Computational Social Science in Medicine


August 23, 2010


“Medicine is a social science”, this has been the mantra of public health since 1848. Today, medicine is a computational social science. In this talk, I’ll give an overview of the Global Burden of Disease Study (GBD), and describe some of its many algorithmic challenges. GBD is a systematic effort to produce estimates of how 200+ diseases, injuries, and risk factors impact people around the world. Naturally, there are a lot of numbers to crunch. But you may be surprised to learn how many of the relevant numbers are missing. And the numbers we do have often don’t add up. This is where we need computational tools, and where we leverage research from probability theory and machine learning, as well as economics and political science. I’ll give you a quick tour of the interdisciplinary area that is Health Metrics.


Abraham Flaxman

I’m an n-th year grad student at CMU, working with Alan Frieze on Random Graphs and their applications. This summer I’m an intern at SVC, learning about auctions with Jason Hartline. Abraham Flaxman was a post-doc in the MSR Theory Group before Jennifer and Christian fled Seattle to found MSRNE. Abie did a second post-doc at the Institute for Health Metrics and Evaluation in the UW Global Health Department, and learned how interesting global health research is and how important computer science skills are in that field. He is now an Assistant Professor of Global Health at the University of Washington and instead of approximately counting colorings of random graphs he is approximately counting mosquito nets. He blogs about the computer science challenges in global health at