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F1000Research, Wellcome Open Research, (4), p. 35, 2020

DOI: 10.12688/wellcomeopenres.15011.2

F1000Research, Wellcome Open Research, (4), p. 35, 2019

DOI: 10.12688/wellcomeopenres.15011.1

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

Journal article published in 2019 by Marlee Tichenor ORCID, Devi Sridhar ORCID
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Data provided by SHERPA/RoMEO

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.