I find it odd that the @IHME_UW would choose to advertise its broad impact on the US Covid response by tweeting a picture of Deborah Birx and the IHME model predicting that the pandemic would go to zero with 100% probability by July 2020.

And indeed one year later there are indeed many unanswered questions.

Most importantly: what happened, why were the serious (and ultimately correct) concerns expressed by much of the research community ignored, what has been learned, and what is going to be different in the future?

(This is not Monday-morning quarterbacking on my part. Here's a thread I wrote one year ago — the day after the IHME model was released — explaining why I was concerned about their methodology and unhappy with their confidence ranges.)

(And from 11.5 months ago, a thread explaining why their optimistic predictions for the end of the pandemic were driven by unjustified—and unjustifiable—modeling assumptions.)

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More from @CT_Bergstrom

28 Mar
In his latest paper about COVID infection fatality rates, John Ioannidis does not address the critiques from @GidMK, but instead engages in the most egregious gatekeeping that I have ever seen in a scientific paper.
John's defenders have done this in the past, but I'm stunned that he'd stoop to the same.

Science doesn't work like that, to say the least. Gideon's degree status is irrelevant and in the entirety of my career I've never seen this issue raised in a scientific paper before.
The condescension and hypocrisy here is mind-boggling.
Read 7 tweets
25 Mar
There's an odd website going around right now that purports to point out twitter accounts that have a left-wing bias.

Now, I don't deny my own left-of-center leanings.

But I think the algorithms need work.

I mean, consider their report on known leftist @megynkelly.
Let's look at what they say about me.

I lean further left than Megyn.

But why? Here are my top influencers.
One of these accounts, @callin_bull, is an account I run.

Another, @stephaniemlee, is one I do retweet.

The third is really weird. @janweider is a very talented photographer who I follow, but have interacted with online only *once*, as shown below.
Read 6 tweets
24 Mar
1. When developing COVID testing protocols, it
is critical to know the sensitivities of alternative COVID testing methods and how they change over the course of an infection.

But this is hard to measure, particularly for individuals who are pre-symptomatic or asymptomatic.
2. A new preprint from UIUC provides some of the best data I've seen, comparing antigen, saliva-based PCR, and nasal swab-based PCR.

3. Instead of using the onset of symptoms as "day zero", they use the onset of culturable virus from nasal swab. Doing so, you get the following sensitivity curves.
Read 8 tweets
24 Mar
If you're going to write a whole OpEd complaining that people don't say "Wuhan virus" and blaming it on "wokeness", it would help to understand enough about the nomenclature that your own example "translation" doesn't drop critically important information.
It would also be useful to know what "wild-type" means, lest you claim that D614G is the original SARS-CoV-2 strain.
Read 4 tweets
19 Mar
A thread about Michael Strevens' new book and the dismissive approach that some scientists take toward philosophy.

I'm going out on a limb here, thinking aloud beyond of my area of expertise. So what follows may be total nonsense. Consider yourself forewarned. Image
For years I've been baffled to see certain prominent science communicators—Richard Dawkins, Neil deGrasse Tyson, Bill Nye, and others—aggressively belittling philosophy and performatively showcasing their own ignorance of the discipline. Image
None of this made sense to me until I read about what Strevens argues it is that makes science unique, and uniquely successful, his so-called Iron Rule of Explanation.
Read 35 tweets
16 Mar
The “blueprint” for the cell phone I’m posting from (including the blueprints for its components) specifies how basically every detail needs to be laid out. There’s a formal sense in which we can say the blueprint contains about the same amount of information as the phone itself.
Not so our brains. There’s not nearly enough information in our genome to specify how all the connections in our brains get wired up.

Most of that comes from learning within the environment.

The information in our brain’s structure vastly exceeds that in its blueprint.
.@mikha_ehl and I used to say that only a little bit of the information it takes to make a tiger is in the tiger’s genome. The vast majority of it is in the jungle.
Read 4 tweets

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