Delta is now two thirds of sequenced samples from the past week, so we can be confident that it has taken over, and soon will be most cases in America, and soon after that most cases around the world. That’s bad news, but given we know the case numbers, it sort of is good news. It means we’ve already ‘taken the hit’ to the reproduction rate, mostly, and if we can stabilize things one final time, then unless there’s a new even worse variant then the last scare is over.
Things are not yet stable, but they continue to echo what happened this time last year, and things continue to be quite hot. If things cool down a bit (in temperature terms), several weeks pass and these trends continue, then they’ll be more clearly where we are at going forward, and we’ll be counting on further vaccinations and on past vaccinations kicking in. We should have enough momentum there to still get us over the finish line, but in many places it’s going to be close.
Let’s run the numbers.
I forgot that July 4th was coming, so my deaths prediction was dumb. Whoops.
Prediction from last week: Positivity rate of 2.7% (up 0.3%) and deaths decline by 5%.
Result: Positivity rate of 2.9% (up 0.5%) and deaths decline by 20% likely due to July 4th.
Prediction for next week: Positivity rate of 3.3% (up 0.4%) and deaths increase by 7%.
Predicting deaths this week is weird, and I’m predicting an increase because I think this week’s count is artificially low due to the holiday. So there will be some catch-up reporting and some reversion, even if the new rise in cases won’t have caught up to us yet. For the positivity rate, it jumped a lot the last day, but I have to assume it will keep rising for now. As it stops being constrained, the positivity rate will once again become a useful measure of our situation.
|May 27-June 2||527||838||1170||456||2991|
|June 3-June 9||720||817||915||431||2883|
|Jun 10-Jun 16||368||611||961||314||2254|
|Jun 17-Jun 23||529||443||831||263||2066|
|Jun 24-Jun 30||550||459||706||186||1901|
|Jul 1-Jul 7||459||329||612||128||1528|
I’d love for this to be real, but it’s probably not. It’s July 4th, and I keep forgetting to look ahead to the holidays in the next week before I make predictions. There’s no way this full decline is real, and it’s hard to know where the real number was.
My brain continues to not understand how it being the 4th of July causes three days of missing data across the country. That’s not a mindset I can process, even now, not fully. It definitely did happen, whether I can process it or not, and it’s very unclear how much of the difference was made up after the weekend was over.
|May 20-May 26||33,890||34,694||48,973||24,849||142,406|
|May 27-June 2||31,172||20,044||33,293||14,660||99,169|
|Jun 3-Jun 9||25,987||18,267||32,545||11,540||88,339|
|Jun 10-Jun 16||23,700||14,472||25,752||8,177||72,101|
|Jun 17-Jun 23||23,854||12,801||26,456||6,464||69,575|
|Jun 24-Jun 30||23,246||14,521||31,773||6,388||75,928|
|Jul 1-Jul 7||27,413||17,460||40,031||7,050||91,954|
That’s an unsettling jump especially given the holiday weekend with its disruptions to reporting, but given the jump I’m going to presume that there wasn’t much disruption to testing, only to deaths. That means we saw a 20% or so rise in cases, up from 10% last week, which was across the board and concentrated in the places one would expect. In terms of absolute levels things are still fine, and there isn’t much room for further acceleration because Delta is already dominant, but at 20% per week (R ~ 1.15) things will get ugly fast if trends don’t improve.
These changes are very similar to the regional changes one year ago this week, by region, in percentage terms.
Further discussion of likely future trends in the Delta section.
The decrease is unwelcome, but also clearly linked to the holiday, so it’s reasonable to expect some amount of rebound over the coming week. It could also be seen as the end of a previous temporary bump, in which case we wouldn’t expect much further decline right away but wouldn’t expect a bounce-back. My guess is the next week will hold steady from here, which is still not bad at all. Last week we were at 46.7% fully vaccinated and 54.4% with one does, and we picked up 0.9% and 0.7% on those respectively. That’s at least an effective 1.5% drop in R0, and I’m guessing more than that. As I say each week, that adds up fast.
Periodic reminder from MR that fractional dosing of vaccines would save many lives and end the pandemic faster with no downside. This links to a new paper in Nature Medicine arguing the same thing. And a preprint showing 1/4 doses of Moderna create immunity similar to natural infection. As a reminder, I continue to believe that Moderna’s day-after side effects are due to the dose being actively too large rather than simply not being strictly necessary. And Moderna is getting half-doses ready for children, so we know they can provide them, and also arguing feasibility was always silly. For children, the new half-doses should be overkill the same way the full-doses are overkill for adults.
Or simpler version:
If you have had one shot of the Johnson & Johnson vaccine, should you then get a shot of Pfizer or Moderna? If it is available, absolutely, yes you should. There’s every reason to think that mix and match will work here, one shot of J&J isn’t that differently effective than one shot of mRNA, and no reason beyond supply limitations to not take the second shot. Yet because it is not Officially Recognized all the Very Serious People are falling in line and finding ways to tie themselves up in knots and pretend that a second shot would not be useful. Here’s Nate Silver commenting on the bizarre NYTimes attempt at this. Here’s the Washington Post attempt. It’s all disgraceful bull**** designed to back up official policy that doesn’t make sense, with gems like ‘if you don’t feel safe enough without a booster, use additional measures like mask wearing.’ They’ve committed to one J&J shot counting as ‘vaccinated’ while one shot of Moderna doesn’t, and now they have to pretend that definition makes sense.
Remember to always be praising people when they finally do the right thing, regardless of whether they first exhausted all alternatives. The last thing you want to do is punish correct action by using it as justification for someone now being that much more blameworthy for not doing it sooner! Still, sometimes…
More vaccinations are the only viable way to deal with Delta. As Matt says here, there’s no going backwards, and we should have and will have very little tolerance for attempts to reimpose intrusive measures:
Map pairing that’s going around Twitter that might not be entirely fair, but come on:
Within a few weeks Delta will be almost all cases, and there won’t be a need for a distinct Delta section, but for now it still makes sense.
Where are we on that right now? Mostly we’re there.
This is a seven day rolling average of data that’s lagged days behind that to begin with, and this matches where I previously presumed the trend-line was. If it was 65% or so in this 7-day rolling average of lagged data, current case counts likely reflect something more like 75%-80%, and the Alpha+Gamma is accounting for almost all of the remainder as per this graph. That means we have accounted for over 90% of the effect of the shift from pre-Alpha to Delta.
If we take this week’s numbers seriously in that context, and don’t make any adjustments, we’d get a final R0 for Delta under exact current conditions of R0 = 1.18 or so, once we take into account the lag in our case numbers.
Trevor Bedford thread attempts to ballpark the potential size of the wave coming from Delta. It’s useful to check one’s intuitions and estimate calculations against those of others. Trevor uses a basic SIR model, assumes that vaccinations are fixed and independent of infections (and counts only those currently fully vaccinated, but gives them credit for full immunity, and ignores varying distributions of vaccinations, much of which he notes is wrong but that he hopes such effects will cancel) and as always ignores all control systems in all directions and comes up with a further 11% of the population likely to be infected before this is all over.
In addition to all that, I’ve written several times about why SIR is not a great approximation in situations where different people are making varying adjustments in their behaviors and taking radically different levels of risk, which he’s also not considering. Nor does it take the children versus adults distinction seriously.
I think these issues mostly point in the direction of a smaller wave, and there’s one that towers over the rest of them, which is that vaccinations will continue until morale improves.
We are continuing to see vaccine shots given out at a good clip. At a bare minimum, I would expect the bulk of those who have only had their first shot to get their second shot. He’s starting with 46% fully vaccinated and an R0 = 1.18 (matching my estimate above). If we move that 46% to something like 55%, that’s enough to get R0 = 1, and all that would require is everyone who has had a first shot as of July 5 getting a second shot. It doesn’t work that way, because the first shot’s protection is already present and can’t be double counted, but other factors point the other way.
Another way to think about this is that when Trevor says 11% additional infections, that’s 11% additional infections or vaccinations, and can mostly be considered a hard upper bound. More vaccinations means less overshooting after R0 gets down to 1, combined with all the other issues, make me continue to think that the Delta wave is unlikely to get all that big.
There’s also the seasonality perspective. This week, we saw a 21% increase in cases. A year ago this week, we saw a 21% increase in cases, both with similar regional patterns. A reminder:
|Date in 2020||Cases Total|
|June 11-June 17||158164|
|June 18-June 24||215751|
|June 25-July 1||300510|
|July 2-July 8||365107|
|July 9-July 15||431972|
|July 16-July 22||461441|
|July 23-July 29||444797|
|July 30-Aug 5||392193|
|Aug 6-Aug 12||365028|
|Aug 13-Aug 19||322126|
Thus, it seems premature to conclude that we are in a permanent R=1.18 world going forward pending additional vaccinations. We also have this situation at very low overall Covid levels, so control systems via individual action have a long way to adjust if necessary. We also have vaccinations continuing, with this week’s disappointing crop still dropping R0 at least by 1.5% (and at least one vaccination week won’t be reflected in cases yet, likely 2-3, so we have a head start here).
My baseline scenario continues to be that cases rise for a bit, but things stabilize in most places before reaching levels that require behavioral adjustments, especially by the vaccinated. But I do continue to expect some regional/local issues in places with lower vaccination rates.
Meanwhile, over in the UK, Guardian provides this graph:
Periodically commenters will ask what the evidence is that Delta is more lethal than Alpha. I’ve seen such estimates from several sources, and no formal estimates doubting it, but such effects can’t hold a candle to the power of vaccination, and especially of vaccination of the most vulnerable populations.
Scott Alexander Analyzes Lockdowns
Scott Alexander writes Lockdown Effectiveness: Much More Than You Wanted To Know. This was not, in this case, more than I wanted to know. Instead it felt more like a ton of empty calories, with comparison after comparison and calculation after calculation that had so many caveats (that were explicitly mentioned – Scott plays fair on such matters) that I don’t feel much more enlightened than when I began reading, and the main update I made was that the evidence available to find was such that Scott was unable to provide an update.
Sam Bankman-Fried summarizes it this way, which seems right:
Comparisons of this form stack the deck in favor of lockdowns, because they discount non-GDP effects (SBF’s #3), and also by considering the average countermeasure against the average gain, instead of comparing effects on the margin.
That second one is worth unpacking a bit if it isn’t obvious to you. The value of lockdown was being considered en masse rather than on the margin. Given that we end up controlling the situation either way and never end up in ‘everyone is infected’ mode, stricter long-term lockdowns have increasing marginal cost per case prevented or life saved. Thus, if it’s not clear whether lockdowns in general are good, or whether lockdowns above a given much lower level (like red state level versus blue state level) are good, that means that on the margin we did too much locking down. If we didn’t do enough, lockdowns up to that point would look very good.
Another note is that Scott is much too kind about the ‘maybe some of these provisions were not all that great’ aspect of the problem. Closing parks and beaches and playgrounds isn’t ‘we made lives worse for not much gain,’ it’s ‘we actively forced people into more dangerous situations and made the pandemic worse, while also making lived experience worse and burning out public tolerance and trust.’
What was the right rate of mandated lockdown, given our ability to prioritize measures? My belief is that private action reacts better and the control systems are very strong, and that the real reason to do lockdowns is the tail risk of complete disasters (and the big silent reason not to do them is to keep that ammo for when you really need it and/or to minimize risk of complete disaster via loss of civil order and people losing their minds).
That’s the argument that an analysis like Scott’s is missing the central point of decision making under uncertainty, rather than stacking (or not stacking) the deck in a particular way.
Once we got past the first few months, I’m firmly in the ‘we did too much locking down on the margin’ camp. I believe things would have gone better if we had let people make more of their own decisions. Even better would have been smarter restrictions, but I’ve learned not to make that the comparison point in such questions.
In Other News
EA Forum post (via MR) reiterates some of the various ways the pandemic was botched.
Thread explaining why vaccines provide better immunity than natural infection.
Belgium mandates CO2-level monitors in businesses as a proxy for ventilation (news story).
This seems like an excellent idea. Businesses liking it makes sense too, but in general there is the worry that ‘the government tells you that you can’t open, then tells you that you can open if you do X’ will make you happy whether or not the prohibition or requirement makes any sense, as it’s better to pay a small additional cost than stay closed.
Poor ventilation is quite bad for many non-Covid reasons, and it’s very good to see this acknowledged. Fixing air quality is an underappreciated cause area, whether via filters or better designs, and if that caught on more it would be a large upside to everything that’s happened.
Great news, New York gets to keep its outdoor dining:
Which of course led to this as the featured comment, gotta love the user name:
To which I’d respond on the sidewalk because I have never seen an outdoor dining area block a sidewalk to pedestrians in a meaningful way, not once, what city does this person even live in. It’s amazing we have any nice things at all.
And not as great news, New York, insert your own joke here:
Nate Silver points us to the news about American life satisfaction. It’s up!
More surveys at the original post, including that worry is down to pre-pandemic levels, but daily enjoyment still lags behind. My top takeaway here is that tough times make people better appreciate life, and that we all went through some tough times and then things improved, and we now have comparison points that make me feel better. Daily life scores are still lagging, so the ‘life is actually better now’ hypothesis doesn’t fit the data. It also doesn’t fit my observations otherwise, as life in general is pretty great but it’s still not fully back to the old baseline.
MR links to this LW post on the recent mask wearing studies, titled ‘we still don’t know if masks work.’ I agree with its finding that the study in question didn’t prove anything in any direction, but that doesn’t mean we don’t know if masks work, because we are allowed to know things that didn’t come from a Properly Done and Formatted Scientific Study.
Evidence that some people’s defenses against Covid kick in without causing antibody tests to come back positive. For now I don’t think this has much practical impact, since proving that something happens and showing that it happens frequently enough to matter are very different things.
Lab leak: Confirmation that many scientists will affirm its plausibility privately but not publicly. I continue to skip over most lab-related items, and the situation hasn’t changed.
NYTimes so no link, but MR points us to a birthday paper. The key finding is that your risk of Covid goes up when you have a birthday, presumably because you have a birthday party, and the effect size cares not whether you’re blue tribe or red tribe, implying their choices of party were remarkably similar.
In not-ready-for-prime-time-players AI news, IBM Watson has decided to start making tennis predictions. They are, shall we say, not so great.
That’s not how this works. That’s not how any of this works. Djokovic absolutely does not lose to Garin 43% of the time, or anything of the sort. You don’t need to know much about tennis to know that the world #1 is going to dominate the world #8 most of the time, yet Watson can’t figure this out, despite the training data providing more than enough information to solve this puzzle.
That would be fine if quite odd, if this was a little experiment IBM had privately done and then said ‘whoops, I wonder why that didn’t work.’ Instead, it’s publishing the output as if it’s the next iteration of tennis analysis. I don’t blame Watson, it’s a computer program. I blame the humans, who took a problem that AI should be quite good at, clearly botched it at the most basic level, then didn’t notice they’d botched it somehow.
That’s the part I don’t understand. I’ve gotten similarly nonsensical analytical results plenty of times, but when I do I say the whoops thing and learn about how to make better predictions. To paraphrase Seth, if they think this is publishable tennis analysis, keep Watson the hell away from any and all medical care, or it will end quite badly for all concerned.
The other part I don’t understand is how they got this kind of answer, given what I know about machine learning, and I’d love to hear a plausible gears-level theory of how this happened, even ignoring that the humans should catch it within five seconds. How did the algorithm get one of the most normal basically-in-sample situations so wrong?
If one is curious, my friend Seth offers this tracking of how it would be doing gambling, which can best be summarized as ‘lighting money on fire.’
Out of interest, does your opinion on lockdowns differ between the more static American ones and the more reactive/dynamic European ones?
Dynamic is better to extent the dynamic choices are made well? But the Europeans definitely seemed to completely let their guards down before it was over as a result, which seemed like a reasonably large disaster?
Thanks for the answer.
Hello, since I see you are running a free advice column in comment section (thanks for your public service!), perhaps it is not too inapropriate to ask:
I am interested in what is the difference in the level of protection after 7 days of a second shot vs after 14 days (Pfizer)?
We don’t know for sure but all signs I can see point to 7 days being sufficient to get almost all of the protection you would get from 14. Biologically there’s no reason to think it takes the full 2 weeks.
Sorry that this is probably super basic, but could you quickly explain why (or link me to an explanation for why) cloth masks are useful if covid is airborne? I thought the point of cloth masks was to prevent the transmission of droplets.
It’s a combination, and even a cloth mask has a non-zero effect on smaller particles. If it was purely droplets cloth would be a lot more effective than it is. I use KN95s myself, even now, since I actually find it more comfortable than cloth.
Do we know if (K)N95 masks are any better than surgical masks? With good fit they obviously are, but in realistic situations (e.g. throwing one on in a few seconds because the pizza guy is at the door), I expect fit to be very poor indeed.
Could be significant electrostatic attraction effects for aerosol sized droplets.
That said I am more in the “we don’t know if cloth masks work” camp
> Map pairing that’s going around Twitter that might not be entirely fair, but come on:
Well, it’s not exactly unfair.
Back in April I blogged about the relationship of state vaccination levels and Trump-Biden margins. It was statistically significant with good effect size, both by a one-sided t-test of vaccination fraction between Trump & Biden states, as well as a regression of vaccination on Trump margin (statistically significant regression F-stat, statistically significant t-stat on the negative slope coefficient).
A couple days ago, I decided to revisit the test on July 4, in honor of (not quite) meeting Biden’s goal of 70% of all adults vaccinated. Turns out I didn’t need to, because Charles Gaba had done the regression of vaccination on Trump margin at the much finer-grained county level. Still statistically significant, slope coefficient a stunning -0.4. That is, for every percent increase in Trump voters, a bit less than half of them will refuse vaccination.
Not entirely fair and not exactly unfair live in very similar spaces – I don’t think we disagree much here. It was more that the map lining up *exactly* with the safe blue states was a little over the top and might give an overly strong impression.
For the state-level data showing near-exact overlap, I agree with you that there’s possibly an element of coincidence.
For the finer-grained county-level data, I think the case is pretty convincing.
“Evidence that some people’s defenses against Covid kick in without causing antibody tests to come back positive. For now I don’t think this has much practical impact, since proving that something happens and showing that it happens frequently enough to matter are very different things.”
I suspect this class of things (infection gets underway but is halted before the entire immune machinery gets brought in) happens all the time with all kinds of diseases and represents a significant portion of the spectrum of people who are exposed (particularly to low-medium doses, perhaps?) but never develop a noticeable illness.
> Coronavirus waves compared
This matches an analysis I did of the 1st and 2nd waves in Boston, using mRNA levels in sewage as the predictor, and the COVID-19 tracking project’s figures for hospitalization, ICU admission, ventilator usage, and death to be predicted from mRNA.
One of the striking results comes from comparing the 1st and 2nd wave (spring 2020 vs year-end 2020 to start of 2021):
(1) In the first wave, a small(ish) amount of mRNA detected in wastewater led to a huge surge in medical loads like hospitalization and ventilators.
(2) In the second wave, a huge(ish) amount of mRNA detected in wastewater led to a moderate surge in medical loads like hospitalization and ventliators.
People explain this in a couple of ways: a different population being infected (by the 2nd wave, all the older people were scared and taking quarantine seriously, so the 2nd wave patients were younger), or the treatment protocols for COVID just got better as we learned to deal with it (prone position ventilators, dexamethasone, remdesivir, …).
If you believe those explanations — and I see only anecdotal evidence, but they seem a priori plausible — then viral strains didn’t matter quite so much as behavioral changes in both patients and care providers.
Of course, Delta is a much larger perturbation in the viral strain, so maybe it matters more now. It’s just not the only thing.
That life satisfaction graph seems to have an error in the labels, since it puts Dec. 2020 *after* Jan. 2021. I’m *guessing* that Dec. 2020 was the low point right before the inauguration, the inauguration was a brief high point, and there was a return to low point in Feb. 2021 as people remembered we were still in a huge wave but didn’t quite realize we were also on our way out of it. But if the mislabeling is even slightly different from that, then it leads to very different interpretations.
The x-axis on the life satisfaction graph also doesn’t match the labeled points. I would treat the entire thing as deeply suspect.
I see you count the negative hard to quantify effects of lockdowns as being underestimated, but the positive hard to quantify effects are also underestimated (which is to say not estimated at all really).
Commute lengths have long been understood to have one of the absolutely highest negative correlation with happiness and human flourishing of anything measured. And unlike many effects which probably are noise or confounded by genetics in hard to understand ways, the effect of commutes is real and direct. People move or change jobs to have a shorter commute and they get happier, and stay that way without reverting to the mean.
For years technology has made office work irrelevant but society has been stuck in a bad equilibrium. If the new equilibrium with more work from home sticks, there is no plausible way that the net sum of hard to quantify effects from lockdowns turns out to be negative.
I think it was mostly right to close down offices, but also I doubt many offices would have reopened if the government allowed them to open, if the work could plausibly be done from home. So I doubt this positive factor should be credited to official lockdowns much.
I feel like here in Hungary at least, among my friends there is a lot of response of office jobs to government rules. Also it was weird to see everyone, including lots of people who hate Fidesz, suddenly stop wearing masks in grocery stores and on the metro when the government said they didn’t have to because the vaccinations hit a milestone.
I would love to see a breakdown of the life evaluation data by age cohort. I am 60 years old and have seen enough that COVD was not hysteria-inducing for me but younger folks seemed to have a bit more difficult a time handling it. (Part of that may be due to their having children younger than my teenager, though.)
I would say I found this surprising, but I have lived through enough manufactured panic over other things in the past couple of decades (“Trump is literally Hitler!” “World War III!” “Swine Flu!” “Bird Flu!” “Anthrax!” “Smog!*”) that it was oddly nice to have an actual, honest-to-goodness reason for a bit of panic.
*Sorry, the “smog” one was a Bugs Bunny/Elmer Fudd flashback.
Generally such surveys do have crosstabs where you can see such things, albeit with low sample sizes, but I’m too busy to dig into it to try and find them right now.
I’ve read your last few posts, and I apologize if you’ve already addressed this, but what is the guidance for children? I have seen a few mainstream media sources making claims that delta is especially harmful to younger populations, but I wasn’t sure how much to trust them
That’s FUD. Young children do not need to worry about Covid.
“Periodically commenters will ask what the evidence is that Delta is more lethal than Alpha. I’ve seen such estimates from several sources, and no formal estimates doubting it”
The method of dueling studies is unreliable in the ideal situation where study authors are cooperative. When study authors are adversarial, the method becomes immoral, as it encourages pollution of the literature. I apologize for being harsh, but I think this is a bad habit.
As you do not only report what is happening but also offer policy and individual-focused suggestions, I am curious to know: what is your specific goal (or goals)? When suggestions are offered it is necessarily _towards_ something, after all.
Is your goal to minimize number of deaths due to COVID-19 infection? To end the pandemic as rapidly as possible? To balance death minimization with minimizing economic (or social-culture) damage? I don’t want to put words in your mouth—it wouldn’t surprise me: is it something different altogether?
I do not read this blog regularly—please pardon me if you have addressed this already. ―James
My primary goal is: What is going on, and how should I/you react to it now, in our own lives? Put on one’s own mask first.
My secondary goal is to understand how the world works, help others to understand, and to figure out how one can change it for the better, and build a system for doing so, and providing good incentives and following proper virtues and game theory.
My tertiary goals would stuff like minimizing deaths, infections and economic/experiential losses, good old first level objectives. They all matter and you have to be willing to make trades, and if you say your goal is X and not Y then that’s an error.
Those tennis odds look about right for a single game. Coincidence?
If that was the bug it would be one hell of a thing, but it’s definitely not what they’re intending to communicate.
Nate Silver’s excerpt from NYT don’t-get-a-booster article ends with this quote:
…people who received the J.&J. vaccine should not need a booster, nor can they get one, “unless they game the system, unless they pretend they’re vaccine-naive and go and get an mRNA vaccine and essentially lie,” Dr. Moore said, “and I certainly don’t recommend people doing that.”
Is it crazy to think the Straussian reading is intentional here? (Can you even call it a Straussian reading when it’s this obvious?)
This is false. I got J&J in March then upgraded to Pfizer in late April. I declared when making my Pfizer appointment that I had received J&J (and again at the administration site) and there was no problem.
J&J recipients can get the mRNA booster whenever they want, no lying required.
There’s some news about the Pfizer vaccine possibly being less effective vs. Delta than earlier variants: https://nypost.com/2021/07/06/pfizers-covid-19-vaccine-less-effective-in-israel-against-delta-variant/
If true, it’s kind of disappointing – we go from 95% effectiveness against infection to 64%, a 7.2x decrease in effectiveness. If we just need another Delta booster, that would be fine; probably about 3 months, per my guess, but some places are saying it could be because vaccine-mediated immunity is already running out in Israel, which I find unlikely. But if that’s true, we could be looking at 6-month boosters for quite some time.
Is this overblown or does it seem like it could be true?
Maybe my math is wrong, but for this to be true now, wouldn’t it mean that fully one third of vaccinated Israelis have presented with new symptomatic infections? Wouldn’t that be literally millions of new cases?
I don’t think so? I’m not 100% sure. My take on the effectiveness number is that it’s basically a risk multiplier – being vaccinated and exposed to COVID would only infect you 1/20th as often (at 95%). Now it would be 1/2.85th as often at 64%. I don’t think the effectiveness numbers are population-wide, just individual.
It’s true that this report exists, but the math it implies doesn’t match our world, so at a minimum it doesn’t work the way this is presenting.
That’s relieving, thank you.
This was an interesting listen: https://www.microbe.tv/twiv/twiv-777/
Here the hosts mostly concur with a flu researcher that, based on our experience with flu strains, the fitness advantage required for a new mutant to displace other variants is surprisingly small, and a bit of immunity from existing infection with prior strains is enough to make a new variant more fit in the actually-existing population even if it would be no better in a naive population. (I think there’s a Philip Lemoine blog post about this with regard to B.1.1.7.)
… So they’re pretty sure a large chunk of at least some of the 2020-21 sars-cov-2 variants’ increased fitness is antigenic drift allowing limited immune escape, rather than any real difference in how they work, but comparing how fast the new ones “take over” doesn’t tell us one way or the other. This did me a bit of a bamboozle at first, but it was helpful framing all this in the context of antigenic drift in flu strains.
They’re skeptical about media claims about delta, pointing out that, if wild R0 is such and such, and alpha is such and such more, and delta so much more than that, then delta is basically the measles, which is obviously silly. So there are some realistic upper bounds on how bad it might actually be, and it might be somewhat worse, or it might just be very effective antigenic drift, but there are good reasons to doubt concerns based on in-vitro and animal model experiments.
Good discussion about how hard it is to actually measure R parameters in this context without an awful lot of sequencing and mass longitudinal testing. Current surveillance can’t distinguish between antigenic drift and (they would put the scare quotes here) “increased transmissibility”.
TWiV have been mostly on the very serious people side so far, so it’s interesting to see them push back and say that in this case the very serious people are confused scaremongers, and it isn’t really that bad.
Can anyone else comment here? Really worth listening to the whole thing. My summary may not be very accurate on the technical stuff.
No idea how Watson is getting the odds this badly wrong. BUT
Their odds sucking can’t really explain why they are underwater in the simulated betting strategy (with some small caveats).
Suppose you have really miscalibrated beliefs, and that market odds are efficient. You’ll be massively overconfident in the probability of certain events relative to the market odds, so you’ll make big bets. Your confidence will be completely misplaced. (You will expect to make huge amounts of profit in expectation, and this is not a rational expectation). And if the odds are efficient, you will not be punished for doing so. You’ll break even.
Why? Because the odds are efficient, and your miscalibration is just random noise. E.g. Djokovic is 95% likely to win, you think he’s 40% likely to win, so you bet massively against… at odds that are priced by the market at 95% implicit probability. If he indeed loses 5% of the time, you break even (in expectation, etc). No matter how bad your miscalibration is. Also note that moving from “zero informational advantage relative to market i.e. mimic market odds” to “mildly wrong” to “quite wrong” to “extremely wrong” doesn’t change the expected payoffs. (It will tend to make you bet higher stakes, because you have more misplaced confidence).
When does this not hold?
1) When the market odds aren’t efficient, and their bias is correlated with your overconfidence (i.e. you make systematic errors, the market makes systematic errors in the same direction, so despite you thinking you are getting great odds you are in-fact getting bad odds, given you have zero informational advantage).
2) Spreads. Which is just to say that if you bet large stakes often enough and there are substantial trading fees, you always lose in expectation. This is just the same as stock picking etc. (But there are betting markets with very low spreads!)
There’s a corollary here – when a bookmaker is acting as the market maker, if they misprice the odds, they get destroyed – all the money takes the profitable side. So they need some spread to protect themselves. And importantly here, if your beliefs accurately capture *any* information not captured in the market odds, then even if your beliefs are less accurate on average, you can profit in expectation by betting against me (at the odds I think are “fair”). E.g. suppose I think every event is 50-50, but your beliefs contain a tiny bit of signal causing deviation from this, plus a big random shock. Even though the signal is small and the shock is large, you’ll still pick the right side more than half the time. I’ll have a smaller Brier score or whatever. And you will slowly bankrupt me. Hence the need for spreads.
What are your estimates for Covid-19 infection fatality rate (IFR) vs the vaccine-related mortality (VRM) (e.g. uninfected people who died in relation to getting vaccinated who would be otherwise alive at that time if not vaccinated)? I assume that the average IFR is around 1% (there’s obviously a high age-related variance), and that the average VRM – as suggested by the VAERS data – might be close to 0.01%. In other words, it would mean that vaccines are generally 100x safer than getting infected and clearly preferable in almost all cases, but they’re not extremely safe.
I would be curious about comparing these two metrics (IFR vs VRM) in specific groups (e.g. healthy men, 18-35 yo, Pfizer) – if IFR was low and vaccine-related complications were relatively frequent in this demographic, then I could imagine the vaccine having “only” a 20-40x advantage. If we adjust for effective treatment (FLCCC Protocol gaining popularity?) and consider the rare cases of people who might be willing to continue strong self-isolation until we get strong herd immunity, then I could theoretically imagine a limited number of cases in which not getting vaccinated might be preferable from the individual standpoint.
(Not to send a bad message – I keep on endorsing mRNA vaccines and I got mine)
VAERS, by their own admission, is not a reliable source for statistical data.
4800 reports over 150 Million vaccinated individuals is .003, not .01 percent.
And five of those reports say the patient suffered death as a side effect, but recovered, so what other errors are there in that raw data?
Maybe the patients were only mostly dead, and not all dead.
0.003% vaccine-related mortality would make vaccines 300x better than Covid-19 (at the population level), but it’s still a non-negligible risk.
I’ve heard of different estimates, such as: 25,000 deaths from the vaccine, OpenVAERS mentioning 20,000 deaths due to underreporting, and the CDC reporting 25,000 excess unexplained deaths. These numbers seem to add up, but I have no confidence in them, so I would like somebody competent (like Zvi) to estimate the likely vaccine-related mortality.
That’s 30 micromorts, around one and a half day’s worth of normal all-cause mortality https://en.wikipedia.org/wiki/Micromort
(though the normal all-cause mortality for the general population is tens of times higher than for young people)
IFR for unvaccinated I have at 0.6% by default, vaccines cut this down by… a lot.
VRM is epsilon.
“The World Bank, IMF, WHO, and WTO are very pleased to announce they just held the *first* meeting of their joint taskforce on covid vaccines.”
Just below it clarifies that it is their first meeting of a joint task force on vaccines for developing counties. I’m not sure why this is so shocking, that this specific mix of groups hadn’t had this specific task force already. Was it a given that these five organizations would band together on this issue?
“More vaccinations are the only viable way to deal with Delta”
How should we be thinking about rapid testing in the presence of vaccinations? I’d still think it could reduce Rt significantly.
Testing combined with action in the wake of positive tests helps with Rt. Yes, we still have the option to do lots more testing (and in theory also tracing) if we so desire, but vaccinations only make this harder, and if this was going to happen I think it would have happened by now. I do know there exist places doing frequent testing anyway, but I don’t expect enough of that to have an impact.
Author of the ‘we still don’t know if masks work.’ article.
The title is not precise, and my betting position is that universal mask wearing would reduce total cases by 10-20% (as we will hopefully find out from the Bangladesh study).
However I think we should be a bit more wary about the attitude of, “even if we can’t measure it, we know masks SHOULD work”. At least so far, the quality of evidence for mask effectiveness is similar to that of ventilators, HCQ and vitamin D. All of them have an inherently plausible story as to why they should work, and initially small scale observations showed promise. But larger scale studies have shown lesser effects and the best randomized trials have shown the least effect.
As a public health intervention masks can be considered “effective” with a much lower standard of evidence than a medical intervention would have. This has meant that the quality of evidence for masks has basically stagnated at the plausible physical model stage.
I don’t agree that this is the level of evidence we have. It might be the level of Official Study Evidence we have, or it might not, but that’s not what the word evidence means. I agree that it would be better to have better evidence and better measurements of how much they work, but I do not consider ‘doesn’t work at all’ to be in the reasonable hypothesis space.
Some idiots reject vaccinations because of politics, some idiots reject vaccinations because of the mistrust to government initiatives, and now we have idiots from FDA and CDC who deny vaccination to the people who want it to keep their completely useless message to the idiots in the first two groups pure and shine.
@TheZvi, you mentioned you disagree with some Microcovid calculations. Could you please point out which ones (and maybe what would make them better)? Would be great to be able to use Microcovid with some adjustments … Thanks!
I’ve pointed out differences when I encountered them in the past, but not going to go over it enough to make a list at this point – suffice to say that it’s a reasonable approximation if you need to put numbers on things, but don’t get too attached to the exact numbers.
Fair enough, and appreciate the response!
Zvi, do you have any good tips on differentiating between the fearmongering/clickbaits and legitimate early concerns? I keep on hearing about the firth waves, epsilon variant, black fungus, persistence of long Covid, RSV infection spike in Canada, and less natural immunity due to the less (healthy) exposure to pathogens under the sanitary restrictions. This makes me wonder if everything is mostly OK and we’re doing fine, or if the world is in the middle of a serious but less visible crisis.
BTW, what is your current stance on ivermectin and fluvoxamine?
The Boolean that either there’s a crisis or things are mostly OK is part of the issue here, and what’s driving the clickbait. Things are in some sense never ‘mostly OK’ and in another sense have been mostly OK for a long time.
You differentiate clickbait/fearmongering from legitimate early concerns the way you do in anything else. Consider the arguments and reasoning (and motives/incentives), have gears models of what’s being claimed, evaluate important claims, think about the implications of their claims and whether you can test them, look for whether the person is seeking truth and correcting for error and at their track record, pattern match the way it’s being pitched/presented versus your past experience, etc etc. Alas, there is no easy answer.
My position on ivermectin is it’s $500/hour for my time if you want me to go get one beyond what I’ve already written about its advocates. Fluvoxamine I also haven’t evaluated in detail because I’ve had too much going on to also focus on treatments – they don’t impact the path of the pandemic much, and it doesn’t seem so effective that I’d change my behaviors.
Well, I don’t really care about the ivermectin advocates, such as The Famous Podcaster You Don’t Like. I do care whether meta-analyses like [ivmmeta dot com] and the FLCCC protocols should be signal-boosted based on the available evidence, so we can save thousands (if not millions) of lives globally during the upcoming spikes.
I think that this topic is very relevant to individual decisions and behavior. For me and many other people – in case of a symptomatic infection – it would mean a choice between:
– using home remedies and going to hospital if my state significantly worsens (probably to get pretty ineffective remdesivir and hope not to face other pathogens/medical errors/collapsed healthcare)
– and using probably a very effective and safe treatment at home as soon as I get a positive test result.
Click to access S1301_SPI-M-O_Summary_Roadmap_second_Step_4.2__1_.pdf
Interesting SAGE modeling document from the UK for your next weeks COVID post.
(seems like WordPress tries to render that link inline and fails, so at least in my browser it shows “Firefox Can’t open this page”). Can’t edit my comment anymore so can’t fix it unfortunately.
Zvi – i just looked at israel numbers and they are having a huge surge! Is that something to worry about? I thought they were supposed to have herd immunity?!