PLoS Medicine
(Accessed 5 October 2013)
http://www.plosmedicine.org/

Policy Forum
Methodological and Policy Limitations of Quantifying the Saving of Lives: A Case Study of the Global Fund’s Approach
David McCoy, Nele Jensen, Katharina Kranzer, Rashida A. Ferrand, Eline L. Korenromp
http://www.plosmedicine.org/article/info%3Adoi%2F10.1371%2Fjournal.pmed.1001522

Summary Points
:: A recent trend in global health has been a growing emphasis on assessing the effectiveness and impact of specific health interventions.
:: For example, it has been estimated that 8.7 million lives were saved between 2002 and mid-2012 by “Global Fund–supported programmes” (as distinct from The Global Fund alone) through antiretroviral therapy (ART); directly observed tuberculosis treatment, short course (DOTS); and distribution of insecticide-treated mosquito nets (ITNs).
:: This paper assesses the methods used by The Global Fund to quantify “lives saved,” highlights the uncertainty associated with the figures calculated, and suggests that the methods are likely to overestimate the number of “lives saved.”
:: The paper also discusses how the attribution of “lives saved” to specific programmes or actors might negatively affect the overall governance and management of health systems, and how a narrow focus on just ART, DOTS, and ITNs could neglect other interventions and reinforce vertical programmes.
:: Furthermore, the attribution of “lives saved” to Global Fund–supported programmes is potentially misleading, because such programmes include an unstated degree of financial support from recipient governments and other donors.

Perspective
Saving Lives in Health: Global Estimates and Country Measurement
Daniel Low-Beer, Ryuichi Komatsu, Osamu Kunii
http://www.plosmedicine.org/article/info%3Adoi%2F10.1371%2Fjournal.pmed.1001523

Extract
One of the most compelling reasons for development aid to health is that it saves lives, often for a few hundred dollars per year of life saved. Relatively uniquely in development, health has a set of high-impact interventions that can save lives directly. Insecticide-treated bednets (ITNs) protect families from malaria, antiretrovirals (ARVs) reduce mortality from HIV, and tuberculosis detection and treatment reduce TB mortality. Prevention activities, particularly for HIV, can save millions more lives. Yet, health programs have not always communicated with simple methods the lives they save.

In this week’s PLOS Medicine David McCoy and colleagues discuss the “lives saved” model of The Global Fund to Fight AIDS, Tuberculosis and Malaria (The Global Fund). The Global Fund, together with WHO, UNAIDS, and scientists from the article by McCoy and colleagues [1],[2], have published simple peer-reviewed methods to calculate the lives saved from a restricted set of HIV, TB, and malaria interventions that have known mortality outcomes [3]–[7]. Our method includes only those health interventions with known, documented mortality effects: ARV treatment; directly observed treatment, short-course (DOTS); and ITNs. Our methodology uses documented data reported to the Global Fund on the individuals receiving these services. These results are first verified by national disease programs (we invest 5%–10% of our funds to build the capacity of country monitoring and evaluation systems), then by the Global Fund (which uses independent local fund agents to check the national data systems measuring these services every six months), and finally by on-site checks in a sample of health facilities to verify that people receive these services (as part of performance-based funding) [8].

In addition, the Global Fund’s method applies the agreed, partner mortality estimates and models from WHO and UNAIDS [4] to these service results—for example, the latest scientific data on how HIV treatment or TB treatment will reduce the chance that a person will die of HIV or TB.

Extensive criteria are used to exclude countries where The Global Fund is not a significant contributor; that is, where The Global Fund does not contribute at least US$50 million; is a significant percentage of HIV, TB, and malaria spending; and does not support a key national-level activity, such as drug procurement. Where this does not occur, as has been the case in Uganda, Kenya, or South Africa in recent years, the results are not included.

The method to assess lives saved provides a conservative estimate. The estimate [3],[4] does not include the impact of HIV prevention (which in certain countries—e.g., Thailand, Uganda, Kenya, and Zimbabwe—has saved several million lives per country); the impact of malaria outside Africa and among adults; and the significant, secondary impact of DOTS treatment on reducing TB (as shown by the declines in TB prevalence in China, and in TB prevalence by 45% in Cambodia). Furthermore, reporting of services by programs in country are subject to substantial delays before they are reported globally. The most recent scale up in ITNs and ARV treatment are not fully included; for example, the lives saved are only half the number of people reported on ARVs. We do acknowledge the method [3],[4] has major limitations. Most importantly, it does not directly measure mortality, because in many countries in which we work vital registration systems are too weak, so the method is based on the latest partner estimates of mortality from WHO and UNAIDS.

The article in this week’s PLOS Medicine by David McCoy and colleagues has great value in discussing the assumptions in the methods the Global Fund uses to assess lives saved and the partner estimates—of ARV adherence, use of ITNs, and the limitations of focusing only on a limited set of services. We agree that assumptions require additional sensitivity analysis, and we will update our estimates in 2014 as modeling is refined with new and improved data from country impact evaluations and updated WHO and UNAIDS estimates. We have published more detailed analysis of the ARV, ITN, and DOTS estimates as used by the McCoy and colleagues  [4]. Yet, the uncertainty ranges, with the lives saved from ITNs as low as 27,000, were based on very limited data and provided little additional value. We fully agree with the need for increased country data on estimates and mortality assumptions of lives saved. Most importantly, global modeling needs strengthening with wider and deeper country measurement of epidemic trends and lives saved…