 8 , 9 , 10 ]. However, to our knowledge, no studies have been conducted on the cost‐effectiveness of KP‐led distribution of HIVST in Western Africa [ 11 ]. In this region, more than half of new acquisitions are likely among KP [ 12 , 13 ].…”