@MaxJordan_N@EpiEllie@AmakaEMD@DrDeidraCrews That sounds reasonable. Admittedly I am not trained in genetic epi, so I may be totally off-base and welcome correction. Let’s say there are a bunch of genetic variants that increase risk of hypertension. Holding all else equal (waving hands), 2 increase risk by same degree 1/
@MaxJordan_N@EpiEllie@AmakaEMD@DrDeidraCrews Variant A is represented at 4% among a US Black same, 8% among an insular European sample that’s often studied. Variant B is present in 4% of US Black sample and 0% in European samples (my understanding is that people of African descent in US more genetically varied than...
@MaxJordan_N@EpiEllie@AmakaEMD@DrDeidraCrews ...most “White” populations as conceptualized in these US sense so I think this is plausible. So here there is some relationship between the “race” node and genetic variants bc of all the processes that have grouped people and structured society. But it’s not a 1-1 overlap.
@MaxJordan_N@EpiEllie@AmakaEMD@DrDeidraCrews 5/ so then there’s ALL the other things and environments that produce risk. In the US these are often patterned around racial categories. In fact sometimes they are SO racially patterned that it’s hard to tease each one apart from other “exposures” that are racially patterned...
@MaxJordan_N@EpiEllie@AmakaEMD@DrDeidraCrews 7/ In both popns combined, in simple bivariable analyses, variant B will be associated with higher absolute level of risk of outcome than variant A. But if you restricted to Black popn, you might see that effects actually equal.
@MaxJordan_N@EpiEllie@AmakaEMD@DrDeidraCrews 8/ And Black race will be statistically associated with higher risk than White race but not bc of any increased genetic risk, just bc of the racial patterning of other non-genetic risk factors.
@MaxJordan_N@EpiEllie@AmakaEMD@DrDeidraCrews 9/ and each non-genetic factor in example actually increase risk a lot more than variant A or variant B. Absolute risks associated with these factors will be high, but relative risks may vary a lot depending on whether research is in Black & White popns combined, Black or White
@MaxJordan_N@EpiEllie@AmakaEMD@DrDeidraCrews In this example, (1) the variants, (2) race, and (3) all the non-genetic exposures that are driven by racialization are all statistically associated with the outcome but for different reasons. And different analyses will give different estimates of effects.
@MaxJordan_N@EpiEllie@AmakaEMD@DrDeidraCrews 11/ This example just scratches at the surface but I hope starts to illustrate how considering these 3 sets of factors as statistically connected through racialization processes can guide better study design and analyses and make us attentive to sources of bias.
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Someone close to me is in this vaccine trial. I am so moved by every single volunteer for these trials. They took a risk to give the world a tremendous gift. I’m literally crying. The world owes them so much...
And it looks like all the severe cases were in placebo group, so vaccine may not just reduce risk of getting sick overall but also prevent severe illness. 🙏🏾
Also some promising news about placebo arm folks: “Dr. Zaks said Moderna’s study results were so strong that the company felt an ethical obligation to offer the vaccine to the placebo group as soon as possible.” From @nytimes. Stay tuned
.@ER_Mayeda cautions, Methods of correcting for selection bias, eg, IPW, only as good as understanding of selection processes that gave rise to data. Reminds me of polling in 2016 & 2020 US elections. When system is dynamic, can’t rely on past trends; need other ways of knowing
Reading this article (in which I'm quoted near the end), I realized why I have such a strong visceral reaction to some of the negative coverage of @ProfEmilyOster's work on #COVID19 and schools...prospect.org/coronavirus/wh… 1/
..The treatment of @ProfEmilyOster reminds of 2016 press coverage of @HillaryClinton! An outsized focus on that woman's flaws had big long-term consequences.(I'm not a media studies or communications person, so I may be totally off, but I swear there's a PhD thesis in here! 2/
On to my promised tweets on #epitwitter data about #SARSCoV2/#COVID19 among children and particularly in school settings. It's less comprehensive than I hoped, but I'm trying not to let the perfect be the enemy of the good... 3/
Again, many great quotes but this one deeply resonated with my personal experience: “Yet when Black women ‘do say no to additional projects, we are seen as anti-team player, unwilling to be collegial,’ Lima-Neves said...”2/
The most galling thing said to me in 2020 was from a senior leader in response to my asking him why his leadership team was all-White over many years despite the presence of talented non-White faculty (like myself)...
So THEN someone in our “You’re on yr own” US executive says, “Actually I do have some thoughts!”
and bullies the actual *CDC* (the home of elite force of disease detectives who live to identify and squash outbreaks) into saying...2/
“Hey school districts, in case you were thinking about doing the extraordinary & forward-thinking work of standing up a whole #SARSCoV2 surveillance system in your K-12 schools bc yr federal govt has abandoned you...3/
@HeidiKKim The excess deaths among the Asian subgroup in April and May are striking.
Part of the spin I’m seeing online is the 1/3 of deaths not #COVID19. But the timing and patterning of these so close to the COVID19 deaths that I suspect many actually are miscoded deaths that really were COVID. What do y’all think?