What do you mean ‘problem’? Everybody involved wants the inspection to go well, the correlation between the outcome of the inspection and the quality of the school/firm’s books is incidental at best.
This is a very good point, and in my eyes explains the observations pretty much completely. Thanks!
(yet it was contained in the UK, which is great and suggests I’m talking BS)
I continue to be extremely surprised by the UK decline in numbers. The Netherlands is reporting a current estimated R of 1.1-1.2 for the English strain and 0.8-0.9 for the wild types. They furthermore estimate that just over half of all newly reported cases are English strain by now. But the UK daily cases have dropped by 80% in 40 days, which at a reproduction time of 6 days would mean R = 0.79 throughout.
In the past I suggested a few potential, not mutually exclusive, explanations:
The UK has implemented significantly more effective measures, and if we just copy them we can totally beat the English strain.
The height of the UK peak in the second week of January was caused by Christmas and New Years holiday craze, which caused significant delayed reporting (‘better take that test after I visit all my friends and family, otherwise I won’t be allowed to join them’) and massively overestimates the peak, and also the decay.
The Dutch models are crap.
The UK numbers are crap.
The English strain has spread throughout the London area so rapidly that it hit local group immunity, and the plummet afterwards is caused by a lack of geographical spread. Once this picks up again the UK will see a stark rise in cases.
I previously put my money on hypothesis number 5, but as time goes on it steadily loses credibility. If anybody has a suggestion for what’s going on in the UK right now I’m all ears, I am currently not taking their drop in cases at face value.
The loss of life and health of innocent people who got suckered into a political issue without considering the ramifications?
I mean, the group of people who holds out on getting a vaccine as long as possible will definitely be harder to convince than the average citizen. But with these numbers (death rate, long term health conditions, effectiveness of vaccines) around are you seriously suggesting trying to help them is not cost-effective? From the post I think you’re talking about tens of millions of people in the USA alone, if not 100M+.
I personally have a very tough time fitting your interpretation into my model of the world. To me the popularity and actions of Facebook et al. are mostly disconnected from our ability to communicate with family and close friends.
In my opinion the timeline seems to be a little more as follows:
People are on Facebook and Twitter and other social media platforms both to stay in touch with friends and to complain about the outgroup.
COVID-19 hit, significantly reducing quality of life everywhere. People realign their political discussions and notions of outgroup along COVID-lines—are you a believer in lockdowns and masks and science or the opposite? This temporarily supersedes other political discussions, not because people have wonderfully unique and insightful opinions on COVID countermeasures but because this is the biggest event happening and as such is necessarily political.
After approximately one year of lockdowns and countermeasures people have sunk significant parts of their public profile into their thoughts regarding COVID. A large portion of the public, as well as officials, will support silencing opposition if only to retain a coherent public image (after all, if communication on COVID is not more important than free speech, what have you been doing all these months?).
Facebook rises to the occasion and offers to selflessly censor people according to criteria set by the WHO.
I’d like to couple this with a prediction that Facebook will not start censoring older messaged by the WHO and other Respected Officials. I see Facebook’s cooperation more as a power grab with plausible deniability than a desire for certain messages (officially endorsed) over others (crackpot/other). It only exists through the support of the very serious people, so it is counterproductive to start challenging them on their own history.
Lastly I think that if you genuinely want to have a heart-to-heart with your friends and family it is silly to restrict yourself to communicating via Facebook. Call them, start a blog, meet somewhere outside for a walk if you want. This has the twin benefit of you not having to worry about issues being ‘controversial’ as defined by Facebook, and them not having to publicly change their thoughts over your message. Also it is much less embarrassing if it turns out you were unbelievably overconfident all along.
You are correct, but the hope is that the probabilities involved stay low enough that a linear approximation is reasonable. Using for example https://www.microcovid.org/, typical events like a shopping trip carry infection risks well below 1% (dependent on location, duration of activity and precautions etc.).
I meant after the first shot, sorry for the confusion.
I think ojno has a point. Furthermore, to the best of my knowledge the protection from the vaccines takes a bit of time (10 days? 14 days?) to kick in after the vaccination. Arguably “proceed with the same caution as before” is a better message than “go nuts, dance and hug and visit all your friends” in this period, and for simplicity’s sake this has become the default message.
Who am I kidding, this is of course because we don’t want vaccination to be unfair. If you get social benefits from being vaccinated (by not having to abide by some of the restrictions) then the prioritisation discussion would be even fiercer than it is now. Plus, the more Sacrifices to the Gods you publicly support (h/t Svi) the more of a Serious Person you are, which the CDC tries very hard to be.
Mathoverflow has discussion on it. In short:
This area definition is equivalent to the standard definition, although this was (to me) not immediately obvious.
Some statements (linearity of integrals, for example) are obvious from the one definition, while others (the Monotone Convergence Theorem) are obvious from the other definition. Unfortunately, proving that the two definitions are equivalent is pretty much the proof for these statements (assuming the other definition).
The general approach of “given a claim, test it on indicator functions, then simple functions, then all integrable positive functions, then all integrable functions, then (if desired) integrable complex functions” is called the standard machine of measure theory, so there is educational benefit to seeing it.
It was pointed out to me that it is really not accurate to consider the UK daily COVID numbers as a single data-point. There could be any number of possible explanations for the decrease in the numbers. Some possible explanations include:
The current lockdown and measures are sufficient to bring the English variant to R<1.
The current measures bring the English variant to an R slightly above 1, and the wild variants to R well below 1, and because nationally the English variant is not dominant yet (even though it is in certain regions) this gives a national R<1.
The English strain has spread so aggressively regionally that group immunity effects in the London area have significantly slowed the spread, while not spreading as quickly geographically.
Most notably, hypotheses 2 & 3 predict that the stagnation will soon reverse back into acceleration (with hypothesis 3 predicting a far higher rate than 2), as the English variant becomes more prevalent throughout the rest of the UK. Let’s hope the answer is door number 1?
To what extent does ‘positive PCR test’ equate to ‘infectious’? Or is there some other good indicator? I know most health authorities say something like “if you have been contact with a person who tested positive, then from the point they are no longer symptomatic/first negative test after you have to be careful for X days’, so I assumed they are (somewhat) related.
To the best of my knowledge there are four evil inaccurate but not-completely-moronic reasons for sticking with a 2-dose vaccination plan. Just to be clear: none of these arguments convincingly suggest that 2-dose will be a better method to combat the pandemic.
Many officials may be convinced that “no Proper Scientific Procedure has investigated this” is identical to “there is no knowledge”. In non-pandemic times, if you squint juuust right, this looks like a cost-benefit analysis of delaying medical research versus endorsing crackpot pharmaceutics. I find it more than plausible that many people (and certainly most bureaucracies) are not capable of adjusting this argument to a pandemic. In their defense, you have to be somewhat of an expert in the field to make the cost-benefit assessment on a case-by-case basis (even though it is obvious in this case).
Are there legal/reputational risks to publicly supporting 1-dose vaccines before the Medical Establishment has given it a seal of approval? This would explain why nobody blinked now that they are the norm—people were simply waiting for some agency to accept the blame if in hindsight it turned out to be a mistake.
80% is noticeably lower than 95%, so you can expect about 4 times as many thrillseekers to take the vaccine, go to the local mall, lick every object they can find and come down with something terrible. It could even be COVID. This is awful for public perception of the vaccine. Or, taking less of an extreme, people might risk-compensate to the point where 2x80% is not as much better than 1x95% as naive math might suggest (although I fail to see how it could ever close the gap. People aren’t compensating that much.… right?).
At certain points during the distribution it is conceivable that increasing the immunity in a particularly vulnerable subgroup of the population from 80% to 95% might have a higher impact (on the death toll, medical systems, you name it) than increasing the immunity of an arbitrary selected subgroup of the remainder of the population from 0% to 80%. This chance is bigger if you instituted some messed up prioritization on your subgroups in the first place (see: everywhere).
Anyway, the case for 1-dose is overwhelming. I just wanted to point out how otherwise intelligent people might get this question so incredibly wrong, seeing as I’ve run into shades of all four of these arguments in the past.
Oh, it’s so much worse than that. What happens when the central planner combines threats to those who don’t distribute all the vaccine doses they get, with other threats to those who let someone ‘jump the line’? Care to solve for the equilibrium?
You conclude that vaccination facilities will reduce their orders so they are guaranteed to be able to distribute all. I think in practice it is much easier to cook the books and/or destroy vaccines as necessary.
More pressingly, this is the first mention I’ve run into of the potential seriousness of the South African variant. But (perhaps for the first time since February) it really seems to be the case that “more data is needed before we can make an informed judgment on this”?
There has been previous discussion about this on LessWrong. In particular, this is precisely the focus of Why the tails come apart, if I’m not mistaken.
If I remember correctly that very post caused a brief investigation into an alleged negative correlation between chess ability and IQ, conditioning on very high chess ability (top 50 or something). Unfortunately I don’t remember the conclusion.
Edit: and now I see Mo Nastri already pointed this out. Oops.
Your point on alternative hypotheses is well taken, I only mentioned the superspreader one since that was considered the main possibility for strong relative growth of one variant over another without increased infectiousness. Could you expand on the likelihood of any of these being true/link to discussion on them?
I also thought this, but was told this was not the case (without sources though). If you are right then the scaling assumption is probably close to accurate. I tried briefly looking for more information on this but found it too complicated to judge (for example, papers summarizing contact tracing results in order to determine the relative importance of superspreader events are too complicated for me to undo their selection effects—in particular the ones I saw limited to confirmed cases, or sometimes even confirmed cases with known source).
EDIT: if I check microCOVID for example, they state that the chance of catching it during a 1 hour dinner with another person who has been confirmed to have COVID is probably between 0.2% and 20%, The relevant event risks for group spread (as opposed to personal risk evaluations) are conditional on at least one person present having COVID. So is this interval a small chance or a large chance? I wouldn’t be surprised if ~10% is significantly high that the linearity assumption becomes questionable, and a 1 hour dinner is far from the most risky event people are participating in.
I agree that this means particular interactions would have a larger risk increase than the 70% cited (again, or whatever average you believe in).
In the 24-minute video in Zvi’s weekly summary Vincent Racaniello makes the same point (along with many other good points), with the important additional fact that he is an expert (as far as I can tell?). The problem is that this leaves us in the market for an alternative explanation of the UK data, both their absolute increase in cases as well as the relative growth of this particular variant as a fraction of all sequenced COVID samples. There are multiple possible but unlikely explanations, such as superspreaders, ‘mild’ superspreaders along with a ‘mild’ increase in infectiousness, or even downright inflated numbers due to mistakes or political motives. To me all of these sound implausible, but if the biological prior on a mutation causing such extreme differences is sufficiently low they might still be likely a postiori explanations.
I commented something similar on Zvi’s summary, but I don’t know how to link to comments on posts. It has a few more links motivating the above.
I had a long discussion on this very topic, and wanted to share my thoughts somewhere. So why not here.
Disclaimer: I am not an expert on any of this.
The scaling assumption (if the new strain has an R of 1.7 when the old one has an R of 1, then we need countermeasures pulling the old one down to 0.6 to get the new one to 0.6 * 1.7 = 1) is almost certainly too pessimistic an estimate, but I have no clue by how much. A lot of high risk events (going to a concert, partying with 10+ people in a closed room for an entire night, having a multiple hour Christmas dinner with the entire family) will become less than linearly more risky. I interpreted the “70%” (after some initial confusion) to represent an increase in risk per event or unit time of exposure. But if you are sharing the same air with possibly contagious people for a long period of time your risk is all the way on the saturated end of the geometric distribution, and it simply can’t go above 100%. So high risk events will likely stay high risk events.
At the same time, I expect a lot of medium and low risk events to become almost proportionally more risky. This includes events like having one or two people over for dinner while keeping the room properly ventilated, going to supermarkets, going to the office and using public transport. Something that has been bugging me is that the increase in R-value has been deduced from the actual increased rate at which it spreads, so it is simply not possible that every activity has less than 70% (or whatever number you believe in) increased risk, since that is apparently the population average under the UK lockdown level 2 conditions. So some of this nonlinearity has already been factored in, making it very difficult to say what stronger lockdowns would mean.
In conclusion, I think it is possible that even if the new variant is 70% more transmissible that lockdown conditions that would have pushed the old strain down to 0.7 or only 0.8 might be sufficient to contain this new strain, and of course if the new strain is less transmissible than this we have even more leeway. At the same time I have absolutely no clue how to get a reliable estimate of the “old R needed”.
My father sent me this video (24 min) that makes the case for all of this being mostly a nothingburger. Or, to be more precise, he says he has only low confidence instead of moderate confidence that the new strain is substantially more infectious, which therefore means don’t be concerned. Which is odd, since even low confidence in something this impactful should be a big deal! It points to the whole ‘nothing’s real until it is proven or at least until it is the default outcome’ philosophy that many people effectively use.
I think this is a great video, it explained a lot of things very clearly. I’m not a biologist/epidemologist/etc., and this video was very clear and helpful. In particular the strong prior “a handful of mutations typically does not lead to massive changes in reproduction rate” is a valuable insight that makes a lot of sense.
That being said, the main arguments against this new strain variant being a large risk seem to be:
The prior mentioned above.
The fact that current estimates of increased transmission rates are based on PCR testing, which does not identify variants.
The possibility of alternative explanations for the increase in nationwide infections in the UK, which have not been sufficiently ruled out (in particular superspreaders).
I think he is claiming that the NERVTAG meeting minutes are drawing a causal link between the lower ct value of this variant on PCR tests and its increased transmissibility, and that this is an uncertain inference to draw.
However, personally I think the strongest case for the increased transmissibility of this new variant comes not from indirect evidence as presented above, but from the direct observation of exponential growth in the relative number of cases over multiple weeks/months. See for example the ECDC threat assesment brief or the PHE technical briefing. These seem to strongly imply that, while being agnostic about the mechanism, this new variant is spreading very rapidly. So all things considered the linked video makes me update only very weakly towards a lower probability of this new variant being massively transmissible—a good explanation for growth shown in both reports is still missing if it is not inherently more transmissible.
Good point, I’m likely misinterpreting nextstrain website then.