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

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.

Cost-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

INTRODUCTION

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 ("additional-testing"), 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.