Philippe Lemoine is a PhD candidate in philosophy at Cornell University, with a background in computer science. He’s also a blogger, a research fellow at the Centre for the Study of Partisanship and Ideology, and a lockdown sceptic. During the pandemic, he’s written several detailed articles about the efficacy of lockdowns. I interviewed him via email.
On December 4th, you published an article on your blog titled ‘Lockdowns, science and voodoo magic’, which criticised the well-known paper by Flaxman et al. That paper (which has been cited more than 1,300 times) concluded, “major non-pharmaceutical interventions – and lockdowns in particular – have had a large effect on reducing transmission”. Could you briefly summarise your criticisms?
I made two main points against that paper. First, the model assumed that only non-pharmaceutical interventions affected transmission, so any observed reduction in transmission could only be ascribed by the model to non-pharmaceutical interventions. Since in fact transmission went down quickly everywhere during the first wave, the only question was how much of that reduction would the model attribute to each intervention. But the fact that non-pharmaceutical interventions were jointly responsible for the entire reduction in transmission was not something the model inferred from the data, it was assumed at the outset by the authors when they defined the model. A consequence of this fact is that, when they compute a counterfactual scenario in which there weren’t any non-pharmaceutical interventions to estimate how many lives were saved by lockdowns and other restrictions, the authors just assume that cases would have continued to rise until the herd immunity threshold was reached and would only start to go down then. Although the authors did not deem it necessary to reveal this small detail, this meant that, in their counterfactual, more than 95% of the population was already infected by May 3, which is preposterous. Even one year and a half after the beginning of the pandemic, there isn’t a single country where the proportion of the population that has been infected even comes close to such a figure, not even in countries where restrictions were extremely limited. So when the paper finds that non-pharmaceutical interventions in general and lockdowns in particular saved three million lives in Europe alone during the first wave, they only reach that conclusion by comparing the actual number of COVID-19 deaths to the number of deaths in a ridiculous scenario where essentially everyone had been infected. Yet this preposterous estimate was taken seriously by the entire scientific establishment and, as you noted, the paper became one of the most cited studies on the COVID-19 pandemic.
The second point I made is that, not only was this result based on totally unrealistic assumptions, but the authors failed to disclose a key result that completely undermined their conclusion. As I explained above, the model was bound to attribute the entire reduction in transmission that was observed in Europe during the first wave to non-pharmaceutical interventions, the only question was how much of it would be attributed to each intervention. Their headline result was that, apart from lockdowns, nothing else had any clear effect, which meant that lockdowns were responsible for the overwhelming majority of the 3 million lives that, according to this study, non-pharmaceutical interventions had collectively saved. However, Sweden was included in the study and never locked down, yet only a tiny fraction of its population was infected during the first wave. How is that possible if only lockdowns have a substantial effect on transmission? I knew this made no sense, so I downloaded the code of the paper to reproduce their analysis on my computer and take a closer look at the results. Their model allowed the effect of the last intervention, which happened to be a lockdown everywhere except in Sweden, where it was a ban on public events, in each country to vary. What my analysis of their results showed is that, in order to fit the data, the model had to find that banning public events reduced transmission by ~72.2% in Sweden but only by ~1.6% elsewhere. In other words, according to the model, banning public events had somehow been 45 times more effective in Sweden than anywhere else. Now, unless you believe there are magical anti-pandemic fairies in Sweden that somehow made banning public events 45 times more effective than elsewhere, this obviously never happened. Rather, what this means is that the model was garbage, which in turn means that we have no reason to believe the paper’s headline result that lockdown had a huge effect on transmission. There is a lot more in my piece about that paper, which I methodically demolish, but those are the main points.
Then on March 4th, you published a report for the Centre for the Study of Partisanship and Ideology titled “The Case against Lockdowns”. This was followed by an op-ed in the Wall Street Journal titled “The Lockdowns Weren’t Worth It”. Could you briefly summarise the case against lockdowns, as you see it?
First, I think it’s impossible to estimate precisely the effects of non-pharmaceutical interventions because too many factors contribute to transmission, and we lack the kind of background knowledge we’d need to be confident that the statistical techniques people use to estimate those effects are reliable, so people who claim to be able to do that are full of it. I just published another piece in which I take a very close look at a study which found that non-pharmaceutical interventions had a substantial effect on the number of cases and deaths in the US during the first wave. This study is far more sophisticated than Flaxman et al.’s paper and, in particular, the authors did not assume that only non-pharmaceutical interventions affect transmission, and tried to model the effect of voluntary behavioural changes. Nevertheless, as I show in my article, when you look at it closely and perform various sensitivity analyses, the conclusions no longer hold. So we have no way to estimate precisely the effects of non-pharmaceutical interventions and we should be honest about this. However, whatever their precise effects, they can’t be huge because otherwise they would be much easier to detect. The contrast with the effect of vaccination is particularly striking in that respect. In the case of vaccination, the effect is so obvious that you can see it on a simple chart, whereas in the case of non-pharmaceutical interventions you have to squint and use very complicated statistical techniques that, although they impress people because they look scientific, we have no reason to think are reliable in this context. Now, if you do a cost-benefit analysis, even if the only costs of lockdowns you take into account is the immediate effect they have on people’s well-being and you make ridiculously optimistic assumptions about how much stringent restrictions reduce transmission, they don’t pass a cost-benefit test. In fact, not only do they fail to pass a cost-benefit test, but it’s not even close. The costs of lockdowns, by which I mean just their immediate effect on well-being, so far outweigh their benefits that one cannot reasonably doubt a more rigorous cost-benefit analysis would reach a different conclusion.
According to some people, claiming that lockdowns don’t have a large effect on the spread of COVID-19 is tantamount to “denying germ theory”. What do you say to those people?
Nobody is denying that transmission occurs during physical interactions, but it doesn’t follow that lockdowns have a large effect on transmission, so people who make this argument simply haven’t thought things through. In theory, lockdowns could even increase transmission, so this argument is very confused. For instance, it could be that, although lockdowns decrease between-household contacts, the effect on transmission at the aggregate level is more than compensated by the increase in within-household contacts they produce. To be clear, I don’t believe this is the case, I’m just saying it’s a theoretical possibility that obtains in some models, even though nobody denies the germ theory of diseases. There are many possible explanations for why lockdowns don’t result in the very large reduction in transmission that one might have expected. For instance, we don’t expect lockdowns to be equally effective at reducing all types of contacts and, as I just noted, they even increase the frequency of some types of contacts, such as within-household contacts. So it could be that the types of contacts that lockdowns manage to reduce a lot don’t contribute a lot to transmission, while the types of contacts they aren’t very useful for preventing contribute a lot to it. Another important point is that, even in the absence of a lockdown, people change their behaviour in response to the pandemic. So it could be that the types of contacts that contribute the most to transmission are the same types of contacts that people tend to reduce voluntarily even in the absence of a lockdown. Anyway, whatever the explanation, it’s pretty clear that lockdowns don’t have a very large effect. It would be very surprising if such a fact were inconsistent with the germ theory of diseases, but fortunately it isn’t. It’s just that people who make this argument are confused. The effectiveness of lockdowns and restrictions in general is an empirical question that cannot be solved by theorizing from the armchair.
Much of your writing about lockdowns has dealt with the deficiencies of epidemiological models. Why have most models done so poorly at predicting the epidemic’s trajectory?
This is a difficult question and I’m not sure what the answer is. I’m very confident that part of the story is that most of those models don’t take into account the kind of voluntary changes of behaviour I was just talking about. If your model is based on the assumption that people’s behaviour only changes in response to government interventions, it should be no surprise that it performs terribly. But I don’t think it’s the whole story and I increasingly suspect that the fact the models don’t adequately model population structure is another factor. Most epidemiological models that have been used to make projections assume that, within large age groups, people mix homogeneously. But this is totally unrealistic since, for instance, a 55-year-old is not equally likely to run into any other person in the 50 to 59 age group. Rather, a particular 55-year-old is very likely to have contacts with some people in that age group (such as friends and family), but very unlikely to meet many other people in that age group and has essentially no chance of running into the vast majority of people in that age group. Anyway, nobody really knows why those models perform so terribly at larger scales, but in order to investigate the problem epidemiologists would first have to acknowledge it. Unfortunately, they mostly ignore it and act as if their models had not proven incapable of explaining the data, except in the sense that you can always “explain” any data if you are willing to make enough purely ad hoc hypotheses, so they don’t even get started.
As far as I’m aware, no Western government has published a cost-benefit analysis of lockdowns. Why were these far-reaching policies implemented with so little regard for costs?
As I noted above, any serious cost-benefit analysis would immediately show that lockdowns are not worth it. Yet as you say no Western government has published any to justify their policy. This is particularly surprising when you know that, in most Western governments, the use of cost-benefit analyses is largely institutionalized and the authorities are often required to make one before they can embark on projects as banal as building a bridge. Yet they apparently didn’t feel the need to publish a cost-benefit analysis to justify what are effectively the largest attacks on individual freedoms in the West since the end of World War 2. One interpretation is they realise that, as I noted above, no cost-benefit analysis would ever vindicate lockdowns. But this wouldn’t explain why they are pursuing lockdowns and I don’t believe in that explanation for a second anyway. In a way, if that were really the explanation, I would almost find that reassuring because it would at least imply a level of competence and understanding which I think is entirely lacking from our political leaders. Rather, I think their decisions are the result of a combination of cluelessness not just on their part but also on the part of their advisors and a variety of bad incentives that conspire to create absurd policies, such as the desire not to leave themselves open to the accusation of not having done anything to curb the epidemic. This desire must be strong as they are constantly under pressure from the largely pro-lockdown media to enact more restrictions. In order to answer this unremitting call to “do something”, they do something, even if that’s completely absurd, as long as they have something to show to the people who constantly ask them to “do something”. The idea of measuring the costs of their decisions against their supposed benefits often doesn’t even enter their heads because their decision-process is not governed by rational considerations, but rather by this ungodly combination of emotion, illusion of control, bad incentives and even worse advice.
You’re a Frenchman. Given what we know now, what should Emmanuel Macron have done in March of 2020?
With the benefit of hindsight, I think he should have just told people to try to limit their contacts to reduce the amount of stress on hospitals, but leave them free to make their own choices and focus his efforts on preparing government services to respond as best as possible. I think there are lots of reasons to blame Macron and French officials for their conduct at the beginning of the pandemic, especially for their lack of preparation and their carelessness in the weeks leading up to the explosion of cases in the country, but if we put aside the lies they told repeatedly during that period and since then, they at least had the excuse that we didn’t know much about the virus and how different policies would affect spread. I was in favour of the first lockdown and, while I now think that I was wrong and that I should have predicted lockdowns would become entrenched after we had used them once, it was a genuinely difficult decision because we didn’t know much. But after the first wave there was no longer any excuse and Macron should be judged harshly for keeping us more or less locked down for months after the first wave, even though it was already very clear by that point that restrictions did not make a very large difference to transmission, yet had a very negative impact on the population’s well-being.
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Purely on the basis of mathematical probability none of us should exist today. But we do.
Purely on the basis of mathematical probability the Bayesian should have had an infinitely small, albeit nonzero probability of sinking.
But it did sink.
“When the facts change, I change my mind – what do you do, sir?” John Maynard Keynes. Sounds like a Bayesian to me, updating his beliefs with new information.
As to the frequentists dealing only in facts, hard facts. Poppycock, as the Dutch would say. The Law of Large Numbers says that if only you had more frequent sampling then you might converge to the right answer however you may still need even more data.
If you want actual facts then you must dismiss these mere Statisticians and consult the Mathematicians. Probability theorists look down on frequentists and Bayesians alike.
Probability is the likeliness that the outcome a random selection experiment will have a certain value or set of values. Eg, the probability of getting an even number when throwing a dice is 0.5 (50%). In practice, this means the number of even numbers selected by rolling a dice for a long time will converge to half the number of times the dice was being rolled.
This calculation is based on something called relative frequency. Given a set of n values, the relative frequency of a certain value x is the number of times x occurs in the set divided by the number of values in the set (n, multiplying the result with 100 yields a so-called percentage).
Relative frequencies can obviously also be calculated for sets whose members weren’t selected randomly. That’s the trade of
duplicitous activistssocial scientists: They take a miniscule number of observations about the real world, say 13 of 15 people who were jailed last Tuesday were black, calculate the relative frequency of an event they’re interested in and then fraudulently claim this would be the probability of the event occuring despite it isn’t. In this case, this would work as follows: There are 2,485,724 black people living in the UK (2021/22 census). 13 of them were jailed last Tuesday, relative frequency 0.000005. These represent 3.7% of the total population which is thus 67,181,729. 2 of non-black people were jailed last Tuesday, relative frequency 0.00000003. Now, the headline generator is turned on:Extreme structual racism in the UK judical system! Study shows blacks 166¹ times more likely to be jailed!!
That’s contrived exampe I just made up. But it demonstrates how such claims are justified.
¹ 0.000005 / 0.00000003 = 166 ⅔.
Only if the die is fair (edit: and has an even number of sides).
It also depends what numbers are placed on those sides.
This also depends on gravity neither suddenly stopping nor fluctuating in unpredictble ways, say, because this happens on an irregularly rotating space station. Also on a numbering system which includes even numbers. And a lot of other implicit assumptions someone could dream up here. But these escape vents for the poor creativity of people who can only come up with nonsense when being asked to come up with anything notwithstanding, people who read the text will have understood what was meant.
I am a complete dunce when it comes to mathematics.
I can only wonder about strange things others with seafaring experience have pointed out: why the whole crew and the captain survived and were first into the lifeboat, why the crew didn’t raise the alarm when the ship started dragging its anchor, why didn’t they close all the wide-open windows and make other preparations for the storm, why didn’t the captain make sure that someone was on “anchor watch” 24/7, why didn’t they heed the weather warnings of the storm, like all the fishermen who kept their own boats safely in harbour that night, and what are the statistical chances of both of the acquitted defendants in that fraud case being killed almost on the same day, a thousand miles apart, one on land and the other at sea?
Is someone bearing a grudge? It certainly isn’t Yahweh, or more correctly “E-a weh”, though He always gets the blame for the things that Satan does.
Or in this case, things that Satan’s human agents do.
I completely agree. I saw the extraordinary ‘coincidence’ at once and it immediately prompted me to question what had happened or what we were being told. Satan’s agents, not Yahweh. And certainly not pure chance or simply human error!
Yes, and I forgot to mention the keel which seafarers said had been retracted, when it should have been fully lowered for stability.
Yet another interesting point. Thank you.
Same here. The “coincidences” smell very fishy. I am inclined to think that Lynch and his co-defendant weren’t supposed to win the court case.
I was wondering about that, too. Or maybe if they had lost and been imprisoned, they couldn’t have been dispatched without suspicion, like Epstein, so they were allowed to win and be released, in order to make them easier targets for revenge.
Maybe the real coincidence was his name ?
A friend of Lynch did a TV interview today and who has written a fresh obituary which includes how Lynch started in the Industry – through music and not it seems through science or engineering.
He mentioned the technology the US has been developing for over three decades called HAARP.
It is the most powerful atmospheric heater in the world.
HAARP, the most powerful ionosphere heater on Earth
Whether or not it applies to HAARP, he was suggesting that over the past three decades technology may have been developed which could cause severe local weather conditions.
All of this is denied by the US – with claims that it is for use in investigating the upper atmosphere.
But the HAARP project was initiated by the US military and developed in Alaska away from centres of population, industrial and farming activities.
Those activities are of course carried out on the ground and not in the upper atmosphere.
Wow— That’s scary stuff! You may be onto something there, because no one could actually see a “waterspout” in the pitch-blackness of four o’clock in the morning out over the sea. News reports are now saying “wind gust” instead of “waterspout”. If you watch the videos of the Bayesian’s mast lit up against the total darkness, then being obscured by lashing rain, tipping slightly before the lights went out, and remember that the nearby Dutch ship that rescued the survivors also managed to weather the same “wind gust”, it makes you wonder if it really is possible for humans to deliberately “cause severe local weather conditions”, as Lynch’s friend said.
Can they really pinpoint their weather weapon so precisely? Maybe they can, like the strange “D.E.W.” pinpointing of the Californian, Hawaiian and Australian wildfires that melted cars, dissolved houses to the ground, but left green trees standing all around.
If you do a search you will find in the US and in China people have been colouring the roofs of their houses blue.
Why?
Because unlike all the other colours, blue will not absorb radiation from non-visible Directed Energy Weapons [DEAs] which can also be used to affect local weather conditions.
It is of course all described as conspiracy theory and the like.
The problem with that is what the authorities like to describe as the conspiracy theory of yesterday becomes the conspiracy fact of today, like the Wuhan gain of function research funded by the US with the help of Dr Anthony Fauci.
Thanks for that important point about the colour blue, which I’d forgotten, but now that you mention it, I remember some saying that Hollywood celebrities like Oprah Winfrey had painted their roofs blue, and those houses survived the Hawaiian fires.
Well here are a few interesting snippets.
Who lost this fraud case against Mike Lynch? Hewlett-Packard.
And who owns Hewlett-Packard?
Vanguard, Black Rock & State Street.
And who has been in charge of Black Rock and then Vanguard?
Someone named after an Ottoman Sultan.
And where has Hewlett-Packard been heavily investing for years?
Turkey.
And who did the Captain of the Bayesian work for before joining the Bayesian?
A Turkish millionaire/billionaire.
I’m sure there’s no connection at all, just sayin’ it’s interesting…
Maybe instead of blaming God, Professor Alexander might look closer to where he lives and works now.
CIA?
Maybe , all the crew surviving surely gives the game away !
The cook died
Maybe he wasn’t in on it. “Collateral damage”.
The semi-official version is that the crew were working and so on upper decks which accounts for their survival.
The problem with that theory is it was 4am and the boat was at anchor so pretty much everyone would have been in their cabins but strangely the crew were not:
The 16 minutes that plunged the Bayesian yacht into a deadly spiral
If this was an assassination, someone may be working overtime reading all the speculation about it and developing embellishments to the cover story(s) to cover them.
Like the crew were up late darning their socks because it was sock darning night.
Nice one!
You are spot on again. The crew should have been tucked up in bed asleep at 4 o’clock in the morning, except for the watchmen. What were they all doing up on deck, ready for the off?
Was there only one cook?
There were a lot of people to feed on that boat.
The menu might have been less popular than desirable.
From the link for Chamberlain’s death “The driver of the car, a 49-year-old woman from Haddenham, remained at the scene and is assisting with enquiries.”
If it was an assassination there will always be a patsy and cover story which does not even have to be a good one but enough to muddy the water in news reports – standard operating procedure.
We have JFK assassination for the classic patsy – Lee Harvey Oswald and the Warren investigation and report to cover it all up.
The mortality rate among key eye witnesses was way above statistical averages.
All doctors in attendance on Kennedy after the assassination in a recent documentary – Fall 2023 – admitted they were told to change their evidence if they knew what was good for them.
I’m not sure what connection any intelligence services would have with this, since they didn’t lose any money from the court case.
Our security services do what they are told to do.
Its the people doing the telling and the people telling the people who do the telling and the people who tell them to do the telling whose interests and motives one needs to understand.
But sadly, how can any ordinary member of the public find out?
After all, a secret intelligence service ain’t much good if it cain’t keep a secret is it?
Very Interesting snippets indeed and all go to confirm me in my supposition that the deaths are extremely fishy!
They certainly are !
You could win the case with that info , best not go Jogging or sailing for a while !
I trust the Italians and their British colleagues will thoroughly investigate the whole thing, and discover the truth.
Winning the Lottery is unlikely as well but someone does win it, and sometimes individual boats will sink and individual planes will crash, even if this is mostly unlikely for boats and planes as a whole.
Could it be foul play? The sinking of the yacht is certainly very suspicious. Wait until there is a bad weather forecast, then either send a diver or bribe a crew member to sabotage the yacht. Meanwhile, someone is watching the other defendant, and pushes him into the path of a car.
So very many suggesting foul play.