WEBVTT

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Go test 1-2, testing 1-2, finally have a little show here, I hope this sound is all

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coming through.

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If you're in the chat it would be great for a little help on the audio visual.

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You can also check this, if you don't mind, see if we're all kind of in sync on the live

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stream, that would be really handy, perfect says Pamela, good to see you, good to see you.

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I'm going to do this without headphones today too, so if you can give me any feedback on

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my volume that would be great, or Jay's volume for that matter.

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In case you're unaware, and Jay is definitely unaware, I was a patch plant physiologist

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who was raised to make slices of animals brains, and I had Vivo, I scored them for

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a few hours, and while I did that I would record pairs or groups of neurons under the

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microscope, and also use transfection to control surrounding neurons with optogenetics.

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So I'm pretty familiar with how transfection can be used in academic medicine, academic

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investigation, how you can manipulate individual neurons, drive it by genes, you can look

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me up on the internet, Jonathan, who you are, PubMed.

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So today we have a special guest, Jay Bhattacharya.

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The bifurcation of Earth is, he's a very special guy with regard to that.

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Remember that if you're not familiar with him, he is a professor of health policy at

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Stanford University, and a research associate at the National Bureau of Economics Research.

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He directs Stanford's Center for Demography and Economics of Health and Aging.

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His research focuses on the health and well-being of vulnerable populations, with a particular

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emphasis on the role of government programs, biomedical innovation, and economics.

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Recent research also focuses on the epidemiology of COVID-19, as well as an evaluation of policy

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responses to the epidemic.

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His broader research interests encompass the implications of population aging for future

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population health, which I have listed as a must-ask question.

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The medical spending in developed countries, the measurement of physician performance tied

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to physician payment by insurers, that's a crazy one.

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The role played by biomedical innovation on health, he has published 135 articles, and

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top peer-reviewed scientific journals in medicine, oh, I can be over here, can I, yes, I can.

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He published that, yes, scientific journals in medicine, economics, health policy, epidemiology,

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statistics, law, and public health, among other fields, he holds an MD and a PhD in economics

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and book.

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MD and a PhD in economics, I almost thought it was an MD in economics for a minute there,

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and both earned at Stanford University, so let me see if I can cut this out like that.

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Oh, there you are, hello, sir.

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Thank you very much for joining me.

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I hope that introduction wasn't too, that's like 2-2-2-3-2-2-2-2-2-2-2-2-2-2-2-2-2-2-2-3-2-2-2-2-2-2-2-3-2-2.

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You left a community, which is I'm a fringe epidemiologist, that's what I thought.

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That's right.

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That's right.

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Fringe epidemiologist, he says.

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So, let's talk about being a fringe epidemiologist.

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That first question kind of peels right into that, so how did this great Barrington declaration

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inform was it from a poker group or are you guys all aficionados of the same dog breed or how did

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that happen? So it's a it's it's it's a little bit of a random thing like I got to know Martin

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Koldorf in the summer of 2020 because my friend Scott Atlas who was also at Stanford had been

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invited by by President Trump to be his COVID advisor. Scott tried to like organize a meeting

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inside the White House with me Martin and a few other scientists to try to talk to Trump about

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lockdowns, school closures, Debbie Birx and and Tony Fauci tried to block that. It took for and

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it took a like basically finally at the end of August, middle of August, I think,

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we he got permissioned for us to go visit the White House and that's why I met Martin Koldorf

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at the at the footsteps of the White House. Wow. Martin had been a guy known about him because

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he is an amazing statistician. I work on I've been working on vaccine safety actually with the FDA

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and he Martin had developed the statistical infrastructure for how to track vaccine

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vaccine injuries in with with a real time surveillance. Anyway, so I met Martin, we hit it off

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immediately at the foot first up the White House and I mean we started writing we wrote a couple

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op-eds together. One day in late September, Martin calls me up and says, Jay, do you want to come

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to have a little conference? What we'll do is we'll we'll invite some journalists and we'll invite

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Sinatra Gupta from Oxford who I I mean I've been mired her forever and I never met her before

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we'll invite the three of us will go meet with some journalists and try to tell them about the

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epidemiology of of lockdowns the harms of lockdowns. In fact, that's exactly what we told President

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Trump. We told that the President Trump that closing schools was a really bad idea was hurting

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children that the evidence from Sweden was that it wasn't particularly effective at stopping this

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rather than whatever the disease was and so like that there was a really bad idea to close schools

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and that you needed to protect older people better like the basically the idea of a great

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branch decoration and so we met in western Massachusetts very close to where Martin lives

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and it's a town I never heard of before so when we when I arrived I it was like you know actually

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this was like in the middle of a crazy lockdown in New York and and it felt it felt really illicit

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like I got to fly across country and and on the drive-in I asked the the the the driver was

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driving you what the name of the town was never heard of it before because it said Great Barrington

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and so when we met we just we weren't like actually thinking about writing we were going to write

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like a declaration we were just going to talk to people talk to journalists that have invited

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there that when we met we really cleared that we derived basically at the same place I mean

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I thought it was like particularly novel idea like the idea that you protect vulnerable older people

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and you don't lock down that's the way we managed every other viral pandemic last

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respiratory viral pandemic of the last century we arrived at the same place we thought okay well

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why don't we put out a little short statement about what we think and I came up with the name

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Jay I've stabbed quite proud of myself because I remembered the word Great Barrington I'm like

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that would be a great title for the declaration you know I was thinking like port here in statement

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you know from the like the 60s or whatever I see yes and so and you know you can't tell if the

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word Great applies to the the city or to the or to the declaration which is that I'm being

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really fantastic and so I yeah anyways it got a lot of attention I mean almost immediately

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it was it got a tremendous amount of attention almost a million people signed it tens of thousands

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of doctors and scientists signed it and you know what I think the reason why it got that

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attention was that at that point oh sorry Jake no I signed it I just wanted to say oh thank

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I'm really grateful you are grateful to do that I mean I think that the reason why it got

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attention is because people understood like most people really understood deep in their heart that

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there was that what we were doing was absolute nonsense it was hurting kids it was hurting poor

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people it was hurting vast numbers if you all these lockdowns were and it wasn't like you know

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if the promise was it was gonna get rid of the disease well how come it was coming back in

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October 2020 right it wasn't working and it was hurting people and it was violated civil

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rights at scale and it was and especially the harm to kids was was pretty close to the top of my

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mind and I have three kids and all three of them you know basically they didn't see my two of them

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didn't see the inside of a classroom for a year and a half and the third one was in college it

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took a long time I mean basically it felt to me like we were robbing our kids of their childhood

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for no real purpose well imagine quite frankly this is the one thing that really scared me is

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that imagine not having you as a father instead having somebody who can't grasp it or understand

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the limitations or the you know explain anything and just has to go from what they get on television

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it could bend much much what scares me the most is the idea that the children seem to watch the

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parents lose control and that's a real dangerous sort of blanket effect of what they did with the

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lockdown I mean you were still seeing the aftermath of that and that you're seeing like levels of

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anxiety and depression and kids like you scare the living daylight out of them tell them that

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they are going to kill if they just lead normal childhoods they're going to kill mom and dad or

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grandpa grandma and so they better treat everybody as biohazard or else I mean that's going to have

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consequences and it just has had consequences really negative ones it's just heartbreaking to go

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watch it anyway so that's how would the great grandpa question happen we we put this out and I

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think people were just ready to hear that that wasn't needed like I I call it the least original

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thing I've erode j I mean I it's not like I I mean it was we were saying obvious things right

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and and yet if people were interested because it shattered the idea that there was a consensus

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around the lockdowns I mean that's how you impose a lockdown or or or the kinds of like

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policies you have to like get the population to agree to be scared and to have this sense that

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all the scientists all the wise people agree that you have to do this or else and what the great

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branch of decoration is it shattered that consensus shattered the idea that there was a consensus

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it because you know the consensus wasn't there right you know this right I mean I from from from

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the beginning of the pandemic you've been you've been saying counter counter consensus things

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and scientists if you talk to scientists you know you get a hundred opinions if you have 100

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scientists you get 150 opinions sometimes right and so you just it was it was it was really clear

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that to me talking to other scientists that that there wasn't a consensus and so when we put the

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the Declaration out I think that's why it got so much attention both from the public but also from

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scientific authorities you know scientific bureaucrats like Tony Fauci and Francis Collins

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or Jeremy Farron in the UK they were they were for them it was a threat to their power

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it was a threat to the idea that they that they knew best what to do and everyone better

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listen to them or else everyone's gonna die I mean that was essentially I mean like they you know

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they didn't say it that way but that's essentially what they were they were implying

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and the great branch and declaration said no look other scientists have a different view or

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proposed or thinking of different policies is better and it was a call for a conversation

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like we were calling for focus protection it's called for conversation how best to do that

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how do you how really do you protect older people because the idea up to then was like the

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lockdowns were going to protect them but it didn't protect them you know lots and the older people

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have died on the basis of the idea that lockdowns can protect them we've done really stupid things

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right like why do we send covid why did why did New York send covid infected patients back to

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nursing homes this happened lots of places by the way not just New York it's because the the

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premise was that keeping hospital beds empty was more important than protecting vulnerable people

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why did we close schools like because somehow kids were even even despite the fact that

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Sweden you had evidence from Sweden for the spring that not closing schools didn't result

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in a worse epidemic really I just for the especially for the teachers the the rates of death for

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teachers was was lower than the average of the rest of the population yeah it was it was really

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shocking oh what is this what that's ridiculous now I get they're saying my zoom meeting is going

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to end well we can we can you know I'm signed in under the wrong account then dog on it

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I'm gonna have to sign in different than I guess okay well we can we start though we we've recorded

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this right so we can yeah yeah I mean it's it's this is uh it's it's fine I just him in a little

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annoyed that I could have seen that coming I guess I thought I had longer in this don't worry

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um I'll send you a link in like 30 seconds okay see shortly okay

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dumb d-dum d-dum d-dum d-dum d-dum d-dum d-dum d-dum d-dum d-dum d-dum

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dumb d-dum d-dum d-dum d-dum d-dum

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this one is the one I paid for open zoom

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um

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um-d-dum d-dum d-dum d-dum

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sorry guys I'm gonna fix this right now and then it'll be dumb

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save and now that we've got him he said I've got a lot of time so I'm actually gonna probably

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have to cut him short and then uh what will happen is uh

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I'll have to switch right away for Peter McCullough which is crazy but there it goes

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hopefully he'll be up very shortly I'm gonna start this meeting and then uh hopefully he'll be here

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at least all the settings are right now I hope the sound is all right are we good sound is all right

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I think this is gonna be a fun conversation um I might have to keep him here all the way till

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six o'clock but uh I think it's gonna be a good conversation here he comes he's already back

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see how quick we are now we're back Jedi master level stuff there thank you sir for tolerating my

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IT uh sure better rather than I am Jay so just uh no worries um so where were we we were I was

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about to ask you I sort of pair up a general question that kind of segway's well in in what we

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were talking about about the Great Bearing Declaration and where it evolved from and where it got you

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um oh Jay can you can you can you allow me to or of course I can yes there we can

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and so if you if that helps you at all to pick up where you left off or recording in progress

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gotcha otherwise um so we were just talking about the Great Bearington Declaration you were

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finishing kind of saying um how it evolved and and why it was important because because it gave

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people first time this this clear uh message that there isn't a consensus that something is

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isn't right so it's a pretty incongruent message relative to the television

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um what was the in that time what was the the most common way of them trying to dismiss you

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was it just that they don't know what they're talking about even though that was part of the

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reason why you chose you three right as you you realize that you're let's say professional

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standing should bring some weight so that people would be less likely to be able to dismiss you

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well how did you how did that come out in reality versus what you expected

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well so uh the four days after we wrote the declaration we learned this uh from foyer

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request four days after we wrote the declaration the head of the NIH Francis Collins wrote to Tony

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Fauci an email where he called me Martin and Sinatra of Martin Coldoff of Harvard University

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Sinatra Gupta of Oxford University the three of us fringe epidemiologists uh that's that's

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I got a book I got a little uh i'll see if i have like card that has the fringe epidemiologists

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i can't find it it's a fringe epidemiologists somewhat friend of mine made a fringe epidemiology

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card i i think i will go to my grade with that title well don't give them all the way i want one

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of those i definitely will the next time we'll next time we meet you i will give you what i promise

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um but yeah so so uh he called us fringe epidemiology then he called for devastating takedown literally

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in an email devastating takedown the premises of the the declaration and then what started

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happening was hit pieces hit pieces by the washing and post uh in fact Francis uh Tony Fauci shared

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it and a hit piece almost immediately by wired magazine where Fauci showed up accusing us of

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wanting to let the virus rip when we were calling for focus protection of vulnerable people um i

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mean it was basically a propaganda campaign um in in in the uk parliament a conservative

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member parliament denounced uh cenetra uh there was a website that came up uh all of a sudden

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accusing us of like saying all being you know all kinds of nasty attacks and in the British

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medical journal the British medical journal published a false attack on us claiming that we

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had financial conflicts of interest it was insane i paid my own way to great parenthood mass

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uses for the flight i didn't accept any money in fact jay i've taken zero dollars for any of my

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covid work to date i've lost money on covid um because i just don't feel right taking money in the

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middle for when people are suffering in this way so i just i the whole thing was just they

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and the British medical journal published it claiming that somehow that we were coke funded

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when in fact that it was the it was like the imperial college model that led to the panic in

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march of 2020 that was coke funded um the whole thing was just it was it was it was an absolutely

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disgusting ad hominem attack based on lies because the problem was they couldn't actually engage with

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us honestly in a discussion it's not like that is if we had all the the ideas i mean i i i you know

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it's just where if you're a scientist you know you make a mistake let me you you're wrong a lot

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of the time and it's the it's the process of like uh seeing what other people think looking at data

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doing experiments that's how you learn as scientists right they didn't treat us that way they treated

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us as if we were heretics to be expelled and excommunicated um i'd say this this wasn't it wasn't

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even the first time like in the pandemic um in april of 2020 i had done a study in Santa Clara

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county california um i don't know if you've seen it maybe you've seen it was it was it was a

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study measuring antibody levels in the population a seroprevalence study and it was we done one in

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Santa Clara county and another one in LA county shortly after that and uh you know we we used this

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uh this test kit that we'd gotten from a a guy who runs uh made testing in major league baseball

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he had ordered it um we did a lot of work to try to figure out what the false laws and

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false negative rates were uh we were we put out a paper which i thought was a pretty careful paper

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that there was some uh some some comments that folks folks had on twitter and elsewhere that

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made it then we released an updated version of it in a in a in in the pre-print ultimately the

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paper was published in the international level of epidemiology right so it's like we got the math

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right um the hunch line for the paper from the beginning was that the disease had had spread to

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about three percent of the population in LA county for in LA county four percent three percent

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in in Santa Clara county um it was uh it was something like it was April early April 2020 and

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that meant that you know there were a thousand official cases then in in in Santa Clara county

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but our estimates implied 50,000 people had already been infected or at least had antibodies to the

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to the there were specific to the SARS-CoV-2 um that meant that infections how do you rate was

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not you know the the you know was the World Health Organization said 3.4 percent case fatality

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rate our estimate was that that implied something like 0.2 percent infection fatality rate um for

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people especially for and there was this massive age gradient with older people having much higher

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risk um that led to hit pieces on me and on my wife and my family it led to i wasn't ready for

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that my face skin wasn't this i thought my skin was thick after you know two decades in academics

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but it turns out what i wasn't used to uh attacks on me death threats constantly for two straight

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years jay every time i appear in public every time i'd write something they there was just like

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uh assumptions of bad faith accusations of false accusations of conflicts of money complex of

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interest um essentially everything but actually engage with the scientific results right i i i

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can only imagine i mean i i remember this paper um and i remember i might have even still been

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on my bike when that paper came out so there might even be a later bike ride on my youtube

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channel where i did it um but the the what my narrative would be on that or what my question

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would be on that is um just taking notes on it so we that whole study would be on a testing kit that

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at that time um part of the illusion of consensus i would say was that these testing kits were

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very high fidelity with almost no false positives and appropriate to apply to anybody that was

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suspicious of having a test or i mean having an infection and at the same time overlapping with

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this i think biologically incorrect concept of asymptomatic spread being a very widespread

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phenomenon and i know that at that time i couldn't iron it out i couldn't figure it out but i know

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that there was a very concerted effort to establish the idea that you can't know if you're infected

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and even if you test negative on a test you could still be positive and just not know it and this

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goes back to the you know testing before you leave campus to make sure you don't infect your

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grandparents it was really uh a wicked web they wove um and so i think this was really important

22:22.180 --> 22:26.260
evidence that again even if you don't interpret the evidence the way that i would

22:26.980 --> 22:32.820
its evidence for this illusion of consensus about well there's a new virus and it's just got here

22:33.380 --> 22:40.580
and we're accurately tracking it when it that clearly brought that into question yeah i mean i

22:40.660 --> 22:45.620
think um so just a couple of things like at the time there were those test kits um these were

22:45.620 --> 22:52.580
for antibody test kits not the PCR test kits um and uh like on the on the PCR absolutely grew

22:52.580 --> 22:58.180
with you that the PCR was was vastly like misinterpreted and misused i don't even know what the right

22:58.180 --> 23:06.500
word is um they they they tuned the PCR test so that it was hypersensitive right so even if you had

23:07.460 --> 23:13.620
uh like just fragments of dead dead virus in you it would turn positive because they they did

23:13.620 --> 23:18.340
you know 40 doublings or whatever but a lot of 40 doublings for you a lot positive and then

23:18.340 --> 23:24.980
they tied that to quarantining uh to contact tracing it was it was a it was guaranteed to create

23:24.980 --> 23:30.740
this the idea that the virus is is everywhere and that you are at risk of spreading it from to

23:30.820 --> 23:36.100
everyone and um and you better you know and and essentially create panic and fear i wrote a piece

23:36.100 --> 23:42.420
in uh in the summer of 2020 arguing against contact tracing on basically with that as the main premise

23:43.300 --> 23:49.620
the premise being that the contact tracing um was identifying many people who are not really at

23:49.620 --> 23:56.740
risk of spreading the disease causing untold harm to the especially the children um and uh the

23:57.220 --> 24:02.660
that and that it was an inappropriate tool for trying to control the spread of a of a of a

24:02.660 --> 24:07.300
respiratory virus i mean a contact tracing maybe could work for HIV because you know who you had

24:07.300 --> 24:11.300
sex with but you don't you're really hard to tell who you breathe next to breathe near or

24:11.300 --> 24:17.540
breathe in the same room as um and so the idea that you could you could like get uh you could stop

24:17.540 --> 24:21.940
the spread of the disease this way with this testing was insane but i just a quick thing

24:21.940 --> 24:26.260
about the antibody test at the time in april 2020 it's basically impossible to get the antibody

24:26.260 --> 24:31.220
test um it was kind of a unique thing that we were wondering about that actually you said major

24:31.220 --> 24:35.140
league baseball so you had some kind of hookup otherwise you wouldn't have been i mean it was

24:35.140 --> 24:39.060
it was actually just completely serendipitous jay so like what happened was that i wrote an

24:39.060 --> 24:44.900
op-ed in march of 2020 in the waltz v journal saying that we didn't know how deadly the disease

24:44.900 --> 24:50.100
was we didn't know how widespread it was and effectively calling for a sera prevalent study i

24:50.100 --> 24:56.180
figured the cdc would run it um the cdc didn't run it so much later uh what happened instead

24:56.340 --> 25:01.220
was that there was a man who runs uh testing for for uh you know steroid testing for major league

25:01.220 --> 25:05.860
baseball he had had the foresight to order a bunch of antibody tests from this chinese company

25:06.740 --> 25:11.940
and uh he when he saw that op-ed he called me up or called me and my colleagues up and said look

25:11.940 --> 25:17.380
i i don't want to use this to make money i'd rather use it for science and so he offered up those

25:17.380 --> 25:23.140
tests which i never would i would have access to to run this study we we organized that study

25:23.140 --> 25:27.540
within the matter of a couple of weeks um it was it was it was it would normally it would take

25:27.540 --> 25:31.620
a year to organize a study like right just getting everything in place it was it was really just it

25:31.620 --> 25:36.420
was it was quite something to get uh like quite a feat of of like logistics to like get everything

25:36.420 --> 25:43.140
together um and the results were right like a hundred other groups then replicated the result

25:43.140 --> 25:48.340
that we got uh that as far as the false positive rate for that test the way we measured it was first

25:48.820 --> 25:52.420
that the the manufacturer had done some rest asked him as the false positive but they've

25:52.420 --> 25:58.740
done is they've taken blood stored blood from 2018 or something and run the the blood the blood on

25:58.740 --> 26:04.980
the uh run the run the test on that stored blood from 2018 and they found a false positive rate of

26:04.980 --> 26:10.980
like point oh five percent very very small false false positive rate um we of course we didn't

26:10.980 --> 26:15.060
believe them because it's the manufacturer so you have to like get it independent so we got when we

26:15.460 --> 26:19.060
went and found some some colleagues to run some independent studies here at Stanford

26:20.020 --> 26:23.780
for a small group then when we released the study it turned out there were like dozen

26:23.780 --> 26:28.420
laboratories around the on the world that were also playing with the same antibody test kit

26:28.420 --> 26:34.580
and they basically got the point oh five percent same the same we we gotten um it was actually a

26:34.580 --> 26:39.460
major scandal around those antibody test kits right around then Jay um a lot of the test kits

26:39.460 --> 26:43.460
turned out to be fraudulent the UK for instance had bought a bunch of like test kits from Chinese

26:43.460 --> 26:49.540
companies that had been which is terrible test yes um like you know with like lots of cross

26:49.540 --> 26:55.460
positivity to other SARS-CoV-2 viruses and so on um uh I'm sorry SARS-CoV-2 to other coronaviruses

26:55.460 --> 27:01.220
and so on um and so like it was it was it was but there are like fortuitously our test kit

27:01.220 --> 27:05.220
turned out to be good the one of the few good ones it was actually approved by the FDA for uh

27:05.220 --> 27:13.060
for EUA later that summer um and uh yeah so I think we actually got the number right and I said a

27:13.060 --> 27:22.740
hundred other uh independent uh groups confirmed uh pretty widespread uh antibody levels uh use

27:22.740 --> 27:27.540
you're using different test kits basically all around the world that summer and into that fall

27:27.540 --> 27:33.140
there was um the best paper that I've been using to teach was a cell article actually

27:34.660 --> 27:42.020
and uh I don't know if I can flash this up there and show it to you but um the the paper actually

27:42.020 --> 27:51.300
looks at um in this column in the dark blue is actually uh people that were just blood donors um

27:51.300 --> 27:57.700
in 2020 and even there they can find uh T cells that are specific for the S protein the M protein

27:57.700 --> 28:04.820
and the N protein of SARS-CoV-2 already in 2019 in blood donors um and they also confirmed the B

28:04.820 --> 28:11.620
cells um and they showed that actually more people converted T cells than converted B cells which

28:11.700 --> 28:18.260
also makes sense from the sorry I don't have you on the screen um making uh makes sense from the

28:18.260 --> 28:23.540
the perspective of how the immunology activates itself and sequence like that so there were some

28:23.540 --> 28:29.700
really giant confirmations of there being a signal before the pandemic started I mean I think um

28:29.700 --> 28:34.660
it's quite likely that the the disease was here in 2019 there's no there's I mean it's just it's

28:34.660 --> 28:40.100
inconceivable to get from like the official start day of the pandemic is what like late January 2020

28:40.100 --> 28:46.020
2020 in the US and by early April that's like a month and a half and you know three weeks of

28:46.020 --> 28:50.580
lockdown it had already spread to three percent like you already antibodies in three percent of

28:50.580 --> 28:55.940
the poverty that the antibodies of course fade right so as you as you as you well know um so the

28:55.940 --> 29:01.780
idea that uh three percent of the population have antibodies there's no way if the start date is

29:01.780 --> 29:07.460
January late January 2020 to get to April 20 early April 2020 and say oh well three it's spread to

29:07.540 --> 29:13.700
three percent um you know in the middle of a lockdown it had to have been here earlier um there

29:13.700 --> 29:20.420
was a couple of studies really interesting ones from September 2019 like looking at stored blood in

29:20.420 --> 29:26.900
and goal in Angola I think was the and then another one in northern Italy looking at stored blood

29:27.540 --> 29:35.220
in um uh in from blood banks from September 2019 October 2019 that found positive antibodies um

29:35.300 --> 29:39.460
and I think some of those T cells results that you're you're pointing to Jay I think that also

29:40.340 --> 29:46.340
says something really important about cross immunity right you you might have had immunity

29:46.340 --> 29:51.540
because you were exposed to other coronaviruses um and there were some really interesting uh

29:51.540 --> 29:58.660
studies that I remember reading in 2020 of of like preschool teachers and what happens when they

29:58.660 --> 30:03.860
got infected like they they basically had different like a different disease course in part because

30:03.860 --> 30:10.500
they've been exposed to you know you have small kids I know I've had small kids you get sick all

30:10.500 --> 30:16.980
the time with presumably the other coronaviruses um and so they had some cross immunity uh so just

30:16.980 --> 30:22.260
it's uh so what I got a I got a really sharp question for this part of the discussion if

30:23.060 --> 30:30.420
if we agree that this seroprevalence data is real um and we look at at what was happening

30:31.060 --> 30:37.220
in 2019 we don't even we don't see any peaks in all cause mortality we don't see any peaks

30:37.220 --> 30:42.900
in pneumonia we don't see any peaks in some kind of signal that would indicate that something

30:42.900 --> 30:49.700
especially deadly was spreading in the background and then suddenly in in certain places at certain

30:49.700 --> 30:56.820
times we have these giant spikes which which they sold to us as evidence of instantaneous spread

30:56.820 --> 31:02.820
but your data suggests that's not the case but there's no signal before that so how do I

31:02.820 --> 31:08.580
reconcile those two things? Well I think um you know you could you could like so I talked to

31:08.580 --> 31:12.580
Synetra Gupta for instance about this you know she's she's a theoretical epidemiographer professor

31:12.580 --> 31:17.460
of theoretical epidemiology um what she tells me is that these are consistent with s these are

31:17.460 --> 31:21.620
consistent with sIR models with particular sIR models are these compartment models I'm sure

31:21.620 --> 31:27.540
your audience knows uh that they're used to forecast forecast and track uh like the the

31:28.180 --> 31:34.660
spread of diseases um that there are formulations of sIR model consistent with the patterns that

31:34.660 --> 31:41.860
we've seen um so like for instance imagine it's it starts in september august 2019 or something

31:41.860 --> 31:47.140
like there's a it's the path of these sIR models there's flat flat flat flat and then a big

31:47.300 --> 31:51.780
spread because it's like there's this like early it's not exponential but like it's exponential

31:51.780 --> 31:57.940
like growth um very very early because you just you know one two four it's very small until you

31:57.940 --> 32:04.580
get to you know two to the 15th or something and then you get then you have to get big numbers um and

32:04.580 --> 32:11.140
the how how fast that spreads uh you know it's it's possible that that that it's it's that uh

32:11.140 --> 32:15.300
let me give you one other data point that I that I've seen that most people don't know about um

32:15.860 --> 32:22.980
there was a paper by two uh two economists at the ohio state who she had done and uh

32:23.780 --> 32:27.540
blanking on the uh the second author's name and what they found was that there was

32:27.540 --> 32:33.780
cremation data from china from muhan in october 2020 a big spike in cremation

32:34.900 --> 32:41.380
in muhan china uh so it's not that there was no signal earlier it's that the signals were kind of

32:41.380 --> 32:48.340
hidden um suppressed uh and you can you can look and see some they they apparently got uh they

32:48.340 --> 32:52.580
they got these data leaked to them uh and they actually couldn't they they tried to get the paper

32:52.580 --> 32:57.300
published and uh they even the pre-print servers wouldn't put it they finally I think they got

32:57.300 --> 33:02.420
SSR on or some pre-print server to put it up so you can go find the paper um who she had done

33:02.420 --> 33:07.220
so there there is there may be uh the other thing it's a curious it's a curious observation

33:07.220 --> 33:12.500
because um are you aware of andrew huff do you know that that guy is from eco-health alliance

33:12.500 --> 33:18.180
actually he in his uh story about the pandemic also mentions that he was searching data on the

33:18.180 --> 33:24.820
internet and found uh some signal that was related to crematoriums in china I don't know if it was a

33:24.820 --> 33:32.500
signal from a satellite or some other information he had uh which is interesting you said the last

33:32.500 --> 33:41.860
name was done on that paper d-u-n-n-l-u-c-i-a-d-u-n-n um cool but yeah so it was uh I'll send you the

33:41.860 --> 33:45.460
paper afterwards I don't have the technology you have of like bringing papers up which is

33:45.460 --> 33:52.260
very very cool I'd say um uh but yeah I think um I think I think that that it's I mean there

33:52.260 --> 33:57.460
are still quite a lot we don't know there are also people there are interests of great powers that we

33:57.460 --> 34:04.740
keep some of this you know like I mean like you know some of this uh like if the full story gets

34:04.740 --> 34:09.380
out uh about exactly how it I mean I I mean just one of these things were like there's lots of

34:09.380 --> 34:14.740
people having interest in not having the full story completely get out um as you know as you

34:14.740 --> 34:20.340
can tell from the the the cover up around uh the support of the NIH for getting to function research

34:20.340 --> 34:27.460
that's there's a lot of like people who just their reputations will get harmed um uh so anyway

34:27.460 --> 34:33.300
so like the the point is that uh that it's it's possible that it's not possible likely that it was

34:33.300 --> 34:38.820
he it was spreading before 2019 I don't see how you can and what you said I agree with uh I don't

34:38.820 --> 34:44.500
see how you can explain it as it arrives in late January 2020 and then all of a sudden pops up

34:44.500 --> 34:51.940
everywhere Iran, Italy, UK, Sweden, New York uh all of a sudden pops up everywhere

34:53.060 --> 34:58.980
without it either uh yeah I mean I think the most likely explanation is it was here earlier it was

34:58.980 --> 35:05.940
here in 2019 and then you had like exponential spread flat flat flat and then you notice the

35:05.940 --> 35:09.700
oh I remember what I was gonna say this is one other thing if you're not if you don't you don't

35:09.700 --> 35:15.540
have a test to look for it before what like January 2020 and in the US we don't really have a test

35:15.540 --> 35:23.780
a PCR test to look for it until really available to like March 2020 um that is true there was a paper

35:23.780 --> 35:31.700
by Alex Washburn um early in the pandemic looking at ILI spikes uh it uh influenza like illness spikes

35:32.260 --> 35:38.820
that it would show up something like that right like an ILI spike um he also was arguing for

35:38.820 --> 35:45.700
an early spread based on the ILI spikes um so I think I think it's it's going to be a complicated

35:45.700 --> 35:50.420
story partly because it it matters what you can see in what you don't see oh sorry Jacob no no I

35:50.420 --> 35:58.340
was just I'm trying to find another piece here but um there's a interesting uh theory on the

35:58.340 --> 36:03.460
internet that circulates around that flu actually disappeared at the start of the pandemic but then

36:03.460 --> 36:08.180
people say they stop testing and that's why it disappeared so it's interesting that's that

36:08.180 --> 36:12.660
actually if you look it did it did actually disappear there was no there was almost no flu

36:12.660 --> 36:19.140
for for two years so then how did so what signal did he see an ILI then what's he looking for if

36:19.140 --> 36:25.220
he's not looking so see he was looking for like ILI is not like flu testing data so this ILI is

36:25.220 --> 36:31.700
like you it's clinical uh your admissions for uh but they weren't giving any money for ILI cases

36:31.700 --> 36:37.460
so there was no impetus for anybody to record any ILI when they could get 35 000 for calling

36:37.460 --> 36:42.740
the same thing so um the flu disappearing is like uh there's a what's the name of the group I think

36:42.740 --> 36:49.300
I'll biofire that the tests um test for like and there's the sentinel labs that the CDC has to test

36:49.300 --> 36:54.820
for flu and the flu did disappear I mean just it absolutely disappeared for two years like you

36:54.820 --> 36:58.580
could find almost none of it but either in the southern hemisphere or the northern hemisphere

36:58.580 --> 37:06.740
almost in any country um it was gone um the okay so what could explain that uh there's two theories

37:06.820 --> 37:10.980
that I've seen that that's might work I'm not I'm not sure I convinced by either theory but I'll

37:10.980 --> 37:19.300
tell you what the theories are um one is that the flu and the and the and the covid virus

37:19.300 --> 37:26.260
I compete in the same evolutionary space in the same niche and so and it just the

37:26.260 --> 37:31.620
covid just outcompeted the flu in the in our in our noses I've seen a couple of papers that

37:31.620 --> 37:36.740
suggest that that's not true that in fact that you can have both so I don't I'm not I once for a

37:36.740 --> 37:40.260
long time I believe that was true but once I saw those papers I was not sure that's true

37:40.820 --> 37:46.500
um the other theory that I've seen that's possible imagine you have a disease like the flu that is

37:46.500 --> 37:53.540
in endemic equilibrium right so you you're it's a it's it's hovering around the herd immunity

37:53.620 --> 38:00.500
threshold uh in the population at large right uh so so you you're you're you're if you whenever

38:00.500 --> 38:05.380
the immunity level goes above it the flu rates go low whenever it goes below it you see a little

38:05.380 --> 38:12.580
up you see some uptick like in the in the winter season or whatever um versus a disease that's

38:12.580 --> 38:16.500
like relatively new in the population you have some cross immunity like we talked about but not

38:16.500 --> 38:22.820
but but it's not in endemic equilibrium covid is not in endemic equilibrium and then imagine that

38:22.820 --> 38:29.220
you have a panic or fear or even lockdowns or something uh that what what that will do is it

38:29.220 --> 38:36.340
will raise the herd it will lower the herd immunity threshold of both the flu and the and for covid

38:38.100 --> 38:44.420
and that will now if the flu already has immunity in the population that is near the endemic

38:44.420 --> 38:50.580
threshold right hovering around the herd immunity threshold then the lowering the herd immunity

38:50.580 --> 38:57.780
threshold by again by panic by panic or by uh lockdown will will cause the flu to disappear

38:58.580 --> 39:03.060
because you'll have a lot more people that are above that herd immunity threshold but for covid

39:03.060 --> 39:08.740
it won't because uh the relative fraction of the population that's immune is still well below the

39:08.740 --> 39:13.620
herd immunity threshold i'm just talking like april 2020 or whatever it's generated whatever

39:13.780 --> 39:21.220
2020 um and so you could have policies have different effects on different viruses depending on how

39:21.220 --> 39:28.660
close they are to their own herd immunity thresholds i'd see um that's a theory i i've not that's a

39:28.660 --> 39:33.940
theory that uh cenetra told me actually i've not seen a paper that's documented whether it's or

39:33.940 --> 39:39.140
you're tested whether this is this works or doesn't work but the fact is about the sentinel labs in

39:39.140 --> 39:43.940
the cdc looking for the flu it what they went away like they found nothing for two years

39:46.020 --> 39:49.540
i'm going to make this over here for a second so i can put you

39:51.300 --> 39:58.900
up on top so this is this is the one issue that i keep bringing up on my slide stream all the time

40:01.540 --> 40:07.140
is that if you look at the data from oh what oh that's right i can't do that shoot that doesn't

40:07.140 --> 40:13.780
work i gotta leave you up where you were um so how do i get that off if i do this sorry i'm trying

40:13.780 --> 40:22.980
to get too fancy um so if i just show it like this if you take the cdc data and this graph

40:22.980 --> 40:29.220
unfortunately stops in somewhere in 22 so i don't i haven't updated it in a while but the point

40:29.220 --> 40:37.700
still gets well made is that if we start at 2000 if we start at 2014 over here and we follow the

40:37.700 --> 40:47.540
seasonal variation between you know 68,000 and 55,000 deaths per week there's no real signal until

40:47.540 --> 40:56.500
right there smack dab in february or or march of 2020 and then this this is not anything that a

40:56.500 --> 41:01.700
normal model fits and then in new york and many other places it goes right back down to baseline

41:02.660 --> 41:08.500
and that's not what that's still it's still about baseline but um but yeah okay yeah yeah okay but

41:08.500 --> 41:15.780
but in this case we have a signal in the form of uh pneumonia we have a drop in the signal due to

41:15.780 --> 41:22.260
flu that you can't see here in yellow and so i'm still stuck on the idea that pneumonia went up to

41:22.260 --> 41:27.380
two or three times normal death that we used to be able to handle pneumonia pretty well and

41:27.380 --> 41:33.620
it's a pretty consistent number across the last let's say eight years and then suddenly we we lost

41:33.620 --> 41:39.620
the plot and we couldn't care for pneumonia anymore um i mean i i think uh what what this

41:39.620 --> 41:45.060
points to and i i think this is the point you're making at which i agree with this is a complicated

41:45.060 --> 41:50.020
situation it's not just that covid came in and killed people although i do think that covid

41:50.180 --> 41:56.020
came and killed people but i i also think that it let the the the policy response

41:56.820 --> 42:02.580
distorted how we managed respiratory disease generally and actually just disease more generally

42:03.540 --> 42:08.740
i mean there are incredible reports of people dying at home with heart attacks yes and then

42:08.740 --> 42:15.940
reported as covid and then reported on the news as covid i mean you know that we uh i think it was

42:16.420 --> 42:22.740
CARES Act uh that that put in the uh the ten thousand dollar funeral benefit or

42:22.740 --> 42:26.580
nine thousand dollar funeral benefit if you have covid on your death certificate

42:27.140 --> 42:30.500
um it doesn't have to be the primary cause just to be on our death certificate in fact if you go

42:30.500 --> 42:35.460
to the FEMA page it'll tell you how to request that they make sure the check for covid

42:35.460 --> 42:39.780
so that it shows up on the death certificate that's correct so you can get the benefit

42:39.780 --> 42:44.020
if you die of cancer without covid on the death certificate you get zero dollars from federal

42:44.020 --> 42:48.180
funeral benefit so there are definitely incentives to oh i i did a study

42:50.020 --> 42:54.100
in uh well actually since i didn't publish it i'm not going to talk about that let me just

42:54.100 --> 43:01.140
talk about that uh something that is published a study done by the Santa Clara county public health

43:01.140 --> 43:08.260
authorities in 2020 looking at autopsy reports and then going back and do and do like checking

43:08.260 --> 43:13.140
to see what fraction of the patients that were diagnosed sort of designated as dead from covid

43:13.140 --> 43:18.260
actually actually had covid as the primary cause of death and it's like you know it's

43:18.260 --> 43:24.900
not i mean i think like at least 25 over counting in in summer of 2020 at least for older people

43:24.900 --> 43:29.860
in that autopsy studies with what they found alameda county in california also had a similar

43:29.860 --> 43:35.700
finding there's definitely over counting um in that sense uh john e and medius has a really

43:35.700 --> 43:39.940
interesting sort of modeling study looking at trying to find or trying to figure out how much

43:39.940 --> 43:44.980
over counting there was and he finds i mean something on that order for in in western countries

43:44.980 --> 43:51.380
of 25 to could be higher uh percent uh over counting probably under counting in in poor countries

43:52.500 --> 43:58.820
um and so it's it's it's so there's that the the lockdowns themselves cause a lot of death

43:58.820 --> 44:07.620
there's also iatrogenic harm right so we used a protocol for managing patients in a hospital

44:07.620 --> 44:12.820
with ventilators that the wall tout organization promulgated based on the chinese authorities

44:13.700 --> 44:18.420
that uh that was dropped i think sometime in early summer 2020 after people started to

44:18.420 --> 44:24.340
realize we were killing patients on that we using that ventilator protocol right uh we

44:24.340 --> 44:30.740
so and and so you and and you're you're a lot of a lot of the uh the rhetoric around the time

44:30.740 --> 44:36.500
is that you know you if you and actually still uh to for a long time was if you get covid stay at

44:36.500 --> 44:41.220
home until you're so sick then come to the hospital what if you had pneumonia then right

44:41.220 --> 44:45.780
pneumonia still is still is a deadly killer um you probably should have gone to the hospital earlier

44:46.340 --> 44:54.020
to get uh to get an antibiotic treatment um a lot of the a lot of that spike that you showed

44:54.020 --> 44:59.300
it's got to be complicated it's got to be partly covid partly by atrogenic harm partly just

44:59.300 --> 45:04.340
disruptions in basic services for for basic things that otherwise could be treatable

45:04.820 --> 45:10.980
a lot it could be i mean essentially general panic i haven't seen a great decomposition of

45:10.980 --> 45:17.860
that and i think we really need one like we need to understand uh what what you know each of these

45:17.860 --> 45:24.260
items are important i've seen people say that it's not consistent with epidemic spread of a disease

45:24.260 --> 45:27.780
and that i'm not sure about i mean like i said i talked with sineptor Gupta and she says that

45:27.780 --> 45:34.580
it's consistent with um with sIR models uh with the right parameterization and there are very

45:34.580 --> 45:41.700
flexible models so it's it's it's still possible but so flexible model makes it weaker in a way

45:41.700 --> 45:46.020
right because flexible model means you can make the model say whatever you wanted to say including

45:46.020 --> 45:50.500
what they made it say at the beginning of the pandemic so i always would take that with a grain

45:50.500 --> 45:55.780
of salt well i think i think the the question is like if you want to say it's not consistent with

45:55.780 --> 46:01.380
epidemic spread uh the way that you understand what epidemic spread is is these sIR models

46:01.380 --> 46:05.540
and they are flexible that is that in a sense that you're right i agree with and that is that

46:06.260 --> 46:11.940
it when you have a very flexible model essentially what you have is uh it's not falsifiable or much

46:11.940 --> 46:17.940
a very difficult to falsify um i'm not sure that's true for the sIR models i think it is falsifiable

46:17.940 --> 46:24.580
but but it does encompass a very wide range of viral spread uh patterns uh depending on the

46:25.460 --> 46:31.140
the parameterization of it so i don't i i guess i'd say i don't

46:32.500 --> 46:37.060
like the the pattern that you showed i've seen other folks put that up and say look that's not

46:37.060 --> 46:42.340
consistent with epidemic spread i don't i don't know that's true but i also i also think that the

46:42.340 --> 46:49.860
general point which is that there was a lot of panic and that that panic itself caused a lot

46:49.860 --> 46:57.620
of harm deaths even that is that's indisputably true uh are you familiar with denny rancor's work

46:57.620 --> 47:04.420
this guy uh in canada yeah i think one of the main observations that he makes that's very compelling

47:04.500 --> 47:12.740
to me is that even in counties in america you can see the lack of spread like an event and then

47:12.740 --> 47:19.780
it's over and then another event and it's over and it doesn't cross borders for example germany has

47:19.780 --> 47:26.740
no signal in the first uh first year of the pandemic almost a year and a half um which can't be

47:26.740 --> 47:31.860
attributed to lockdowns because that's of course one of those things that we've been arguing from

47:31.860 --> 47:37.220
the beginning that lockdowns can't do that so it's tricky i think it's i mean it's there's a

47:37.220 --> 47:42.660
there's a study i don't know i'm sure you've seen it uh from um mumbai a colleague of mine at the

47:42.660 --> 47:49.380
university of chicago a nuke malani conducted a sera prevalence study in in mumbai in uh july

47:49.380 --> 47:54.020
of twenty twenty i think i think it was the date um and we found it was then the slum areas of

47:54.020 --> 47:58.340
mumbai the sera prevalence was seventy percent and then the richer areas is twenty percent

47:58.980 --> 48:03.940
so i think i think like i've done i did a study look trying to measure the effect of lockdowns

48:03.940 --> 48:08.740
uh comparing sweden and south korea versus other countries um that that did lock down

48:08.740 --> 48:14.900
the close schools and close businesses and found very little average effect of lockdowns on disease

48:14.900 --> 48:20.100
spread and i think the key i don't know i mean i didn't like this is how i'm thinking about now

48:20.660 --> 48:28.500
the main hypothesis i have now right is that is that um is that lockdowns worked for a certain

48:28.500 --> 48:35.620
class of people right a class of people who didn't lose their jobs essentially was like the laptop

48:35.620 --> 48:43.220
class right so lockdowns are lockdowns are luxury of the laptop class um and for the rest of the

48:43.220 --> 48:50.020
population it didn't work and so you could have populated places that have a larger fraction

48:50.020 --> 48:58.100
of the population that that isolate themselves for whom it works even as the disease spreads in

48:58.100 --> 49:03.460
among among people who can't isolate themselves for economic reasons or other reasons um so you're

49:03.460 --> 49:08.660
gonna have heterogeneous spread and just looking at the average spread is not the key thing um

49:08.660 --> 49:13.860
germany was like pretty i mean germany was really interesting right that like they they had they

49:13.860 --> 49:18.660
they basically declared victory over the virus before before like to spread everywhere uh

49:18.660 --> 49:25.460
china did the same thing country after country uh so it's possible then that lockdowns temporarily

49:26.500 --> 49:30.180
protected certain groups of certain classes of the population

49:31.620 --> 49:38.100
um you know you know another great example for this is like peru i don't know if you ever

49:38.100 --> 49:44.820
looked at the peruvian data j um the per in peru they had like they had one of the worst lockdowns

49:44.820 --> 49:48.980
in the world like the most raponium and of course there's vast numbers of poor people in peru

49:49.860 --> 49:57.860
and there was huge numbers of deaths during the lockdown um the at one point in the pandemic

49:57.860 --> 50:04.340
per the peruvian authorities reclassified all of those deaths as covid deaths when they were like

50:04.340 --> 50:09.860
you know people starving um people like and so and the disease i mean of course disease

50:09.860 --> 50:14.020
probably also spread to those folks too um despite the lockdowns i think that

50:14.020 --> 50:19.060
it's such a complicated thing like if you have unequal societies you're going to have different

50:19.060 --> 50:24.740
impacts of lockdowns on different parts of those those societies um a lot of those disease spread

50:24.740 --> 50:31.860
models are pretty bad and though it's going as associated with socioeconomic realities um

50:31.860 --> 50:38.420
and so yeah i think there's a lot to learn um i guess i'm not ready to like uh discard the disease

50:38.420 --> 50:42.820
spread hypothesis based on it's still quite possible that's that's part of the story

50:43.780 --> 50:48.820
yeah in fact it's like i mean i say it go further i say it's likely that's a part of the story

50:48.820 --> 50:56.580
but the panic is really a major part of it as well yeah i think um the the three-year

50:57.380 --> 51:04.420
odyssey that i've been on has led me to conclude that that there might have been

51:05.220 --> 51:12.100
let's say for example you had this plan and you knew that when you executed the plan that

51:12.100 --> 51:18.500
trillions of dollars would shift and power would shift um and so the question is would

51:18.500 --> 51:25.220
a national security state leave that up to chance or would they kind of tip the scales to be ready

51:25.220 --> 51:32.260
and and and control that thing and so for me that's what that's how it adds up if we go back to this

51:32.660 --> 51:37.780
atrogenic harm uh comments that you were making earlier about the ventilators actually being a

51:37.780 --> 51:44.180
bad idea do you find it spooky then how it was such a illusion of consensus about the fact that

51:44.180 --> 51:49.540
we would run out of ventilators the elon musk had to shift his production to ventilators because

51:49.540 --> 51:55.300
this was thought to be the cure it's almost impossible for that to have been organic um

51:57.140 --> 52:01.860
i think i uh so like the ventilators are really curious thing right so first of all i remember

52:01.860 --> 52:07.300
seeing the earlier reports out of china like case reports out of china from early january 2020

52:08.100 --> 52:14.980
suggesting ventilators as a way to and and uh it was almost like it wasn't just for the patient

52:14.980 --> 52:21.780
it was for the doctors like the idea was that if you put a patient on a ventilator uh it was not

52:22.660 --> 52:28.980
yeah yeah like you reduce the risk to the to doctors and so um you could very easily

52:28.980 --> 52:32.740
imagine an organic phenomenon wouldn't have to be a plan it would just be

52:33.460 --> 52:38.100
doctors don't want to expose themselves to risk they have this technology that think would help

52:38.100 --> 52:44.900
patients and help them and they just adopt it and the WHO basically endorses it um and so it's like

52:44.900 --> 52:50.260
it just spread like i i guess my model uh is a little different than yours in that sense like i

52:50.260 --> 52:57.060
think a lot of the a lot of the the like just take the the pharmaceutical companies making

52:57.060 --> 53:02.420
gadsillions of dollars a lot of it is a lot of this opportunistic like once you start to see

53:03.060 --> 53:09.620
the panic happening you have got you have like uh media organizations that all of a sudden are

53:09.620 --> 53:15.300
seeing up increases in in their huge increases in the interest in their publications and their money

53:16.020 --> 53:20.260
and so they they want to keep augmenting the panic because that's that's what their bottom line is

53:20.740 --> 53:27.540
that they as soon as the governments some governments see that they can take control over over like

53:27.540 --> 53:32.740
you you know impose things that they've never otherwise would be able to do uh run run uh early

53:32.740 --> 53:40.180
elections like in in um in like what happened in uh for instance in uh in Canada so uh work

53:40.180 --> 53:49.860
or uh to to like establish that uh a long-term uh you know long-term staying power in the you

53:49.860 --> 53:55.380
know like i remember after 9-11 there was huge huge support for the for the bush administration

53:55.940 --> 53:59.940
like unprecedented levels like it's kind of a rally around the flag thing and so like if

53:59.940 --> 54:05.460
governments of course uh you know it'd be almost malpractice political malpractice not to like take

54:05.460 --> 54:10.980
advantage of it i think a lot my model for a lot of this jay is that um you once you've caused

54:10.980 --> 54:16.340
panic in the population at large once that has happened for through whatever process uh we can

54:16.340 --> 54:22.740
talk about that i do think that there was some deliberate uh desire to spread panic uh uh but

54:22.740 --> 54:29.300
once that started once that it's it's it creates all kinds of opportunities for act for various

54:29.300 --> 54:33.860
actors many of whom thinking that they're doing good but they're actually ended up doing harm

54:33.860 --> 54:40.660
to try to take advantage that is definitely close to how i have interpreted this and now it's just

54:41.700 --> 54:48.260
in in pessimism or an optimism looking at it as uh how much of it was nefarious and i i definitely

54:48.260 --> 54:57.940
agree that that there is this uh potential for it i just am frightened because um i i was so moved

54:58.020 --> 55:04.180
by this uh there was a chatham house talk in 2011 that was given by the by a guy by the name of

55:04.180 --> 55:12.340
mark von ronst um he's a a belgian guy who oversaw the flu in uh 2009 the flu epidemic the swine flu

55:12.340 --> 55:19.700
epidemic and in that presentation he i don't know the exact quote but he he is lamenting

55:20.500 --> 55:26.340
that in 2009 they didn't have the capability that they do now with twitter and facebook and with

55:26.900 --> 55:32.900
with media messaging um they could have never achieved um what they really needed to achieve

55:32.900 --> 55:37.140
back then but he knows how they could do it now and that was with with you know he could see

55:37.140 --> 55:41.700
that facebook and these things would be really useful and one of the things that he's saying in

55:41.700 --> 55:52.340
that in that talk is that they publicized seven people dying of the flu and then extrapolated

55:52.340 --> 55:58.980
what the uk had said and said that we can expect so many hundred people to die in belgian this

55:58.980 --> 56:06.020
month and it was the exact expectation of every year but they made it sound like because they

56:06.020 --> 56:13.380
accentuated this seven people had died of the new flu that somehow a new phenomenon was occurring

56:13.380 --> 56:18.980
and there are other videos where these flu virologists will lament that nobody takes the flu

56:18.980 --> 56:24.900
seriously anymore and so there's all this anecdotal evidence that their public health

56:26.020 --> 56:33.300
apparatus has been grasping at straws to try and get something to catch um and you know and it

56:34.260 --> 56:40.100
Ralph barracks original sort of plan with using coronaviruses was to use them as a vaccine platform

56:40.100 --> 56:45.460
because they're so innocuous so it's really strange if you go back to barracks originally

56:45.460 --> 56:51.620
they were trying to blame it all on him now but his overarching motivation for investigating

56:51.620 --> 56:56.340
coronaviruses was that was that they were innocuous and therefore could be a potential platform for

56:56.900 --> 57:01.300
genetic technologies and that kind of thing i don't know where i was going with that question

57:01.300 --> 57:07.380
uh so actually let me just to say i think i've seen that van rans video um i think i think he

57:07.380 --> 57:11.860
laments if i remember if it's the same video i'm remembering he's he's like lamenting that there

57:11.860 --> 57:17.460
there are people that might they like to contradict the public health uh fear mongering um that was

57:17.460 --> 57:23.380
the problem yes but we that that you know if you just needed better control um and you know in the

57:23.380 --> 57:30.420
uk there's this uh this group that advised the government called spy b spi b behavior or behavioral

57:31.300 --> 57:37.700
they they embrace this idea of nudges nudges in order to create panic that was like that was like

57:37.700 --> 57:42.740
that was essentially like uh seen as like a a responsible thing to do to cut to create panic

57:42.740 --> 57:49.700
in the population during this pandemic um and uh the control of information to the public at large

57:49.700 --> 57:59.060
was a central i uh central fix uh fixation of of of of of many public health authorities there are

57:59.700 --> 58:07.380
foyer documents from mark zuckerberg and uh to tatoni fauci from the earliest days of the pandemic

58:07.380 --> 58:14.340
about how to manage the the perception of the fear or perception of the risk in the public at large

58:15.300 --> 58:21.620
and uh you know frankly it it was it worked it worked like there are still people who think

58:21.620 --> 58:25.940
that the if you get covid the like i mean i mean i mean i mean this is i don't know maybe there's

58:26.100 --> 58:29.780
not still people i hope they're not still people but like they were up until 2022 there are people

58:29.780 --> 58:34.420
who thought that if you got covid there's one chance and two of of being hospitalized and one chance

58:34.420 --> 58:39.540
in you know three of dying or something when in fact the truth was orders of magnitude less than that

58:40.900 --> 58:46.820
um and so the the and the and the what the stories that they told themselves was that you needed

58:46.820 --> 58:54.020
people to be appropriately scared so a that they complied with the the orders of public health and

58:54.020 --> 58:58.820
be that so that they didn't they they acted in ways in their private lives that reduced the

58:58.820 --> 59:05.140
risk of spreading the disease to to to vulnerable people um what the problem with that is that like

59:05.140 --> 59:11.780
as soon as you unleash fear in the population like that it takes on a life of its own it it creates

59:12.340 --> 59:17.220
all kinds of harm um that have long standing i mean i think i don't for instance i don't think

59:17.220 --> 59:21.220
schools close in the united states for as long as they did if you don't have that fear and panic

59:21.220 --> 59:27.140
like who wants to harm their children by like not letting them have basic a basic childhood

59:27.780 --> 59:31.700
right no one no one really wants to do that it's only and when you're in the grips of fear that

59:31.700 --> 59:36.900
you're abnormal that's not it's it's only it's only that that can lead to to some of the crazy

59:36.900 --> 59:42.180
things we've seen um i think i think i don't think you don't think it's inverted that the fact that

59:42.180 --> 59:47.540
we couldn't lock down is what frightened everybody that that all these people took it so seriously i

59:47.620 --> 59:53.780
mean i wasn't afraid of being at home with my kids i hated it but i was and i lamented that

59:53.780 --> 01:00:00.260
they were not able to hang out but it never occurred to me that the way it did to my neighbors that

01:00:00.260 --> 01:00:05.140
wow it must be serious if they're closing the schools for the rest of the year oh my gosh

01:00:05.140 --> 01:00:10.260
they're not gonna they might not open schools in the fall can you believe how serious this is

01:00:10.260 --> 01:00:14.020
that's the question you ask if you're skillfully watching television at that time

01:00:14.980 --> 01:00:20.340
no you absolutely right jay i agree with that i think it's it's uh it's it's kind of a feedback loop

01:00:20.340 --> 01:00:25.460
right you lock down that causes fear and then that causes uh support for lock further lockdowns

01:00:25.460 --> 01:00:30.500
and other restrictions and so you just have this like this feedback loop that lit plate and i

01:00:30.500 --> 01:00:36.420
remember the first time i saw uh a uh a poll of how popular the lockdowns were i think it was like

01:00:36.420 --> 01:00:41.380
april or may 2020 and i was like 80 percent of the population was fully on board i was like i

01:00:41.380 --> 01:00:46.580
was shocked yep and i thought there would be widespread protests there were some protests but

01:00:46.580 --> 01:00:54.020
but those protests were seen as like a counter cultural act a heretical act um and uh they were

01:00:54.020 --> 01:00:59.620
like they were suppressed and uh you know like that was that so it was really funny actually to see

01:00:59.620 --> 01:01:07.700
the george floyd protests happen in uh early late spring early summer 2020 and the public health

01:01:07.700 --> 01:01:11.940
authorities sign a letter saying oh yeah we those that's that's good public health

01:01:13.380 --> 01:01:17.780
actually i kind of interpret that as young people needed some outlet to like

01:01:18.980 --> 01:01:23.940
express their frustration i mean i so i was like yeah fine like people people should people

01:01:23.940 --> 01:01:28.740
should be allowed to i think everyone should have been allowed to protest the the fear was used to

01:01:28.740 --> 01:01:33.380
control people it's going to have consequences they're really hard to like predict up front

01:01:34.100 --> 01:01:38.900
um it just it plays itself out in in in ways that are just uh damaging to people

01:01:39.460 --> 01:01:44.500
um and so i think i think i i agree with you that the lockdowns induce the fear but also the other

01:01:44.500 --> 01:01:50.340
direction um it's a good feedback loop i mean the masks also i mean that was a really outward

01:01:50.340 --> 01:01:54.100
selling yeah it's it looked that you're in a pandemic you're wearing you see everyone wearing

01:01:54.100 --> 01:01:59.700
like you know full body suits that you're it's like you're in a movie uh that was part of it and i

01:01:59.780 --> 01:02:04.420
think part of actually master really interesting in that sense because it it did induce fear

01:02:04.420 --> 01:02:09.700
like it reminded people to be scared but it was also like i think a lot of public health people

01:02:09.700 --> 01:02:15.220
thought of it as a way to like give uh uh give people a sense of control false sense of control

01:02:15.220 --> 01:02:21.060
over their disease risk right so we've caused this fear we want to manage it even though there's

01:02:21.060 --> 01:02:25.940
no good uh no good randomized evidence suggests masks could could do what we say or they do but

01:02:25.940 --> 01:02:31.300
let's tell people that so that uh so that it that that they feel like they have some autonomy

01:02:31.300 --> 01:02:38.260
over the risk they're taking wow it's just crazy what they've done to us i really what i lament

01:02:38.260 --> 01:02:45.540
the most is that they've they've specifically misled these college age kids who really had to

01:02:46.260 --> 01:02:53.780
conform in a way that no one else really in america had to conform um and and so i remember jay like

01:02:54.500 --> 01:03:00.740
there was a the close the air force academy to for uh for like they sent home the freshman

01:03:00.740 --> 01:03:06.500
sophomores and juniors uh and then they kept they kept the seniors in spring of 2020 and they kept

01:03:06.500 --> 01:03:10.900
the seniors and they put them in like solitary confinement they were not allowed to leave their

01:03:10.900 --> 01:03:14.820
dorm rooms they basically brought food to them they didn't have any human contact for months

01:03:15.380 --> 01:03:20.740
two kids killed themselves two air force cadets killed themselves in spring i remember seeing that

01:03:20.820 --> 01:03:26.420
going this is this is just cruel it's inhumane um and these are kids that are very very low risk

01:03:26.420 --> 01:03:31.300
of getting hurt if they get covid and actually even just the clothing of colleges like if you

01:03:31.300 --> 01:03:38.580
know this disease is risky for old people why would you send young people back home to create

01:03:38.580 --> 01:03:43.700
multi-generational homes that didn't need to exist for for for several months why not keep them at

01:03:43.700 --> 01:03:52.500
college um you know i just i it was it was um i mean i i tend to be the kind of person that

01:03:52.500 --> 01:03:58.980
that like will attribute that to like just intellectual errors um and maybe that's what it was but

01:03:58.980 --> 01:04:03.460
i think a lot of those intellectual errors come out of panic right the idea that young people are

01:04:03.460 --> 01:04:08.420
somehow like the the the vector of the disease vector of disease other human beings are simply

01:04:08.420 --> 01:04:13.460
just bio hazards to be avoided um i mean i'm sure this happened to you like you walked down

01:04:13.460 --> 01:04:19.140
the street and if you're not wearing a mask uh the a masked person will jump out into the

01:04:19.140 --> 01:04:24.820
off the sidewalk to get away from you uh i mean that happened how do you how do you get to that

01:04:24.820 --> 01:04:29.380
point well you get to that point because public health authorities and and uh governments are

01:04:29.380 --> 01:04:36.100
telling people to treat people like bio hazards yeah the the the only people that are wearing masks

01:04:36.100 --> 01:04:42.180
in the Pittsburgh area now are between the ages of like 18 and 23 and they'll wear it all day long

01:04:42.260 --> 01:04:46.740
at work um you have to sometimes depending on the hospital you go to they have a sign that says

01:04:46.740 --> 01:04:52.420
please wear a mask but not everybody's wearing one um but it they're still very much sustaining

01:04:52.420 --> 01:04:57.860
this idea that that something about mother nature has changed drastically in the last three years

01:04:57.860 --> 01:05:04.420
and uh it's a permanent change and it's terrifying because we're really if if the adults don't wake

01:05:04.420 --> 01:05:10.340
up soon then the the kids will be permanently brainwashed like this i think it's i mean i think

01:05:10.660 --> 01:05:15.140
those like masks are seen as like we're we're sold as if they were a costless or harmless

01:05:15.140 --> 01:05:19.060
intervention um you know like there are these there's this psychological syndrome like people

01:05:19.060 --> 01:05:25.460
were the kids young people wear the mask in order to hide because of their insecurities um that the

01:05:26.500 --> 01:05:31.060
the masks if they don't work or like the cloth masks certainly don't do anything you tell people

01:05:31.060 --> 01:05:35.540
to wear it yeah older people will wear cloth masks go into situations that they probably should

01:05:35.540 --> 01:05:41.220
have stayed away from or during times of high disease spread and take risks that they wouldn't

01:05:41.220 --> 01:05:46.500
otherwise have taken except for the fact they were wearing a mask um and and you know like i got i

01:05:46.500 --> 01:05:50.420
got all these heartbreaking emails through the whole pandemic from people but probably among the

01:05:50.420 --> 01:05:55.060
most heartbreaking we're we're like parents of autistic kids telling me what what the masking was

01:05:55.060 --> 01:06:00.980
doing to their to their to their kids or hearing impaired kids uh your parents of hearing impaired

01:06:00.980 --> 01:06:05.860
kids um i just it's the idea that like you could have any intervention with with no good

01:06:05.860 --> 01:06:11.140
evidence behind it and assume that it's going to have no harm at all because these are medical

01:06:11.140 --> 01:06:15.300
interventions you have to treat them seriously like you have to have great evidence before you

01:06:15.300 --> 01:06:20.980
recommend them at scale um and it's just for public health is to act the way it did in the absence

01:06:20.980 --> 01:06:26.980
of evidence um it was such it i mean i have to say what i was uh we keep talking about the illusion

01:06:27.060 --> 01:06:32.260
consensus it was such an inversion for me from my expectations after 20 years of working in

01:06:32.820 --> 01:06:38.980
in academics and public health um to see how people behave they they behave so irresponsibly

01:06:39.700 --> 01:06:44.980
like that that like fear mongering i thought was like anathema in public health like we we were

01:06:44.980 --> 01:06:51.380
supposed to uh exclude calmness like to talk to calm pop people down not to treat fear mongering

01:06:51.380 --> 01:07:01.300
as if it were a virtue right yeah i i i can speak much to that um i had uh i had a lot of uh

01:07:03.060 --> 01:07:09.620
a lot of run-ins with people trying to calmly objectively in private messaging just say well

01:07:09.620 --> 01:07:16.180
maybe you can temper this this position a little bit um and and people were willing to go the full

01:07:16.260 --> 01:07:20.100
distance of saying that you know if you're not going to follow the rules then you shouldn't be

01:07:20.100 --> 01:07:25.060
in society which is uh that's a pretty extraordinary stance to take

01:07:27.460 --> 01:07:32.180
yeah well i mean as in academic i said i was like i was let me just talk to about scott atlas because

01:07:33.140 --> 01:07:37.700
since since the theme is like less like sort of what sort of the mechanisms of control and

01:07:37.700 --> 01:07:44.900
in the illusions consensus uh like my colleague scott atlas he uh for 20 for for decades he was

01:07:44.900 --> 01:07:51.060
the head of neuro radiology at stanford a very accomplished doctor wrote uh wrote a textbook

01:07:51.860 --> 01:07:57.300
and for the last decade or so he's been advising um you know republican president presidential

01:07:57.300 --> 01:08:04.420
candidate and other politicians about public health and so it wasn't a surprise when um when

01:08:04.420 --> 01:08:10.100
president trump asked him to be to be his advisor he and i had been talking uh throughout the pandemic

01:08:10.100 --> 01:08:14.020
talking about paper legal it's like an accident in many ways i'm sure you felt this a pretty exciting

01:08:14.020 --> 01:08:19.380
time to be a scientist like how many times you get to learn about new brand new things where

01:08:19.380 --> 01:08:25.780
everyone's learning together i mean that's a real interesting thing right um and uh uh he's

01:08:25.780 --> 01:08:31.540
said he's come to the view that i i'd come to which is you know we should not be uh we should not be

01:08:31.540 --> 01:08:36.820
like panic mongering we should not be harming the lives of children we should not be locking down

01:08:36.820 --> 01:08:40.100
we should be better protecting vulnerable older people that's that's the view he's

01:08:40.180 --> 01:08:47.700
talking in the he's like uh he's on fox uh trump finds him my colleagues at stanford uh viewed that

01:08:47.700 --> 01:08:57.140
as a betrayal uh there was a letter written by uh the former dean of the medical school at stanford

01:08:57.140 --> 01:09:03.620
phil piezo man and phil piezo who then spread that uh sent that letter all around stanford

01:09:04.260 --> 01:09:10.900
uh young people junior professors without tenure several of them told me that they felt

01:09:11.460 --> 01:09:14.660
essentially social pressure to sign it because if what if they don't sign it

01:09:14.660 --> 01:09:17.220
well are they going to get tenured will that be held against them who knows

01:09:18.420 --> 01:09:26.020
right you and it essentially accused scott of of pseudoscience for the crime of not fully

01:09:26.020 --> 01:09:33.300
embracing the mask religion right uh he actually accused him weirdly of like i mean it implied that

01:09:33.300 --> 01:09:38.740
he wasn't in favor of hand washing i mean i defy you to show me anywhere where he said it

01:09:38.740 --> 01:09:43.300
wasn't favor hand washing and then the faculty sent it at stanford they voted i mean i don't know

01:09:43.300 --> 01:09:49.540
what to call it other than an excommunication right it was like expel the heretic from the flock

01:09:50.260 --> 01:09:54.580
right it was a it was a it was a it was a it was a and it was a mechanism of social control

01:09:55.140 --> 01:10:01.860
of of a of a qualified scientist who didn't agree with with what they were saying rather than have

01:10:01.860 --> 01:10:06.260
a debate or discussion at a place like stanford with that's our obligation right that's

01:10:06.260 --> 01:10:10.900
that's what it means to be a university is to allow those debates and discussions to happen

01:10:10.900 --> 01:10:15.780
platform them uh and keep away from the ad homin and they said they they excommunicated him

01:10:16.420 --> 01:10:20.900
um i i i think that that happened to so i mean people who signed the great bank directors they're

01:10:20.900 --> 01:10:26.340
people who told me that they lost their jobs because they signed it i mean i don't know i

01:10:26.340 --> 01:10:30.740
frankly for a while i felt so bad i mean because i felt like i couldn't protect anybody i mean i

01:10:30.740 --> 01:10:36.820
felt helpless i i don't know but i i don't know i i i don't know what else to do like it you have

01:10:36.820 --> 01:10:42.500
to our job is to say what we see as scientists we now always be right and we may disagree but we

01:10:42.500 --> 01:10:47.700
just to have productive conversations with each other and hopefully learn from each other uh and

01:10:47.700 --> 01:10:52.340
sometimes it's you know brass knuckles but it's not it's not brass knuckles at the people it's brass

01:10:52.340 --> 01:10:57.860
knuckles at the ideas um that's what science is supposed to be it it was a complete inversion of that

01:10:58.580 --> 01:11:04.340
that's a really nice way of explaining it the it's brass knuckles with the ideas and that that's

01:11:04.340 --> 01:11:12.180
really really important um do you think that the pandemic has made this phenomenon of group think

01:11:12.180 --> 01:11:21.380
worse or better for us if they driven us more to our corners or i guess i i guess i'm kind of

01:11:21.460 --> 01:11:28.980
an optimist uh in that in that sense i think um it's exposed the group the propensity to group

01:11:28.980 --> 01:11:34.980
think that was already there inside science i didn't see it before the pandemic i have to be

01:11:34.980 --> 01:11:40.100
honest i did not see it before the pandemic i didn't i felt it to sound a little bit i mean in very

01:11:40.100 --> 01:11:44.980
serious like oh yo i i don't want to work on that because i don't want to you know step on people's

01:11:44.980 --> 01:11:51.940
toes or whatever i but i didn't think it was like at the heart of of of biomedical sciences

01:11:52.740 --> 01:11:58.260
and i think a lot of people now in the biomedical sciences have started to see that it's there

01:11:59.060 --> 01:12:06.660
and now only question is how can we structure the the institutions of biomedical sciences

01:12:06.660 --> 01:12:14.340
so that uh people will will feel free to to speak people will i think most scientists now

01:12:14.340 --> 01:12:20.260
understand that that's not there and most scientists want that and so we have an opportunity for reform

01:12:21.620 --> 01:12:27.140
like a unprecedented once in a generation opportunity reform if we can just figure out how to get the

01:12:27.140 --> 01:12:32.180
the the sort of the right levers in place to do that um that's what i've been focused on try to

01:12:32.180 --> 01:12:37.700
work on uh like i think the key thing for me my role has been to try to uh come up with reforms

01:12:37.700 --> 01:12:42.420
that are very broad number of scientists and and other the populace that large can agree on

01:12:42.420 --> 01:12:47.460
would be would be and try to build a coalition around that because it's you know science we think

01:12:47.460 --> 01:12:52.820
of is like this like thing that's separate from the society it's not it's part of society as

01:12:52.820 --> 01:12:59.780
everyone now knows that every like it's science itself that has been part of the uh the very fabric

01:12:59.780 --> 01:13:04.020
of how we run our society the last three and a half years right and everyone sees that it's power

01:13:04.020 --> 01:13:09.540
and that means now everyone has an interest in reforming it so that it it can function the way

01:13:09.540 --> 01:13:13.460
it's supposed to function not the way it did as a as a tool for authoritarian power

01:13:15.140 --> 01:13:23.300
um what about just the the legal aspect of the pandemic we talked you talked a little bit about

01:13:23.300 --> 01:13:29.380
these people making all kinds of money um some lawyers would argue i think a lot of lawyers would

01:13:29.380 --> 01:13:34.420
argue that the only reason why that money can be made is because there's no strict liability for

01:13:34.420 --> 01:13:41.700
many of these classes of pharmaceutical products and be that as it may that's compounded by

01:13:41.700 --> 01:13:47.940
this ability for them to declare an emergency and then basically apparently a lot of these people

01:13:47.940 --> 01:13:55.700
are more or less acting with without consequence um so it's hard to ask these people to reflect on

01:13:55.700 --> 01:14:00.340
what they did and then change their behavior where as it almost demands that we have to

01:14:01.060 --> 01:14:04.900
take these people out of the driver's seats that they're sitting in and put other people

01:14:04.900 --> 01:14:12.100
there i mean how do we solve this problem i mean the the power of pharma um on our social

01:14:12.100 --> 01:14:17.540
structures is almost unimaginably great and i think the united states in particular

01:14:18.580 --> 01:14:24.340
where you have direct consumer advertising there's that's legal and possible um what that means is

01:14:24.340 --> 01:14:30.580
that pharma controls the uh the purse strings of our media companies the largest media companies

01:14:31.220 --> 01:14:37.220
they have as you said pharma they have a liability shield for especially for vaccines

01:14:37.780 --> 01:14:43.700
um that was put in place with the argument for it being put in place was you don't want frivolous

01:14:43.700 --> 01:14:48.980
suits against the pharmaceutical companies that then send a signal to people that did not be vaccinated

01:14:49.060 --> 01:14:54.180
but the the flip side of that is a is a is a commitment to responsible behavior by pharma

01:14:54.180 --> 01:15:01.380
which we didn't have during the pandemic and so so you have like essentially like social

01:15:01.380 --> 01:15:06.500
contracts have been broken all over the place regarding these things and that's why i think

01:15:06.500 --> 01:15:11.780
it is a moment for reform you talk about legal action actually i've been one one major legal

01:15:11.780 --> 01:15:16.980
action i've been involved with is this Missouri versus Biden case which is the case aimed at the

01:15:16.980 --> 01:15:20.980
Biden administration's uh why call up the ministry of truth there their censorship

01:15:20.980 --> 01:15:26.980
industrial complex that case which is now sitting in front of the Supreme Court uh it's revealed

01:15:26.980 --> 01:15:34.100
essentially a vast enterprise by federal government bureaucrats that will go to social media companies

01:15:34.100 --> 01:15:41.860
and why i say bureaucrats i mean like fbi uh the the the cdc the assertion general's office

01:15:42.260 --> 01:15:46.900
uh the nih will go to the social and the white house itself will go to social media companies

01:15:46.900 --> 01:15:51.540
and say here are the people i want censored here are the people here are the ideas i want censored

01:15:51.540 --> 01:15:55.540
this is probably why you're on twitch i mean if you probably i'm sure i think i saw you on youtube

01:15:55.540 --> 01:16:00.260
once upon a time it was probably impossible you're on youtube yeah yeah probably a part of list you

01:16:00.260 --> 01:16:05.780
can't you can't do you can't do this on youtube at least maybe not not definitely not back then i

01:16:05.780 --> 01:16:11.460
had to move yeah i mean i think you were you were on the i know i was on the list i was put on twitter

01:16:11.460 --> 01:16:17.140
blacklist the day i joined twitter that is not consistent with the american first amendment

01:16:17.700 --> 01:16:23.700
like that is a and it's an even more important is a violation of the of our basic civil civil civil

01:16:23.700 --> 01:16:30.900
rights uh and for science it is anathema you cannot have science without free discussion of ideas

01:16:30.900 --> 01:16:36.100
we're going to have ideas that we disagree with happen in science it's just part and sometimes

01:16:36.100 --> 01:16:41.220
those ideas will be uh will be misattributed by others the way that you deal with that is by

01:16:41.220 --> 01:16:47.540
free speech um so i so i think legal action is very very important uh if you'd ask me before

01:16:47.540 --> 01:16:51.380
the pandemic whether legal action and political action was important for science i said well

01:16:51.380 --> 01:16:56.660
those are important maybe but they're secondary now i think um they're actually many they're pretty

01:16:56.660 --> 01:17:01.620
much at the center like if you really want to reform things you're going to need political action

01:17:01.620 --> 01:17:07.540
for reform we're going to need legal action to constrain the the excesses of yes pharmaceutical

01:17:07.540 --> 01:17:12.500
companies but also governments uh and and and other entities that have been that have uh

01:17:12.500 --> 01:17:19.620
i mean i i just take one um that i just i still can't wrap my mind around um universities mandated

01:17:19.620 --> 01:17:26.020
vaccines for young people at scale even after credible evidence came out that young men especially

01:17:26.020 --> 01:17:32.100
had faced i call unacceptably high rates of myocarditis from the vaccine and yet they mandated it in

01:17:32.180 --> 01:17:38.340
order to go to school uh the the idea that there's no liability shield that applies to

01:17:38.340 --> 01:17:45.140
pharmaceutical companies doesn't apply to universities um and many of them did it without uh you know

01:17:45.140 --> 01:17:50.660
they they weren't mandated to mandate it they just did it um i think that there's going to be legal

01:17:50.660 --> 01:17:58.500
action at scale wow that's exciting in a way i mean it's dark but um i think there's a lot of

01:17:58.580 --> 01:18:03.620
peripheral malfeasance that went on in universities that could also catch into this like the

01:18:03.620 --> 01:18:09.220
selling of the remnants of tests and this kind of thing um if this kind of of suit were to catch

01:18:09.220 --> 01:18:17.140
momentum it would also be a really wonderful opening for us to readdress this age group because i

01:18:17.140 --> 01:18:22.020
do think that there's a purposefully they're purposefully disconnected from us i don't want

01:18:22.020 --> 01:18:28.340
to make any parallels to to too many other historical times when these these things happened but

01:18:28.340 --> 01:18:35.780
it does feel as though these college kids were really challenged um to stand up for themselves

01:18:35.780 --> 01:18:40.900
and they were really beat down pretty hard um by these universities in a coercive manner i mean

01:18:40.900 --> 01:18:48.900
in a coordinated manner um i mean i i i i i i have a like uh i i my views we basically robbed the

01:18:48.900 --> 01:18:53.620
young younger generation it with with the idea that we're going to protect older older generation

01:18:53.700 --> 01:18:58.340
middle-aged people so it's a generational theft and i don't think that the young people are going

01:18:58.340 --> 01:19:02.660
to treat us very kindly in there in how they think about us and you know we just we deserve it

01:19:04.180 --> 01:19:10.420
yeah it's uh well if we can we still have time to write the ship i feel like um

01:19:11.380 --> 01:19:18.420
i still feel like we have time to uh to i mean but people are all going to have to take their

01:19:18.500 --> 01:19:23.700
responsibility for what they did and how long it took them to to realize that we were being

01:19:23.700 --> 01:19:31.220
herded and rushed and uh and coerced i mean i i i i i i i i i i'm like i'm by nature optimistic

01:19:31.220 --> 01:19:34.820
day but i have to say like i've been watching the uk covid inquiry i don't know if you've been watching

01:19:34.820 --> 01:19:41.940
it at all not directly no it's a whitewash it's a whitewash and you have like these people who who

01:19:41.940 --> 01:19:46.980
basically were the architects of the lockdowns giving themselves awards you know tony thought

01:19:46.980 --> 01:19:52.020
she's a professor at georgetown now you've got uh you have all these like people who were who were

01:19:53.060 --> 01:19:59.940
basically created a an unprecedented uh authoritarian approach to the pandemic

01:20:00.980 --> 01:20:06.660
and uh caused harm at such scale and they're they're essentially trying to pretend like like the

01:20:06.660 --> 01:20:13.060
the the basic idea of the of the basic economic premise of the uk uh covid inquiry that's far seems

01:20:13.060 --> 01:20:17.860
to be that well we just didn't lock if we'd only locked down harder and earlier it all would have

01:20:17.860 --> 01:20:27.460
been fine see china did it in january 2020 we could have done it um that i think is rapidly becoming

01:20:27.460 --> 01:20:34.980
the the the the standard playbook for managing pandemics and so that means that the next time

01:20:34.980 --> 01:20:40.340
anything like this happens we will do this again and we will lock down the by demonstration has a

01:20:40.340 --> 01:20:46.980
plan in place that says in the next pandemic we will have a vaccine it available at scale within

01:20:46.980 --> 01:20:54.740
130 days how do you test a vaccine for long-term consequences within 130 days and they've already

01:20:54.740 --> 01:20:59.860
done it right they've already tested it in five billion people so all all future vaccines using

01:20:59.860 --> 01:21:06.340
mr and a are safe by their rationale i mean i just saw uh al experience and highlighted this uh a

01:21:06.420 --> 01:21:13.140
report that there was a uh what was the vaccine the mr and a platform vaccine for ebv

01:21:13.140 --> 01:21:19.380
Epstein bar virus that caused myocarditis in this in a in a in an early trial in a young man

01:21:20.580 --> 01:21:28.420
um and they stopped the trial this is Moderna I think um i think the the so i think that the

01:21:28.420 --> 01:21:35.860
idea that we the plan is for future pandemics we uh we have a rapid vaccine the consequence of

01:21:35.860 --> 01:21:41.460
that then is is like just if you take it back one step is what will we do for those 130 days

01:21:41.460 --> 01:21:46.980
while we're waiting for the test of the vaccine lock down of course we'll lock down essentially

01:21:46.980 --> 01:21:52.100
that's the plan that is the current template so i think we need a political movement we need a

01:21:52.100 --> 01:21:57.220
legal movement to undo that and of course this is what the world health organization is creating

01:21:57.300 --> 01:22:05.380
this like uh this this new uh new new uh pandemic treaty it's an opportunity actually in early in

01:22:05.380 --> 01:22:11.620
2024 to put put that front and center in the in the presidential debate do we want that if the

01:22:11.620 --> 01:22:16.180
united states has no to it it'll have it'll send a powerful signal around the world do we want that

01:22:16.180 --> 01:22:22.260
let's make that into a political issue interesting i'm gonna shift back to data for a second but i'm

01:22:22.340 --> 01:22:26.980
not gonna i just drew some data and i want to ask you a question um because i've been trying

01:22:26.980 --> 01:22:32.500
to figure this out and whether it means anything or not but maybe you can help me um so if i

01:22:32.500 --> 01:22:37.700
reverse this over here and put myself down here this is my really bad drawing can you see that

01:22:37.700 --> 01:22:45.940
of an age pyramid so um doesn't look like that anymore about nowadays on the on the the x axis

01:22:45.940 --> 01:22:51.540
going up is age and then this is males and females and so you hear you see a population where there's

01:22:51.540 --> 01:22:56.820
fewer old people than there are babies and it kind of goes up with a uh a more or less

01:22:56.820 --> 01:23:04.980
pyramidal distribution what role do you think if any a distribution different than that whatever it

01:23:04.980 --> 01:23:12.260
would be but with a top heavy distribution could have been seen coming and used as part of the way

01:23:12.260 --> 01:23:17.780
to create the panic that would you know exaggerate any exercise like this do you do you see that as

01:23:17.780 --> 01:23:22.180
a possibility i've never seen anybody really look into this and because that could really

01:23:22.180 --> 01:23:29.220
explain an age vulnerability or it could explain a vulnerability to protocols or or or any number

01:23:29.220 --> 01:23:35.540
of things this could be used against us that couldn't necessarily wouldn't be present in a

01:23:35.540 --> 01:23:40.500
country like Peru or a country like or maybe it is in Peru i don't know they're off the top of my

01:23:40.500 --> 01:23:44.660
head what they look like but uh i think you understand the question i'm asking everyone about

01:23:44.660 --> 01:23:49.860
so that's a really great question uh i i don't think i've heard anyone no one's asked me

01:23:49.860 --> 01:23:55.220
this in that way and so it's it's a really interesting question so like i think so first of all um that

01:23:55.220 --> 01:24:00.900
pen that pyramid you had on the left the age pyramid you had on the left that is the traditional

01:24:00.900 --> 01:24:07.140
age pyramid that we had through much of the 20th century yeah right right exactly um it's

01:24:08.020 --> 01:24:13.860
it's not a surprise that we didn't lock down for century respiratory virus pandemics given that

01:24:13.940 --> 01:24:20.660
age pyramid right we essentially like during in 1968 there was a massive flu pandemic in the

01:24:20.660 --> 01:24:31.300
united states and we had we had a woodstock happen during it right uh 1968 1957 1976 even

01:24:31.300 --> 01:24:40.900
2009 we uh the idea was develop uh uh treatments try to repurpose drugs that they're they're already

01:24:41.220 --> 01:24:44.820
they're focus protection on the most vulnerable people which were that little tiny group at the

01:24:44.820 --> 01:24:49.540
top um and and for the rest of the population don't you know the idea of a lockdown would be

01:24:49.540 --> 01:24:54.660
unthinkable um of course also the other thing that played in that is like like zoom and this

01:24:54.660 --> 01:25:00.260
kind of technology actually allowed uh a certain class of people to think that they could escape

01:25:00.820 --> 01:25:06.580
the harms of the lockdown so now let's go to the pyramid on the right uh it doesn't quite look

01:25:06.580 --> 01:25:10.980
like that but like in the united states but it looks a little bit like that um uh where

01:25:10.980 --> 01:25:17.380
where it's top heavy you have a large a group of people uh in the older population um and uh

01:25:17.380 --> 01:25:23.460
actually a much smaller younger population the the political power of that population is enormous

01:25:23.460 --> 01:25:28.980
the the orientation of public health toward that that that that that group up at top is it is

01:25:28.980 --> 01:25:34.820
enormous um it's then i guess that particularly surprising that you would see public health make

01:25:34.820 --> 01:25:40.580
decisions with aiming at trying to protect that population at the expense of the population

01:25:41.380 --> 01:25:47.780
because it's small this is just smaller and less powerful um i i do think that it's i mean the

01:25:47.780 --> 01:25:53.380
irony is that it ended up they ended up harming old people too like that like there's data that

01:25:53.380 --> 01:25:59.620
came out uh in 2020 suggesting that there was a like a huge increase in deaths from dementia

01:25:59.700 --> 01:26:04.580
because you isolate old people you cause all kinds of harm to them i think the irony is like

01:26:04.580 --> 01:26:12.180
by by by trying to protect older people via a lockdown via these draconian measures you ended

01:26:12.180 --> 01:26:19.620
up harming them and also alienating and harming the the that uh huge numbers of young people um

01:26:19.620 --> 01:26:24.500
that population pyramid that you're absolutely right i i hadn't like uh i hadn't thought about

01:26:24.500 --> 01:26:29.060
bringing that together but i think that played a big big role in especially when you connect

01:26:29.060 --> 01:26:35.860
it with political power or the various generations um big role in in the the strategies that we

01:26:35.860 --> 01:26:40.980
follow the and the policies that we follow during during during during covid and potentially the

01:26:40.980 --> 01:26:47.700
the the outcome right if we if we could see that pyramid accurately and could expect a

01:26:48.660 --> 01:26:53.860
a two or three year brief increase in all cause mortality because these old people are getting

01:26:53.860 --> 01:27:01.940
past expected age of death then that could have been empowering or or how's what's the right

01:27:01.940 --> 01:27:08.900
word it could have facilitated this in in terms of their ability to exaggerate it as much as possible

01:27:09.540 --> 01:27:13.540
um i want to try and formulate this right but is there any

01:27:16.100 --> 01:27:22.420
combination of data and testimony or or a specific data set that you would need

01:27:23.300 --> 01:27:30.420
to see where you would start to consider the possibility that that that there was no more

01:27:30.420 --> 01:27:37.300
significant spread in 2020 than there was back in 2002 where 10,000 people were supposedly

01:27:37.300 --> 01:27:44.260
infected and 700 people died and so if we had the data to show that actually just by scaring

01:27:44.260 --> 01:27:51.140
everybody which we've already acknowledged has a huge effect um and also adding that up right

01:27:51.140 --> 01:27:58.660
because you in my mind uh one has to factor in not just that we were misled about ventilators

01:27:58.660 --> 01:28:04.500
and not just that they went crazy on our on our constitutional rights but that that all occurred

01:28:05.060 --> 01:28:09.700
at the same they decided that all of these things were a good idea at the same time including the

01:28:09.700 --> 01:28:17.460
line and so the question becomes then at what point are we obligated to take their word or

01:28:18.180 --> 01:28:26.100
or how do we verify that and in a real bona fide pandemic occurred as opposed to

01:28:26.740 --> 01:28:31.220
a flash in the pan that they knew already would only be a flash in the pan or a

01:28:32.180 --> 01:28:36.340
a background signal that they knew they could take advantage of maybe even they put it there

01:28:36.340 --> 01:28:42.740
i mean that's obviously crazy but it in light of what we know about how we're governed on all

01:28:42.820 --> 01:28:50.420
other aspects of our reality how often they will lie about political things uh and and funding for

01:28:51.380 --> 01:28:59.380
for highways and and and whatever else um it just seems to me very difficult to dismiss the

01:28:59.380 --> 01:29:06.900
possibility that as i said before that that we are not doing an accurate accounting and if we did

01:29:06.980 --> 01:29:10.980
an accurate accounting especially from the epidemiological perspective we might find

01:29:11.700 --> 01:29:17.780
that none of these models will fit if you had the real data i mean i question for example we go

01:29:17.780 --> 01:29:24.020
back to that that the model you know as you extend the variables and change it to fit things um

01:29:25.220 --> 01:29:32.420
one has to do that in every separate geography then in order to fit an sir model to every outbreak

01:29:32.420 --> 01:29:38.820
that occurred so you can do that in an isolated place but if you take into account all the timing

01:29:38.820 --> 01:29:45.540
of those isolated fits then there's no spread between them and there's no additive effect

01:29:45.540 --> 01:29:50.100
and there there are none of these things that would be expected from again what is supposed to

01:29:50.100 --> 01:29:55.860
be a relatively uniform pathogen that started at a point and those are the kinds of things that

01:29:56.420 --> 01:30:02.020
it seems to me aren't accurately reflected on anymore with the idea of just saying well it happened

01:30:02.500 --> 01:30:10.340
obviously it happened and obviously something happened but i wonder if we're we're giving them

01:30:10.340 --> 01:30:18.340
too much benefit of the doubt with regard to did they get it right or not i mean i i guess so a

01:30:18.340 --> 01:30:22.340
couple there's a few elements of that so like first uh the scientific element right so you're

01:30:22.340 --> 01:30:30.500
asking um if i if i if i can rephrase it a little bit if you're asking what would uh lead to a

01:30:30.580 --> 01:30:37.700
rejection of uh an sir kind of framework what data set would one need to reject an sir

01:30:37.700 --> 01:30:42.180
kind of framework i mean i do think that's possible i don't think i don't think that the sir model

01:30:42.180 --> 01:30:51.540
has zero empirical content like you can you can see uh phenomena like you know just take take

01:30:51.540 --> 01:30:57.460
the spread of uh take take uh the rise of obesity in a population right it's really hard to fit that

01:30:57.460 --> 01:31:05.940
in sir framework it just doesn't like the the model it doesn't look like a infectious idea

01:31:07.940 --> 01:31:12.660
so it's not that that sir framework is devoid of empirical content it's it's but it is a very

01:31:12.660 --> 01:31:21.060
broad model so that you can get very large very very diverse phenomena that fit under some

01:31:21.060 --> 01:31:25.700
parameterization of an sir model now of course that's different from saying it's true it just

01:31:25.700 --> 01:31:32.420
just means it's survived uh of a an attack on it based on a falsification test right so i mean

01:31:32.420 --> 01:31:37.140
that's i don't i don't know i i think um you know like social science phenomena are funny in this

01:31:37.140 --> 01:31:45.300
way right it's not like physics they're often multiple stories that explain something that's

01:31:45.300 --> 01:31:51.940
happening in a social science setting and uh i mean i guess as uh with my background i kind of

01:31:51.940 --> 01:31:59.940
become very comfortable with the the existence of multiple stories and it's uh but i also become

01:32:00.580 --> 01:32:07.220
i understand like how challenging it is to try to decompose the phenomena that you see as you

01:32:07.220 --> 01:32:15.220
said we saw what we saw what we saw it happened um what how much each explanation for the various

01:32:15.940 --> 01:32:21.220
things that led to that thing that we saw happen are responsible like we're still arguing over the

01:32:21.220 --> 01:32:26.980
great depression you know uh 80 years later as to the particular like the the various things

01:32:26.980 --> 01:32:32.900
that we think caused it i think the one it's the one trying to come up with some analogy and the

01:32:32.900 --> 01:32:38.180
one that keeps coming back to me which is falling short always but it's the best one i got is

01:32:39.060 --> 01:32:45.780
can you imagine a scenario and where they convinced us that before the pandemic there were no cars

01:32:46.740 --> 01:32:52.180
and then they told us but there's a real easy test we can sell you a test um and when you

01:32:52.180 --> 01:32:57.940
swab your garage and you find rubber and it's in the around shape you've got a car

01:32:58.500 --> 01:33:03.060
and not everybody's going to have you know not everybody's going to smell like gasoline not

01:33:03.060 --> 01:33:07.940
everybody's going to be driving in a car some people can have a car and be asymptomatic and

01:33:07.940 --> 01:33:13.220
they take their bike to work all the time but you've got a car in your garage and they could

01:33:13.380 --> 01:33:18.260
convince us that this is spreading around the world when in fact it was in the background all

01:33:18.260 --> 01:33:23.940
the time all they have to do is never have any data about cars before this and they don't have

01:33:23.940 --> 01:33:30.020
any data about SARS-CoV-2 and related viruses before this in a from a global perspective they

01:33:30.020 --> 01:33:36.020
have it from a few hundred bats in a and a few other places um and it's wherever they look they

01:33:36.020 --> 01:33:42.820
kind of find a signal um and so i'm really and i'm not trying to beat a dead horse or or push you

01:33:42.900 --> 01:33:46.820
in a direction you don't want to discuss no no this is i think it's really interesting i feel

01:33:46.820 --> 01:33:51.940
i feel that there's also this extra portion which we talked about before we turned on the

01:33:51.940 --> 01:33:59.940
the stream that that um they are especially out on a limb when they imply that this phenomenon

01:33:59.940 --> 01:34:06.180
is being driven by an RNA molecule um i would actually have a lot harder time biologically

01:34:07.140 --> 01:34:13.860
uh discussing this if somehow or another there was a high fidelity DNA molecule at the center of

01:34:13.860 --> 01:34:18.900
this with a whole host of enzymes that we've never seen before and other attributes which could

01:34:18.900 --> 01:34:26.020
explain how something that was released at a point could then result in a high fidelity spread that

01:34:26.020 --> 01:34:31.780
you know that if you do some of the funny calculations like how many viruses would be in the wet market

01:34:31.860 --> 01:34:37.700
and then how many are there now and there's this many cases um it's an extraordinary biological

01:34:37.700 --> 01:34:43.460
phenomenon that they claim happened um and with no precedence in in previous biology there's no

01:34:43.460 --> 01:34:48.580
evidence of an RNA molecule that's capable of copying itself to this degree we've never seen

01:34:48.580 --> 01:34:54.100
a background signal with this degree of fidelity before so it it begs the question of whether

01:34:54.100 --> 01:35:01.460
that was always there um so a couple of notes um made while you're talking like what for

01:35:01.460 --> 01:35:08.580
for which you said so one is um it it's not without precedent that there would be uh a

01:35:08.580 --> 01:35:15.380
test dentic if you will it that has happened and even even in the recent past it was like 2008

01:35:15.940 --> 01:35:24.020
in Dartmouth there was a there was a huge number of people that were diagnosed with pertussis

01:35:24.980 --> 01:35:32.260
which should be pretty rare and especially since so many people have had the DPT vaccine

01:35:32.260 --> 01:35:37.780
at scale that it should if you shouldn't have seen such a massive outbreak of pertussis in a

01:35:37.780 --> 01:35:44.020
place like Dartmouth New Hampshire um I think it was 2008 I'm trying to blank the blanking on the date

01:35:44.660 --> 01:35:49.380
if you type in pertussis Dartmouth New York Times you'll find the New York Times story about this

01:35:49.860 --> 01:35:59.860
um the uh it turned out that it was based on a faulty test that in fact the pertussis uh diagnosis

01:35:59.860 --> 01:36:06.100
was was which was made on the base of the test and then just some you know coughing symptoms um

01:36:06.100 --> 01:36:10.820
was actually a false diagnosis the test itself was picking up pertussis that didn't exist that

01:36:10.820 --> 01:36:16.340
there wasn't there there was a false positive pure false positive and that that that the outbreak

01:36:16.420 --> 01:36:22.420
then was not actually pertussis but people had panicked around this you know sort of dangerous

01:36:22.420 --> 01:36:28.180
disease spreading around because of the test so I'm not saying that that's not possible that

01:36:28.180 --> 01:36:34.500
certainly is possible there what happened was that people found out that the test was faulty uh that

01:36:35.460 --> 01:36:41.700
and so faulty that it uh that then then they go back into a core correlation it's like okay

01:36:41.700 --> 01:36:50.100
yeah we were we were misdiagnosing this um so at the end of 2020 just to put a put a uh an anecdotal

01:36:50.100 --> 01:36:58.500
data point on the field at the end of 2020 the FDA had approved 226 different EUA test products

01:36:59.220 --> 01:37:08.020
so it wasn't one faulty test there was a possibly over 200 tests with various faulty properties

01:37:08.020 --> 01:37:13.860
now it all had to be false I think that so like I I mean you're the expert on the biology of this

01:37:13.860 --> 01:37:20.100
I don't know how to speak to the uh the RNA fidelity um but I will say like I think there's

01:37:20.740 --> 01:37:27.220
I don't think we've ever tested the uh a virus spreading or a disease spreading at scale the way

01:37:27.220 --> 01:37:34.980
we've tested this thing huge just I mean unimaginable numbers of tests and not just tests but like

01:37:34.980 --> 01:37:41.300
genetic sequencing of of of the viruses and I wonder if we if we did this to every single virus

01:37:41.300 --> 01:37:47.700
what we would find we probably haven't we've not probably we haven't looked like our systems

01:37:47.700 --> 01:37:52.980
even for flu for instance are these like sentinel labs very little sequencing there's some sequencing

01:37:52.980 --> 01:37:58.100
but not as much not not nearly as much I want to I want to throw one thing in there just because

01:37:58.100 --> 01:38:03.540
I feel like it's something you might not be aware of given the discussion we're having now um prior

01:38:03.540 --> 01:38:09.780
to 2020 if you go back to all these papers where they're looking at coronaviruses um the main

01:38:09.780 --> 01:38:17.540
strategy using PCR was to target a 350 base pair amplicon of the RNA dependent RNA polymerase the

01:38:17.540 --> 01:38:26.180
most conserved region of the most vital protein in the viral genome and indeed depending on the

01:38:26.180 --> 01:38:33.940
country and depending on the the test you're looking at there was an RNA dependent polymerase

01:38:34.900 --> 01:38:41.060
amplicon there was also an N protein or an E protein amplicon the interesting thing about N and E are

01:38:41.060 --> 01:38:47.620
also these are proteins that are relatively homologous across coronaviruses so one of the things that I

01:38:47.620 --> 01:38:54.020
think we have to somehow or another get all the way to the finish line is to resolve this idea that

01:38:54.100 --> 01:39:00.180
the PCR was specific enough to be used in the way it was used and that's also part of this

01:39:00.740 --> 01:39:07.060
conflated background signal if you were searching for RNA noise and there's always RNA noise there

01:39:07.060 --> 01:39:13.860
so you're going to get a certain percentage um of a positive signal this is also why I believe

01:39:14.500 --> 01:39:21.140
it's dangerous to focus exclusively on the overcycling of the PCR because that dismisses and it limits

01:39:21.140 --> 01:39:27.060
the debate to where this where this malfeasance could occur and it doesn't have to be with overcycling

01:39:27.060 --> 01:39:32.100
it could be that there is a conflated background signal and all of these people unwittingly or

01:39:32.100 --> 01:39:38.500
unwittingly took advantage of that um it's it's confusion frustration and doubt but it's it is

01:39:38.500 --> 01:39:43.060
something that the precedence of the biology of coronaviruses before the pandemic is that they

01:39:43.060 --> 01:39:49.380
lamented that there wasn't a pan coronavirus primer set so that they could just find them

01:39:49.380 --> 01:39:57.620
easier that mark von Ronsky has a paper from 2008 or nine where he is specifically trying to

01:39:57.620 --> 01:40:02.100
develop a pan coronavirus vaccine and makes the argument that it's easy because there's so many

01:40:02.100 --> 01:40:07.380
homologous proteins so there's a lot of precedence for the possibility and a lot of biological

01:40:08.180 --> 01:40:12.500
possibility there with regard to how much is homologous and if they just pull the bait and switch

01:40:12.500 --> 01:40:17.940
sometimes it could be really specific and other times it might not be and I'm afraid we've lost

01:40:17.940 --> 01:40:23.460
this huge history of of all of these EUA products many of which are not even available

01:40:23.460 --> 01:40:27.620
anymore they're totally gone just like I mean a lot of these sequencing labs are totally gone

01:40:28.820 --> 01:40:36.340
and so it becomes very very tricky now because we I feel like we have a lot of assumptions that we

01:40:36.340 --> 01:40:44.260
need to re-question and I think that's what this you know lack of spread also has spurred me on

01:40:44.260 --> 01:40:49.620
to do I'm sorry there's no question there no worries actually it's interesting because I

01:40:49.620 --> 01:40:56.340
remember when Amacron came the way that they originally diagnosed Amacron at scale versus Delta

01:40:56.340 --> 01:41:03.140
was that you know there's my now you please correct me Jake because you're the biologist not me but

01:41:03.140 --> 01:41:08.580
there was three primers that are used and you needed to have matching of all three primers to diagnose

01:41:08.580 --> 01:41:15.300
COVID diagnosed the SARS-CoV-2 virus when Amacron came the problem was only two of the three primers

01:41:15.300 --> 01:41:22.260
need matched Amacron and so they inferred Amacron from matching just two of the three primers

01:41:24.100 --> 01:41:29.380
which strikes me as funny right because but it's so I and I and I hear your point about the the

01:41:29.380 --> 01:41:35.860
existence of so many PCS I should say like for me the the cycling problem is that is it's such a

01:41:35.860 --> 01:41:39.780
huge problem I take your point that there's it does it's not sufficient for what you want but

01:41:39.780 --> 01:41:47.540
for is what for me it was sufficient to make me wonder about the use of the the the test testing

01:41:47.540 --> 01:41:53.380
the way they had it if if you have like I remember there was a there's a center for evidence-based

01:41:53.380 --> 01:42:00.420
medicine report by Carl Huntington and Tom Jefferson on the cycling problem and what they what they

01:42:00.820 --> 01:42:05.380
did was like a literature review pretty high quality literature review looking at

01:42:07.140 --> 01:42:12.500
the correlation between the number of cycles you needed to get a positive signal and whether the

01:42:12.500 --> 01:42:20.420
original sample was infectious in in the in vitro and you know what you see is this like just this

01:42:20.420 --> 01:42:26.180
like you know 20 20 cycles it's 100 percent in fact 100 percent of the samples are infectious

01:42:26.180 --> 01:42:33.060
by like 27 cycles it's like 50 percent and by 30 cycles it's like you know pretty low by 40

01:42:33.060 --> 01:42:42.820
cycles at zero right um that has huge implications for the epidemiological policy and clinical use

01:42:42.820 --> 01:42:51.780
which is my my uh bailiway that should have it should have told people you don't you don't quarantine

01:42:51.780 --> 01:42:58.020
people if it takes 40 40 cycles to like find a positive in fact you couldn't even have done

01:42:58.020 --> 01:43:01.700
like like I didn't understand why people weren't doing this like they could have done if they

01:43:01.700 --> 01:43:06.820
were really serious they said they said they said they want to say okay is the virus replicating in

01:43:06.820 --> 01:43:12.900
the human well you could do a PCR test one day and let's say it takes 30 cycles to be positive and

01:43:12.900 --> 01:43:18.660
the next day it takes 26 cycles to be positive well I mean that now you have some evidence that

01:43:18.660 --> 01:43:24.180
you have two to the fourth uh doublings that have happened right um in the in the person so you

01:43:24.180 --> 01:43:31.300
could have like used serial PCR's again leaving aside the the false positives which you know you

01:43:31.300 --> 01:43:37.220
can talk about uh but you know more about than me um but like the serial false positive like the

01:43:37.220 --> 01:43:43.300
serial test to like see with just the cyclings whether someone is actually becoming infectious

01:43:43.300 --> 01:43:49.540
or not and use that information epidemiologically from with recommendations to quarantine or not

01:43:49.540 --> 01:43:54.580
whereas someone who's like 30 cycles 30 cycles 30 cycles left them out of quarantine there are

01:43:54.580 --> 01:44:00.420
students at Stanford that were putting that were like like athletes that were tested over and over

01:44:00.420 --> 01:44:05.460
again that were just positive all the time are you sure that there's not a time lapse

01:44:05.460 --> 01:44:10.900
acute PCR paper because if there isn't that's an actually a really huge insight that you just made

01:44:10.900 --> 01:44:16.420
there i haven't seen one i mean i i've made a case i've made a case like this in a port document

01:44:16.420 --> 01:44:21.220
in for a couple of places where i was an expert witness suggesting that this was this would be

01:44:21.220 --> 01:44:27.460
a reasonable use of the PCR test um but uh but the but the but the lab folks on the other side were

01:44:27.460 --> 01:44:32.740
just very dismissive of me um my chat is correcting you you're actually a biologist because you're

01:44:32.740 --> 01:44:38.660
also a professor of medicine sorry well i mean i my my backgrounds at fringe epidemiology and

01:44:38.740 --> 01:44:45.220
economic stress hey so i want to do one more PCR thing just so that you have it on your radar um

01:44:45.220 --> 01:44:53.300
so in talking to the the head of the PCR testing in Canada um i don't remember his name off the

01:44:53.300 --> 01:45:00.340
top of my head so he happens to listen i very much apologize um they did not use nested primers in

01:45:00.420 --> 01:45:08.820
Canada across the entire country um which which i and i i just want to give you this for from the

01:45:08.820 --> 01:45:12.980
perspective of cocktail parties or anytime you get to talk to another academic biologist who

01:45:12.980 --> 01:45:21.620
insists that PCR is highly accurate like insanely accurate um it is very much my understanding that

01:45:22.260 --> 01:45:29.460
academic biologists are making this assumption that like they do there are positive and negative

01:45:29.460 --> 01:45:36.660
controls both of which use nested primers and in reality none of the e-way products use nested

01:45:36.660 --> 01:45:41.060
primers and none of the products that were approved in Canada were using nested primers which

01:45:41.860 --> 01:45:48.740
is makes it orders of magnitude easier um to have a false positive because remember they're

01:45:48.740 --> 01:45:54.420
reading fluorescence so with qPCR i i'm just gonna say it in case you are not aware of it but i'm

01:45:54.420 --> 01:46:00.020
assuming my my readers or my listeners aren't qPCR is a reaction that occurs with some kind of

01:46:00.020 --> 01:46:08.740
understood reaction uh reaction dynamics and those reaction dynamics can tell you a little bit about

01:46:08.740 --> 01:46:14.740
how well the PCR primers match because the better that they match the more complete each cycle will

01:46:14.740 --> 01:46:21.380
be in doubling if they don't match as well then the doubling will not fit the exponential growth

01:46:21.380 --> 01:46:26.660
curve in it will be more linear and that linear signal in any of these products that just goes

01:46:26.660 --> 01:46:33.140
on the on the fluorescence won't be visible to anybody that's reading them and so a lot of these

01:46:33.780 --> 01:46:39.220
products almost have this built-in possibility that if you're not really trying to use them for

01:46:39.220 --> 01:46:44.740
accuracy but you're trying to use them for mass measurement it will go really terribly wrong

01:46:45.700 --> 01:46:51.700
and so i i've had a lot of conversations with my former academic colleagues where they're very

01:46:51.700 --> 01:46:57.700
surprised and actually completely incredulous that of course they use nested primers and i i'm sorry

01:46:57.700 --> 01:47:02.500
to disappoint you but they didn't i mean i i think um

01:47:05.700 --> 01:47:09.620
from a policy point of view i mean actually it's just from a clinical point of view let's say

01:47:10.180 --> 01:47:16.740
uh like what i learned in medical school was that you should never treat a number or test

01:47:16.740 --> 01:47:22.980
you treat a patient like you want to have a full clinical picture before you make real decisions

01:47:22.980 --> 01:47:30.500
about about what uh what the right thing to do is um the the um the epidemiologists that were that

01:47:30.500 --> 01:47:36.020
were like the architects of the policy i think the way they were reasoning was well it doesn't

01:47:36.100 --> 01:47:43.140
matter if you get a false positive what matters is a false negative that's actually true they

01:47:43.140 --> 01:47:48.740
probably did convince a lot of people with that argument yes yeah and i think that that's i mean

01:47:48.740 --> 01:47:53.380
that's my best reading of what happened like they just said there was a virtue to minimize

01:47:53.380 --> 01:47:58.260
the false negatives to zero and and we've had false positive at a scale it doesn't matter

01:47:58.980 --> 01:48:03.380
what nothing that we're doing as far as they were concerned none of the policies they were

01:48:03.380 --> 01:48:06.900
implementing were costly or harmful in any way that was worth taking into account

01:48:08.260 --> 01:48:14.980
and so if you impose it on somebody on the on a false basis of a false positive that's that's not

01:48:14.980 --> 01:48:20.020
a big deal it doesn't matter whereas if you have false negative well that person might spread the

01:48:20.020 --> 01:48:24.420
disease to grandma uh and uh thinking that they're positive that they're that they're actually

01:48:24.420 --> 01:48:30.580
negative when they're actually positive um so so i i think that that's really the underlying

01:48:30.580 --> 01:48:34.660
dynamic we saw here with all of the decisions because every single one of these decisions

01:48:34.660 --> 01:48:40.180
about testing is a is a is a is a there's a lot of technical language but the key thing is

01:48:41.460 --> 01:48:46.340
what does it do to make the sensitivity and specificity of the test how should we interpret

01:48:46.340 --> 01:48:53.140
the test what's the prevalence of the disease these are like basic epidemiological ideas that

01:48:53.140 --> 01:49:01.700
were just essentially tuned to to create panic tuned to create uh you may you see each of these

01:49:01.700 --> 01:49:06.900
decisions dismissing the possibility of false positive is like because the idea is like well

01:49:06.900 --> 01:49:14.660
it's it's just a virtue to have almost no false negatives yeah that really makes a lot of sense

01:49:14.660 --> 01:49:20.660
and it's a frightening um clarity that it sets to that too because um i always make this argument

01:49:20.740 --> 01:49:27.380
on my stream that so much can be done in a closed meeting um to convince people to behave in

01:49:27.380 --> 01:49:32.660
concert um if you make them feel important that this is a national security question and we don't

01:49:32.660 --> 01:49:38.100
know what's going to happen and we need your help um there's lots of ways where i think people

01:49:38.100 --> 01:49:44.660
could have been influenced to kind of at least keep their head down for a while um and again if

01:49:44.660 --> 01:49:48.980
you put your head up and you you encountered what you encountered or what i encountered then you

01:49:48.980 --> 01:49:54.740
probably kept your head down too um we have been talking for one hour and forty six

01:49:54.740 --> 01:49:58.260
we've been talking for one hour and forty six minutes i don't want to take too much more of your

01:49:58.260 --> 01:50:04.820
time i i just i want to say thank you i want to give a shout out to um Greg Glassman and Emily

01:50:04.820 --> 01:50:11.700
Kaplan of the broken science initiative that serendipitous serendipitously brought us together

01:50:11.700 --> 01:50:17.700
at their gatherings um i have them to thank you for your friendship and i can't thank you enough

01:50:17.700 --> 01:50:21.140
for taking the time to argue with me and discuss this stuff with me it was been great

01:50:21.700 --> 01:50:25.540
yeah i've learned a lot from you not just from this podcast but from over the whole

01:50:25.540 --> 01:50:30.100
whole last three years and grateful for you as well my friend that's really uh way too much

01:50:30.100 --> 01:50:35.460
praise for me thank you very much though um you're welcome to come back i have a whole four

01:50:35.460 --> 01:50:39.540
more pages of questions i didn't get to because we discussed everything in too much depth so

01:50:40.260 --> 01:50:43.380
when you have a spare board moment you can always let me know

01:50:43.940 --> 01:50:47.140
take care jay okay bye bye

01:50:49.620 --> 01:50:55.380
wow that was uh that was pretty great i'm not going to belabor it too much because at six o'clock

01:50:55.380 --> 01:51:00.820
i have uh peter makala again so thank you very much for joining me i will see you guys again soon

01:51:01.460 --> 01:51:05.780
um and that soon is in like 50 minutes so i'm uh

01:51:05.780 --> 01:51:08.900
i've been doing it for a long time

01:51:08.900 --> 01:51:10.980
so i'm going to change the password to my zoom

01:51:10.980 --> 01:51:15.860
but i'm going to send it to you um so i will see you guys again very soon

01:51:15.860 --> 01:51:19.060
thank you for having me back in the flash

01:51:20.020 --> 01:51:24.100
right

01:51:38.180 --> 01:51:48.340
it's better better music

01:51:49.060 --> 01:52:59.060
50 minutes, 50 minutes at 6 o'clock.

