Maybe the UK’s case curve has flattened after the end of the spike due to the asymptomatic people that are getting tested for whatever reasons and turn positive for the reason you state? It doesn’t feel likely (perhaps it’s just the other omicron subvariant giving it a push? or just the “control system” of people relaxing?). The hospital admissions continued to go down as one would expect if this was the case, though the data at ourworldindata is a few days behind.
I know it’s unlikely, but if it was indeed omicron, its faster generation time also would make its numbers drop faster if they managed to move R under 1
I presume 12 feet is a quarter of the risk of 6 feet [...] there is no magic number
My intuitive oversimplified model of this has been analogous to the direct sound vs reverberant sound in acoustics (in slow motion).
I’d expect the risk from direct viruses to follow the inverse square law (at least to the extent that the risk is linear to the expected number of viruses around you, which can’t be true for high risks). And maybe be even be reduced by cloth masks which stop big droplets (?).
But the reverberant viruses are supposed to be the main drivers of the pandemic, right? And those don’t care about distance for small enough rooms where virosols (heh) have more than enough time to travel everywhere before falling down. This is where N95s and ventilation become crucial, but distancing not so much.
In this model, there is a special distance, a “critical distance” (which depends on the context, masking, etc), after which the direct viruses are as important as the virosols and extra distancing starts not mattering.
Is my intuitive model nonsense?
Can immune escape by itself explain the transmission advantage or do we also need it to be spreading better?
Makes sense to me...
On the other hand, if it takes longer to show symptoms but it’s still equally transmissible since early but for longer, you get higher Rs without surprising new mechanisms of transmission. Also, it may also be escaping our current precautions instead of the immunity.
Why does it follow that a longer time to develop symptoms suggests immune escape?
Also, if the timeline is longer, then the estimates of how much more transmissible Omicron is, based on the time it’s taken for it to displace Delta, should be even greater, right?
On the other hand, those lockdowns may only last until the cases start going down again, but you can’t get unvaccinated.
If not mandating vaccination for indoor dining, then what?
Even that minimally coercive approach you describe is pretty coercive; I don´t expect the benefits to outweigh the ugly side of making many tens of millions of people be injected with something they don´t like or trust or want. Some people are still getting convinced to get vaccinated just with time alone, and many other things could be done better to convince more people without more restrictions. I don´t know what to expand on without making this too long.
the WHO who still refuse to admit Covid is airborne
Sort of. For some months now, the WHO states that it can spread “in poorly ventilated and/or crowded indoor settings [...] because aerosols remain suspended in the air”
EDIT: (used to ask why the link wasn’t formatting properly)
And if the choice is between ‘no indoor dining (or other X) for anyone’ and ‘no indoor dining (or other X) for the unvaccinated’ I know which one I’m choosing, and which one leaves me more free.
I agree that “no indoor dining for anyone” is worse than mandating vaccination for indoor dining. But I also don´t think the situation merits either. Protecting the immunocompromised and people that want but can´t get vaccinated doesn´t make up for the concerns.
we’d not only not make them mandatory, they’d be forbidden.
The space between those two is very small, maybe even negative.
Regarding the intelligence tests after COVID: Fourth, I can imagine some people that had COVID and go test themselves might actually want/expect to see some effect and end up not doing their best, to be a victim or have an excuse or something to blame for whatever.
It’s unlikely that these corporations would make the assumption that all future IP would also be “confiscated”
Do you have a good explanation to Moderna’s market price drop?
Even if they made that assumption, what are they supposed to do? Stop investing in future developments, and slowly go out of business?
Borrow less, invest less, or, as you say in your last line, focus on other ways of making money that don’t require innovation and IP?
Right! My untrained intuition still resists a bit; I should play with the numbers.
Niice, it makes sense! Thanks!
So to recap, I was right in that riskier assets can have higher avg returns, but I was missing the usually bigger and opposing effect where as the assets gets riskier, the same avg returns rely more and more on lucky very big gains while doing worse more often (at least if they are sort of lognormal).
My second point I still think was correct, right? -- i.e., that if Scott believed ETH had some chance of total collapse (a mixture distribution), then this skews it to the other side and pushes the median below the mean, and gives some reason to think ETH is more likely to outperform BTC. Does this make sense?
If ETH is less risky than BTC then the median performance of ETH will outperform BTC and his probability could be consistent with EMH
Wait. Does this mean that EMH expects less risky investments to have higher performance on average? That sounds shocking enough that I must be confusing something here. Or is this some sort of median vs mean distinction that I’m not seeing
About 17 and the EMH. Can’t Scott be just thinking that ETH is sufficiently more risky than BTC so it may have higher expected returns even with the EMH (the EMH allows this, right?). Or even that he might think ETH has some chance of total collapse (like an outlier at 0) so even with equal expected returns it’s much more probable that ETH outperforms BTC than the other way around (?)
What’s this supposed to be estimating or predicting with Bayes here? The thing you’ll end up doing? Something like this?:
Each of the 3 processes has a general prior about how often they “win” (that add up to 100%, or maybe the basal ganglia normalizes them). And a bayes factor, given the specific “sensory” inputs related to their specific process, while remaining agnostic about the options of the other process. For example, the reinforcer would be thinking: “I get my way 30% of the time. Also, this level of desire to play the game is 2 times more frequent when I end up getting my way than when I don’t (regardless of which of the other 2 won, let’s assume, or I don’t know how to keep this modular). Similarly, the first process would be looking at the level of laziness, and the last one at the strength of the arguments or sth.
Then, the basal ganglia does bayes to update the priors given the 3 pieces of evidence, and gets to a posterior probability distribution among the 3 options.
And finally you’ll end up doing what was estimated because, well, the brain does what minimizes the prediction error. Is this the weird sense in which the info is mixed with bayes and this is all bayesian stuff?
I must be missing something. If this interpretation was correct, e.g., what would increasing the dopamine e.g. in the frontal cortex be doing? Increasing the “unnormalized” prior for such process? (like, it falsely thinks it wins more often than it does, regardless of the evidence). Falsely bias the bayes factor? (like, it thinks it almost never happens that it feels this convinced of what should happen in the cases when it doesn’t end up winning.)
Whatever prevents the most infection, hospitalization and death is the right answer either way
I first read this sentence as suggesting that killing people is the best way to prevent infection.