All of ZachWeems's Comments + Replies

I think there's some confusion in your discussion of variant growth rates. Moritz Gerstung and Andy Slavitt are both quoting numbers around 10% per day, which corresponds to the new/old variant ratio having a ~7 day doubling time. 

This is consistent with the CDC Nowcast.

For comparison, BA.1/Delta had a ~2.5 day doubling time, Delta/Alpha ratio about 5 days, and Alpha/wild about 12 days.

Looking at cumulative numbers per population on OurWorldInData:

As of Nov 21, Germany had performed 1001 tests per thousand people, vs 4697 for the UK.

They'd found 64.6 cases per thousand vs 144.6 in the UK.

The cumulative CFR was 1.84% vs 1.46% in the UK. Checking 3 weeks later for lag effects, Dec 12 was 1.62% vs 1.35%.

My guess is that all else equal, the UK has had a similar or higher IFR, but is catching a larger fraction of infections. In general. I'm not going to try to tease apart the differences in the current or recent situations.

Retracted: Helix changed their PCR tests. The new ones won't have an SGTF signal for this variant.

Retracting a comment on a previous post:

Previously said Helix had PCR tests that would "flag" this variant & predicted they'd give us handy graphs from this data. The company says they changed their PCR's a couple months ago, and the new ones won't flag the variant.

the body starts attacking the cells that produce the antigen... including the brain as polyethylene glycol goes through the blood brain barrier

How do you know what you think you know? Specifically, regarding the PEG enabling the LNP's to cross the BBB, and regarding a followup by immune cells that have crossed the BBB?

Various points on Delta & vaccination:

-On the UK vaccination data, the 79% number is for Pfizer and AZ combined. Since the vast majority of US vaccinations are Pfizer or Moderna, the Pfizer number should be much closer to the truth. Their EV is 87.9%, with a confidence interval from 78.2 to 93.2%.

-Looking at Israel's Delta/vaccination document linked to in my other comment, they don't have many hospitalizations or severe disease cases for either vaccinated or unvaccinated. So I don't expect their expected value number to be very meaningful, due to huge... (read more)

I dug into the Israel vaccine data some. Full data is lacking and I strongly suspected the true VE is significantly higher, based on the UK's 78.2-93.2% estimate for Pfizer 2 dose. Below is my thought process.

TL;DR I thought I would find a clear reason the Israeli data was wrong. I tried to see if the interval was so large that the Israeli estimate was meaningless or if there was a huge bias, but nothing solid came up, so I've gone from "confident" to "somewhat nervous".

Here's the announcement: https://www.gov.il/en/departments/news/06072021-04

And a more q... (read more)

Oops, missed this. I don't check LW messages much. 

20% was not an exact value. At the time I wasn't aware of any estimates. Since then I've heard that the standard curve fit returns a ~50% growth per 6.5 days, some or all of which may be due to immune escape.)

I had a couple assumptions that made me think the SA strain was less contagious in expectation:

1. High contagiousness is more likely when high mutation numbers were seen, and correspondingly emergence would tend to be later. The SA variant gained local dominance earlier than the UK.
2. There was (and is

I notice I'm confused- SA's variant, if legitimately due to a huge jump in R, doesn't have huge numbers of mutations. 

If the UK variant had a 45% jump in R, and SA's has a 20%, and >20% is much more commonly due to IC'd patients, then it seems reasonable that the super-fit, highly mutated strains show up alongside the more mundanely fit, moderately mutated ones. The super-fit's take longer to bake but they take off faster. But then again I'm trying to make a theory to explain 2 data points that I'm not 100% are both correct, so as much as this feels correct it probably isn't.

AFAICT the reason immunocompromised patients are important is they can stay infected for several months. I read a paper recently where such a patient held on for about 5 months, and by my count, samples averaged 3 mutations per month (although I'm sure there's a better way to adjust the numbers than what I did). So there's time to infect enough IC'd patients, plus n months to evolve in them. If antibodies are a necessary ingredient that would delay these steps more. Then there's time for the highly fit strain to outcompete other strains, which is proportio... (read more)

This post helped me clarify my thoughts on interference with supervisors.

Before this, I was unclear on how to draw the boundary between interference (like a cleaning robot disabling a human to stop punishments for broken furniture) and positive environmental changes (like turning on a light fixture to see better) in a concrete way. The difference I thought of is that the supervisor exerts direct pressure to keep the agent from altering the supervisor. So a rule to prevent treacherous turns might look like "if an aspect of the environment is optimizing... (read more)

I don't think this demonstration truly captures treacherous turns, precisely because the agent needs to learn about how it can misbehave over multiple trials. As I understand it, a treacherous turn involves the agent modeling the environment sufficiently well that it can predict the payoff of misbehaving before taking any overt actions. The Goertzel prediction is what is happening here.

It's important to start getting a grasp on how treacherous turns may work, and this demonstration helps; my disagreement is on how to label it.

Currently we can access all course materials at once. For the time being, it might be better to hide the incomplete bits so nobody can wander ahead and miss things. Slash, it might be better to force users to try one section before unlocking the next; otherwise people might eternally put off the hard sections.

That said, the platform looks new so it might not support this.