Results Methodology

The Global Fund is committed to being transparent about the data that we use, the methodologies we adopt, the results we report, and the impact that is achieved by our partnership. The Global Fund is also eager to show the reasoning behind the approaches we take, and any limitations we identify. The 2022 Aid Transparency Index acknowledged the Global Fund’s rigorous systems and commitment to transparency and gave the Global Fund a rating of “Good.”

Notes on Programmatic Results

A Partnership Approach to Results Reporting

This approach to reporting the results and impact of the Global Fund has been developed by the partnership itself, under the leadership of the Board, technical partners and other stakeholders.

The core objective of the Global Fund is to end AIDS, tuberculosis (TB) and malaria by 2030 in the countries where we invest. In developing the Global Fund Strategy 2017-2022, we conducted extensive consultations in 2015 and 2016 across the partnership on how best to report results and measure the impact of Global Fund investments in national programs. The consensus was that full national results were the best way of measuring progress against the targets set out in the Global Fund Strategy 2017-2022 and towards the ultimate goal of ending the three diseases by 2030. National results should therefore be the starting point for any assessment of the Global Fund’s performance. This approach has been maintained in the Global Fund Strategy 2023-2028. The Global Fund’s objective is to ensure the success of the country-led national programs that we support alongside other bilateral and multilateral funders, and to complement countries’ own domestic contributions.

For the reasons above, the Global Fund reports the full national results of the countries where we invest, rather than reporting solely on the specific projects we fund. This reflects a core principle of the Global Fund: We support national health programs and strategies to achieve national goals. By reporting full national results, the Global Fund can show the impact of the programs we support together with all international and national partners. These results demonstrate where countries are on track to achieve the 2030 targets of ending the three diseases. With this approach, we avoid the pitfall of celebrating the achievements of specific programs supported by the Global Fund when a country as a whole is making insufficient progress or sliding backwards. Furthermore, reporting national results prevents misleading efforts to attribute shares of impact to different actors. Most of the programs and interventions the Global Fund supports involve a mix of domestic resourcing and Global Fund investments, and many involve other external donors. Attributing results to different partners in a common program leads to arbitrary assumptions and ignores the inherently interconnected nature of public health interventions.

An example of this would be a national HIV treatment program where the Global Fund procures the antiretrovirals and supports community outreach, PEPFAR funds clinical delivery and laboratory testing, and the government funds the supply chain and underlying infrastructure. In this case, the contribution of each partner is essential for the program to function. Examining scenarios that modify the contribution of a single funder while holding others fixed would likely be misleading or require arbitrary assumptions. Consistent with the collaborative approach in which these programs are funded, the Global Fund believes that where governments, bilateral partners, technical partners and the Global Fund all contribute to the same program, they ought to cite the same results.

Reporting on national results keeps the focus on the big picture and ensures the Global Fund’s interventions are designed to maximize our contribution to achieving each country’s overall goals for the three diseases.

To complement reporting on full national results, the Global Fund provides more granular country profiles for high-impact countries – those with the greatest disease burden. These are updated regularly and are available on the Data Explorer site.

The Global Fund also makes available information on the progress of individual grants in an open data format, accessible via the Global Fund’s Data Service. Data from our portfolio are available through our application programming interface (API), where data sets and reports are available for download. The API is available on the Data Service.

Performance of Global Fund Investments

While the Global Fund focuses our results reporting on national results, we also monitor and report on the performance of specific programs and interventions funded by Global Fund grants. This ensures we are delivering value for money and monitoring the performance of our investments. The Global Fund’s Key Performance Indicators Handbook for the 2023-2028 Strategydownload in English ] encompasses the reporting of specific key performance indicators (KPIs) to our Board on a range of metrics covering areas attributable to the performance of Global Fund investments, such as the performance of individual programs against agreed grant milestones and targets, absorption rates, fulfilment of co-financing commitments, supply chain metrics, performance of equity/gender/human rights indicators, support in delivering people-centered, high-quality services, progress in pandemic preparedness, and health products market-shaping initiatives.

The Global Fund also provides additional country-specific financial and programmatic information to complement our regular reporting on national results and overall KPIs; this enables stakeholders to see how Global Fund investments work alongside the investments of governments and other partners in high impact countries. These country results profiles for high impact countries are available on the Global Fund's Data Explorer site.

Investing in Better Data in Countries

Global Fund investments have been critical in strengthening national digital health information systems, making the right HIV, TB, and malaria data available at the right time. Key Global Fund priorities for supporting digital health information systems are:

  1. Supporting national and sub-national capacity for data analysis, interpretation, and use.
  2. Strengthening the foundations and governance of interoperable national data systems.
  3. Optimizing more advanced levels of digitalization according to country context and readiness (e.g., using maturity profiles).

The Global Fund has invested more than US$150 million annually over the 2021-2023 grant cycle in strengthening digital health and information systems in countries to improve data availability, quality and agility, thus improving how health data and intelligence is interpreted and acted upon. Moreover, the Global Fund has been supporting national health programs in more than 80 countries to apply disease transmission models and costing tools to inform the development of national strategic plans and funding requests, strategically allocating resources across interventions, geographies, and population groups in order to maximize impact. The Global Fund has also been supporting technical partners to institutionalize impact assessments as part of national programs. For example, UNAIDS’ capacity building workshops for disease burden estimation have incorporated impact assessments.

Notes on the Methods to Estimate Lives Saved by HIV, TB and Malaria Global Fund-supported Programs

The methods for reporting on lives saved by Global Fund-supported programs are the same methods currently used by our technical partners (see the details below) and follow the recommendations of an expert group that met in July 2014 to address methodological issues around estimating lives saved. The group included leading experts, technical partners and other global health organizations, including PEPFAR, WHO, UNAIDS, the RBM Partnership to End Malaria and the Stop TB Partnership. The expert group made several recommendations to enhance the Global Fund’s approach to calculating the number of lives saved, and published a detailed meeting report, the Expert Panel on Health Impact of Global Fund Investments Genevadownload in English ] . Furthermore, the Strategic Review 2015, commissioned by the independent Technical Evaluation and Reference Group (TERG) and then reviewed and endorsed by the Global Fund Board’s Strategy Committee, concluded that the model used by the Global Fund to assess impact was satisfactory.

To provide ongoing support and guidance, the Global Fund has also established a modeling guidance group consisting of technical partners, including WHO and UNAIDS, modeling experts from leading academic institutions, and other partners. This expert group provides ongoing advice and technical support on the disease transmission models used by the Global Fund, details methodological issues around measurement of impact and efficiency of Global Fund-supported programs, and addresses the limitations of current approaches.

Data Sources

Every year, WHO and UNAIDS publish updated estimates of burden of HIV, TB and malaria and generate an estimate of lives saved through interventions provided by the national health programs for the three diseases. The figure of lives saved in the Global Fund Results Report 2023 corresponds to the portfolio of countries where the Global Fund has been investing since our inception using the latest WHO estimates of lives saved by TB and malaria interventions and the latest UNAIDS and Avenir Health estimates for lives saved by HIV interventions. The calculations are described below.

Computation Method

The number of lives saved in a given country and year is estimated by subtracting the number of deaths that occurred from the number of deaths that would have occurred in a counterfactual hypothetical scenario where key disease interventions did not take place, as follows:

In the period defined by uppercase tau symbol, the lives saved is estimated as:
Formula used to calculate lives saved
where Delta D x Taurepresents disease-specific deaths averted and Uppercase X symbol represents the different diseases, consisting of:

  • HIV
  • TB among HIV-negative persons[1]
  • Malaria

For the report published in September 2023, uppercase tau symbol represents the full calendar years of 2005-2022 inclusive.

In each case, for each disease, deaths averted are calculated as the difference in deaths occurring over period uppercase tau symbol under two scenarios, computed as:
Formula used to calculate deaths averted

 is a model for disease Lowercase x symbol in country Lowercase c cymbol, that represents the observed course of the epidemic;  represents the same model estimated under a counterfactual scenario, representing the absence of effort to combat the disease (the derivations of these models for each disease are described below).  is the number of deaths in year Lowercase t symbol in a particular model; Uppercase C with subscript x is the set of countries in the Global Fund portfolio for disease Lowercase x symbol.

Function x,c,t is the fraction of the national-level impact for that disease in that country in that year that is included in Global Fund reporting. Until the end of 2016, the Global Fund only included the total national number of lives saved for a given supported country where a set of criteria in relation to the reported programmatic results were met. The criteria included meeting a minimum threshold of the Global Fund disbursement to the specific programs, either in absolute number or as a percentage of reported public expenditure. From 2017, and following consultation with the Board and key partners, a fully contributory approach is applied, in which the total number of lives saved is counted for a given year and in a given country where the Global Fund invests. Thus, Function x,c,t is an indicator function for whether a country’s results are included in a particular year; and Function x,c,t equals 1.0 where t is greater than or equal to 2017.

Disease-specific Models

A brief overview of models used by the technical partners to estimate lives saved is provided below.


Details on Spectrum AIM and GOALS models can be found here.

: This model is exactly equal to the respective estimates published by the UNAIDS AIM model.

: This model is identical to with the following exceptions:

In the period prior to 2017:

  • The model used is the AIM model.
  • The coverage of antiretroviral therapy (ART) is assumed to be zero in every year.

In the period since 2017:

  • The model used is the GOALS model, unless the country did not have a GOALS model, in which case its AIM model is used instead.
  • The coverage of ART and all other programs is assumed to be zero in the year 2017 and thereafter.
  • The parameter values relating to “risk behaviors” in the year 2015 are used for every year thereafter.


To estimate the number of deaths averted by TB interventions, the actual numbers of TB deaths is compared with the number of TB deaths that would have occurred in the absence of TB treatment (and without ART provided alongside TB treatment for HIV-positive cases). The latter figure can be estimated conservatively as the number of estimated incident cases multiplied by the relevant estimated case fatality rate (CFR) for untreated TB. CFRs restricted to HIV-negative TB deaths and cases are applied here to avoid double counting with deaths averted from HIV-positive TB patients. The estimate of the number of deaths averted is conservative, because it does not account for the impact of TB services or availability of ART on the level of TB incidence; it also does not account for the indirect, downstream impact of these interventions on future levels of infections, cases and deaths (details on WHO methods for estimation of burden and deaths averted can be found here).

: This model is exactly equal to the respective estimates published by the WHO Global Tuberculosis Programme to estimate the global burden of TB disease and lives saved.

: This model is identical to with the following exception:

  • The CFR for all cases is equal to that for untreated cases (i.e., representing there being no treatment) with no impact transmission or other disease dynamics.

is only defined in respect of the number of deaths, which is derived thus:
Formula used to calculate deaths caused by TB
where Theta symbol is the case-fatality rate for untreated cases. (Note that this value is the same for all countries and over time.)


Applying WHO methods, deaths averted are calculated by comparing the current annual estimated burden of malaria with the per capita at risk malaria mortality rates in the year 2000.

: This model is exactly equal to the respective estimates published by the WHO Global Malaria Programme.

: This model is identical to with the following exceptions:

  • The epidemic rebounds to the extent estimated (non-contemporaneously) to have occurred in the year 2000.

is only defined in respect of the number of deaths, which is derived thus:
Formula used to calculate number of deaths caused by malaria

Where is the ratio of the population at risk in year Lowercase t to that in the year 2000, as per the malaria simulation model of Imperial College London, Uppercase Y zero lowercase c thus:
Formula used to calculate population at risk from malaria

Where Population At Risk is the number of people who are living in malaria risk areas, which is estimated by WHO.

Notes on the method to estimate results of Global Fund investments to mitigate the impact of COVID-19 can be found heredownload in English | Français ] .

[1] For TB, the models are limited to TB among HIV-negative persons; outcomes for HIV-positive persons with TB are counted among the HIV statistics only.