Metric partnerships: global burden of disease estimates within the World Bank, the World Health Organisation and the Institute for Health Metrics and Evaluation

Abstract

The global burden of disease study—which has been affiliated with the World Bank and the World Health Organisation (WHO) and is now housed in the Institute for Health Metrics and Evaluation (IHME)—has become a very important tool to global health governance since it was first published in the 1993 World Development Report. In this article, based on literature review of primary and secondary sources as well as field notes from public events, we present first a summary of the origins and evolution of the GBD over the past 25 years. We then analyse two illustrative examples of estimates and the ways in which they gloss over the assumptions and knowledge gaps in their production, highlighting the importance of historical context by country and by disease in the quality of health data. Finally, we delve into the question of the end users of these estimates and the tensions that lie at the heart of producing estimates of local, national, and global burdens of disease. These tensions bring to light the different institutional ethics and motivations of IHME, WHO, and the World Bank, and they draw our attention to the importance of estimate methodologies in representing problems and their solutions in global health. With the rise in the investment in and the power of global health estimates, the question of representing global health problems becomes ever more entangled in decisions made about how to adjust reported numbers and to evolving statistical science. Ultimately, more work needs to be done to create evidence that is relevant and meaningful on country and district levels, which means shifting resources and support for quantitative—and qualitative—data production, analysis, and synthesis to countries that are the targeted beneficiaries of such global health estimates.

History of global burden of disease assessment at the World Health Organization

“…Apart from the issue that IHME population estimates now differ from those used by the UN agencies, the complexity and computational intensity of IHME data imputation and modelling makes it extremely difficult for others to replicate or use their methods, or to explain how the outputs relate to country data. As Tichenor et al [60] have noted in relation to an abortive attempt by the World Bank to use IHME's work on a human capital index, the World Bank in the end decided to produce their own index so that they knew how it was derived from what data, and to have a platform to advocate for better data collection. An attempt by WHO on 2018 to switch from its own index of Universal Health Coverage to one developed by IHME [61] was rejected by the UN Inter-agency and Expert Group on SDG Indicators as it was deemed to be too removed from country data, with complex modelling and data imputation, to be acceptable to the UN Member States.…”

The role of burden of disease assessment in tracking progress towards achieving WHO global air quality guidelines

“…Recent studies discuss the status of the current risk functions, identify the key uncertainties in the current GBD estimates and recommend solutions (Pope et al 2018 ; Burnett and Cohen 2020 ; Shaffer et al 2019 ). IHME and WHO provide a unified approach to exposure assessment for BoD estimation and have agreed to produce a single GBD Study with the aim of fully unifying methods in the spirit of the WHO/IHME collaboration ( Tichenor and Sridhar 2019 ) . Yet, the critical assessment of the BoD methodology remains important for the development of strategies to reduce the impact of air pollution.…”

Burden and changes in HIV/AIDS morbidity and mortality in Southern Africa Development Community Countries, 1990–2017

“…Accordingly, SADC countries are relatively underperforming with respect to the expected reduction in disease burden compared to other countries of similar SDI. At current rates of decline in the burden of HIV/AIDS, SADC countries might not meet the SDGs target for the disease and are far from the UNAIDS goal of ending AIDS by 2030 [11]. Our study suggests that SADC countries have made some progress, but HIV/AIDS mortality and morbidity rates are still unacceptably high.…”

“…Timely and robust evidence on mortality and trends are essential to informing policy and goal setting, program evaluation, and decision-making. Such assessment is an essential starting point for informed health policy debate to measure progress in achieving the 2030 United Nations (UN) health-related Strategic Development Goals (SDGs) [3,11,12] and UN Fast-Track approaches "90-90-90" and "95-95-95".…”