Category Archives: global health

IHME Seminar: Overdiagnosed

I have fallen way behind in noting the IHME weekly seminars, but I was just thinking of this wonderful one from last semester, and I couldn’t wait any longer to link to it: Overdiagnosed: Making people sick in the pursuit of health by H. Gilbert Welch.

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Smoking trends by US counties

I’m away from work for some really exciting family stuff, but while I wait on that, our paper on trends in smoking prevalence has just come out, along with a fun interactive data visualization of the results, and some media coverage that I think tells the story quite well.

What makes this work methodologically challenging is that the data comes from telephone surveys, but people who smoke stopped using landlines more than people who don’t smoke:

smoking_brfss_nhis

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Open data and the scientific python ecosystem is making my life easier

Last week I gave a talk on my work on the Iraq mortality survey. It was the first time that I’ve had a chance to talk about it since our paper was published. And since the data is all online and the scientific python tools are getting slick, I was able to make charts like this one:

dc_pct

See how little code it takes here.

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GBD 2010: The Global Burden of Ischemic Heart Disease in 1990 and 2010: The Global Burden of Disease 2010 Study

I wish I had been more diligent in collecting the disease-specific papers that have come out following the Global Burden of Disease 2010 Study… here is the latest one to go into print: Moran et al, The Global Burden of Ischemic Heart Disease in 1990 and 2010: The Global Burden of Disease 2010 Study, in Circulation.

ihd_compartments

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Journal Club: Transmission Assessment Surveys (TAS) to Define Endpoints for Lymphatic Filariasis Mass Drug Administration: A Multicenter Evaluation

While I’m catching up on journal club reading, two weeks ago we discussed Chu et al, Transmission Assessment Surveys (TAS) to Define Endpoints for Lymphatic Filariasis Mass Drug Administration: A Multicenter Evaluation, which takes on the question of how to decide when it is safe to stop a massive disease elimination program.  This work must rely on some cool mathematical epi modeling, to say how many years of what level of coverage is necessary before you can hope the LF is gone.

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Filed under disease modeling, global health

Journal Club: Changing therapeutic geographies

We had a very different sort of research paper in journal club three weeks ago, and I was too busy to jot it down until now. Dewachi et al, Changing therapeutic geographies of the Iraqi and Syrian wars. This is certainly not our usual metrics-heavy approach, so it was good exercise to try to understand it.

geography

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IHME Seminar: Crowds, crisis, and convergence: crowdsourcing in the context of disasters

Last week for IHME seminar, we heard from Kate Starbird about Crowds, crisis, and convergence: crowdsourcing in the context of disasters. It reminded me of the visual displays of quantitative information I hacked on after the 2010 earthquake in Haiti.

Did I ever tell you how the US State Department called to ask if they could use that graphic in a presentation? I thought it was a prank.

reports

As often is the case, a recording of the talk is available online.

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Filed under global health, videos

IHME Seminar: Bayesian reconstruction: estimating past populations and vital rates by age with uncertainty in a variety of data-quality contexts

A recent IHME seminar by Mark Wheldon described a Bayesian approach to estimating past populations and vital rates by age. I like this stuff. The talk is online, and there is a CSSS working paper on it, too: http://www.csss.washington.edu/Papers/wp117.pdf‎

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Journal Club: Repeat Bone Mineral Density Screening and Prediction of Hip and Major Osteoporotic Fracture

Last week we read Repeat Bone Mineral Density Screening and Prediction of Hip and Major Osteoporotic Fracture by Berry et al. It argues that repeat screening does not improve predictions. But I think the world needs a better way to measure the quality of predictions like these. Area-under-the-curve doesn’t cut it when you are predicting the unpredictable.

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Population Health Metrics Research Consortium Gold Standard Verbal Autopsy Data 2005-2011

One exciting announcement that I got to make at the Verbal Autopsy Congress last October is that the PHMRC gold standard verbal autopsy validation data is now available for all researchers. You can find it in the Global Health Data Exchange: Population Health Metrics Research Consortium Gold Standard Verbal Autopsy Data 2005-2011.

Insert an example of doing something with it here.

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Filed under global health, machine learning