Alan Jacobs' Two versions of covid skepticism summarizes a longer piece by Madeleine Kearns. Both are worth reading.

To his quotes I’ll add the core folly Kearns charges both the Covidians and the Skeptics with:

[swapped first two paragraphs; tweaks for clarity]

So this Philosophy Stackexchange answer by bobflux has me thinking, even as I’m about to get my booster shot. It’s long, but well-argued.

Intuition: Antibiotic resistance means you must finish your whole prescription so you kill the whole population, instead of just selecting for resistant ones. There is a similar concern with leaky vaccines.

My short summary, in table form plus three notes:

Expanding on those three paths:

1. Dengue vax caused antibody-dependent enhancement (ADE), where the vaccine increased viral load, making Dengue more deadly to the vaxxed. Ouch.

2. Marek vax in chickens extends infections of “strains otherwise too lethal to persist”. What used to paralyze and kill old birds is now 100% lethal even to young. All must be vaxxed, and will be carriers.

3. Common cold: Those with mild case go out and about, spreading mild variants and immunities. Those very sick stay home and spread less. Utilitarians have a moral obligation to host Covid Parties.

~End Summary~

I’m happily on the annual-flu-shot train, esp. on the hope that by the time I’m 70 and need it, my system will have seen a lot of variants. Also, I haven’t heard any worries about breeding more resistant flu. I’ve been assuming for awhile that COVID would follow the common-cold path of becoming prevalent and mild, at worst flu-like with annual vaccines. And given that it’s impossible to avoid exposure, it seems better to get side effects of the spike protein rather than infection effects of the live virus.

Now twice in the last week I’ve come across the 2015 paper about the Marek experiment and am thinking about the evolutionary dynamics, and monocultures. How to tell what path we are on? When is it better to Stoically accept the current infections to spare future generations?  

More immediately, should I go through with the booster shot? (Given it’s scheduled for tomorrow, that’s the default and most likely outcome. But I am wondering. )

Voice for compassionate harm reduction “when truth itself has supply-chain problems.”

readup.com

🔖 Alan Jacobs' post, beats me. What he said.

On the narrow point, there are risk-benefit analyses – like Peter Godfrey Smith on lockdowns – but like Jacobs and contra Dougherty, that’s not most of what I see. Dougherty seems better on sources of fear.

Watching Sydney’s Delta cases repeat the early-phase exponential growth of Melbourne, ADSEI’s Linda McIver asks:

Would our collective understanding of covid have been different if we were all more data literate?

Almost certainly, and I’m all for it. But would that avoid

watching Sydney try all of the “can we avoid really seriously locking down” strategies that we know failed us, … like a cinema audience shouting at the screen,

Not necessarily. Probably not, even, but that’s OK. It would still be a huge step forward to acknowledge the data and decide based on costs, values, and uncertainties. I’m fine with Sydney hypothetically saying,

I might be more (or less) cautious. I might care more (or less) about the various tradeoffs. I might make a better (or worse) decision were I in charge. That’s Okay. Even with perfect information, values differ.

It’s even fine to be skeptical of data that doesn’t fit my preferred theory. Sometimes Einstein’s right and the data is wrong.

What’s not okay is denying or ignoring the data just because I don’t like the cost of the implied action. Or, funding decades-long FUD campaigns for the same reason.

PS: Here is Linda’s shout suggesting that (only) stage-4 lockdown suppressed Delta:

The July 5 Lancet letter reaffirms the authors' earlier skeptical view of LabLeak. They cited some new studies and some older pieces in favor of Zoonosis. Summary of those sources below. (This post was originally a CSET-Foretell comment.)

(Limitation: I’m summarizing expert arguments - I can evaluate arguments and statistics, but I have to rely on experts for the core biology. )

Cell July 9: Four novel SARS-CoV-2-related viruses sequenced from samples; RpYN06 is now second after RaTG13, and closest in most of the genome, but farther in spike protein. Also, eco models suggest broad range for bats in Asia, despite most samples coming from a small area of Yunnan. The upshot is that moderate looking found more related strains, implying there are plenty more out there. Also, a wider range for bats suggests there may be populations closer to Wuhan, or to its farm suppliers.

May 12 Virological post by RF Garry: Thinks WHO report has new data favoring zoonotic, namely that the 47 Huanan market cases were all Lineage B, and closely-related consistent with a super-spreader; however, at least some of the 38 other-market cases were Lineage A. Both lineages spread from Wuhan out. Zoonosis posits Lineage A diverged into Lineage B at a wildlife farm or during transport, and both spread to different markets/humans. LabLeak posits Lineage A in the lab, diverging either there or during/after escape. Garry thinks it’s harder to account for different strains specifically in different markets. And the linking of early cases to the markets, just like the earlier SARS-CoV. A responder argues for direct bat-to-human transfer. Another argues that cryptic human spread, only noticed after market super-spread events, renders the data compatible with either theory.

Older (Feb) Nature: Sequenced 5 Thai bats; Bats in colony with RmYN02 have neutralizing antibodies for SARS-CoV-2. Extends geog. distribution of related CoVs to 4800km.

June Nature Explainer: tries to sort un/known. “Most scientists” favor zoonosis, but LL “has not been ruled out”. “Most emerging infectious diseases begin with a spillover from nature” and “not yet any substantial evidence for a lab leak”. Bats are known carriers and RATG13 tags them, but 96% isn’t close enough - a closer relative remains unknown. “Although lab leaks have never caused an epidemic, they have resulted in small outbreaks”. [I sense specious reasoning there from small sample, but to their credit they point out there have been similar escapes that got contained.] They then consider five args for LL: (1) why no host found yet? (2) Coincidence first found next to WIV? (3) Unusual genetic features signal engineering (4) Spreads too well among humans. (5) Samples from the “death mine” bats at WIV may be the source. In each case they argue this might not favor LL, or not much. Mostly decent replies, moving the likelihood ratio of these closer to 1.0, which means 0 evidence either way.

Justin Ling’s piece in FP: I’m not a fan. As I’ve argued elsewhere, it’s uneven at best. Citing it almost count agains them. Still, mixed in with a good dose of straw-man emotional arguments, Ling rallies in the last 1/3 to raise some good points. But really just read the Nature Explainer.

I think collectively the sources they cite do support their position, or more specifically, they weaken some of the arguments for LabLeak by showing we might expect that evidence even under Zoonosis. The argument summaries:

Pro-Z: (a) Zoonosis has a solid portfolio; (b) There’s way more bats out there than first supposed; (c) There’s way more viruses in them bats; (d) Implicit, but there’s way more bush meat too;

Anti-LL: Key args for LabLeak are almost as likely under zoonosis. Although not mentioned here, that would, alas, include China’s squirreliness.

Based on these I revised my LL forecast from 67% ➛ 61%. The authors put it somewhere below 50%, probably below 10%. Fauci said “very, very, very, very remote possibility”. That seems at most 1:1000, as “remote” is normally <5%. Foretell and Metaculus are about 33%, so I may be too high, but I think we discounted LL too much early on.

Measuring bot misinfo on facebook - DANMASK-19

Not exactly a surprise, but Ayers et al measure a campaign. Posts in bot-infested groups were twice as likely to misrepresent the DANMASK-19 study.

Authors suggest: penalize, ban, or counter-bot. Hm.

Sigh

Re: earlier posts:

The apparent discrepancy November/December discrepancy between higher CovidTracking counts (COVID19 deaths) and lower CDC official excess death counts has essentially vanished.

The actual excess deaths amount to +6,500 per week for December. There was just a lot of lag.

I give myself some credit for considering that I might be in a bubble, that my faith in the two reporting systems might be too strong misplaced, and looking for alternate explanations.

But in the end I was too timid in their defense: I thought only about 5K of the 7K discrepancy would be lag, and that we would see a larger role of harvesting, for example.

Yesterday I commented on a cousin’s post sharing a claim about 9 reported child vaccine deaths. I looked up each death in VAERS and noted two were actually gunshot wounds, 3-5 were special cases, so only 2-4 were notably concerning. I suspect this didn’t help: she quickly deleted my comment.

David Broniatowski says I shouldn’t be surprised. He argues that both debunking and censorship are counterproductive. Remember,

Russian Twitter “troll” accounts weaponized demeaning provaccine messages as frequently as vaccine refual narratives when conducting a broad campaign to promote discord in American society.

What to do instead? The hard work of opening “collaborations with public health partners”, and especially with physicians, who are generally trusted. This is of course harder. And I’m not a physician so that’s out.

Open letter from David Broniatowski:

The vaccine rollout in the USA has slowed driven, in part, by the fact that the most eager and confident citizens have now been vaccinated. The hurdle now is no longer one of vaccine supply, but rather, demand. In two new editorials, and a podcast, all in the American Journal of Public Health, I make the case that:

1. Debunking misinformation is insufficient to convince hesitant people to vaccinate. Rather, we must listen to their concerns and communicate the gist of vaccination in a manner that accords with their values.

2. Blanket removal of online content by Facebook, Twitter, and Google/YouTube may be counterproductive, driving hesitant people to seek out information on alternative platforms. On the other hand, social media platforms are excellent tools for microtargeting and can help public health agents to reach people who are the most hesitant. We can use social media, in combination, with traditional methods, to build relationships with the most hesitant people and increase their likelihood of vaccinating.

Together, these strategies can help us cross the threshold of herd immunity to end the pandemic.

Podcast is here. [<- Link may not render, but it works. -ct]

Thanks to Mike Bishop for alerting me to Jiminez' 100-tweet thread and Lancet paper on the case for COVID-19 aerosols, and the fascinating 100-year history that still shapes debate.

Because of that history, it seems admitting “airborne” or “aerosol” has been quite a sea change. Some of this is important - “droplets” are supposed to drop, while aerosols remain airborne and so circulate farther.

But some seems definitional - a large enough aerosol is hindered by masks, and a small droplet doesn’t drop.

However, point being that like measles and other respiratory viruses, “miasma” isn’t a bad concept, so contagion can travel, esp. indoors.

VAERS Caveat

Please people, if using VAERS, go check the details. @RealJoeSmalley posts stuff like “9 child deaths in nearly 4,000 vaccinations”, but it’s not his responsibility if the data is wrong, caveat emptor.

With VAERS that’s highly irresponsible - you can’t even use VAERS without reading about its limits.

I get 9 deaths in VAERS if I set the limits to “<18”. But the number of total US vaccinations for <18 isn’t 4,000 - it’s 2.2M.

Also I checked the 9 VAERS deaths for <18:

Two are concerning because little/no risk:

5. 16yo, only risk factor oral contraceptives
6. 15yo, no known risks

Two+ are concerning but seem experimental. AFAIK the vaccines are not approved for breastfeeding, and are only in clinical trial for young children. Don’t try this at home:

2. 5mo breastmilk exposure - mom vaccinated. (?!)
3. 2yo in ¿illicit? trial? Very odd report saying it was a clinical trial but the doctors would deny that, reporter is untraceable, batch info is untraceable. Odd.
4. 1yo, seizure. (Clinical trial? Else how vaccinated?)

Two were very high risk patients. (Why was this even done?):

3. 15yo with about 25 severe pre-existing / allergies
4. 17yo w/~12 severe pre-existing / allergies

Two are clearly unrelated:

1. Error - gunshot suicide found by family, but age typed as “1.08”.
2. 17yo, firearm suicide - history of mental illness

For evaluating your risk, only the two teens would seem relevant. They might not be vaccine-related, but with otherwise no known risk, it’s a very good candidate cause.

VAERS Query

I’m not able to get “saved search” to work, so here’s the non-default Query Criteria:

• Age: < 6 months; 6-11 months; 1-2 years; 3-5 years; 6-17 years
• Event Category: Death
• Serious: Yes
• Vaccine Products: COVID19 VACCINE (COVID19)
• 
  

Group By: VAERS ID

Sullivan compares COVID to AIDS, Camus, and . One person thinking through what vaccination & far fewer fatalities mean. When to stop masking? Will we? The thinking through is the point, but for summary, he concludes:

So get vaccinated. Then use reason. The point is to get back to normal life, not to perpetuate the damaging patterns of plague life. So take off your masks, if you want. Plan parties for vaccinated friends. Get your vacation plans ready. And stop the constant judging and moralizing of people with masks and those without. Summer is coming. Let’s celebrate it.

Individual thresholds may vary - but I endorse his call not to get attached to plague life, as many of Camus' villagers did.

Note: discusses condoms, and the interesting but imperfect analogy to face masks, esp. as the plague is beaten.

HTT Nuño Sempere’s January forecasting newsletter. And be sure to check out his marvelous Metaforecast service!

~ ~ ~

So: Metacululs and RootClaim give very different probabilities that COVID-19 originated in a lab (see earlier post summarizing Monk):

• Metaculus: 15% for Hubei lab origins (either accidental or deliberate) - median never went above 30% during the last year.
• RootClaim: 76% accidental release, and 2% deliberate, based on a (simplified?) Bayesian analysis.

Metaculus has ~3K forecasts on that question over the last year+, and over 260 comments, most well-informed. They’ve done well in COVID-19 forecasts vs. experts. (And famously one of their top forecasters nailed the pandemic in late January 2020, as Sempere reminds us.)

Rootclaim, as far as I can tell, begins with some crowdsourcing to formulate hypotheses, get initial probabilities, gather sources, and maybe to help set likelihoods. Then they do a Bayesian update. At one point they used full Bayesian networks. It seems this one treats each evidence-group as independent.

Both are heavily rationalist and Bayesian-friendly, and had access to each other’s forecasts. So the divergence is quite interesting - I wish I had time to dig into it some more.

Just re-found this @ayjay essay in an old tab.

The question I would ask churches that are re-opening without masks or distancing, but with lots of congregational singing, is: How do you think infectious disease works, exactly? How do you think COVID–19 is transmitted? What’s the theory you’re operating on?

I still know people using an incoherent mix of, well, all of these:

• There is no real pandemic.
• It’s a Chinese bio-weapon.
• Masks (etc.) don’t work.
• There’s easy and effective treatments.

CDC total deaths snapshot: December weekly #s gained about 4,500 vs. two weeks ago: there are now 4 weeks right near 80K, slightly above the highest April week.

That’s bad. But still hard to square with covidtracking deaths being 50% higher than in April.

Update 19-Feb

Week of 26-Dec is now at 81,406, up by ~1K. The week of 2-Jan is higher now, above 82K, gaining 1-2K.

#### Update 23-May

December totals are now about +26K versus April, or about +6,500/week. That’s pretty much all the discrepancy I was concerned to explain.

That further supports the live CovidTracking numbers from last autumn.

Essay worth reading in its entirety: The Great Reinforcer by Stuart Ritchie.

To be sure, out of the gloom of the pandemic came some incredible advances – the stunning progress made on vaccines chief among them. But these bright spots were something of an exception. For those of us with an interest in where science can go wrong, the pandemic has been the Great Reinforcer: it has underlined, in the brightest possible ink, all the problems we knew we had with the way we practice science.

Acknowledging stunning successes in the science of COVID-19, he reviews our regrettable and predictable failures. And hitting a little too close for comfort, notes how much harm comes from a desire to help.

A good column by our SVP for technology & innovation.

A friend notes that the US has a long of equating vaccines and public health with commie conspiracies. This from 1955, citing US Rep. Clare Hoffman.

What do today’s anti-vaxxers think of the polio vaccine?

~ ~ ~

Among the saner anti-vax objections is the observation that any prior exposure could lead to an overactive immune response in a later exposure – a leading explanation for the 1918 lethality. The careful objectors say simply, “we don’t know it won’t”. True, though I’d be curious whether their odds are notably different from pro-vaxxers. (Do they both agree we’re x% sure it won’t, and just value that differently, or do they have very different x?)

According to my social media, a popular version of the objection is that something is so wrong with the vaccine that half the vaccinated population dies in 5 years, from overreacting to the common cold, or some variant of “gray goo”. This appears to be as informed as the polio-vax scare above.

A stronger version would be that we recreate 1918, but bigger. Suppose SARS-COV-3 appears in 2048, and has a similar relationship that Spanish flu (1918) had to Russian flu (1889): those who got COV-2 (or its vaccine) have a hyperactive immune response. In a world where we don’t vaccinate now, maybe 1/3 of the population gets COV-2, and so suffers heightened mortality in 2048. In the world where we vaccinate everyone, the whole population faces heightened mortality in 2048.

A great deal turns on “heightened”. Like meteor strikes, the main force comes from an exceedingly rare worst-case event. If it’s worth spending on meteor defense, shouldn’t we “spend” to avoid a vaccine own-goal, however unlikely?

It’s worth remembering some things about 1918:

• The priming seems mostly to have affected those exposed in early development, not universally. Hence the peak mortality at 28 years old.
• Even that mortality was 5-10%, not 90%. (And I’m pretty sure case fatality, so infection mortality would be more like 1-3%.)

So the bookends choice looks more like:

1. Do nothing. COV-2 infects about 1/3 of the planet, and ~12M people die. So, about 10M more than now. COV-3 does something similar, but infection mortality is 1-3% among 28-year-olds, so globally we lose up to 1% of them. (Unless we’re prepared for it, and prevent secondary infections.)

2. Vaccinate. COV-2 stops relatively soon, so maybe 5M total (using Metaculus' forecast for end of 2021.) COV-3 does something similar, but now peak infection mortality among 28-year-olds olds is more like 3-9%, so globally we lose 1-3% of them. (Unless we’re prepared for it.)

Scenario 2 is bleak enough - and you can tweak it to be worse. But in this 1918-specific version, it’s mostly an argument against vaccinating the pregnant and very young. Two groups we already tend to exclude.

But that’s just one scenario. Presumably whatever happens won’t look exactly like 1918. We don’t know what it will look like. But we do know we can probably save 7M lives now by vaccinating. The weight of the “what if” scenarios might be a good argument for limiting vaccination to some degree (just in case), but seem a poor argument against not doing it at all.

Thought exercise: suppose the fastest, cheapest, best way to immunize the population was via GMO corn? I assume it would have no effect on the arguments. But would it shift the battle lines?

[Edit: the thought exercise is not intended as a desirable alternative. It’s here to pump intuition among pro-vax but anti-GMO folks, as the argument outlined above seems similar to anti-GMO arguments. ]

[Edited 2021-02-02 to shorten and include Alexis' suggestion. -crt] [2021-05-23 Updated the CDC “excess death” numbers at the end. tl;dr they went up even more than required. 84,715 for the week of Dec. 26.]

In The Vaccine’s Race Against Time, Andrew Sullivan remembers his experience at the end of the US AIDS epidemic, and reminds us that “plagues … often finish strong.” It’s a good read.

At my church’s weekly service, we used to have general prayers like, “For all those suffering from COVID-19”. But since late autumn it seems we’ve had more specific prayers for parents, siblings, kids struggling with it. Half a dozen in recent weeks. Maybe dropping off now - let’s hope.

Happily the US is vaccinating, if unevenly. Sullivan urges us to continue other measures, because deaths after the cure are all the more tragic. Happily, my VA in-laws have had their first dose. So have many healthcare and at-risk friends nearby. However, my CT elders are still waiting.

Numbers

Whatever you think of the daily COVID counts, total deaths is pretty solid. And there are over 400K excess deaths (all causes) for 2020. That’s a lot. As expected, the December deaths rose to match April’s, despite some foolish (or malicious) contrarian claims in early November.

CDC Excess Deaths Count
Now (January 31, 2021)	Last month - detail

A remaining puzzle

Lag?

One answer is regular lag. Based on past lag, we expect the top bars to get another 2,000 or so as more certificates flow in. That would still keep them roughly on par with April. So that won’t do.

Special lag?

There could be extraordinary lag – prehaps due to volume, or holiday delays. But it feels ad hoc. In its favor, a 2016 paper found that it took 13 weeks to get to 84% of all-cause deaths, and twice that to get to 95%. Okay, but 4-6 weeks has worked most of 2020. Is there independent reason to think the reporting system has slowed? [Charles goes and checks.] Hm, yes. At least the CDC says so in their weekly report:

Longer delays in reporting of hospitalization and mortality data may occur due to the holidays and the large number of COVID-19 illnesses occurring in recent weeks.

Still… could it be something else?

Displacement?

Maybe COVID is displacing other deaths via a combination of: (1) Miscounting, (2) Harvesting, and (3) “On Balance”.

1. Miscounting: Yes, 3,000 people are dying daily of “PIC” – Pneumonia, Influenza-like illnesses, and COVID-19. But 1,000 of those are actually the usual (non-COVID) P and I, getting miscounted.

2. Harvesting: Maybe all 3,000 are COVID-19, but 1,000 would have died anyway within say 4 months.

3. On Balance: Yes, 3,000 die from COVID-19. Also, far fewer are dying of other causes, esp. (non-COVID) P and I.

Miscounting

Miscounting would be the most embarrassing for those involved. Can we test it? In it’s favor, the same weekly report quoted above says the ILI-net is receiving far fewer visits, as people avoid the usual doctor’s office and ER for diagnosis, or only go when they suspect COVID. We can also see essentially no influenza-coded deaths so far this winter (second chart).

ILI-net visits

Influenza-Coded Deaths (dark blue)

Still, maybe the sum of all non-COVID deaths will account for a portion of those 1,000. Testable.

Harvesting / On Balance?

In Harvesting, a younger, faster Reaper beats the old man to the punch. Same people die, just sooner, of a different thing. So fewer excess deaths than COVID-19 deaths. On balance, we get 3,000 daily COVID deaths, but an excess death count of only 2,000.

It need not even be the same people, as long as on balance the numbers match. COVID-19 is much more transmissible, so interventions that keep it around R=1 (as we have) would drastically curtail flu etc. That seems to have happened during Australia’s winter.

So…

I like to think the CovidTracking hospitalization & deaths counts are reliable. But that seems to imply a 50% rise in December’s CDC deaths count, vs. now when it basically equals April’s peak. [I meant 50% rise in excess deaths. But I was wrong. Area under the curve, not peak-to-peak. A 25% rise in excess deaths accounted for the 7,000/week extra.] So, after that exercise, what are my intuitive guesses:

• Regular lag: +2,000 deaths per week
• Extra lag: +3,000 more
• Miscounting, Harvesting, On balance: +2,000 total

[ Looks now like regular + extra lag just about covers it. ]

If that’s right we’ll see the December total death certificates peaks rise by ~5,000 cases. That still feels high.

Coda

In the meantime, I pray we stay well, avoid making others ill, and update our beliefs with new evidence.

From Pale Rider, Afterword:

…and novelists try to put themselves [in] the heads of those who lived through it…. Like worker bees they are busy weaving threads between the millions of discrete tragedies to create a collective memory - a living photograph of the Spanish flu.

I was reviewing this old interview with Australia’s Paul Monk, covering Coronavirus, China, conspiracy theories, reckoning, and risk to Pax Americana, as they looked to him in late April.

If nothing else, listen to him open by quoting Thucydides.

tl;dr Monk reviews key plagues from Athens to now, discusses the situation in April, and assesses three different China-did-it theories, and closes by arguing that the West must reckon with China, and it’s behavior during COV-2 has been a wake-up call.

I’ve had the pleasure to work briefly with Paul on argument mapping and critical thinking, and this is a good example of weighing plausibility and evidence.

It’s probably better to listen or read the interview, but here’s my summary of key points.

Plagues

I’ve summarized Paul’s summary in a table, filling in numbers from Wikipedia or Ancient.edu (example). It seems the Roman plagues are hard to estimate because they lasted so long.

Conspiracy Theories

Monk does a nice job separating and assessing the China theories for the origin of SARS-COV-2. As of April, but it seems a solid assessment.

First, there’s the utterly mad theories: 5G and control chips. The China theories aren’t like that. That’s key.

1. Unrestricted War: deliberate leak. This gains plausibility from the 1997 book Unrestricted War by two Chinese colonels who suggested this possibility. So, it’s a viable theory - and important to note it was sensible for people to draw the connection. So, two avenues of assessment:

   a. Sanity Check: Why would the Party agree, given grave risks? (a) How could they guarantee they could control it in China? (b) How could they be confident the outside world wouldn’t figure out whodunnit and “there would be hell to pay”? (c) To control in China you’d have to shut down the economy. Why? When you’re trying to dominate economically? Okay, so it would be hugely risky.

   b. Evidence: None. [In the meantime we learned a bit more about how sus' they were acting, but Monk was pretty clear on that already. And their actions are pretty likely on the other China theories too. OK, what about biology? A Taiwanese dissident published a paper saying it was a deliberate release … but her claims for that fell apart. Her publishing circumstances were also dodgy. -And as I try to remind people, evidence is a ratio: to count for this theory, it has to be more likely on this theory than on its contenders. -ed]

   c. Meta Evidence: some serious right-wing analysts looked at and dismissed this claim. You’d expect them to jump on it if they could. The intelligence communities in AU, NZ, CA, UK, and US all concluded this looks unlikely. Again, being their key job, you’d expect them to jump on it if they could - at least confidentially. But there’s no evidence in leaks or actions that this is considered remotely plausible.

2. Unintentional Escape A - It came from Wuhan or another lab, but the usual sort of leak. (Hi, I live in Reston. Ebola anyone?) In this variant, the party simply doesn’t know how it got out, takes awhile to figure it out, and when they do realize “Wow, this is serious”, they say so. If the Party had a history of acting responsibly, this might be more plausible. It doesn’t.

3. Unintentional Escape: B - As before, but once it leaks they think, “This looks bad” and conduct a propaganda campaign to suppress & whitewash. Evidence: they’re definitely conducting a propaganda campaign, including failed attempts to bully Australia and the rest of the WHO into not investigating.

Reckoning

Yes trading with China helped them prosper. Yes, that was good for us too. Yes, it’s middle class grew, and wanted more liberty. No, the Communist Party did not become more tractable. There was a glimmer of hope, and it was quashed.

Monk says it’s time to get consensus of Western & African countries, and tell China, “This cannot work. It can’t work for us and because it can’t work for us, you’re going to realize it cannot work for you. …there’s no other choice."

Risk of Nationalism

1918 and WWI led to the Great Depression, which ushered in reactionary politics around the world: Germany, Japan, Italy, El Salvador. We’re seeing signs now, and that threatens the Pax American that made possible “the greatest expansion in average human wellbeing across the planet … over the last [30-70] years ever in history.” To the extent that other countries follow China to say “Our interests are paramount … then we’re back in the 1930s.”

Silver Linings

Paul thinks people have become more reflective, and the pandemic has highlighted the need for global solutions and clear thinking. I suspect it’s just Paul.

He has a nice analogy to The Martian though.

Another great piece at Fantastic Anachronism: Are Experts Real.

I hadn’t heard about N=59. 😱

…if the N=59 crew are making such ridiculous errors in their own papers, they obviously don’t have the ability to judge other people’s…

In a discussion with @Somensi about excess deaths, I was puzzled by an apparent discrepancy between two sources that have both been reliable, insofar as I can tell:

• The covidtracking.com weekly data on cases, hospitalizations, and covid-attributed deaths.
• The laggy but solid CDC excess deaths counts/estimates.

Puzzle: December Covid vs Excess Deaths

The basic question from mid-December was how to reconcile this and this:

With this:

(Screenshots are from mid-Dec.)

In short, by early December it was clear that covidtracking.com had started diverging wildly from the CDC excess death counts. Two basic theories:

• covid-tracking was correct - CDC counts would catch up in a month or so.
• covid-tracking was wrong - this was an attribution blip.

There’s a lot of noise on the thread, but @Somensi, who I don’t know, was also looking at data, and citing a good source. Doomsters like me have been using CDC excess data since April as evidence that the pandemic was real and could not be simple relabeling of flu deaths. Here the same source is cited to say the December spike couldn’t be real.

People on both sides who knew the CDC data understood it had a lag of 4 weeks or so – because it relies on actual death certificates completing all their procedural checks and getting filed. In 2016 it took 10 weeks for 80% of certificates to get filed. CDC now claims it gets to 60% in ~10 days. (There are plenty of people who don’t get the lag – it seems even to have tripped up JHU’s Dr. Briand, at least in her headline claim that there were no excess deaths in 2020.)

Problem: covidtracking is the most thoroughly-vetted weekly data source in the US. They’ve tracked the CDC excess deaths (after lag) the rest of the year. And reliably, their cases –predict–> hospitalizations 4 weeks later –predict–> deaths a few weeks later. The December death spike followed that pattern. Plausibly, CDC was just lagging.

Problem: CDC 4 weeks back should be pretty good, and it looked nothing like April. As my correspondent said, CDC data “would have to be lagging by an unprecedented amount."

Resolved

It’s obvious once you see it.

That death spike (swoop?) at the end is super fast. If you hover over the attributed deaths chart from covid-tracking, you find that the Nov. 14 cases are exactly in line with their July numbers, about half their April numbers. And in line with the mid-Nov. CDC numbers. The steep rise is mostly in the last 4 weeks.

Corroboration

As of Dec. 23, we can look at how the CDC data has changed. Data should be pretty complete through Nov. 21. We see that Nov. 14 is now about 1,000 higher than before (and than the July peak), and Nov. 21 about 2,000 higher than that.

Not a swoop yet, but basically on par with the covidtracking chart week-for-week. Here that is again from today, highlighting Nov. 21. (The bold line is the 7-day moving average, a far better comparison than the daily total.)

Forecast

We should definitely expect the CDC excess deaths count for December to reach April levels.

The announcement of RR:C19 seems a critical step forward. Similar to Hopkins' Novel Coronavirus Research Compendium. Both are mentioned in Begley’s article.

So.. would it help to add prediction markets on replication, publication, citations?