Parameters for the qualitative adjustments for 2017-2019 allocations

6. NEWS
15 Dec 2016
Determined by the Strategy Committee in June 2016

Last June, when the Strategy Committee approved the qualitative adjustment process for 2017-2019 allocations (see GFO article), it also approved the parameters that are being used to make the adjustments in Stage 1 (epidemiological considerations) and Stage 2 (holistic adjustment – primarily absorption and impact).

Epidemiological considerations

As explained in our previous article, the adjustments in Stage 1 account for two factors: (1) populations disproportionately affected by HIV; and (2) settings with low-endemicity malaria.

Populations disproportionately affected by HIV

The adjustment factor is designed to provide “a modest relative upwards adjustment” in the case of epidemics with a high proportion of people living with HIV (PLHIV) amongst key populations, high numbers of key populations in absolute terms (and, therefore, larger prevention needs), and expanding HIV epidemics in key populations.

Each country with general HIV prevalence of less than 2% is assigned a series of weights according to four categories of adjustment. For the first three categories of adjustment, countries are attributed one of five weights, determined by splitting the countries into quintiles. For the fourth category of adjustment, countries are attributed one of three weights. The country’s four weights are then multiplied together to arrive at an amount that translates to an overall percentage increase to the formula-derived allocation amount. The four categories of adjustment, their rationales, and their weights are shown in the table below.

Adjustment parameters: Populations disproportionately affected by HIV

Adjustment Category
Rationale
Weight
Total PLHIV
 
Inversely weighted so that largest epidemics with large formula-derived allocations are not further advantaged
 
5,4,3,2,1
(5 for quintile of lowest formula-derived allocation amounts; 1 for highest)
Proportion of two largest key populations among total PLHIV
 
Weights advantage countries with larger burdens of HIV among key populations
 
1,2,3,4,5
(1 for quintile of lowest proportion of two largest key populations among PLHIV; 5 for highest)
Population size estimate of two largest key population groups
 
To assure funding to countries with sizable key population communities but limited HIV transmission to date, a weighting of key population size provides some advantage to countries with larger prevention needs
 
1,2,3,4,5
(1 for quintile of lowest size estimates of largest two key population groups; 5 for highest)
New HIV infections estimates rising (2010-latest available)
 
Small weight advantage to countries with expanding epidemics among any single key population
 
1.1 if new HIV infections among a single key population group is at least 10% but less than 20%;
1.2 if new HIV infections among a single key population group is at least 20%; or
1 otherwise.

 

The Strategy Committee said that flexibility should be maintained “around the margins” to include or exclude countries in the adjustment factor or modify the adjustment owing to overriding contextual considerations.

The approach approved by the Strategy Committee is designed to ensure that the overall allocation for HIV remains unchanged after the adjustments for populations proportionately affected by HIV are made. The Committee estimated that the adjustments would move about 4.7% of the funds for HIV (close to $250 million) to approximately 80 countries with general HIV prevalence of less than 2%, with around 15 countries seeing no change and about 25 seeing modest decreases. While in absolute terms, the movement of funds is small, the Committee said, “the adjustment factor will result in significant relative increases in funding to these countries with populations disproportionately affected by HIV (median relative increase of almost 30% on their formula-derived allocations).”

Low-endemicity malaria

The adjustment for low-endemicity malaria aims to address the small number of instances where the allocation formula’s burden indicator over-represents current programming needs in settings with low numbers of population at risk.

The adjustment factor will be applied to countries with population at risk of fewer than one million, and will cap their formula-derived allocations at $6 per person at risk of malaria. The Strategy Committee estimated that this approach would cap the formula-derived malaria allocations of eight countries, redistributing approximately $18 million across the remaining portfolio of countries with populations at risk of at least one million.

Absorption and impact

The adjustment for absorption will be based on a calculation of potential absorption. This will be determined by comparing the level of funding anticipated to be utilized from the 2014-2016 allocation period with the 2017-2019 formula-derived allocation amount. The calculation is as follows:

[Actual and forecasted use of funds from 2014-2016 allocation] divided by [2017-2019 formula-derived allocation]

A result significantly greater than 100% would indicate a significant increase in funding scale compared to current allocation period and, therefore, lower potential absorptive capacity. A result significantly less than100% would indicate a significant decrease in funding scale and, therefore, higher potential absorptive capacity. Past absorption levels may still provide useful supportive data and will be included in the list of supportive information (see previous GFO article).

The adjustment for impact will be based on a calculation of potential impact. This will be determined by comparing the projected impact (lives saved; and infections or cases averted) arising from the 2017-2019 formula-derived allocation amount with the 2020 impact targets set out in the technical partners’ global plans. This will indicate what the gap is between projected impact and the targets. The Strategy Committee said that those country programs with a smaller gap will have smaller potential for impact because they have significantly progressed through their impact curve towards being on track with the global plans. Those country programs with a bigger gap will have larger potential for impact, and may need relatively more support in progressing towards the targets.

The Committee said that past impact (incidence and mortality trends) will remain important contextual information, particularly to draw attention to cases of increasing epidemics.

 

 


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