Getting resources to those who need them: the evidence we need to budget for underserved populations in sub‐Saharan Africa

• Published in: Journal of the International AIDS Society Vol. 24; no. S3; pp. 67 - n/a
• Main Authors: Long, Lawrence C, Rosen, Sydney, Nichols, Brooke, Larson, Bruce A, Ndlovu, Nhlanhla, Meyer‐Rath, Gesine
• Format: Journal Article
• Language: English
• Published: Geneva John Wiley & Sons, Inc 01-07-2021; John Wiley and Sons Inc
• Subjects: Acquired immune deficiency syndrome; Africa; AIDS; Budget; Budgeting; Budgets; Care and treatment; cost; Cost estimates; Demographic aspects; Disease transmission; Economic aspects; Epidemics; Evaluation; Federal aid to community health services; Health care rationing; HIV; HIV infection; HIV infections; Human immunodeficiency virus; Infections; Intervention; Methods; Population number; Prevention; Program budgeting; Public health administration; Resource allocation; Sub-Saharan Africa; Supplement; vulnerable populations; Sub-Saharan Africa; South Africa; Africa
• ISSN: 1758-2652; 1758-2652
• DOI: 10.1002/jia2.25707

Introduction
In recent years, many countries have adopted evidence‐based budgeting (EBB) to encourage the best use of limited and decreasing HIV resources. The lack of data and evidence for hard to reach, marginalized and vulnerable populations could cause EBB to further disadvantage those who are already underserved and who carry a disproportionate HIV burden (USDB). We outline the critical data required to use EBB to support USDB people in the context of the generalized epidemics of sub‐Saharan Africa (SSA).
Discussion
To be considered in an EBB cycle, an intervention needs at a minimum to have an estimate of a) the average cost, typically per recipient of the intervention; b) the effectiveness of the intervention and c) the size of the intervention target population. The methods commonly used for general populations are not sufficient for generating valid estimates for USDB populations. USDB populations may require additional resources to learn about, access, and/or successfully participate in an intervention, increasing the cost per recipient. USDB populations may experience different health outcomes and/or other benefits than in general populations, influencing the effectiveness of the interventions. Finally, USDB population size estimation is critical for accurate programming but is difficult to obtain with almost no national estimates for countries in SSA. We explain these limitations and make recommendations for addressing them.
Conclusions
EBB is a strong tool to achieve efficient allocation of resources, but in SSA the evidence necessary for USDB populations may be lacking. Rather than excluding USDB populations from the budgeting process, more should be invested in understanding the needs of these populations.