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Archive of posts filed under the Public Health category.

You’re a data scientist at a local hospital and you’ve been asked to present to the physicians on communicating statistical information to patients. What should you say?

Someone who wishes to remain anonymous writes: I just read your post reflecting on crappy talks . . . I’m reaching out because I’m a data scientist at a local hospital in the US and I’ve been asked to present to our physicians about communicating statistical information to patients (e.g., how to interpret the results […]

Routine hospital-based SARS-CoV-2 testing outperforms state-based data in predicting clinical burden.

Len Covello, Yajuan Si, Siquan Wang, and I write: Throughout the COVID-19 pandemic, government policy and healthcare implementation responses have been guided by reported positivity rates and counts of positive cases in the community. The selection bias of these data calls into question their validity as measures of the actual viral incidence in the community […]

“They adjusted for three hundred confounders.”

Alexey Guzey points to this post by Scott Alexander and this research article by Elisabetta Patorno, Robert Glynn, Raisa Levin, Moa Lee, and Krista Huybrechts, and writes: I [Guzey] am extremely skeptical of anything that relies on adjusting for confounders and have no idea what to think about this. My intuition would be that because […]

Megan Higgs (statistician) and Anna Dreber (economist) on how to judge the success of a replication

The discussion started with this comment from Megan Higgs regarding a recent science replication initiative: I [Higgs] was immediately curious about their criteria for declaring a study replicated. In a quick skim of the info in the google form, here it is: In the survey of beliefs, you will be asked for (a) the probability […]

Our ridiculous health care system, part 734

I went to get a coronavirus test today. We had to get the test for work, and I had no problem with that. What I did have a problem was with that, to get this test, I needed to make an appointment, fill out three forms and take an online “course” (clicking through a set […]

One dose or two? This epidemiologist suggests we should follow Bugs Bunny and go for two.

Joseph Delaney writes: I [Delaney] am starting to see the hot take of “why don’t we experiment with giving only one dose of an mRNA vaccine”. For example, see this. We briefly brought up one such argument a couple weeks ago, but only in the context of a discussion of something else.  I hadn’t looked […]

Flaxman et al. respond to criticisms of their estimates of effects of anti-coronavirus policies

As youall know, as the coronavirus has taken its path through the world, epidemiologists and social scientists have tracked rates of exposure and mortality, studied the statistical properties of the transmission of the virus, and estimated effects of behaviors and policies that have been tried to limit the spread of the disease. All this is […]

“Inferring the effectiveness of government interventions against COVID-19”

John Salvatier points us to this article by Jan Brauner et al. that states: We gathered chronological data on the implementation of NPIs [non-pharmaceutical interventions, i.e. policy or behavioral interventions] for several European, and other, countries between January and the end of May 2020. We estimate the effectiveness of NPIs, ranging from limiting gathering sizes, […]

Literally a textbook problem: if you get a positive COVID test, how likely is it that it’s a false positive?

This post is by Phil Price, not Andrew. This will be obvious to most readers of this blog, who have seen this before and probably thought about it within the past few months, but the blog gets lots of readers and this might be new to some of you. A friend of mine just tested […]

What do Americans think about coronavirus restrictions? Let’s see what the data say . . .

Back in May, I looked at a debate regarding attitudes toward coronavirus restrictions. The whole thing was kind of meta, in the sense that rather than arguing about what sorts of behavioral and social restrictions would be appropriate to control the disease at minimal cost, people were arguing about what were the attitudes held in […]

What about this idea of rapid antigen testing?

So, there’s this idea going around that seems to make sense, but then again if it makes so much sense I wonder why they’re not doing it already. Here’s the background. A blog commenter pointed me to this op-ed from mid-November by Michael Mina, an epidemiologist and immunologist who wrote: Widespread and frequent rapid antigen […]

“A better way to roll out Covid-19 vaccines: Vaccinate everyone in several hot zones”?

Peter Dorman writes: This [by Daniel Teres and Martin Strossberg] is an interesting proposal, no? Since vaccines are being rushed out the door with limited testing, there’s a stronger than usual case for adaptive management: implementing in a way that maximizes learning. I [Dorman] suspect there would also be large economies in distribution if localities […]

Covid crowdsourcing

Macartan Humphries writes: We put together a platform that lets researchers contribute predictive models of cross national (and within country) Covid mortality, focusing on political and social accounts. The plan then is to aggregate using a stacking approach. Go take a look.

Are we constantly chasing after these population-level effects of these non-pharmaceutical interventions that are hard to isolate when there are many good reasons to believe in their efficacy in the first instance?

A couple days ago we discussed issues of communicating uncertainty in a coronavirus mask experiment. That study itself is not so important, but I remain interested in the larger issues of inference and communication. I sent the discussion to epidemiologist Jon Zelner, who wrote: The struggle is real! I think this is a nice example […]

Discussion of uncertainties in the coronavirus mask study leads us to think about some issues . . .

1. Communicating of uncertainty A member of the C19 Discussion List, which is a group of frontline doctors fighting Covid-19, asked me what I thought of this opinion article, “Covid-19: controversial trial may actually show that masks protect the wearer,” published last month by James Brophy in the British Medical Journal. Brophy writes: Paradoxically, the […]

“We’ve got to look at the analyses, the real granular data. It’s always tough when you’re looking at a press release to figure out what’s going on.”

Chris Arderne writes: Surprised to see you hadn’t yet discussed the Oxford/AstraZeneca 60%/90% story on the blog. They accidentally changed the dose for some patients without an hypothesis, saw that it worked out better and are now (sort of) claiming 90% as a result… Sounds like your kind of investigation? I hadn’t heard about this […]

Authors repeat same error in 2019 that they acknowledged and admitted was wrong in 2015

David Allison points to this story: Kobel et al. (2019) report results of a cluster randomized trial examining the effectiveness of the “Join the Healthy Boat” kindergarten intervention on BMI percentile, physical activity, and several exploratory outcomes. The authors pre-registered their study and described the outcomes and analysis plan in detail previously, which are to […]

Estimating efficacy of the vaccine from 95 true infections

Gaurav writes: The 94.5% efficacy announcement is based on comparing 5 of 15k to 90 of 15k: On Sunday, an independent monitoring board broke the code to examine 95 infections that were recorded starting two weeks after volunteers’ second dose — and discovered all but five illnesses occurred in participants who got the placebo. Similar […]

How science and science communication really work: coronavirus edition

Now that the election’s over, we can return to our regular coronavirus coverage. Nothing new since last night, so I wanted to share a couple of posts from a few months ago that I think remain relevant: No, there is no “tension between getting it fast and getting it right”: On first hearing, this statement […]

The Pfizer-Biontech Vaccine May Be A Lot More Effective Than You Think?

Ian Fellows writes: I [Fellows] just wrote up a little Bayesian analysis that I thought you might be interested in. Specifically, everyone seems fixated on the 90% effectiveness lower bound reported for the Pfizer vaccine, but the true efficacy is likely closer to 97%. Please let me know if you see any errors. I’m basing […]

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