A Case Study on How Allocative Efficiency Analysis Supported by Mathematical Modelling Changed HIV Investment in Sudan
This brief presents a real-life example of how a group of government decision-makers, programme managers, researchers and development partners worked together to improve the allocation of HIV resources in Sudan and thereby better address the HIV ob...
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| Language: | English en_US |
| Published: |
World Bank, Washington, DC
2016
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| Online Access: | http://documents.worldbank.org/curated/en/2016/07/26570785/analysis-action-case-study-allocative-efficiency-analysis-supported-mathematical-modelling-changed-hiv-investment-sudan http://hdl.handle.net/10986/24989 |
| Summary: | This brief presents a real-life example
of how a group of government decision-makers, programme
managers, researchers and development partners worked
together to improve the allocation of HIV resources in Sudan
and thereby better address the HIV objectives that the
country strives to achieve. The initial modelling analysis
showed that by reallocating funds towards antiretroviral
treatment (ART) and prevention programmes in Sudan, 37
percent of new HIV infections could be averted with the same
amount of funding. These allocations combined with
additional technical efficiency gains would allow for
increasing ART coverage from 6 percent in 2013 to 34 percent
in 2017, and more than double programme coverage for key
populations. The reallocations in the 2015 to 2017 HIV
budget for the national response are projected to avert an
additional 3,200 new infections and 1,100 deaths in these
three years compared to initially planned allocations.The
reallocations were achieved through a rigorous HIV
allocative efficiency analysis and evidence-informed policy
process, conducted by a multi-disciplinary team of national
and international partners working for the common goal to
make Sudan’s HIV response more manageable and sustainable.
The case study discusses process and outcomes of this
effort. It also offers some reflections on the application
of mathematical modelling to strengthening decision-making
of finite HIV resources, and some lessons learned about how
to go ‘beyond modelling’ to application of modelled
allocative efficiency improvements to improving actual
budget allocations for better health outcomes. |
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