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Optimum resource allocation to reduce HIV incidence across sub-Saharan Africa: a mathematical modelling study

Wednesday, 7th of September 2016

The Lancet HIV Volume 3, No. 9, e441–e448, September 2016

Articles

Optimum resource allocation to reduce HIV incidence across sub-Saharan Africa: a mathematical modelling study

Dr Jessica B McGillen, DPhilPress enter key for correspondence informationPress enter key to Email the author,

Sarah-Jane Anderson, PhD,

Mark R Dybul, MD,

Prof Timothy B Hallett, PhD

Published Online: 02 August 2016

DOI: http://dx.doi.org/10.1016/S2352-3018(16)30051-0

Summary below; full text is at http://www.thelancet.com/journals/lanhiv/article/PIIS2352-3018(16)30051-0/fulltext

Background

Advances in HIV prevention methods offer promise to accelerate declines in incidence, but how these methods can be deployed to have the best effect on the heterogeneous landscape and drivers of the pandemic remains unclear. We postulated that use of epidemic heterogeneity to inform the allocation of resources for combination HIV prevention could enhance the impact of HIV funding across sub-Saharan Africa.

Methods

We developed a compartmental mathematical model of HIV transmission and disease progression by risk group to subnational resolution in 18 countries, capturing 80% of the adult HIV burden in sub-Saharan Africa. Adults aged 15–49 years were grouped by risk of HIV acquisition and transmission, and those older than 50 years were assumed to have negligible risk. For each top-level administrative division, we calibrated the model to historical data for HIV prevalence, sexual behaviours, treatment scale-up, and demographics. We then evaluated four strategies for allocation of prevention funding over a 15 year period from 2016 to 2030, which exploited epidemic differences between subnational regions to varying degrees.

Findings

For a $US20 billion representative expenditure over the 15 year period, scale-up of prevention along present funding channels could avert 5·3 million infections relative to no scale-up. Prioritisation of key populations could avert 3·7 million more infections than present funding channels, and additional prioritisation by within-country geography could avert 400 000 more infections. Removal of national constraints could avert a further 600 000 infections. Risk prioritisation has greater marginal impact than geographical prioritisation across multiple expenditure levels. However, targeting by both risk and geography is best for total impact and could achieve gains of up to three times more than present channels. A shift from the present pattern to the optimum pattern would rebalance resources towards more cost-effective interventions and emerging epidemics.

Interpretation

If domestic and international funders were to align strategically to build an aggregate funding pattern that is guided by the epidemiology of HIV, and particularly by the emerging understanding of local dynamics and epidemic drivers, more cost-effective and impactful HIV prevention investments could be achieved across sub-Saharan Africa.

Funding

The Bill & Melinda Gates Foundation.