WEBVTT 00:00.000 --> 00:14.520 Go test 1-2, testing 1-2, finally have a little show here, I hope this sound is all 00:14.520 --> 00:15.520 coming through. 00:15.520 --> 00:22.480 If you're in the chat it would be great for a little help on the audio visual. 00:22.480 --> 00:28.120 You can also check this, if you don't mind, see if we're all kind of in sync on the live 00:28.120 --> 00:33.800 stream, that would be really handy, perfect says Pamela, good to see you, good to see you. 00:33.800 --> 00:37.440 I'm going to do this without headphones today too, so if you can give me any feedback on 00:37.440 --> 00:41.000 my volume that would be great, or Jay's volume for that matter. 00:41.000 --> 00:47.120 In case you're unaware, and Jay is definitely unaware, I was a patch plant physiologist 00:47.120 --> 00:52.520 who was raised to make slices of animals brains, and I had Vivo, I scored them for 00:52.520 --> 00:58.720 a few hours, and while I did that I would record pairs or groups of neurons under the 00:58.720 --> 01:04.920 microscope, and also use transfection to control surrounding neurons with optogenetics. 01:04.920 --> 01:10.520 So I'm pretty familiar with how transfection can be used in academic medicine, academic 01:10.520 --> 01:16.960 investigation, how you can manipulate individual neurons, drive it by genes, you can look 01:16.960 --> 01:22.680 me up on the internet, Jonathan, who you are, PubMed. 01:22.680 --> 01:27.360 So today we have a special guest, Jay Bhattacharya. 01:27.360 --> 01:32.680 The bifurcation of Earth is, he's a very special guy with regard to that. 01:32.680 --> 01:38.760 Remember that if you're not familiar with him, he is a professor of health policy at 01:38.760 --> 01:43.080 Stanford University, and a research associate at the National Bureau of Economics Research. 01:43.080 --> 01:49.080 He directs Stanford's Center for Demography and Economics of Health and Aging. 01:49.080 --> 01:53.280 His research focuses on the health and well-being of vulnerable populations, with a particular 01:53.280 --> 01:59.400 emphasis on the role of government programs, biomedical innovation, and economics. 01:59.400 --> 02:07.760 Recent research also focuses on the epidemiology of COVID-19, as well as an evaluation of policy 02:07.760 --> 02:10.000 responses to the epidemic. 02:10.000 --> 02:14.680 His broader research interests encompass the implications of population aging for future 02:14.680 --> 02:19.240 population health, which I have listed as a must-ask question. 02:19.240 --> 02:24.480 The medical spending in developed countries, the measurement of physician performance tied 02:24.480 --> 02:27.880 to physician payment by insurers, that's a crazy one. 02:27.880 --> 02:33.320 The role played by biomedical innovation on health, he has published 135 articles, and 02:33.320 --> 02:38.520 top peer-reviewed scientific journals in medicine, oh, I can be over here, can I, yes, I can. 02:38.520 --> 02:44.280 He published that, yes, scientific journals in medicine, economics, health policy, epidemiology, 02:44.280 --> 02:50.080 statistics, law, and public health, among other fields, he holds an MD and a PhD in economics 02:50.080 --> 02:51.080 and book. 02:51.080 --> 02:56.200 MD and a PhD in economics, I almost thought it was an MD in economics for a minute there, 02:56.200 --> 03:03.120 and both earned at Stanford University, so let me see if I can cut this out like that. 03:03.120 --> 03:05.760 Oh, there you are, hello, sir. 03:05.760 --> 03:07.400 Thank you very much for joining me. 03:08.400 --> 03:15.120 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. 03:15.120 --> 03:18.360 You left a community, which is I'm a fringe epidemiologist, that's what I thought. 03:18.360 --> 03:19.520 That's right. 03:19.520 --> 03:21.280 That's right. 03:21.280 --> 03:24.520 Fringe epidemiologist, he says. 03:24.520 --> 03:27.640 So, let's talk about being a fringe epidemiologist. 03:27.640 --> 03:33.300 That first question kind of peels right into that, so how did this great Barrington declaration 03:33.300 --> 03:40.180 inform was it from a poker group or are you guys all aficionados of the same dog breed or how did 03:40.180 --> 03:49.140 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 03:49.140 --> 03:57.220 Koldorf in the summer of 2020 because my friend Scott Atlas who was also at Stanford had been 03:57.220 --> 04:05.220 invited by by President Trump to be his COVID advisor. Scott tried to like organize a meeting 04:05.220 --> 04:10.260 inside the White House with me Martin and a few other scientists to try to talk to Trump about 04:10.260 --> 04:17.380 lockdowns, school closures, Debbie Birx and and Tony Fauci tried to block that. It took for and 04:17.380 --> 04:22.500 it took a like basically finally at the end of August, middle of August, I think, 04:23.300 --> 04:28.820 we he got permissioned for us to go visit the White House and that's why I met Martin Koldorf 04:28.820 --> 04:34.740 at the at the footsteps of the White House. Wow. Martin had been a guy known about him because 04:34.740 --> 04:40.020 he is an amazing statistician. I work on I've been working on vaccine safety actually with the FDA 04:40.020 --> 04:45.060 and he Martin had developed the statistical infrastructure for how to track vaccine 04:45.060 --> 04:52.020 vaccine injuries in with with a real time surveillance. Anyway, so I met Martin, we hit it off 04:52.020 --> 04:59.860 immediately at the foot first up the White House and I mean we started writing we wrote a couple 04:59.860 --> 05:06.740 op-eds together. One day in late September, Martin calls me up and says, Jay, do you want to come 05:06.740 --> 05:12.980 to have a little conference? What we'll do is we'll we'll invite some journalists and we'll invite 05:12.980 --> 05:18.980 Sinatra Gupta from Oxford who I I mean I've been mired her forever and I never met her before 05:20.420 --> 05:24.100 we'll invite the three of us will go meet with some journalists and try to tell them about the 05:24.100 --> 05:29.220 epidemiology of of lockdowns the harms of lockdowns. In fact, that's exactly what we told President 05:29.220 --> 05:33.140 Trump. We told that the President Trump that closing schools was a really bad idea was hurting 05:33.140 --> 05:38.100 children that the evidence from Sweden was that it wasn't particularly effective at stopping this 05:38.100 --> 05:43.380 rather than whatever the disease was and so like that there was a really bad idea to close schools 05:43.380 --> 05:47.220 and that you needed to protect older people better like the basically the idea of a great 05:47.220 --> 05:54.340 branch decoration and so we met in western Massachusetts very close to where Martin lives 05:54.340 --> 06:00.500 and it's a town I never heard of before so when we when I arrived I it was like you know actually 06:00.500 --> 06:06.420 this was like in the middle of a crazy lockdown in New York and and it felt it felt really illicit 06:06.420 --> 06:13.140 like I got to fly across country and and on the drive-in I asked the the the the driver was 06:13.140 --> 06:16.740 driving you what the name of the town was never heard of it before because it said Great Barrington 06:16.740 --> 06:21.460 and so when we met we just we weren't like actually thinking about writing we were going to write 06:21.460 --> 06:25.540 like a declaration we were just going to talk to people talk to journalists that have invited 06:25.540 --> 06:29.860 there that when we met we really cleared that we derived basically at the same place I mean 06:29.860 --> 06:34.980 I thought it was like particularly novel idea like the idea that you protect vulnerable older people 06:34.980 --> 06:39.060 and you don't lock down that's the way we managed every other viral pandemic last 06:39.060 --> 06:43.460 respiratory viral pandemic of the last century we arrived at the same place we thought okay well 06:43.460 --> 06:49.940 why don't we put out a little short statement about what we think and I came up with the name 06:49.940 --> 06:53.700 Jay I've stabbed quite proud of myself because I remembered the word Great Barrington I'm like 06:53.700 --> 06:58.740 that would be a great title for the declaration you know I was thinking like port here in statement 06:58.740 --> 07:04.180 you know from the like the 60s or whatever I see yes and so and you know you can't tell if the 07:04.340 --> 07:08.580 word Great applies to the the city or to the or to the declaration which is that I'm being 07:08.580 --> 07:14.420 really fantastic and so I yeah anyways it got a lot of attention I mean almost immediately 07:14.420 --> 07:19.860 it was it got a tremendous amount of attention almost a million people signed it tens of thousands 07:19.860 --> 07:26.980 of doctors and scientists signed it and you know what I think the reason why it got that 07:26.980 --> 07:32.580 attention was that at that point oh sorry Jake no I signed it I just wanted to say oh thank 07:32.580 --> 07:37.460 I'm really grateful you are grateful to do that I mean I think that the reason why it got 07:37.460 --> 07:43.620 attention is because people understood like most people really understood deep in their heart that 07:43.620 --> 07:47.620 there was that what we were doing was absolute nonsense it was hurting kids it was hurting poor 07:47.620 --> 07:52.100 people it was hurting vast numbers if you all these lockdowns were and it wasn't like you know 07:52.100 --> 07:55.780 if the promise was it was gonna get rid of the disease well how come it was coming back in 07:55.780 --> 08:02.340 October 2020 right it wasn't working and it was hurting people and it was violated civil 08:02.340 --> 08:07.780 rights at scale and it was and especially the harm to kids was was pretty close to the top of my 08:07.780 --> 08:15.220 mind and I have three kids and all three of them you know basically they didn't see my two of them 08:15.220 --> 08:18.580 didn't see the inside of a classroom for a year and a half and the third one was in college it 08:18.580 --> 08:24.420 took a long time I mean basically it felt to me like we were robbing our kids of their childhood 08:24.420 --> 08:29.380 for no real purpose well imagine quite frankly this is the one thing that really scared me is 08:29.460 --> 08:35.940 that imagine not having you as a father instead having somebody who can't grasp it or understand 08:35.940 --> 08:42.820 the limitations or the you know explain anything and just has to go from what they get on television 08:42.820 --> 08:48.660 it could bend much much what scares me the most is the idea that the children seem to watch the 08:48.660 --> 08:55.380 parents lose control and that's a real dangerous sort of blanket effect of what they did with the 08:55.380 --> 08:59.460 lockdown I mean you were still seeing the aftermath of that and that you're seeing like levels of 08:59.460 --> 09:03.940 anxiety and depression and kids like you scare the living daylight out of them tell them that 09:03.940 --> 09:08.500 they are going to kill if they just lead normal childhoods they're going to kill mom and dad or 09:08.500 --> 09:14.500 grandpa grandma and so they better treat everybody as biohazard or else I mean that's going to have 09:14.500 --> 09:20.180 consequences and it just has had consequences really negative ones it's just heartbreaking to go 09:20.180 --> 09:25.060 watch it anyway so that's how would the great grandpa question happen we we put this out and I 09:25.060 --> 09:29.700 think people were just ready to hear that that wasn't needed like I I call it the least original 09:29.700 --> 09:36.580 thing I've erode j I mean I it's not like I I mean it was we were saying obvious things right 09:38.180 --> 09:43.300 and and yet if people were interested because it shattered the idea that there was a consensus 09:43.300 --> 09:48.100 around the lockdowns I mean that's how you impose a lockdown or or or the kinds of like 09:49.060 --> 09:55.460 policies you have to like get the population to agree to be scared and to have this sense that 09:55.460 --> 10:01.300 all the scientists all the wise people agree that you have to do this or else and what the great 10:01.300 --> 10:05.780 branch of decoration is it shattered that consensus shattered the idea that there was a consensus 10:05.780 --> 10:10.660 it because you know the consensus wasn't there right you know this right I mean I from from from 10:10.660 --> 10:14.340 the beginning of the pandemic you've been you've been saying counter counter consensus things 10:15.220 --> 10:21.300 and scientists if you talk to scientists you know you get a hundred opinions if you have 100 10:21.300 --> 10:26.660 scientists you get 150 opinions sometimes right and so you just it was it was it was really clear 10:26.660 --> 10:31.700 that to me talking to other scientists that that there wasn't a consensus and so when we put the 10:31.700 --> 10:38.980 the Declaration out I think that's why it got so much attention both from the public but also from 10:39.620 --> 10:45.620 scientific authorities you know scientific bureaucrats like Tony Fauci and Francis Collins 10:46.660 --> 10:52.500 or Jeremy Farron in the UK they were they were for them it was a threat to their power 10:54.180 --> 10:58.500 it was a threat to the idea that they that they knew best what to do and everyone better 10:58.500 --> 11:02.420 listen to them or else everyone's gonna die I mean that was essentially I mean like they you know 11:02.420 --> 11:05.540 they didn't say it that way but that's essentially what they were they were implying 11:06.180 --> 11:12.420 and the great branch and declaration said no look other scientists have a different view or 11:12.420 --> 11:18.020 proposed or thinking of different policies is better and it was a call for a conversation 11:18.020 --> 11:21.380 like we were calling for focus protection it's called for conversation how best to do that 11:21.380 --> 11:26.580 how do you how really do you protect older people because the idea up to then was like the 11:26.580 --> 11:30.580 lockdowns were going to protect them but it didn't protect them you know lots and the older people 11:30.660 --> 11:36.340 have died on the basis of the idea that lockdowns can protect them we've done really stupid things 11:36.900 --> 11:42.580 right like why do we send covid why did why did New York send covid infected patients back to 11:42.580 --> 11:47.060 nursing homes this happened lots of places by the way not just New York it's because the the 11:47.060 --> 11:51.940 premise was that keeping hospital beds empty was more important than protecting vulnerable people 11:53.060 --> 11:57.380 why did we close schools like because somehow kids were even even despite the fact that 11:57.380 --> 12:01.220 Sweden you had evidence from Sweden for the spring that not closing schools didn't result 12:01.220 --> 12:07.860 in a worse epidemic really I just for the especially for the teachers the the rates of death for 12:07.860 --> 12:14.340 teachers was was lower than the average of the rest of the population yeah it was it was really 12:14.340 --> 12:23.140 shocking oh what is this what that's ridiculous now I get they're saying my zoom meeting is going 12:23.220 --> 12:28.740 to end well we can we can you know I'm signed in under the wrong account then dog on it 12:33.060 --> 12:38.020 I'm gonna have to sign in different than I guess okay well we can we start though we we've recorded 12:38.020 --> 12:44.420 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 12:44.420 --> 12:48.100 annoyed that I could have seen that coming I guess I thought I had longer in this don't worry 12:49.060 --> 12:53.060 um I'll send you a link in like 30 seconds okay see shortly okay 12:56.900 --> 13:01.620 dumb d-dum d-dum d-dum d-dum d-dum d-dum d-dum d-dum d-dum d-dum d-dum 13:03.300 --> 13:06.260 dumb d-dum d-dum d-dum d-dum d-dum 13:08.020 --> 13:12.020 this one is the one I paid for open zoom 13:12.740 --> 13:14.740 um 13:14.740 --> 13:16.660 um-d-dum d-dum d-dum d-dum 13:17.220 --> 13:20.340 sorry guys I'm gonna fix this right now and then it'll be dumb 13:23.220 --> 13:28.500 save and now that we've got him he said I've got a lot of time so I'm actually gonna probably 13:28.500 --> 13:34.180 have to cut him short and then uh what will happen is uh 13:34.580 --> 13:43.140 I'll have to switch right away for Peter McCullough which is crazy but there it goes 13:43.140 --> 13:48.580 hopefully he'll be up very shortly I'm gonna start this meeting and then uh hopefully he'll be here 13:50.740 --> 13:56.820 at least all the settings are right now I hope the sound is all right are we good sound is all right 13:56.820 --> 14:06.740 I think this is gonna be a fun conversation um I might have to keep him here all the way till 14:06.740 --> 14:11.220 six o'clock but uh I think it's gonna be a good conversation here he comes he's already back 14:11.220 --> 14:18.820 see how quick we are now we're back Jedi master level stuff there thank you sir for tolerating my 14:18.820 --> 14:27.460 IT uh sure better rather than I am Jay so just uh no worries um so where were we we were I was 14:27.460 --> 14:33.380 about to ask you I sort of pair up a general question that kind of segway's well in in what we 14:33.380 --> 14:38.820 were talking about about the Great Bearing Declaration and where it evolved from and where it got you 14:39.460 --> 14:45.140 um oh Jay can you can you can you allow me to or of course I can yes there we can 14:46.100 --> 14:52.420 and so if you if that helps you at all to pick up where you left off or recording in progress 14:52.420 --> 14:58.420 gotcha otherwise um so we were just talking about the Great Bearington Declaration you were 14:58.420 --> 15:05.140 finishing kind of saying um how it evolved and and why it was important because because it gave 15:05.140 --> 15:12.580 people first time this this clear uh message that there isn't a consensus that something is 15:12.660 --> 15:16.260 isn't right so it's a pretty incongruent message relative to the television 15:16.980 --> 15:25.460 um what was the in that time what was the the most common way of them trying to dismiss you 15:25.460 --> 15:29.060 was it just that they don't know what they're talking about even though that was part of the 15:29.060 --> 15:35.860 reason why you chose you three right as you you realize that you're let's say professional 15:35.860 --> 15:40.820 standing should bring some weight so that people would be less likely to be able to dismiss you 15:40.820 --> 15:45.380 well how did you how did that come out in reality versus what you expected 15:46.740 --> 15:52.500 well so uh the four days after we wrote the declaration we learned this uh from foyer 15:52.500 --> 15:57.940 request four days after we wrote the declaration the head of the NIH Francis Collins wrote to Tony 15:57.940 --> 16:03.780 Fauci an email where he called me Martin and Sinatra of Martin Coldoff of Harvard University 16:03.780 --> 16:08.580 Sinatra Gupta of Oxford University the three of us fringe epidemiologists uh that's that's 16:08.660 --> 16:13.860 I got a book I got a little uh i'll see if i have like card that has the fringe epidemiologists 16:13.860 --> 16:17.780 i can't find it it's a fringe epidemiologists somewhat friend of mine made a fringe epidemiology 16:17.780 --> 16:22.980 card i i think i will go to my grade with that title well don't give them all the way i want one 16:22.980 --> 16:27.140 of those i definitely will the next time we'll next time we meet you i will give you what i promise 16:27.700 --> 16:34.820 um but yeah so so uh he called us fringe epidemiology then he called for devastating takedown literally 16:34.900 --> 16:39.300 in an email devastating takedown the premises of the the declaration and then what started 16:39.300 --> 16:44.740 happening was hit pieces hit pieces by the washing and post uh in fact Francis uh Tony Fauci shared 16:44.740 --> 16:51.700 it and a hit piece almost immediately by wired magazine where Fauci showed up accusing us of 16:51.700 --> 16:57.140 wanting to let the virus rip when we were calling for focus protection of vulnerable people um i 16:57.140 --> 17:04.100 mean it was basically a propaganda campaign um in in in the uk parliament a conservative 17:04.900 --> 17:12.740 member parliament denounced uh cenetra uh there was a website that came up uh all of a sudden 17:12.740 --> 17:18.500 accusing us of like saying all being you know all kinds of nasty attacks and in the British 17:18.500 --> 17:24.020 medical journal the British medical journal published a false attack on us claiming that we 17:24.100 --> 17:30.820 had financial conflicts of interest it was insane i paid my own way to great parenthood mass 17:30.820 --> 17:36.580 uses for the flight i didn't accept any money in fact jay i've taken zero dollars for any of my 17:36.580 --> 17:42.500 covid work to date i've lost money on covid um because i just don't feel right taking money in the 17:42.500 --> 17:47.540 middle for when people are suffering in this way so i just i the whole thing was just they 17:47.540 --> 17:51.540 and the British medical journal published it claiming that somehow that we were coke funded 17:52.260 --> 17:58.020 when in fact that it was the it was like the imperial college model that led to the panic in 17:58.020 --> 18:03.380 march of 2020 that was coke funded um the whole thing was just it was it was it was an absolutely 18:03.380 --> 18:10.580 disgusting ad hominem attack based on lies because the problem was they couldn't actually engage with 18:10.580 --> 18:17.380 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 18:17.620 --> 18:21.460 it's just where if you're a scientist you know you make a mistake let me you you're wrong a lot 18:21.460 --> 18:27.300 of the time and it's the it's the process of like uh seeing what other people think looking at data 18:27.300 --> 18:32.100 doing experiments that's how you learn as scientists right they didn't treat us that way they treated 18:32.100 --> 18:38.260 us as if we were heretics to be expelled and excommunicated um i'd say this this wasn't it wasn't 18:38.260 --> 18:45.300 even the first time like in the pandemic um in april of 2020 i had done a study in Santa Clara 18:45.300 --> 18:49.140 county california um i don't know if you've seen it maybe you've seen it was it was it was a 18:49.140 --> 18:54.980 study measuring antibody levels in the population a seroprevalence study and it was we done one in 18:54.980 --> 19:00.180 Santa Clara county and another one in LA county shortly after that and uh you know we we used this 19:00.180 --> 19:07.060 uh this test kit that we'd gotten from a a guy who runs uh made testing in major league baseball 19:07.940 --> 19:11.780 he had ordered it um we did a lot of work to try to figure out what the false laws and 19:11.780 --> 19:17.220 false negative rates were uh we were we put out a paper which i thought was a pretty careful paper 19:17.220 --> 19:21.300 that there was some uh some some comments that folks folks had on twitter and elsewhere that 19:21.300 --> 19:27.140 made it then we released an updated version of it in a in a in in the pre-print ultimately the 19:27.140 --> 19:30.900 paper was published in the international level of epidemiology right so it's like we got the math 19:30.900 --> 19:37.140 right um the hunch line for the paper from the beginning was that the disease had had spread to 19:37.140 --> 19:41.940 about three percent of the population in LA county for in LA county four percent three percent 19:41.940 --> 19:48.420 in in Santa Clara county um it was uh it was something like it was April early April 2020 and 19:48.420 --> 19:53.780 that meant that you know there were a thousand official cases then in in in Santa Clara county 19:53.780 --> 19:59.860 but our estimates implied 50,000 people had already been infected or at least had antibodies to the 19:59.860 --> 20:05.620 to the there were specific to the SARS-CoV-2 um that meant that infections how do you rate was 20:05.620 --> 20:11.940 not you know the the you know was the World Health Organization said 3.4 percent case fatality 20:11.940 --> 20:17.460 rate our estimate was that that implied something like 0.2 percent infection fatality rate um for 20:17.460 --> 20:21.300 people especially for and there was this massive age gradient with older people having much higher 20:21.300 --> 20:28.660 risk um that led to hit pieces on me and on my wife and my family it led to i wasn't ready for 20:28.660 --> 20:33.060 that my face skin wasn't this i thought my skin was thick after you know two decades in academics 20:33.060 --> 20:38.260 but it turns out what i wasn't used to uh attacks on me death threats constantly for two straight 20:38.260 --> 20:43.220 years jay every time i appear in public every time i'd write something they there was just like 20:43.220 --> 20:48.740 uh assumptions of bad faith accusations of false accusations of conflicts of money complex of 20:48.740 --> 20:57.620 interest um essentially everything but actually engage with the scientific results right i i i 20:57.780 --> 21:04.820 can only imagine i mean i i remember this paper um and i remember i might have even still been 21:04.820 --> 21:09.940 on my bike when that paper came out so there might even be a later bike ride on my youtube 21:09.940 --> 21:18.340 channel where i did it um but the the what my narrative would be on that or what my question 21:18.340 --> 21:23.620 would be on that is um just taking notes on it so we that whole study would be on a testing kit that 21:23.700 --> 21:29.620 at that time um part of the illusion of consensus i would say was that these testing kits were 21:29.620 --> 21:36.420 very high fidelity with almost no false positives and appropriate to apply to anybody that was 21:36.420 --> 21:43.700 suspicious of having a test or i mean having an infection and at the same time overlapping with 21:43.700 --> 21:50.340 this i think biologically incorrect concept of asymptomatic spread being a very widespread 21:50.340 --> 21:56.820 phenomenon and i know that at that time i couldn't iron it out i couldn't figure it out but i know 21:56.820 --> 22:03.220 that there was a very concerted effort to establish the idea that you can't know if you're infected 22:03.220 --> 22:09.300 and even if you test negative on a test you could still be positive and just not know it and this 22:09.300 --> 22:14.260 goes back to the you know testing before you leave campus to make sure you don't infect your 22:14.260 --> 22:21.540 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 --> 01:52:04.060 50 minutes, 50 minutes at 6 o'clock. 01:52:19.060 --> 01:52:48.060 50 minutes, 50 minutes at 6 o'clock. 01:52:49.060 --> 01:52:59.060 50 minutes, 50 minutes at 6 o'clock.