I had two colleagues call my attention to a cool use of GBD 2010 estimates recently: the Economist observed World Hepatitis Day by calling attention to the deaths due to hepatitis as compared to the deaths due to HIV. It is very nice to see these numbers getting out into the world.
But there are a lot of metrics to use for this comparison, and a lot of ways to show them besides a four-colored map. Find a country of interest from their map, and then make a detailed comparison on the GBD-Compare tool: China, North Africa/Middle East, United States.
Very cool new visualizations of the GBD2010 results are now on-line: http://viz.healthmetricsandevaluation.org/gbd-compare/
Have you got 15 minutes for science? Take this strange survey that I’ve been excited about for the last two years. I’ve been calling it the Disability Weights Survey, but now that it’s all professionally implemented and communications-department approved, it is officially the GBD 2010 Health Measurement Survey.
The survey is part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2010 led by the Institute for Health Metrics and Evaluation (IHME) at the University of Washington, in collaboration with four other leading institutions: Harvard University, Johns Hopkins University, the University of Queensland, and the World Health Organization.
Our goal is to collect responses from at least 50,000 people worldwide. Please consider sharing this and encouraging participation within your organization. In addition, we would ask you to consider forwarding information about this survey to colleagues and contacts outside your organization who might be interested in participating.
The survey takes about 15 minutes to complete. Participation is completely voluntary and anonymous. In the near future, we hope to translate the survey into additional languages.
The political situation in Iran has been in the news and on the nets a lot this week. I hope that the friends and families of all my Iranian colleagues are safe. I’m thinking of you.
I haven’t had time to write anything this week because I am up to my neck in this Seven-Samurai-style software engineering project. You know, where a bunch of untrained villagers (that’s me) need to defend themselves against marauding bandits (that’s the Global Burden of Disease 2005 Study), so they have to learn everything about being a samurai (that’s writing an actual application that people other than this one villager can use) as quickly as possible.
I guess this analogy is stretching so thin that you could chop it with Toshirō Mifune’s wooden sword. But, if anyone knows how a mild-mannered theoretical computer scientist can get a web-app built in two weeks, holler. If you prefer to explain in terms of wild-west gunslingers, that is fine.
Here’s my game plan so far: I’m going to make the lightest of light-weight Python/Django apps to hold all the Global Disease Data, and then try to get my epidemologist doctors to interact with it on the command-line via an interactive python session.
The rest of this post is basically a repeat of the Django tutorial, but specialized for building a data server for global population data. As far as interesting theoretical math stuff, hidden somewhere towards the end, I’ll do some interpolation with PyMC’s Gaussian Processes using the exotic (to me) Matérn covariance function. Continue reading
If you’ve read some of my previous posts, you might be wondering, what does Health Metrics have to do with sampling independent sets in graphs? (What is Health Metrics? you might also be wondering.)
In my new job, I’m not that interested in sampling independent sets. I’m mostly interested in sampling from a weird distribution that comes out of a Bayesian denoising problem.
Let me set the stage: a huge project that IHME is part of is the Global Burden of Disease study, which will (among other things) rank 200 diseases and injuries according to how severely they impact humanity. How you could possibly, ethically make this list is the topic of many books, and I won’t try to get into it now. IHME director Chris Murray seems to favor measuring impact in “disability adjusted life years” (DALYs), which is a fairly individualistic, fairly egalitarian approach.