What attracted you to the health metrics field?
I had always harbored an intense fascination with infectious disease, though for me, that interest began exclusively within the biological sphere of analysis. At the core, I sought desperately to understand the discrete mechanisms by which microscopic agents of disease could send people spiraling into infirmity. A human geography class and subsequent medical anthropology class spurred the revelation in me that an individual’s – or even a community’s or an entire population’s – health is also significantly determined by complex mechanisms of space and place, formal and informal structures of power, and human idiosyncrasies that take starkly different forms worldwide. To think, or even hope, that biology alone could explain a phenomenon that was so intricately connected to these myriad externalities would be entirely misguided, if not irresponsible. As I moved through college, I also began to open my eyes to a world shockingly rife with inequality, especially when it came to health and the enormous disparities in agency people faced in navigating their own. This was as true about communities immediately surrounding us in the Inland Empire as it was about somewhere more remote, like rural Nepal. In this way, the entire notion of health for me took on an entirely new dimension – justice. No longer was it solely about understanding health’s principal components, but it became about identifying and resolving the inequities that deny swathes of the world’s population even the most basic quality of life.
In an age increasingly driven by big data, the health metrics field allured me in its potential to rigorously address the seemingly impossible and historically abstract questions stemming from my new outlook: What is the state of the world’s health? Who is better off than others and why? How might we try to close these gaps, and how do we know we are doing a substantive job? With incisive measurements and estimates we can actually make informed decisions that will fundamentally improve the global health landscape rather than perpetuate inequality by virtue of misguided plans, wasted resources, and the relentless passage of time. As someone who hopes his work will (however directly or indirectly) meaningfully impact the very way people will be able to live their lives, there is no other field in which I would rather be.
What work are you doing at IHME?
I work on the Socio Economic Exposures and Determinants (SEED) team under the larger Global Burden of Disease umbrella. Primarily, I am responsible for the computation of the recently devised Socio-demographic Index (SDI) and modeling for its underlying inputs: per capita income, mean educational attainment, and total fertility (the latter of which is my primary focus this year). Constructed by IHME, SDI is highly predictive of health outcomes and provides powerful insight into, among other things, the epidemiological profile of the burden that a location might be expected to face on the basis of its development status.
With this information, we can hone in on locations that exhibit a proportionate burden posed by any cause far different from what their SDI would suggest – for better or for worse – in order to identify and delve into the underlying country-specific factors that also strongly influence health outcomes. Furthermore, making the comparison between observed and expected burden allows us to highlight areas exhibiting relative “success” with regard to a specific cause or set of causes and think about how we might apply their triumphs to similar-SDI countries of dire concern.
How do you think your experience at IHME will contribute to your future work?
There is certainly huge value in granularity, focusing one’s efforts on uncovering and thinking exhaustively about the minutiae of the community to which one’s work immediately pertains in determining how one might be able to improve the health of all those that inhabit it. However, IHME’s major strength, to me, draws from its function as a sentinel for the world’s health at large – that with the comprehensiveness of the work we do here, we can identify patterns and trends in health across space and time that would be impossible to see and connect were we not zoomed out to such a scale. And it is these patterns visible from afar that can significantly inform what can or will be effective here and now. Other scientific and research competencies aside, this sense of “global awareness” (in the truest sense of the term), the disposition and ability to consistently and thoughtfully consider how issues of health operate at a macro level, is something that I most hope to learn and develop from my mentors and peers during my time here. As an aspiring physician who intends to continue studying the fundamental causes of disease and the disparities in being able to deal with them, this will be an invaluable skill to have moving forward.
GBD 2016 Healthcare Access and Quality Collaborators. Measuring performance on the Healthcare Access and Quality Index for 195 countries and territories and selected subnational locations: a systematic analysis from the Global Burden of Disease Study 2016. The Lancet. 23 May 2018.
GBD 2016 Mortality Collaborators. Global, regional, and national under-5 mortality, adult mortality, age-specific mortality, and life expectancy, 1970–2016: a systematic analysis for the Global Burden of Disease Study 2016. The Lancet. 14 Sept 2017: 390;1084–1150.
GBD 2016 Causes of Death Collaborators. Global, regional, and national age-sex specific mortality for 264 causes of death, 1980–2016: a systematic analysis for the Global Burden of Disease Study 2016. The Lancet. 14 Sept 2017: 390;1151–210.
GBD 2016 DALYs and HALE Collaborators. Global, regional, and national disability-adjusted life years (DALYs) for 333 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. The Lancet. 14 Sept 2017: 390;1260-344.
GBD 2016 Disease and Injury Incidence and Prevalence Collaborators. Global, regional, and national incidence, prevalence, and years lived with disability for 328 diseases and injuries for 195 countries, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. The Lancet. 14 Sept 2017: 390; 1211–59.
GBD 2016 SDG Collaborators. Measuring progress and projecting attainment on the basis of past trends of the health-related Sustainable Development Goals in 188 countries: an analysis from the Global Burden of Disease Study 2016. The Lancet. 12 Sept 2017: 390; 1423–59.