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Various actions and decisions in wars, and their efficacy, tends to get debated decades and centuries to come. That still doesn't mean countries don't have to take actions when they get into wars, though.

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On the last point, isn't the cost to utility just the excess utility? The $1 of lost GDP isn't actually a loss to utility, because I kept the $1 instead of getting the first dollar of benefit, and the seller both forewent the dollar of sales but also forewent a similar $1 of operating costs.

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No mention of Australia or New Zealand?

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Agreed. Extremely stringent but comparatively short lockdowns in these countries were not discussed, but offer a different perspective in that they actively pursued and achieved elimination of the virus and a return to normal social and economic conditions (bar border restrictions). New Zealand’s economy actually grew in 2020.(https://www.bloomberg.com/news/articles/2020-12-16/new-zealand-economy-surges-out-of-recession-amid-spending-spree)

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Agreed. Why not look at cases like Vietnam, Taiwan, South Korea, China, Australia, New Zealand etc. where initial strong lockdowns and eradication strategies and then continuing travel restrictions /quarantines brought back normality early on and were then punctuated by localized lockdowns to address outbreaks where they passed the travel barriers? Those are the ultimate examples of lockdowns preventing future lockdowns.

That was mine and many observers’ preferred policy in terms of what to do in spring 2020, and this was followed early on in Denmark for instance, and also in places like Senegal. But then travel opened up without quarantines in the summer of 2020… One can argue this was unreasonable or unrealistic in the US and Europe — but the US still today has a travel ban for Europe since spring/early summer 2020. Just not for other places, due to weird politics.

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Why do you only focus on cases where this strategy succeeded? Many other countries pursued similarly aggressive early approaches that later failed miserably, e.g. many South American countries. (That region is also interesting to study because we have Brazil as a natural control.)

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Cambodia scraped by due to luck; eventually its luck ran out when cases were imported from neighboring Thailand in February 2021.

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Vietnam is a police state, China's lying, and the rest of your list are island nations with secure borders who started with a low infection count. South Korea isn't technically an island but they have the DMZ. All of those countries are unfair comparisons.

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Any particular comparison is "unfair". That's the point of a statistical analysis. Are there relevant differences among these countries? Do any of the "unfairnesses" turn out not to matter?

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Come on. The antecedent probability that we'd find such a high proportion of islands in a world where the vast majority of countries aren't islands, if being an island was casually unrelated to success in handling the pandemic, is minuscule. And, of course, we have an obvious mechanism that would explain the effect if being an island was in fact the explanation.

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Yes, it's clear that being an island in this sense is extremely helpful. Being a police state may or may not be. Even among island nations, we might be interested in what policies (either governmental, or pursued independently by residents) were helpful or not. That's my overall point. We shouldn't just ignore them.

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Would be nice to have a larger dataset that includes places like Indonesia, Philippines, Seychelles, Cyprus, Caribbean nations, etc, to get a better sense of what does and doesn't work for island nations.

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Why would China be lying? When there is a COVID outbreak in China, it's very noticeable, and the government takes great efforts to inform the people. China also has numerous neighbors that quarantine Chinese travelers; they would notice if China had a pandemic.

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They lie about EVERYTHING, ask anyone who has ever seriously traded markets

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China might be lying to some extent (especially about the countryside) but not by three orders of magnitude. It's not North Korea. There are quite a few expats there and they know how to get around the Great Firewall. If the situation in places like Shanghai or Beijing had ever been remotely as bad as in Europe/the Americas/India we'd all know by now.

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It is also the optimal policy that is predicted from a wide range of models.

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Those are also countries that are widely separated by oceans and where border controls can be effective. Africa has also done relatively well due to its relative lack of transportation connectivity. In some ways China also benefits from the same dynamics due to its suspicion of foreigners. Certainly their coercive quarantine measures left nothing to chance. New Zealand discovered this when some tourists did not follow the rules and caused an outbreak.

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Australian states also closed borders to Victoria's during its second wave, which was doable. Granted there are fewer border communities than in the US or Europe, but it's not impossible to close land borders.

(Australian state borders are currently closed to New South Wales - who are having an outbreak which is small by global standards but potentially threatens our COVID-zero status)

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The "island" thing sounds like a pretty red herring to me, unless people believe that the virus reached Italy by sneaking through land borders along the Silk Road, or that flying over the Philippine Sea magically heals all passengers on a plane but flying over Kazakhstan doesn't. Western countries got 99 reasons why they couldn't achieve what e.g. Australia could but land borders ain't one.

By July 2020 Italy had managed to bring case numbers far enough down that it could have implemented an actual test-and-trace program without breaking a sweat, but actually it only implemented a perfunctory one because "muh privacy". In addition, it refused to implement border quarantines -- there were superspreader events when people went to dance clubs right after getting off planes from Brazil or Croatia. Sure, a handful of the seeds of the second wave might have sneaked through the land border with Slovenia, but very clearly that wasn't the main issue.

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The government can implement restrictions/tests at every airport and port in a way that would be impractical to do at every single road crossing between two schengen countries.

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While that is certainly true, and it means that Italy doesn't have a path to get Australia like pandemic numbers, airport and seaport lockdowns could plausibly have meant numbers more in line with the rest of Europe.

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Certain Schengen countries had shut down their borders altogether during the first wave, keeping them open with restrictions can't be much harder than that. (Of course there might still be people crossing them illegally, but probably not enough to go from "test-and-trace programs feasible" to "test-and-trace programs unfeasible". Most illegal immigration to Italy comes from the sea, not from land borders, and Australia isn't that much farther away from Indonesia/New Guinea then Italy is from North Africa.)

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>there might still be people crossing them illegally, but probably not enough to go from "test-and-trace programs feasible" to "test-and-trace programs unfeasible".

Presumably this depends a lot on the nature of those land borders. Do we have any idea how many people have been illegally crossing between Detroit-Windsor or Tijuana-San Diego or in smaller places like Basel or Konstanz?

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> The "island" thing sounds like a pretty red herring to me, unless people believe that the virus reached Italy by sneaking through land borders along the Silk Road

Cases got through to Italy faster through other routes (air) than they would have through land borders. However, this doesn't disprove the argument that *even if* Italy had prohibited entry from abroad as much as feasible, cases would have eventually snuck in through land borders, while the same is not the case for Australia or NZ.

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The infection spread Wuhan > Milan > London > NYC before ANYONE knew it existed. There were effectively four virus origins, because those four cities are connected by the fashion industry. Wuhan is where the garments are made.

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At the time that Milan was blowing up, we also had blow-ups in Qom/Tehran and Daegu/Seoul, and by the time London and NYC had big blowups we also had Madrid, and could have had Seattle.

Is Wuhan a larger garment manufacturing center than other cities in China, Southeast Asia, or Bangladesh?

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Isn't the U.S. getting about 180,000 illegal immigrants every month, which are dispersed around the country immediately? How could any travel restrictions possibly be effective under those circumstances?

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This. Anyone who thinks a zero covid strategy could ever have been feasible in the US for this reason is basically either ignorant of the realities or illegal immigration or bonkers.

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Or ANYWHERE

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Except I also hear the "but those are islands!!!1!" spiel from people in countries with a helluva lot less illegal immigration than the US.

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"Lockdown test and trace" only works if you can test every single person who crosses your border. Island nations were the only places in the world that could do "test and trace," and they needed a low infection rate to begin with to pull it off.

Check the third graph here:

https://hwfo.substack.com/p/does-the-usa-have-the-worst-covid

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China isn't an island nation; Vietnam is at least attempting test and trace. Thailand's, however, did fail due to the porous land border.

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China's numbers can't be trusted, and Vietnam has border security Trump could only dream of and still caught a mid summer infection wave from illegal Chinese immigrants.

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This poster is right.

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I see this a lot (and have posted about it a lot before on this forum and others), but I think people still don't realize how insanely behind the US New Zealand's COVID was at the time to lockdown. Generally speaking, most countries woke up to COVID around March 12th (Rudy Gobert + Tom Hanks). Assuming a 3 week infection to death period, we want to know deaths as of April 2 to infer infections.

On April 2nd, the US had a total of 8000 deaths, implying almost a million infections, and had 1500 people dying a day (and rising) implying 150k daily infections.

New Zealand had 1 death. New Zealand had 5 confirmed cases on March 12th. So the comparison to New Zealand is basically asking why couldn't the US have locked down 5-6 weeks earlier - that's the only time we had a hope of NZ like outcomes. By March 12th the cat was out of the bag - our outbreak was already worse than it got in any of the Vietnam/Taiwan/South Korea ON the day we locked down.

Now Australia is a bit more of an interesting case, and probably the strongest pro lockdown one out there. But still - they had ~900 people die by the end of their summer wave, with a population of 25 million that means on a per capita basis their entire summer wave resulted in as many cases as the US already had by March 15th. It's just a completely different level of disease.

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We didn't have a Summer wave - it is Winter in July in the southern hemisphere.

The July wave was entirely confined to a single city, so dividing by the total population makes no sense. Outside of Melbourne cases were ~0. On a per capita basis the height of the Melbourne outbreak were roughly comparable to the September lull in the US. If you were willing/able to implement right border controls you could have done the same. The US just lacks the state capacity to pursue an elimination strategy.

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Sorry yeah used northern hemisphere seasons.

Ok, so Melbourne looks to be ~5 million people and NYC is ~ 8 million? But the greater NYC metro area is ~ 20 million, but a lot of those are in non New York States. So I may not exactly be comparing apples to apples but lets go with this.

Victoria has had 820 COVID deaths, let's just assume those are all in Melbourne.

On April 4th *alone* NYC had 819 COVID deaths. By 3/29 they had more deaths in New York (state, but mostly City at that point) than Melbourne did over the entire Pandemic. Even if we assume the 20 million number and 4x population, we hit that on 4/4.

Again, it was just a completely different level of disease burden in the US before lockdowns started. This matters a lot - if we assume a non-China type lockdown can get R down to 0.6, 12 weeks of lockdown turns a million cases into 2100. Which is still a decent amount of cases! R of 0.7 (an estimate I've seen for US lockdowns) puts you at 13,000 cases - very much not an under-control outbreak! If you only have 50k cases, you get down to 110 cases with a 0.6 lockdown, and 700 with a 0.7.

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Yeah, it's pretty obvious when you do the back-of-the-envelope math that if some place in the US like NYC had tried to get to zero cases in the initial lockdown, they would have needed to enact a harsh lockdown for 6 months plus.

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Yes, you need to do a Chinese/Australian style lockdown to achieve elimination.

Curfews. Work permits. Mask mandates. All enforced by police/army.

We had all of the above in Melbourne.

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Yes, but I'm saying that such will work way less well if your starting point is USA 3/12 disease levels as opposed to Melbourne name literally any date disease levels.

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The Atlantic provinces in Canada are another example of this strategy. They basically became a small, semi-isolated unit within Canada with fairly lax restrictions (a friend of mine in PEI has been playing Magic: the Gathering every week at his local game store for months now) once they got their initial outbreaks under control. When cases started to go up, they did short but fairly harsh "circuit-breaker" lockdowns and intensively used testing and contact tracing. It worked pretty well. The Maritimes IS fairly isolated and small, which works to its advantage, but it's also not very authoritarian, nor did the provincial governments have reputations for being very competent before the pandemic.

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The Atlantic provinces (Newfoundland, Nova Scotia, New Brunswick, Prince Edward Island) in Canada are another example of this strategy, and I haven't ever seen them mentioned. They basically became a small, semi-isolated unit within Canada with fairly lax restrictions (a friend of mine in PEI has been playing Magic: the Gathering every week at his local game store for months now) once they got their initial outbreaks under control. When cases started to go up, they did short but fairly harsh "circuit-breaker" lockdowns and intensively used testing and contact tracing. It worked pretty well. The Maritimes IS fairly isolated and small, which works to its advantage, but it's also not very authoritarian, nor did the provincial governments have reputations for being very competent before the pandemic.

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The Atlantic provinces in Canada are another example of this strategy, and one that is pretty underreported. They basically became a small, semi-isolated unit within Canada with fairly lax restrictions (a friend of mine in PEI has been playing Magic: the Gathering every week at his local game store for months now) once they got their initial outbreaks under control. When cases started to go up, they did short but fairly harsh "circuit-breaker" lockdowns and intensively used testing and contact tracing. It worked pretty well. The Maritimes IS fairly isolated and small, which works to its advantage, but it's also not very authoritarian, nor did the provincial governments have reputations for being very competent before the pandemic.

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Victoria had the longest lockdown on Earth.

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Now that Australia is putting people in fucking camps, are you finally willing to admit that it wasn’t a short no big deal lockdown?

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Only a short stay in the camps.

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Thats what they ALWAYS say...

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He did mention both in passing, as examples of how to succeed if you move quickly enough and are capable of enforcing travel restrictions.

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"No mention of Australia or New Zealand?"

Yes, 3rd paragraph in Preliminary Theoretical Issues 2

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Was added in response to this comment, and a couple of others. I definitely don't think it's comprehensive enough, even with the addition. I just feels like a lot of key data points are getting left out of the analysis (Not just Au/NZ, Taiwan and Korea as well to name a couple more)

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Sadly even this brief mention is incorrect. Our second lockdown in Melbourne July 2020 was quite successful and that was 4 months into the pandemic.

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Melbourne had a really harsh lockdown for *112 days*, which they did because "test-and-trace" completely failed for them (or they were insufficiently competent to implement it successfully), in order to get cases down from 100 per day (when lockdown started) to zero.

The fact that this happened is actually a really strong argument against "get to zero (or near zero) initially, then control by test-and-trace". If the latter part of the "optimal policy" isn't feasible, this dramatically reduces the payoff to the first half also.

Now, it took 112 days of pretty draconian lockdown in Melbourne to get from ~100 to 0. The initial lockdowns in the US and Australia happened more or less the same date (e.g. looks like March 20 in NYC, March 22 in NSW). How many days should New York have locked down for to get from the ~100k infections per day it was experiencing at the time to zero?

And would getting to zero a) be possible or b) make any sense as a goal in any location with substantial illegal migration? (E.g. the US and probably also Europe)

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"make any sense as a goal in any location with substantial illegal migration?"

Probably not. But that's what internal border controls are for.

I don't think Melbourne eliminated COVID in the shortest possible time; China has regularly tested entire cities and eliminated the pandemic in numerous areas that way (e.g., look at its control of the recent Guangzhou outbreak).

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We were well above 100 a day in July. But yes you need strong border controls to make it work. Not just at the international border - but internally.

Obviously the US is just not capable of implementing such a policy.

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Lockdown was announced on July 7 and appears to have started on July 9. From google (which just pulls the numbers for JHU), the 7dma for Victoria (they don't show Melbourne specifically) was 114 on July 8, and the worst recent day to that point had been 168 four days prior. And obviously the true number of infections was higher, although the positive test rates remained very low (about 0.5%, so hopefully catching the vast majority of positives). So yeah, I was a little under, but not dramatically. What few people seem to remember is that cases then rose for another 4 weeks after the start of lockdown, with the 7dma peaking in early August.

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That is in part because the initial lockdown was relatively mild. Full stage 4 lockdown didn't come into place until 1 August.

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Australia and New Zealand are islands with moats the size of the Pacific Ocean. Trump could only dream of a wall called the "Great Barrier Reef."

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Porous land borders did end up causing Thailand's and Cambodia's current pandemic, but America and Britain never even tried so much as controlling flights. China (which is more ambitious than Thailand and Cambodia) so far has managed to avoid all waves of COVID despite vast land borders.

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>despite vast land borders.

Are these the kind of land borders people commute across daily?

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Britain relies on a regular flow of lorries in and out, with the same driver throughout their run, to supply it; controlling the border was never feasible.

Australia and New Zealand have been so successful because they trade by boat, and the crew of the boat don't have to have much contact with the people on the dock.

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Moats, schmoats, the Arafura Sea is smaller than the Mediterranean and the Torres Strait is almost as narrow as the Strait of Sicily.

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Strictly true, but both sides of Torres Strait are incredibly hard to reach by land. The Queensland end is a two-day drive in a winch-and-snorkel equipped 4WD from the nearest meaningful town, and the New Guinea end doesn't seem to be reachable by any sort of road at all.

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Interesting to consider how this applies to yearly influenza. All the above things considered, would pro-lockdown people suggest yearly lockdowns until universal flu vaccines? It's unfortunate RNA viruses mutate so damn much.

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I have heard a lot of people say that the lesson of this last winter is that we should newly emphasize hand-washing, normalize mask wearing (if sick or just if worried), and similar measures for flu season, given how small the flu season was this year. I haven't heard anyone propose lockdowns though. More in the vein of changing social norms and public awareness.

Not sure if official numbers are out yet, but I heard that the norm is about 20,000-30,000 and this year it was more like 600 - if true, something like a 97-98% drop in deaths. If it had happened without COVID around to rob the headlines and make large numbers of deaths seem trivial by comparison, it would be seen as a massive public health victory.

Actually it raises the question of, if lockdowns don't work then why did that happen? Or is flu different from COVID?

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"Or is flu different from COVID?" Qualitatively but not quantitatively. Measures which reduce the R of COVID from 2.5 to 1.25 also reduce the R of influenza from 1.5 to 0.75

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Unfortunately, I don't think the R0 of COVID-19 is 2.5 any more; the Delta variant's R0 seems to be at least twice that.

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Globally, seasonal flu kills about 500k / year. I don't know about deaths, but flu incidence has gone down 99% globally this past season.

The US typically has 30m symptomatic cases, 440k hospitalizations, and 36k deaths each year. Deaths are hard to estimate last year because they are completely drowned out by un-tested covid deaths (which is in the 100s of thousands?). There is one known US pediatric death from the flu last season, compared to average about 200. Last season there were 1800 positive flu tests in the US, 200 of which were hospitalized (I don't know how many died). https://www.cdc.gov/flu/weekly/index.htm

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I'm not exactly sure why false information seems to be actively spread in this thread (not blaming you, I assume some sort of media-induced biased in some of scott's demographics) but as best as we can tell, influenza deaths increased in the US in 2021: https://jamanetwork.com/journals/jama/articlepdf/2778234/jama_ahmad_2021_vp_210048_1620430592.84249.pdf

Number of cases are hard to measure due to the confounders already mentioned, but one can assume not that much fewer given the amount of deaths.

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There's nothing in your link indicating an increase in influenza deaths. The official stats listed there are "influenza and pneumonia" deaths, which will almost certainly include some of the untested covid deaths. Covid notably causes pneumonia.

Mortality stats generally uses the category "influenza-like illness" (ILI) because it is hard to reliably distinguish flu from a variety of other respiratory diseases. Generally most ILI is the flu, but obviously one wouldn't assume that is still true for 2020.

If you have any statistics about distinguishing influenza from ILI please do share. I have linked the official CDC data above which has information based on actual flu testing, showing a 99% decline in lab-tested flu.

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I just see someone else pointed out that that paper is about deaths in the 2019-2020 flu season, which was significantly worse than usual. The paper you linked says nothing about the 2020-2021 flu season, which reliable data shows was about 99% smaller than usual.

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As well as anti-covid measures cutting flu transmission, consider the possibility that a substantial number of the most vulnerable people who in other years might have died of flu might have died of covid first instead.

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Well, influenza has an IFR depending on age non-monotonically, with a minimum in your early 20s (IIRC) -- infants have a pretty much negligible chance of dying from COVID but not from the flu. (But in first-world countries other than e.g. Israel or Ireland I guess there aren't anywhere near enough of them to sway the statistics either particular way, anyway.)

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I'm sorry to inform you, but you were lied to.

The numbers published by JAMA (as close as you can get to top tier consensus-focused journals) seems to indicate 7.5% increase in influenza deaths in 2020: https://jamanetwork.com/journals/jama/articlepdf/2778234/jama_ahmad_2021_vp_210048_1620430592.84249.pdf

But they lump influenza and pneumonia unassociated with covid-19 together, so somewhat hard to tell.

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That paper is only about the US and as far as I can tell about the calendar year 2020. In the Northern Hemisphere most flu deaths are in January and February, so before anywhere outside Hubei implemented COVID-related restrictions (other than bans on direct flights from China).

Flu deaths in the 2020 southern hemisphere winter (July/August) and the 2021 northern hemisphere winter were down by several orders of magnitude from usual, IIRC

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I have written an opinion piece advocating for increasing measures against the flu: https://ermsta.com/posts/20210527 "Defeating influenza: lessons from covid"

However I don't advocate for lockdowns, as I believe they are wholly overkill. I believe vaccinations, paid sick leave, contact tracing, border screening, situational masks, and self-administered home-testing are the way to go, in vaguely decreasing order of importance. I put a low emphasis on measures that require high compliance from individuals (physical distancing, hand washing, masks). Also hand washing has little impact on flu transmission.

The ambitious goal for flu is to vaccinate south and east Asia (<5% of India and China get flu vaccine), where flu spreads year round and may be the source of flu elsewhere in the world.

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> border screening, contact tracing

Sounds wonderful. I suggest you supplement this with a comprehensive dose of surveillance to catch anyone who is noncompliant. You could setup something like camps for those who do not show enough solidarity to join, or give them a "compliance helper" who watches them to motivate them to do better.

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In a last attempt to fight ignorance in this thread.

please consider reading the mortality statistics for the US in 2020 and note that influenza+pneumonia combined (sometimes hard to separate) but as-best-as-possible separated from covid-19 (assume erring on the safe side of attributing less deaths to them) increased in the US in 2020 in spite of measures: https://jamanetwork.com/journals/jama/articlepdf/2778234/jama_ahmad_2021_vp_210048_1620430592.84249.pdf

Currently, I've seen no indication of a significant decrease anywhere else with reliable mortality numbers, though I'm sure it exists, but you'd need to at least tally up well-monitored countries and their number before making this claim.

Given that the US accounts of a large % of the population where COD can be monitored well, I'd say it's very likely your source are wrong.

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Before the pandemic, I did used to wonder how many sick days would be saved by people following basic hygiene - e.g. hand-washing, not going to work when ill and potentially contagious.

I've been pretty consistently pro-lockdown but wouldn't support them for flu because the threat of flu is much lower. But there are plenty of other things we should do to reduce flu deaths - masks on public transport (if you're ill but have to travel); work from home (if you can) when potentially contagious; improve ventilation in buildings; get vaccinated.

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note, flu deaths increased in the US in 2020 based no the numbers aggregated by JAMA: https://jamanetwork.com/journals/jama/articlepdf/2778234/jama_ahmad_2021_vp_210048_1620430592.84249.pdf

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This seems to contradict everything else I've seen on flu last year - and not just in the US. E. g.

https://www.scientificamerican.com/article/flu-has-disappeared-worldwide-during-the-covid-pandemic1/

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I'm giving you the mortality data in the US as reported by the most reputable medical organization in the US

If you prefer CNN or scientificamerica's hottakes that's fine.

All I'm really trying to say is that you should consider looking at the actual data.

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The data in the Scientific American hot take is from the WHO. The data in the JAMA article is from the CDC and their dedicated flu report seems to think the flu season is milder:

https://www.cdc.gov/flu/weekly/index.htm

The numbers you're talking about are flu and pneumonia combined, and include a number of codes that aren't influenza. Unless I'm misunderstanding the actual data, the "flu and pneumonia" deaths can include lots of non-flu deaths. Given that the CDC and the WHO both produce reports saying that the flu has been minimal this year, I'll go with those.

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I don't want to go into how diagnosis on small samples might be wrong, but I'd say it's fairly intuitive to think that they are more prone to manipulation and misinterpretation than country wide mortality, which is the most uncontroversial number available.

Yes, various forms of pneumonia and influenza are combined, in part because differentiating between which of them was causal to the patient's death is hard, but I've got little reason to believe there was a giant spike in covid unrelated pneumonia this year, though it may be the case.

Have you looked at the actual number of people the WHO and CDC are basing their estimstes on ? I.e the people being tested for the presence of various flu strains in the analysis they use.

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George's paper is about the calendar year 2020, whose flu wave was almost entirely before COVID restrictions even started.

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Probably not lockdowns, since the flu is significantly less dangerous than COVID. But, as others had said, normalizing mask-wearing at the very least does make sense.

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note, flu deaths increased in the US in 2020 based no the numbers aggregated by JAMA: https://jamanetwork.com/journals/jama/articlepdf/2778234/jama_ahmad_2021_vp_210048_1620430592.84249.pdf

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I think the number 1 problem with that strategy is simply that compliance would be very low. Many people already were dubious of following COVID lockdowns, even when they felt they might be necessary. I think very very few people would be able to be convinced that we suddenly need to be having flu lockdowns when we’ve survived without them basically forever.

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It should be noted influenza deaths increased significantly in the US, ~20% accord to the JAMA end-of-year mortality report I read (death being the closest proxy for infection rate in this case, since people aren't neurotic enough to confirm it)

Of course you could come up with a just-so story about how covid-19 and hospital closure somehow causes this (seems unlikely, since there's no correlation with death from influenza after covid, and common sense could well help us infer it to be otherwise, a strong immune reaction remains protective once the pathogen is gone + hospital treatment for influenza is mildly effective to very ineffective to harmful depending on who you ask)

But it still seems like the increased sanitary measures did didly-squat to limit the spread of influenza. Which is rather surprising, but not so much if your working hypothesis is that of a conspiratorial nut (e.g. covid-19 is real but "what mass-media and most review literature portrays to be covid-19" is not)

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What is the purpose of performing multiple high and sub-level analyses of changing definitions of what constitutes a case, what constitutes a hospitalization and what constitutes a death? First of all, more testing initially means a spike in cases. There is already a high false positive rate for testing regurgitating dead nucleotides and amplifying it many times just to get a match. Threshold sensitivities were modified for non-vaccinated vs vaccinated patients. Case counts were modified from 'clinical x-rays' to '# of symptoms' to 'if you had a positive test within 28 days, inclusive if you died from a ladder or car accident'. Testing was eliminated for those who were already vaccinated or partially vaccinated. Older patients were forcibly locked up together in elder care homes with positive cases, even though the # of co-morbidities for each case due to death is already high, and has an average age in the 80s... The cofounding incentives of diagnosing patients as positive or getting treatments, getting payoffs either by medical practitioners or hospitals. The ad nausea footage of the Chinese falling ill and locking up of doors with piling dead bodies when the elephant in the room is that countries like Russia/China and some states in the United States have been fully opened for more than one year yet the cognitive dissonance when none of this materializes in the West. The initialization of pandemic by case counts, not by death rates as changed per WHO's guidelines a decade ago. Moving targets, changing definitions, high compliance rates yet no difference whatsoever or strong correlations when compared to different nations that didn't even bother reacting. Flu cases mysteriously disappearing or causes attributable to other causes of death being removed, when people are denied services to hospitals for testing/treatments because of a focus solely on this .. illness. The alignment of recurring seasonality of influenza/flu season with spike in cases, also post-mortem death rates following 'variants' / high vaccination rates. There are a lot of confounding variables that make this whole point moot. Placebo groups are entirely vaccinated.. already or they weren't treated with a negative control but an alternative vaccine for measles. No baseline studies for animal mortality. Multiple stakeholders/shareholders in multiple corporations/media companies/fact checkers/social media platforms incestuously having a strong profit incentive for booster shots or stronger lockdowns.

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What exactly is the point you are trying to make here? Because it feels to me like you're trying to imply a conspiracy without outright saying that COVID-19 was a hoax in the US. Replying to all of these claims would be difficult, but there's at least one I know is absolutely wrong.

> Case counts were modified from 'clinical x-rays' to '# of symptoms' to 'if you had a positive test within 28 days, inclusive if you died from a ladder or car accident'... Flu cases mysteriously disappearing or causes attributable to other causes of death being removed

We can be pretty sure that the deaths attributed to COVID-19 were actually caused by COVID-19. The CDC has a graph of excess deaths here (https://www.cdc.gov/nchs/nvss/vsrr/covid19/excess_deaths.htm) which shows that for the duration of the pandemic more people than usual died. This number of excess deaths aligns with the number of COVID deaths that hospitals reported, and if anything, indicates that hospitals under-counted. That is to say, unless you can think of some other reason for six hundred thousand people to die in the United States, the only thing they can be attributed to is the one thing that was different in 2020 versus 2017 - COVID.

Likewise, we can be sure that these aren't just flu cases being misreported because that would imply that the Flu was suddenly many times more effective in 2020. This would be especially confusing given that people were self-isolating many times more strictly than before. More importantly, if it WAS some kind of hyper-deadly variant of the normal flu, the reaction by the government and people should have been exactly the same - whatever level of lockdowns they deem appropriate to save the most lives.

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2020 was not only different in terms of COVID. You're assuming all the measures didn't themselves create any deaths, which is unreasonable given that a key effect of lockdowns is restricted access to healthcare.

The point the guy is making is that unfortunately this analysis is not very good and actually quite typical of the stuff you find in the epidemiology literature. I normally quite enjoy SA's essays but this one just had me whacking my head against the table quite a few times.

• Taking model simulations as credible despite that those models are consistently askew? Check.

• Assumption that germ theory is complete and the behavior of respiratory viruses is well understood, even though real world data contains many things that it cannot explain? Check.

• Assumption that "COVID deaths" actually means "died of COVID" although it doesn't? Indeed!

Still, at least the evaluation of the Flaxman study is reasonable.

Look at Swedish excess death for 2020. Depending on how you select the base rate you can get anywhere between zero and 9000 extra deaths. That is not a serious number, the absolute level is the same as in 2012. Modelling predicted 90,000+ COVID deaths if they didn't lock down hard. That is not a success for lockdown nor modelling.

I also have a bone to pick with the attempt to separate voluntary behavior from "lockdown". People's behavior changed because they were lied to by modellers and other assorted pseudo-scientists like Flaxman and Ferguson, and that's also what drove formal legalized lockdowns. Those two things can't be separated. The real question is not "do lockdowns work" - they don't and this can be easily seen in the raw data sans models, it does not require complicated analysis (the economist was on the right track!). The real question is what effect reduction in social interactions and mobility had, versus the costs of that, independent of whether it was compelled or not.

Finally, we should also count not just the economic costs but the destruction of the social capital of science. When you see that the totally fraudulent Flaxman study was cited over 1000 times and is just an exercise in self-delusion, it destroys people's confidence in all institutions but especially scientific institutions. That story has been repeated ten thousand times throughout this era and will have large and unclear effects on society going forward. Certainly, society seems to be splitting into people who take academic modelling and government data seriously, vs those who write it off as the work of the systemically biased.

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Just to pick on one point:

> Assumption that "COVID deaths" actually means "died of COVID" although it doesn't

I don't think Scott literally assumed this. I think his assumption here is that whatever the discrepancy is between these two numbers, it isn't systematically biased in one direction or another. Is there any reason to think that Sweden systematically over-classified people as "died of covid" while Norway systematically under-classified people as "died of covid"? Unless you've got something like that, the analysis should still stand, with just slightly larger error bars.

Also, the bit about sending deaths back to the level of 2012 - that seems to me like a huge cost, no? Or do you think that a decade of medical progress is negligible?

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Firstly, 8 years isn't a decade (2020 vs 2012) and you're assuming that falling mortality rates over time are all to do with medical progress, vs things like healthier lifestyles. I don't think anyone really knows exactly how the progress there breaks down.

You're right that the systematic over-counting would be relatively consistent, however, lockdowns are ultimately justified on *absolute* terms, not relative. Absolute numbers and the exact values on the Y axis are critical. Look at your reply for what can happen otherwise - you're asserting that going back to the 2012 level is a "huge cost" with no idea of the actual absolute numbers involved (they are quite tiny on the scale of a country).

Was anyone in Sweden freaking out in 2012 about the horrible amounts of death that year? No. Nobody noticed nor cared. It was a normal year. This should be a clue that something has gone seriously wrong with our perception of risk and mortality.

You can find a good analysis of all this here:

https://softwaredevelopmentperestroika.wordpress.com/2021/01/15/final-report-on-swedish-mortality-2020-anno-covid/

(note: the comparison of 2020 vs 2012 is one of population adjusted mortality).

I feel like there's a very common reasoning error amongst highly educated people that's been visible throughout COVID times, but also I've seen it in earlier years too. It's something I keep meaning to write about on my own blog but other things always take priority. The error I mean is reasoning exclusively in relative terms, and forgetting to look at absolutes. The most inglorious example of this with COVID is the fixation on R and "exponential" growth. R(t) is just the derivative of the graph of positive test results over some very short time window. It doesn't itself contain any insight or meaning, yet experts routinely say things like "we must lock down because R is above 1" and politicians then parrot them. Lockdowns were originally justified on *absolute* grounds where the absolute value was hospital capacity, because justifying them on relative grounds would have been obviously insane, but the moment they were implemented the activation criteria smoothly shifted to being merely "positive test results are trending up" with the absolute values forgotten.

The fixation on exponential growth is another example of this. Viruses don't grow exponentially, they have S-curve type growth in which their "exponential" phase stops very quickly and then growth starts slowing down again, until they reach a peak and then cases start to fall. And this can all occur very quickly as is well known from outbreaks of other respiratory viruses like flu, common cold, etc. Yet people get stuck on the exponential part and act as if left unchecked COVID cases would constantly double until the entire population is infected. Left unsaid is what would happen after that if the scenario were true: the day before "terminus day" half the population would get infected at once and then infections would suddenly drop to zero (yeah yeah, modulo a final day of mop-up because the population isn't a square number, exponential growth is not always a clean doubling etc - you get what I mean). This is all totally wrong and no disease in history works this way, in fact recognizing that all epidemics are bell curve shaped is the founding observation of the field of epidemiology itself. It means the absolute numbers involved are very important, yet, nobody cares. They're all fixated on relative rates of change.

Outside the world of COVID I've seen this in my own industry (software). It's extremely common for people to make statements like "X cannot scale" when talking about software that solves a problem where the maximum sizes are already well bounded e.g. "number of customers we can reasonably be expected to have in the next 5 years" in a mature bank is not going to be 100,000x higher than it is today, simply because that would require the bank to completely take over all of its competitors and then take over most of another continent, which would never be allowed. Often reasoning in absolute terms as well as relative would let you engineer much better solutions but the last time I did a back of the envelope calculation showing that $SOME_SYSTEM being accused of not being scalable could actually work fine, jaws literally dropped and the customer got all excited, asking that I send him the calculations so he could show other people (they were trivial).

I don't know exactly what leads to this problem but it seems common. I think it's because reasoning in absolute terms ("it's a small problem so what's the big deal") sounds less clever, as if you aren't thinking ahead to what might be and thinking ahead is what clever educated people are expected to do.

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There's a lot going on here, and it's very helpful discussion, so thanks for that. I think the discussion of relative vs absolute amounts is important for a lot of this, but I don't agree with what you think are the implications of all this.

> Was anyone in Sweden freaking out in 2012 about the horrible amounts of death that year? No. Nobody noticed nor cared. It was a normal year. This should be a clue that something has gone seriously wrong with our perception of risk and mortality.

I don't think that "freaking out" should be proportional to absolute amount of death. I think "freaking out" should be proportional to absolute amount of *death we can do something about*. No one was freaking out in 2012 because the fact that we were on trend indicated that we were probably doing about as well as we could do without drastic lifestyle changes. But the fact that we had the death rate of 8 years ago when we've been on a trend of deaths decreasing by 0.5% per year indicates that this year we *could* do something about it.

> R(t) is just the derivative of the graph of positive test results over some very short time window. It doesn't itself contain any insight or meaning, yet experts routinely say things like "we must lock down because R is above 1"

> people get stuck on the exponential part and act as if left unchecked COVID cases would constantly double until the entire population is infected.

> recognizing that all epidemics are bell curve shaped is the founding observation of the field of epidemiology itself.

Maybe some people are making the mistake, but the founding observation of epidemiology is that outbreaks grow as a logistic curve, that is roughly exponentially increasing at first, roughly exponentially decreasing at the end, with the scale of its maximal point being given as a simple function of R. R is not just the rate of roughly exponential growth at the beginning, but 1-1/R is the absolute level at which the curve turns around absent any population-level behavioral changes that change R.

R is really important for understanding the absolute number of people that will be infected absent behavioral changes, and not just the relative number over the next few days.

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> No one was freaking out in 2012 because the fact that we were on trend indicated that we were probably doing about as well as we could do without drastic lifestyle changes.

It's hard to see why drastic lifestyle changes weren't justifable in 2012 but they were justifiable in 2020, assuming the absolute numbers being discussed really are similar. I expect that's the point the OP was making.

> But the fact that we had the death rate of 8 years ago when we've been on a trend of deaths decreasing by 0.5% per year indicates that this year we *could* do something about it.

We always knew we could do something about it. We always knew that widely deploying masks would cut down yearly influenza deaths. We always knew that vaccination, isolation and quarantine protocols could reduce these yearly deaths even further.

Heck, we even always knew that we could reduce traffic fatalities by improving car safety and lowering speed limits.

I think all of these facts were fairly common knowledge, but we didn't do any of these things, so I don't see how your reply actually addresess the OP's argument.

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"the death rate of 8 years ago when we've been on a trend of deaths decreasing by 0.5% per year indicates that this year we could do something about it."

That isn't a logical deduction at all. This is again a very common fallacy seen in the last year - the automatic assumption that the so-called "non pharmaceutical interventions" can affect the spread of a highly infectious respiratory disease. That has never been proven by anyone, it's just a modelling assumption, yet people act as if it's an axiomatic truth and then go ahead and make lots of other inferences on the back of it.

So: transient increases in mortality do not automatically imply that those increases could be eliminated via government action. And the data seems to show that in this case they can't.

Moreover, freaking out due purely to *relative* changes is exactly the fallacy I've just been criticizing. You haven't even put concrete bounds on what level of increase should cause society-wide freaking - just asserted that *any* increase in mortality vs prior baselines should do so. What if the rollback had been to 2015? Lockdowns still worth it then? 2018?

Consider this: if you sum deaths in Sweden from 2017+2018 and then 2019+2020, you get a nearly identical number! (the web page I already linked to shows this graphically). If you are willing to believe 2019 was an unusual outlier rather than the start of a new trend, you could therefore argue COVID didn't affect mortality at all. Now what?

This is why reasoning has to be grounded in absolute values. If it isn't then you can end up with wild over-reactions to noise in the data, which we see all the time now. E.g. newspaper stories claiming cases are "soaring" when looking at the graph shows the graph line barely visible above the the X axis.

"R is not just the rate of roughly exponential growth at the beginning ... but 1-1/R is the absolute level at which the curve turns around absent any population-level behavioral changes that change R."

This statement doesn't make any sense. R is a rate. You can't do an equation on it and get an absolute number of people. Again, you are demonstrating my point: there seems to be great confusion here between absolute numbers (people, cases, hospital beds) and mathematical abstractions.

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I like this. It's nice of you to explicitly set out your points, because it makes them easier to reject.

First:

> You're assuming all the measures didn't themselves create any deaths, which is unreasonable given that a key effect of lockdowns is restricted access to healthcare.

It's implausible the lockdowns were directly responsible for the deaths of hundreds of thousands of people. It's doubly implausible that those excess deaths due to lockdown would directly mirror the spread of the infection according to our tests, especially in states where the government response to the pandemic was weaker. The number of confirmed cases goes up, so do the number of deaths two weeks later. I don't have time to investigate the correlation here, but you can see it just by comparing the two graphs visually.

> Taking model simulations as credible despite that those models are consistently askew? Assumption that germ theory is complete and the behavior of respiratory viruses is well understood, even though real world data contains many things that it cannot explain?

The models are constantly askew because they're sensitive to initial conditions, because they can't literally simulate the behavior of millions of humans, and because our understanding of the effectiveness of lockdown procedures is constantly in flux. We knew this at the start of the pandemic, every single credible scientist made a disclaimer on their models stating something to this effect. The reason we still use models despite all of that is because they're good at capturing the exponential growth we see in pandemic scenarios even if the precise details vary.

As for germ theory. What gives you reason to suspect that germ theory in particular is incomplete? And what specific behavior do you think that germ theory failed to model in this scenario? Keep in mind that germ theory is distinct from the SIR model and derivatives that most people use when doing naive, initial predictions.

>When you see that the totally fraudulent Flaxman study was cited over 1000 times and is just an exercise in self-delusion, it destroys people's confidence in all institutions but especially scientific institutions

Ah, yes, I remember the time the replication crisis happened and nobody ever trusted science again. Certainly, this singular highly cited study (which presumably had some fraction of those citations present counterarguments) which was only moderately influential, during a crisis where information was scarce, will irreparably damage the reputation of the institutions involved in publishing it and the enterprise of science as a whole forever.

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Epidemiology and macroeconomics have *always* been on the list of the hardest sciences to trust, because they basically don't allow for experiments, and require masses of observational data, and deal with the complexities of large scale human society, in addition to the complexities of the individual interactions involved.

Social psychology used to be seen as somewhat more reliable than these sciences, but not since the replication crisis.

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"It's implausible the lockdowns were directly responsible for the deaths of hundreds of thousands of people."

Nobody is saying *all* the deaths were caused by lockdowns, only that *some* were and fallacious logic assuming they cause none at all will lead to a conclusion of undercounting when we know that in reality the classification mechanism used must automatically lead to over-counting.

In the UK when lockdowns started, admissions to ER halved overnight. People were being told to avoid the hospitals. Moreover, elderly people who were already infected were flushed INTO care homes, where they proceeded to infect a lot of other people. All these are part of what I consider to be the consequences of model-driven mass hysteria, which we can usefully refer to as "lockdowns" as we don't have a better word for the whole enchilada right now.

"they can't literally simulate the behavior of millions of humans"

I'll echo WC in saying you should tell Neil Ferguson (nb: not Niall, that's a different academic). Because literally simulating the behavior of millions of humans is exactly what his model tries to do. Go read it - it's an agent based model that literally updates an array of people with their locations and health statuses.

Of course, it "can't" simulate the behaviour of the entire UK population so they just run it on a population slashed by some fraction and claim it's the same. By far not the worst assumption they make.

"every single credible scientist made a disclaimer on their models stating something to this effect"

I think you're agreeing with me then, just that there are no credible scientists. Because for sure if scientists were saying "our models will drastically over-estimate levels of death so please ignore them" then nobody got the memo.

Please. "Scientists" have throughout this entire event consistently claimed not only that models are highly accurate, despite overwhelming evidence to the contrary, but that politicians must take drastic action based on their predictions immediately, without even a few days of delay to let people outside the cosy little academic circle poke at them. The Report 9 from Ferguson et al that directly triggered lockdown in the UK didn't even give any uncertainty bounds.

Re: germ theory. We know germ theory must be incomplete because models that implement it are always wrong by miles regardless of what disease they're trying to model. For one it cannot explain why there's more than one peak - epidemiology has (amazingly) nothing to say on the topic of seasonality, why it happens or how that can be reconciled with the simple models they use. A SIR, SEIR, SEIR+ or whatever model is a direct implementation of germ theory in software. I don't know where you get this idea that they're distinct. SEIR means "susceptible, exposed, infected, recovered" which is the level of understanding of a virus that a child would have. These models are all based on the assumption that the only way people can get infected is by directly coming into contact with someone else who is infected (=exposure), and then rolling a 6 on some many-sided dice.

Yet there's lots of ways the known microbiology of viruses can lead to other views, for example, if infected people create viral aerosols that can hang around inside buildings for long periods then being "exposed" is about your contact with a place, not a person. SEIR models don't handle that at all. It would also imply that being outside is safe which we know from contact tracing studies is true, yet SEIR models have no concept of this. If those aerosols could also be moved around via atmospheric convection it would help explain why yearly influenza outbreaks all start everywhere at once instead of visibly spreading outwards, and why it's possible for (non SARS-CoV-2) coronavirus outbreaks to happen in entirely isolated populations - a topic that has been investigated briefly in the pre-modelling-era epidemiology literature but never solved.

Will Jones has been doing some good explorations of this topic if you want to read about it more.

As for trust in science - the Flaxman study isn't an outlier is it? The >1100 citations it accrued despite being an exercise in circular logic is unsurprising because stories of bogus studies becoming highly cited are a staple of Scott's writing. As for the citations arguing with it - nah. Academics hardly ever do that, especially in epidemiology. Go pick citations from Google Scholar and see for yourself. I just did it, the results are standard. The dominant theme you'll find for this paper and others is that citations virtually never argue with the paper they're citing. Gwern has some stats on this, negative citations are something like <2% of all citations. Real citations are usually almost random. Some of the ones I just spot checked cited Flaxman et al as evidence that "health care workers and seniors are at particularly high risk" (the paper has nothing to do with that), that "aggressive measures appear to be successful" (the paper takes this as axiomatic), that "stay at home orders were widely instituted" (the paper is a very indirect way to show that) and for assuming a serial interval of 6.5 days (the paper takes this as its own assumption).

So actually yes, watching scientists engage in a massive circular back-scratching campaign on the back of a completely fraudulent paper actually will irreparably damage the reputation of the institutions involved. Indeed it already has. Good luck finding average people in the UK who think Prof Ferguson and Imperial College aren't a bunch of illegitimate shysters.

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If one good thing is to come from all of this it will be universal distrust of experts bearing mathematical models. It will probably just be the red tribe though.

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Why is "universal distrust" a good thing? Shouldn't we have better calibrated moderate trust, rather than just flip from "expert always right" to "always ignore expert" or even "expert always wrong"?

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I don't think people do calibrated trust. I also think that laundering conjecture through mathematics is really darned rampant and default to distrust is probably for the best. Note, not, "always distrust expert," rather, "always distrust expert with opinion in the form of mathematical model."

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I think the problem is that detecting which models are good vs bad is very difficult, takes a lot of effort by trained people, journals will not propagate the resulting analyses (they end up only on blogs that you have to be in-the-know to find), and finally, my experience has been that the overwhelming majority of such modelling papers are bad. So just defaulting to distrust seems like a good heuristic.

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Yes. And that was appropriate before.

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Well it will certainly be good for those seeking investment in perpetual motion schemes. No more of that pesky faith in the Second Law of Thermodynamics, which is, after all, merely a mathematical model based on observation -- no underlying theory *at all*.

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...although, the more I think about it, the more I agree with you. For example, if there is wider general mistrust that vaccines, seat belts, and household smoke alarms save lives -- all conclusions based on statistics and modeling -- then this will accelerate Darwinian natural selection a bit, and future generations will be a little smarter. I like it!

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You read Scott's blog. So you're certainly capable of understanding the difference between empirical observations described mathematically and conjecture stated mathematically. Not that you're going to, of course.

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Ah. So there's no empirical data underlying anyone's epidemiological models? An interesting assertion.

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Over time, responses to covid will undoubtedly cause some death: e.g., some patients skipped routine cancer screenings in order to social distance, which almost certainly will cause some people to die who would have survived if their cancer had been detected.

But deaths caused by lockdowns and other responses to covid would be more likely to accumulate over time: the ratio of total excess deaths to covid deaths in November-December 2020 would be higher than in March-April 2020 due to the bad effects of nine months of lockdown piling up compared to when lockdown was novel in March-April 2020.

But that's not what we see. Instead, we see total excess deaths being notably higher than official covid deaths in March-April 2020 (probably due to some doctors misclassifying covid deaths as something else before they became familiar with covid) and by November-December, the two figures correspond well.

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Yes, the CDC's graph of incremental total deaths is convincing: the U.S. had extraordinarily more deaths in 2020 than would be predicted from deaths per year since WWII. Week-by-week excess total deaths match up extremely well with the usual estimates of covid deaths, and even suggest that covid deaths were undercounted in March and April 2020 and then were pretty accurately counted for the rest of 2020.

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Using paragraphs would probably make more people willing to read what you write. Although if it's just conspiracy theorizing it might not be worth reading so maybe you're doing us a favor?

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I also bailed on this huge run-on paragraph.

I have no proof whatsoever, but IME, lack of white space strongly correlates with poor arguments and conspiracy theories.

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It definitely implies "I'm writing this to scratch a psychological itch" rather than "I'm writing this to change people's minds"

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Yeah I think the main thing is that if you care a lot how other people perceive you you're both less likely to rant about conspiracy theories and more likely to type with careful spelling, punctuation, and paragraph breaks.

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As a term, "conspiracy theory" is a lot like "criminal": there are certainly some non-central examples that aren't bad but those are rare enough that I don't feel the need to be too careful attaching negative connotations.

But you do have a point. In the future I'll consider trying to use the term "paranoid fantasy" instead, since that captures a little more precisely the meaning I'm trying to convey.

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The point is probably that even if absolutely everything you say is true, it wouldn't change the outcome. It's just statistical noise.

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I live in Wisconsin, a state that had a judicial fiat against lockdowns for most of the pandemic but is otherwise very similar to its neighbors Minnesota and Michigan, which had fairly significant lockdowns. I've been hollering to the wilderness that the pandemic really didn't seem that much worse, or the economy any better, than these natural comparisons. Nice to see someone do the work to confirm my suspicions.

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fwiw, as someone who lived in Wisconsin under voluntary lockdown, I saw very different outcomes (more cases) among my social group in Wisconsin then I did in comparative internet social groups in other states. Many (20%?) of the households on my block were infected, many (most?) of my housemate's coworkers, etc. Compared to my coworkers in NYC, none of whom were infected, the picture is very different. (Although I'll note that my job instituted a WFH policy about 7 to 10 days before the official NYC lockdown, so that probably is a maximally good lockdown case, compared to my housemate's job, which reopened as soon as the state did)

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Better HVAC could be a game changer. Maybe someone needs to invent a ceiling fan with a filter which is continuously irradiated by UV light, which draws all the droplets up to the ceiling and neutralizes them. If this already exists, let me know.

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That being said. I’m not sure about the whole analysis-by-country thing. I know that is how most of the statistics are framed. But population density plays a role (as well as people per household).

I think there is a “this is bad” threshold (set perhaps by the media) but when northern Italy and NYC had real crisis, I think that influenced people’s voluntary behavior. If there had not been epic level bad, people might have been going out more. Antimaskers never embraced the badness of it all, for whatever reason. In terms of drawing conclusions for future pandemics, “scare them so they obey” May be the moral. If you are right about the role of voluntary restrictions on individual behavior. Which appears to make sense.

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There are so many things that need to be accounted for but are very hard to incorporate. One exception, the age demographics are easy to come by, and honestly I wonder why that isn't standard in all these studies. Another example is pre-existing health, both comorbidities everyone agrees about (obesity, diabetes, compromised immune systems) and those that are more controversial (eg vitamin D deficiency). An issue that seems almost criminal to ignore is the quality of healthcare patients received. Granted, it's hard to quantify and incorporate, but I don't think there's a controversy that initial treatment strategies like putting people on ventilators were between useless and counterproductive, and that the quality of care varied by location and improved over time.

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You need much longer exposure to UV light than you can get with normally circulating air.[1] Or you have to use far more intense light for the short time each parcel of air is close to the UV source, to the point where the light becomes dangerous to people (at least their vision).

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[1] https://www.ajicjournal.org/article/S0196-6553(20)30756-2/fulltext which suggests about 9 minutes of exposure to UVC light to wipe out SARS-CoV-2.

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Hansonian hot take: lockdowns aren't about preventing COVID, they're about preventing dissatisfaction in conscientious distanced citizens, who want official validation that their non-distancing neighbors *should have* stayed indoors as much as them. In other words, staying at home causes lockdowns.

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I have pretty much the opposite take: lockdowns cause unrest, which is why China ended theirs quickly (they didn't want people to have nothing to do all day but sit around thinking about how they were unhappy with the government) and blue states ended theirs slowly (they *did* want people to have nothing to do all day but sit around thinking about how they were unhappy with the government).

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I think it's a cycle. People get scared and demand the government lockdown then they get bored and get angry so the government relaxes the lockdowns rinse and repeat.

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I think that a big thing that causes lockdowns is a prior big wave.

To steal a point from my own comment, in the rest of the country people ask why people in NYC were so insistent on wearing masks for so long, even outdoors where it's extremely unlikely to matter. I think the answer is how bad it got in April 2020. The thing I remember people saying was that the sound of ambulances came from every direction, incessantly, day and night, for weeks on end. The news was talking about how there were emergency tent hospitals in Central Park, how the city had run out of space to store dead bodies. The government essentially told people to stay away from hospitals unless you were having trouble breathing, and even then every hospital in the city had people lining up out the door. The USNS Comfort came to provide relief to the city, and I'm sure it wasn't lost on anyone that the only other time that happened was September of 2001.

The week of April 11, 2020, the number of deaths in the city spiked to more than 7x the normal amount.

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> I think the answer is how bad it got in April 2020. The thing I remember people saying was that the sound of ambulances came from every direction, incessantly, day and night, for weeks on end. The news was talking about how there were emergency tent hospitals in Central Park, how the city had run out of space to store dead bodies. The government essentially told people to stay away from hospitals unless you were having trouble breathing, and even then every hospital in the city had people lining up out the door.

Hmm.

I remember this post from March 27: https://elaineou.com/2020/03/27/racist-virus/

> By now you’ve probably seen this NYTimes article describing the horrific state of affairs at a New York City hospital. Patients dropping like flies, nurses reduced to wearing trash bags, refrigerated trucks brought in to house the overflowing dead.

> my brother’s hospital across the city was nothing like that. His hospital admitted many COVID-19 patients, but few have been severe cases and none have died. Today Hillary Clinton (SHE’S TOTALLY RUNNING YOU GUYS) ordered pizza for everyone, and the hospital workers had a pizza party.

I would have to grant that March 27 predates April 11. But I tend to suspect that, given what was described by March 27, the next two weeks weren't much worse.

Were people lining up out the door of every hospital, or were they lining up out the door of some hospitals that made the news?

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Don't know about this person's brother's hospital, but according to the CDC in NYC the week ending March 27 there were 2805 deaths in the city and the week ending April 11 there were 7862 deaths. Either way I don't think it changes my overall point.

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The Office of the Chief Medical Examiner over on 1st Ave brought back the outdoor white tents for the overflow of bodies. Another sobering sight that was only precedented by 9/11.

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The total expected number of deaths in the week ending April 11 in New York City for an average year is 1053. In 2020, it was 7852.

https://www.cdc.gov/nchs/nvss/vsrr/covid19/excess_deaths.htm

That's the kind of thing that gets people's attention.

An emergency room doctor in NYC wrote an essay about how the incessant ambulance sirens suddenly died off around April 7, 2020 about 1 pm (IIRC), suggesting it took about 2.5 to 3 weeks for intense behavioral changes due to covid to have an effect on hospitalizations.

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None of the emergency tent hospitals were widely used, no? The Javits Center was famously equipped and then never really used, the USNS Comfort was only used for a handful of people.

And morgue space is perennially tight; it’s a semi-regular story in Detroit that morgues cannot contain the amount of homicide victims. This is a statement on the amount of morgue space rather than the number of homicide victims.

I’m not in the corpse business, but I imagine it is optimized for an average amount, such that even a small increase would result overflow. It does seem reasonable that I would want my morgue always at capacity so I wouldn’t plan for space to sit empty waiting for a catastrophe. Moreover, since corpse handling in the US is well-regulated, maybe retrofitting is not practicable?

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Kind of but you could also argue that lockdowns prevent free-riding: if conscientious citizens stay home for the purpose of preventing outbreaks but some free-riders ignore it and don't make any sacrifices, they're reaping some benefit (lower R0 and less coronavirus) without making any sacrifices. It's just coercion to prevent defection.

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A more generous interpretation of that would be "people get pissed if the government let's their friends and family die unnecessarily"

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I'm a little skeptical of assigning some consistent purposeful motivation like this to an action independently taken by at least thousands, probably millions, of individual decision makers. Other than first movers, it probably becomes more about some form of inter-governmental inertia or peer pressure rather than any sort of calculated, considered action with well thought-out reasons. That likely applies to the other side of the coin, too. As soon as a few leaders denounce tyranny and exclaim loudly they're banning lower level governments from shutting anything down, now others that have branded themselves of a similar ideological bent feel like they need to do it too or face a backlash from the half of the 24 hours news cycle their voters pay attention to.

The number of conscientious citizens who honestly care one way or the other is drowned out by the pitchfork mob.

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Well, it could also be social signaling. I mean, *almost everybody* doesn't commit murder because they feel it's wrong, and not because of the law against it. That is, if we repealed all laws against murder, I don't think the murder rate would rise by a factor of 100 because everyone would now think it's OK.

So the law against murder is to some extent a signal where we (as a society) tell anyone who is any kind doubt "we all agree this is wrong so DON'T DO IT in case you were at all unsure." In the same sense, you could consider lockdown measures as a version of social signaling, where the majority tells some wavering minority "we think this is much more serious than you do, and we're prepared to enforce that viewpoint on you."

Whether that's a good or bad thing depends not only on whether you think the majority in this case was actually making the correct call (as it does with murder), but also in whether you think the majority should be in the business of enforcing its will on dissenting minorities at all. A lot of room for philosophical disagreement.

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A few points, at the risk of repeating myself:

1) "This is an absolutely beautiful graph. It’s showing how lockdown strictness (as of May 5) correlates with death rate over time. We find that early in the epidemic, the stricter your lockdown, the worse you're doing. This is the endogeneity... Later in the epidemic, the stricter your lockdown, the better you're doing - probably because the strict lockdown is giving good results."

While the graph indeed looks quite nice, the meaning is much less clear than implied. Unfortunately (from the perspective of being able to do easy causal inference using the time series variation), consider the following two stylised facts:

i) There is substantial spatial correlation in lockdown intensity - e.g. the hardest lockdowns occurred in the northeast and the Pacific west, the loosest restrictions were in the South and plains states.

ii) The various waves of Covid have exhibited substantial amounts of spatial correlation in outbreak levels. The first wave hit the northeast hardest, the second wave the south, the third wave really kicked off in the plains states, and so forth. It doesn't take that creative a thinker to work out plausible climatic patterns that could give rise to this sort of seasonality.

Accordingly, just how sure are we that the picture of "over time, the lockdown state advantage became stronger" is causal? One easy thought experiment is to extend the time horizon of the graph. And indeed, in the short-lived fourth wave (when b.1.1.7 finally broke through, before the vaccines murdered it), something like 9 of the 10 states with worst outbreaks (as measured by weekly cases per capita at that point in time) were states with stricter than average lockdowns. They also happened to be clustered in the northeast and midwest. Of course, this doesn't mean that the stricter lockdowns caused the fourth wave. But it should reduce our confidence in inferring much from that graph, as well.

2) "There was a significant negative correlation (-0.55) between the lockdown stringency index as of January 1, and the number of post-first-wave cases a state had. This was robust to... using all cases instead of just post-first-wave cases (although some of these changes slightly diminished the magnitude of the effect)."

I find it difficult to justify excluding the first wave. Given how rare reinfections are (call it the YOCO constraint), doing so mechanically advantages places that were hit hard early. Which also turned out to be pretty correlated with lockdown propensity.

As you say, the result gets weaker using all cases. But here *cases* have a glaring problem - tests were much scarcer in the first wave than subsequently. So a higher proportion of infections were missed in the first wave than in subsequent waves. So including the first wave but looking at cases amounts to (relatively speaking) throwing out much, but not all, of the first wave. Since deaths were measured much more consistently (both in level terms, and across time), better to just look at deaths. Which almost certainly will shrink the correlation again. (For example, NY and FL have basically identical cases per capita. NY has dramatically higher deaths per capita, though).

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I am bothered that quality of healthcare is not a consideration. Doctors got better at treating Covid over time. And good lord in New York at first the hospitals were, hyperbolically stated, admitting people then sticking them on a ventilator until they died. As you pointed out the disease spread to different regions at different times. By the time patients started going to hospitals in Florida they had learned from New York's mistakes. I'm not claiming I know what specific difference this makes but it really bothers me to see it just kind of ignored.

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By the sounds of it, yes, the hospitals in NYC were not adding a lot of value in the Spring 2020 wave. (And perhaps were even subtracting value: "hello, your measured oxygen is low, but you otherwise seem in good health. May we puncture a hole in your throat"). That presumably did raise IFRs early on, and to the extent that actual therapeutics are discovered over time (separately from merely learning to avoid bad treatment), this could cause IFRs to fall over time. Alas, pretty unclear how much effect this actually had. The only therapeutics I can think of, off the top of my head, were dexamethasone and monoclonal antibodies. Just how big the average real world effects of these were, and how frequently they were used, idk. (Also, while we probably would expect IFRs to fall over time for these above reasons, if, for example, a more dangerous strain arose, then a lockdown which delays infections can increase overall deaths. It's messy).

In principal, if lockdowns delay infections and IFRs fall, this is captured in the death counts and this thus gets accounted for as a "success" of lockdowns when doing the calculations. (E.g. Florida and California famously have ended up with pretty similar death rates. But CA had its major outbreak much later... it had much lower deaths than Florida for a while... until the dam broke. To the extent the IFR had fallen more by this time, that gets baked into CAs numbers).

If the concern is "states that got hit early tended to have more stringent lockdowns, but were hit early because of reasons X, and this gave them higher IFRs, and we shouldn't attribute this effect of X to the lockdowns", then there is a way of dealing with that (control for X, and preferably do the analysis at the county level). This is a reasonable point - one I would make myself - but is well outside the scope of Scott's data analysis here.

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Big thumbs up. Really hard to untangle all of this.

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I am bothered at how COVID Uber Alles quickly became the worlds guiding philosophy

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Good points.

Another thing to remember is that different states had different policy decisions. Cuomo in New York decided to protect the hospitals and sacrifice the nursing homes, while De Santis in Florida chose the opposite priorities, which probably reduced Florida's death rate substantially relative to New York's. (Of course, from a Quality Adjusted Life Year's perspective, a focus on nursing homes isn't as effective as it is from a simple death's perspective.)

By the way, I'm not criticizing Cuomo for his making the wrong decision: all this stuff was brand new to the politicians at the time. (But it is kind of weird to win an Emmy for getting a bunch of oldsters killed.)

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I fail to see the value in separating voluntary quarantining(VQ) vs. mandatory lockdown(ML). If everyone is already staying home what are the negative effects of ML we should be concerned about?

Additionally, VQ is caused by fear/concern. Accordingly, we could have increased VQ by increasing media coverage of the negative consequences and risks associated with Covid. Would this have been in any way superior? It seems this actually has negative effects even absent positive effects(people staying home) where mandatory lockdowns do not.

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I was thinking a similar thing when reading the post. I know the general trend around here is to worry about government intervention qua government intervention, but I really think the stated economic and emotional costs here are very similar whether consider government mandated behaviors or "voluntary" behaviors caused by fear of the virus, so if we're measuring costs along those axis, then movement data is the most important factor to consider, not stated policy aims.

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> If everyone is already staying home what are the negative effects of ML we should be concerned about?

That people won't be able to stop staying home when that is what circumstances warrant.

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All else aside, voluntary quarantining takes account of varying personal costs.

My personal cost of quarantining is low, so I should do it whether it's required or not, as long as my chance * cost of getting Covid is higher. A counterfactual me who lived alone, found exercise essential to her mental health and had no space at home in which she could exercise (or any of a dozen other reasons getting out of the house might be essential) should start quarantining a lot later and stop a lot earlier than I should (and did). If you leave the gyms open, I won't go, she will (until it gets really bad), and people in between us will decide based on their personal cost/benefit calculations. If you close the gyms, she can't go even if it would be worth it to her, I and anyone like me weren't going anyway so can't benefit, so the only people you're forcing to stay home are the ones it's particularly high cost/low benefit for. (The guy who had it last month, and is naturally immune. The lady controlling her high cholesterol/depression/etc. with exercise. And so on.)

You can completely argue that that's still worth it - that A) those people don't have the incentive to count the cost to everyone else of them getting it appropriately, or B) humans are not actually that rational, and in either case you know better than them. But voluntary quarantining does use people's knowledge of their own cost/benefit, and mandatory lockdowns don't.

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founding

It isn't *everybody* who is staying home under Voluntary Quarantine, and it isn't a random 80% or whatever. It's the 80% who are at most risk of COVID *and* suffer the least from being isolated.

For an obvious non-COVID example, I'd estimate that 80% of the US population attends some sort of Christian religious service at least once a year, and does not visit a mosque, synagogue, temple, or whatever. But that voluntary state of affairs is vastly different from "All Americans are required to attend a Christian church at least once a year, and public practice of all other religions is forbidden".

For the COVID example, assume that in some nation 80% of the population lives in healthy multi-person households, 10% lives alone, and 10% lives in abusive households. In a sufficiently severe pandemic, 80% of the population stays home - and 20% *doesn't*, because both solitary confinement and being inescapably trapped in an abusive household both have huge psychological costs. And many of those people will be young and at approximately zero personal risk of dying from COVID.

If the government implements a strict home lockdown, as was apparently done in Spain and Wuhan and mandated but not enforced in California, you don't get to say "well, 80% of the population would have done that anyway, so the costs of the strict lockdown are only 25% higher than the costs of doing nothing and there's not really difference".

Also, some people still hold to the quaint notion that individual liberty is a thing of intrinsic value even if they don't choose to exercise every possible liberty at every possible moment.

I see great value in separating the voluntary from the mandatory, and I see the people who can't see the difference as a far greater long-term risk than COVID-19 ever was.

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Staying at home is kind of a bad example, since it is quite unlikely that in jurisdictions where stay at home orders were really enforced (like presumably infamous French nightime curfew) people would not go out more without them. Also stay-at-home orders do not seem to be very effective at slowing covid covid when everything is already closed.

But I agree with your larger point that infringement on freedom caused by fear of covid is just as bad for people's quality of life as infringement on freedom caused by equally strict government restrictions. Relevant metric seems to me how much people alter their behavior because of the pandemic, and it matters little whether this change is caused by fear of infection or fear of getting punished by the government for violating a lockdown order.

I. e. temporary closing of pubs (bars for Americans), if it decreases covid spread, also decreases levels of VQ caused by a fear of covid, which is related (among other things) to levels of covid in the community, and thus it might in the end lead to smaller overall behavioral change caused by covid.

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> since it is quite unlikely that in jurisdictions where stay at home orders were really enforced (like presumably infamous French nightime curfew)

Small data point: I live in a big city in France (Lyon), and I've never seen a cop during the lockdowns. My bother was controlled by one, but that's it. That's for a family of 5 people.

Same thing for the curfews, but since everything was closed, there weren't many incentives to go out at night (unless you're doing house parties). However, everyone I've talked to mentioned that the curfews were really exhausting (the first ones started at 6 pm!).

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I've been making this point elsewhere, but note that the Swedish data clearly shows that the behavior of Swedes was radically different from the behavior of everyone else. Their deaths curve is broadly similar in shape to every other deaths curve. But their "new cases" curve looks nothing like anyone else's.

We are forced to conclude that either (1) the difference in official policy made a massive difference in overall behavior; or (2) a more restrictive official policy would have made no difference, because the Swedes are the most fractious, official-recommendation-resistant people in Europe, completely different in kind from any other Europeans.

I would suggest that official policy shows up not just in enforcement efforts, but also in the level of popular fear, and the channel from policy -> fear explains why restrictive policies saw high levels of compliance despite low levels of enforcement.

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Honestly, if you are referering to spring 2020, I would be very cautious to inferanything about behavior from case numbers, since those are heavily contaminated by differences in testing regimes. Mobility data are much better indicator of behavioral changes.

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If anything, once a lot of people are in VQ, ML may well have economic *benefits* as opposed to costs. If a small fraction of shoppers are out shopping, then businesses have to make a difficult decision to figure out whether the marginal cost of sending employees to go in to work will is more or less than the expected returns from selling to that small number of shoppers. (It's surely not enough to cover rent and other fixed costs.) Whereas if you move to a mandatory lockdown, no business will lose extra money in this way, and employees will be able to claim unemployment benefits.

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founding

I'm not seeing how this argument doesn't fully generalize to "denying people the ability to make their own choices may have benefits because otherwise they have to make their own choices and they might make bad choices".

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When you put it as "may", it absolutely does generalize. In pure decision theory, when it's a person making a decision against an impersonal unknown of the state of the world, there's never advantage for a rational agent to have fewer options. But in game theory, when it's a person making a decision against another person who is making a decision with knowledge of the first person's options, there often can be an advantage to have fewer options. The classic example is that if two people are playing chicken, and both start out with the options "swerve" and "full speed ahead", if one player has the option "swerve" removed (and this is common knowledge), then that player ends up with a much better outcome.

Of course, it depends on *which* options are removed, and what the game scenario is. But this is a standard economic point - naively one thinks that more options are always better, but in situations involving interaction, this just isn't true.

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> The classic example is that if two people are playing chicken, and both start out with the options "swerve" and "full speed ahead", if one player has the option "swerve" removed (and this is common knowledge), then that player ends up with a much better outcome.

Except that the obvious implication of this approach is that both players should remove their steering wheel before the match.

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I'm not sure why this is an "except". This just shows that we can't simplistically assume that if pruning options for one person improves that person's situation, then pruning everyone's options the same way will improve everyone's situation. There are cases in which it can, say if we're playing a pure coordination game. I didn't mean this to show precisely what our policy should be - I just meant it as a counterexample to the proposed principle that was being used to argue that no limitation of options is ever good.

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> If everyone is already staying home what are the negative effects of ML we should be concerned about?

I dunno, maybe blatant violation of our freedom to associate? As but one example, maybe people who live alone shouldn't have to suffer in isolation and should be able to decide a small group of people with whom they can associate without the government fining them for violating the mandatory lockdown.

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> people who live alone shouldn't have to suffer in isolation and should be able to decide a small group of people with whom they can associate without the government fining them for violating the mandatory lockdown.

I would be surprised if there is anyone in this discussion who doesn't agree with this claim. I don't believe anyone here is advocating a mandatory lockdown that bans people who live alone from forming pods.

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Probably not, but this is a property of mandatory lockdowns nonetheless, and some governments did try to enforce it (we did here in Canada). Official guidelines were that if you lived alone, you could have contact with only one other household.

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Meanwhile, here in Washington State, the official guidelines were that people who lived alone couldn't have contact with any other household. Solitary confinement is understood to be torture when imposed on people in prison, so...

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Sure, we can debate what sort of theoretical lockdowns might've been a good thing. But in that case, let's be sure to also loudly proclaim that the actual lockdowns as practiced were a horrible thing. In other words, please don't shrug it away when people point out the existing systems inexcusably violated people's rights to no good purpose.

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As long as you don't shrug it away when people *also* point out that the existing systems inexcusably encouraged people to spread virus to no good purpose - particularly all the politicians who didn't stop at banning mask mandates, but also made all their public appearances mask-free in order to discourage people from wearing masks.

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founding

>I don't believe anyone here is advocating a mandatory lockdown that bans people who live alone from forming pods.

If you advocate lockdowns at all, then you are advocating that - because that's what people with actual legislative and regulatory power are actually going to implement, actually *did* implement, under the name "lockdown", and your advocacy of something you call "lockdown" will be counted as a vote for what they are going to actually do.

Advocating clever nerdy-technocratic policies that are never going to be implemented in the real world is sometimes fun and informative, sometimes a waste of time, but it's dangerously misleading when the thing you're advocating shares a name but not a reality with a thing other people are actually doing.

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This is why no one should ever use the word "lockdown". I don't know how many governments used that word. Instead they advocated specific policies. I believe that some European governments banned people from visiting each other, but I don't believe that any US government ever banned individuals from entering the homes of other individuals.

We should be debating specific policies that specific governments introduced, not putting up a strawman of everything that any government ever did against a strawman of doing nothing.

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"Most of the debate about whether lockdowns work centers on ideas within the Overton Windows of western countries, after the pandemic had started spreading - ie, given whatever level of lockdown your country had, is the marginal effect of more (or less) lockdown positive or negative?"

I feel this is missing the point. One need not appoint a president for life to implement lockdowns strict enough to actually work, and state of emergency laws are on the books in many Western countries that allow governments to implement lockdowns without violating various constitutions.

I would far rather spend a month or two in a China-style lockdown than a year plus in a Western one (or worse, if the Delta or some other variant spreads enough.) This strikes me as an area where Western governments had an absolutely massive policy failure with millions dead and their Overton window still isn't expanding wide enough to include "actually solving the problem".

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It seems that a dictator is neither necessary nor sufficient, as most of actual dictatorships also failed to curb Covid. The real issue is that efficient government is really difficult, especially when a system accustomed to normalcy is suddenly faced with a novel crisis.

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Interesting that, on naive estimates at least, the dollar-life or dollar-QALY trade-off rate of Covid restrictions is within a factor of 2 of other such tradeoffs determined by government regulation. I wonder how much of the lockdown debate is just people projecting their political values onto a novel factual question-- i.e. you probably think COVID restrictions were a bad deal if-and-only-if you think EPA restrictions are too.

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Editing note…I had to go back to see what a QALY was. It might be good to follow the original mention with the acronym, I would have seen it more quickly, maybe others too. It made it difficult for me to follow the conclusion section at first.

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author

Fixed, thanks.

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My apologies, this is my first comment but a few 'What if's' come to mind. What if 85% of the people under 50 had the SARS-Cov-2 virus infection by Nov. 2020..and it was so mild they never noticed? What if the PCR test is the wrong test , has massive false positives, picks random protein and old viruses, is dialed up to a 45 'magnification' instead of 28 as recommended? What if the virus is 1 micron in diameter and the average mask (sieve) is 500 microns? What if the vapor travels not 6 feet but 100 feet? What if staying indoors is exactly against all the viral transmission rules?

What if the 'lockdown success' in the first wave is actually attributable to Sunshine and Fresh Air (aka Spring)?

What if the 'vaccine success' is again vastly attributable to Sunshine and Fresh Air ( and the CDC dialing down the PCR test at vaccine launch)?

What if .. for every 1% increase in unemployment 37,000 Americans die (as one prepandemic study showed)?

What if the natural, cheap and off-patent solutions, Sunshine (Vit D), Zinc, Quercetin, Ivermectin, Corticosteroids, Melatoni, Iodine and dozens more EACH reduce the Absolute Risk(AR)

of hospitalization and death by 65-94% ? What if people think that vaccines 'effectiveness' is 95% when this citation is Relative Risk (RR) and vaccines Absolute Risk reduction hovers just over 1%? What if the Inventor if mRNA technology Dr. Robert Malone warned the FDA about the toxicity of the spike proteins (generated by the vaccine) a year ago and Dr. Byram Bridle found evidence in Pfizers Japan data and exModerna Dr. Luigi Warren says vaxxed people shed spike proteins and all 3 have been variously trashed, deleted, deplatformed and ghosted? What if mRNA Inventor Dr. Robert Malone

and his 16 patents have been scrubbed from Wikipedia? What if this unprecedented Orwellian fact of this pervasuve laundering is because Google and Jeff Skoll invested in GoF research starting in 2010? What if up is down and down is up, Alice - here in Wonderland? Scrubadubdub.

Friedrich Nietzsche said ,

"The strength of a person's spirit would then be measured

by how much 'truth' he could tolerate, or more precisely, to what extent he needs to have it diluted, disguised, sweetened, muted, falsified"

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author

"What if 85% of the people under 50 had the SARS-Cov-2 virus infection by Nov. 2020..and it was so mild they never noticed?"

We know this isn't true because we can test people for antibodies. In the US these studies showed about 10% of people had had COVID in summer 2020, and about 25-30% of people have had it now. Antibody studies from other countries show concordant results.

"What if the 'lockdown success' in the first wave is actually attributable to Sunshine and Fresh Air (aka Spring)?"

This is what I tried to control for by comparing stricter-lockdown states and countries to weaker-lockdown states and countries. Both had spring at the same time. This is also what eg Brauner et al tried to control for by comparing countries that instituted restrictions at different times. I recommend you reread at least Evidence Section 1, maybe the whole piece, it's surprising that you missed this.

"What if the 'vaccine success' is again vastly attributable to Sunshine and Fresh Air ( and the CDC dialing down the PCR test at vaccine launch)?"

All vaccine studies have compared vaccinated to unvaccinated individuals, all of these people are experiencing spring at the same time.

"What if the natural, cheap and off-patent solutions, Sunshine (Vit D), Zinc, Quercetin, Ivermectin, Corticosteroids, Melatoni, Iodine and dozens more EACH reduce the Absolute Risk(AR)"

See my piece here https://astralcodexten.substack.com/p/covidvitamin-d-much-more-than-you arguing Vitamin D is probably not very effective. I think the same is true of the other things you mention except corticosteroids, which have too many side effects to be given as a universal preventative.

"What if people think that vaccines 'effectiveness' is 95% when this citation is Relative Risk (RR) and vaccines Absolute Risk reduction hovers just over 1%"

This is true of everything. The decrease in absolute risk of death from lung cancer from not smoking is much less than 1%, not because smoking doesn't cause lung cancer, but because absolute risk statistics are misleading except in the context of knowing the preliminary absolute risk and thinking about it very clearly. I think this is a pretty serious mistake and I am skeptical you understand absolute risk.

I haven't heard of the specific doctors you mention, but I don't think they're relevant to lockdown statistics.

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Spring in the north and spring in the south is different. It is better to compare spring in the northeast to winter in the south in many ways. What time of year are people driven indoors where spread is more likely due to being clustered in a climate controlled environment and vice versa? I find that this blunt attempt to normalize by season to be better than nothing, but pretty close to nothing if you don't understand the underlying mechanics that affect the transmission rate. I don't think they understand these affects enough that this normalization works very well. The regional timing of the outbreaks before there was country wide community dispersion is also very difficult to factor out.

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The antibody test strains the meaning of what having Covid means. If a person's innate immune system was sufficient to prevent illness their antibody test will be just as negative as someone who never had the virus in their system.

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What makes you say that? As far as I know, the adaptive immune system starts spooling up on the same signal that kicks off the innate immune system, and there are multiple crosslinks between the two. Even if every virus-infected cell gets slaughtered by NK cells within 24 hours, they will have produced cytokines to recruit macrophages and those will undoubtably eat at least a few infected cells and start presenting antigens, and then off we go to the B cell antibody factory. No?

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Wouldn't someone have to get re-infected to have enough antibody production going on to test positive?

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I don't see how that would happen. If an innate response was sufficient the first time to shut down the infection before antibody production got very far, why would it not work just as well (or better) the second time?

I don't know how probable it is that someone could drive off an infection so fast through an innate response that undetectable levels of antibodies result. That seems to me a priori like a delicate question of whether there is any nontrivial delay between innate attack and antibody production kick-off, and whether there's a mechanism for shutting down antibody production early, and if so when it happens, and whether whatever level is produced is clinically detectable. I don't know nearly enough immunology to even know whether the answers to these questions are known.

But I'm just kind of a priori dubious that the innate immune system could entirely handle an infection without triggering adaptive components *at all*. The two systems are deeply intertwined, and anyway that doesn't seem very efficient and you'd think evolution would've knocked away a barrier to maximum efficiency like that long ago, back when we were coelenterates.

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At the very least, this was interesting:

https://www.ncbi.nlm.nih.gov/books/NBK27090/

The mechanism that regulates the production of b-cells that will produce antibodies seems to depend on prolonged presence of the antigen. I-10 - I-13 describe the control mechanism.

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This is my second reply to this comment. Found another article more specific to Covid:

https://www.pnas.org/content/118/21/e2101718118

I don't think it's spelled out 100%, but reading the first few sections it sure seems like successful innate immune response does not trigger the specific adaptive response that would lead to a positive antibody test.

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Mostly agreed, but you're giving ivermectin too short a shrift. Check out the difference in the most recent COVID peak between Indian provinces that used ivermectin vs those that used remdesivir - it's almost an RCT, and the results are astounding.

Plus the guy who pioneered the use of corticosteroids in the treatment of COVID is all in on it, which isn't much but also isn't nothing.

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Here's the thing that really bothers me about ivermectin:

The official recommendation is don't take ivermectin, instead... do absolutely ******* nothing. I have seen many a reasonable argument as to why ivermectin may not be all that useful in treating Covid. But damned if there's any indication trying it is somehow harmful. So it's not harmful, it may or may not be helpful. The official recommendation is do not use this. There's no making sense of that without resorting to some dark motivations or disgusting stupidity.

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There are no indications that trying Lambert's Extra-Virgin Snake Oil* is somehow harmful. It sickens me that the medical establishment is just doing nothing.

*(now with 40% more colubrids)

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The cool thing about Lambert's Extra-Virgin Snake Oil is that it's 40 year safety record justifies it being sold over the counter in a dozen countries. It also single handedly cured River Blindness and its inventor won a Nobel Prize. https://www.nobelprize.org/prizes/medicine/2015/press-release/

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You say - "We know this isn't true because we can test people for antibodies". Antibodies are gone in a matter of weeks. They're kind of a useless measure. Much better T-cell, B-cell - memory cells in bone marrow. Cleveland Clinic and UBC found evidence of almost universal natural antibodies. UBC measured 8,000 proteins in their assay (I'm no virologist but looking for one single spike protein antibody vs 8,000 markers?). Natural immunity is better, broader and dramatically more protective than a narrow spike protein focused immune trigger. Example: SARS-Cov-1 which is what this one was 'made' from, protects against SARS-Cov-1 18 years later. It also works on SARS-CoV-2 and all the Variants and yet it's 20% different genetically than our new coronavirus while the scary variants are just .03% different.

You kinda skittered past these four "What If's"... "What if the PCR test is the wrong test , has massive false positives, picks random protein and old viruses, is dialed up to a 45 'magnification' instead of 28 as recommended? What if the virus is 1 micron in diameter and the average mask (sieve) is 500 microns? What if the vapor travels not 6 feet but 100 feet? What if staying indoors is exactly against all the viral transmission rules?" The reason you would do that is they negate the entire discussion. I'll skip over them too for the sake of brevity (not to concede any one of one iota).

And to counter your prior Vitamin D article, you didn't mention Vitamin D is related to 2,000 genes 300 of which are immune system related. SARS-Cov-2 is a wimpy virus just like HIV...unless it gets past your immune system and they wreaks health havoc.

Vitamin D deficiency increases Hypertension

Vitamin D deficiency increases Diabetes

Vitamin D deficiency concurrent with Obesity

Vitamin D deficiency occurs with Heart Disease-Stroke

Vitamin D deficiency increases Cancer rates

(Imost common comorbidities of COVID-19.

See also POC (people of colour) 2.5-3X rates)

Whatever the country search their Vitamin Status.

Then check their COVID status on https://www.worldometers.info/coronavirus/

Some countries had different D status within their borders.

There are 702 papers since Jan 2020 on Vit D and COVID-19

with health care people, researchers, clinicians, biologists

hemists - just every corner of science screaming uncharacteristically,

"Take Action!" Read 'em.

https://bit.ly/CovVitaminD

Off on a vitamin D tangent. It's just these idiots have been causing the Vitamin D deficiency with scary health public service announcements for decades. Because of the tangent I gotta stop here but (see link later... not see Linkletter, that would be Art Linkletter and his show "Kids Say the Darndest Things" prolly before you born kid..in the 60s when we were building great immune systems under the sun)

I said -

"What if the 'vaccine success' is again vastly attributable to Sunshine and Fresh Air ( and the CDC dialing down the PCR test at vaccine launch)?"

osaid -

"All vaccine studies have compared vaccinated to unvaccinated individuals, all of these people are experiencing spring at the same time".

By that I mean you completely missed what I said which was the 24 drumbeat from the Miracle Vaccine Train networks is "Look! The Vaccines are Working!" They tout the plummeting infections to the vaccine. Rubbish. People going outside .. getting away from the viruses trapped in close quarters with people and getting fresh air (studies show zippo worries). 'Can you say Black Lives Matter'? 26 million Americans mostly mask-less AND in close proximity... Why didn't Everyone in America die? WTheck ? (I toned that down). We had the most important lessons of the pandemic to learn and we learned none of them?

I said -

"What if the natural, cheap and off-patent solutions, Sunshine (Vit D), Zinc, Quercetin, Ivermectin, Corticosteroids, Melatonin, Iodine and dozens more EACH reduce the Absolute Risk(AR)"

You poo-pooed it and took the Pharma talking points verbatim on ... forget it.

Read up - there are many dozens of cheap and effective solutions.

WHO is trying to make Ivermectin "off limits" because they are concerned about parasitic infections. This, a drug available OTC everywhere costing .003 cent a pill with a 40 yr track record - zero deaths and won the Nobel Prize for it's inventor.

https://c19early.com/

I said -

"What if people think that vaccines 'effectiveness' is 95% when this citation is Relative Risk (RR) and vaccines Absolute Risk reduction hovers just over 1%"

You said -

"This is true of everything. The decrease in absolute risk of death from lung cancer from not smoking is much less than 1%, not because smoking doesn't cause lung cancer, but because absolute risk statistics are misleading except in the context of knowing the preliminary absolute risk and thinking about it very clearly."

This is gobbledygook, start to finish. You compare Smokers with Smokers - a perfectly imperfect analogy.

We are comparing an experimental gene therapy to a placebo. People who smoke cigarettes are up to 3,000%* more likely to die from lung cancer than people who do not smoke. (* by that's just the CDC and we know they have licensed a lung cancer vaccine as 45% of their revenue comes from vaccines. Ironically, LESS likely to die from COVID-19 if you are a smoker and 45% less likely to get Parkinson's btw)

Just illustrative -

Relative versus absolute risk of comorbidities in patients with psoriasis

https://pubmed.ncbi.nlm.nih.gov/27986396/

Conclusions: Presenting attributable risk in the form of the number needed to harm provides a clearer picture of the magnitude of risk and a basis for wiser medical decision making and patient education.

(Right, as everyone would agree)

I admit to not communicating Relative versus Absolute Risk well at all.

And also of making the mistake of thinking You Knew This - and you clearly did not.

In fact, you double down on the very problem. Whew.

So I hand the ball off to ...

Peter Doshi of the BMJ board he writes -

"Only full transparency and rigorous scrutiny of the data will allow for informed decision making, argues Peter Doshi

In the United States, all eyes are on Pfizer and Moderna. The topline efficacy results from their experimental covid-19 vaccine trials are astounding at first glance. Pfizer says it recorded 170 covid-19 cases (in 44,000 volunteers), with a remarkable split: 162 in the placebo group versus 8 in the vaccine group. Meanwhile Moderna says 95 of 30,000 volunteers in its ongoing trial got covid-19: 90 on placebo versus 5 receiving the vaccine, leading both companies to claim around 95% efficacy.

Let’s put this in perspective. First, a relative risk reduction is being reported, not absolute risk reduction, which appears to be less than 1%. Second, these results refer to the trials’ primary endpoint of covid-19 of essentially any severity, and importantly not the vaccine’s ability to save lives, nor the ability to prevent infection, nor the efficacy in important subgroups (e.g. frail elderly). Those still remain unknown. Third, these results reflect a time point relatively soon after vaccination, and we know nothing about vaccine performance at 3, 6, or 12 months, so cannot compare these efficacy numbers against other vaccines like influenza vaccines (which are judged over a season). Fourth, children, adolescents, and immunocompromised individuals were largely excluded from the trials, so we still lack any data on these important populations."

Peter Doshi gets complicated, what he's saying is 'It's a load of crap".

And for my part, I'm seeking a better way to convey this horrible statistical con.

And really I have to say to you "I think this is a pretty serious mistake and I am skeptical you understand absolute risk".

You say -

I haven't heard of the specific doctors you mention, but I don't think they're relevant to lockdown statistics.

I say -

They couldn't possibly be more relevant to Lockdowns.

If you are using faulty PCR tests, faulty infection rates, skewed hospitalization and death rates, AR\RR, social distances, vapor distances, efficacy of mask and on and on - you would never know and yet one can weave a story with faux precision.

These doctors are the glaring evidence that you and the people are not getting the full picture from CNN (who's ad revenue is 44% Pharma) of the NYTimes (owned Blackrock-Vanguard own 16,000 companies including Pharma)a nd FAANG and really everyone with a life & death vested interest. It's historic, unprecedented and permanent. Lockdowns are lunacy.

I though for sure someone, somewhere would see this Wikipedia wipe as the new Orwellian age we are in. The relentless layering of lies means the Truth we seek with aid of science and reason can never achieved. (So, I guess this is my last post. I envisioned this as something an outpost of reasonable truth-seekers) Take care and peace.

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I live in New Zealand, and I feel this post is missing something without talking about us (or other countries that have pursued similar "Zero Covid" policies, like Australia).

With strict border controls and a strict lockdown (and probably significant assistance from our geography), we managed to eliminate Covid-19 in June 2020 and have mostly kept it eliminated since, with mandatory isolation of all arrivals, and a few short lockdowns when Covid managed to leak into the community. Australia's biggest wave (Victoria mid-2020) was eliminated after months of harsh lockdowns, and they've since had similar policies and outcomes. Our economies have also held up fairly well, helped by the ability to maintain minimal internal restrictions whenever Covid had been elmiminated.

I think there are good reasons (mainly geography) to think our experiences can't be just copy-and-pasted to the rest of the world. But I think the lesson specific to lockdowns is that there's a discontinuity when elimination is a plausible option. If e.g. Colorado had decided it was going to institute a seven-week-long harsh lockdown to try to eliminate Covid-19, it'd be at a great cost, but because Covid would be re-imported from another state so easily, the effect on Covid-19 deaths might not be that larger over the course of the pandemic. But in NZ's case, we were in a position where we could eliminate Covid-19 and remain that way.

That also changes the calculus on short "circuit-breaker lockdowns" whenever cases emerge in the community. NZ or Australian states locking down for 1 or 2 cases in a city may seem crazy to outsiders (and I do think there have a few overkill examples of this (looking at you, Western Australia)). But these can in fact have some of the highest benefit-to-cost ratios of all lockdowns. The reason is that they can be the difference between returning to a low restriction elimination state, or a phase transition to an endemic Covid state.

As such, I have a theory that optimal lockdown strategy may be bimodal. Lockdowns make little sense with zero cases, can be very good with a few cases (and strong border controls), may not make as much sense with a moderate amount of Covid, but may again start to make more sense with a healthcare-system threatening wave.

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I feel like I covered this in the first paragraph of the second Preliminary Theoretical Issues: "If, the moment COVID had been reported in Wuhan, other countries had closed their borders tightly, that would have prevented the pandemic (at least for a while). In that sense, lockdowns definitely could have worked."

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I'll add something about NZ and Australia in particular in there.

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I don't quite agree with this new segment. Our policies weren't significant outliers in the world (i.e. NZ entered lockdown at the same time as the UK did). We did benefit a lot from having much less early undetected spread (probably helped by geographic isolation, and maybe the season). Other countries (like Peru) that tried this strategy failed badly.

Test-and-trace has helped but is more applicable to the e.g. South Korean containment model. The main strategy in both Australia and NZ is to keep Covid out entirely via border controls, and whenever that fails, often locking down as well as using contact tracing.

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