Short article from the kick-off of a new IHME journal club, with a focus on diversity and health disparities: [link]
Topics that bubbled up in discussion: composition of search committees, pipeline issues and other barriers to attracting diverse candidates, the scale of the problem with systemic racism.
Second edition of the Diversity Lunch Discussion journal club, with a focus on the Implicit Association Test. Many participants also *took* an IAT—Rose suggests you try taking the Race IAT before our discussion tomorrow: https://implicit.harvard.edu/implicit/takeatest.html
So much knowledge and expertise in this group.
To read: Mortality and life expectancy in Kiribati based on analysis of reported deaths
Darcy AM, Louie AK, Roberts L. Machine Learning and the Profession of Medicine. JAMA. 2016;315(6):551-552. doi:10.1001/jama.2015.18421.
> Must a physician be human? …
Trends in Prescription Drug Use Among Adults in the United States From 1999-2012
Last week, we read Chien et al, Efﬁcient mapping and geographic disparities in breast cancer mortality at the county-level by race and age in the U.S. I’ve been very interested in these sort of “small-areas” spatial statistical methods recently, so it was good to see what is out there as the state of the art. I think I’ve got something to contribute along these lines some day soon.
Maps in small multiples look just lovely, too:
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.