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Speaker 1: Well, joining me now is somebody who during the pandemic

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Speaker 1: quickly became not just my go to expert and trying

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Speaker 1: to understand what's coming next with the pandemic. He was

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Speaker 1: easily the most I think trusted person I would book

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Speaker 1: on meet the press during the pandemic. It's doctor Michael Osterholme.

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Speaker 1: I believe you're still at the University of Minnesota. Is

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Speaker 1: that correct?

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Speaker 2: Still here doing the same thing, slugging.

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Speaker 1: Away, except you are leaving your studio. There was a

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Speaker 1: time you didn't leave your house for quite some time.

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Speaker 2: Right, Actually, I'm here right now.

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Speaker 1: But you did you have left?

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Speaker 2: You have left? Oh yeah, yeah, I'm out and about.

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Speaker 1: You have a new book out with your co author,

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Speaker 1: Mark Olshaker. It's called The Big One. I'll hold it

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Speaker 1: up for the camera and in some ways in the

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Speaker 1: tagline being how we must prepare for future deadly pandemics

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Speaker 1: And on one hand, and I'd sit here and say,

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Speaker 1: we really there's a lot of lessons to be learned

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Speaker 1: from COVID. What I can't wait for the government after

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Speaker 1: action report of what we're going to do better next time?

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Speaker 1: And oh wait, right, we're still waiting for that. The

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Speaker 1: One Big thing that struck me about this book is

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Speaker 1: are American leaders ready for it? Meaning are they ready

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Speaker 1: to actually tackle the preparation part? Or are we still

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Speaker 1: too hungover, frankly from what we went through in twenty

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Speaker 1: twenty and twenty twenty one.

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Speaker 2: Well, let me just start out by saying that when

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Speaker 2: you think about preparing for the big one, that seems

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Speaker 2: miles and miles and miles away before we even get

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Speaker 2: to that, because we're having such a problem preparing for

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Speaker 2: the immediate one, and what we're watching is basically the

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Speaker 2: destruction of the public health system, unlikening I've seen in

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Speaker 2: my fifty years in the business. And so today I

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Speaker 2: imagine this. All the leadership right now, with the CDUC,

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Speaker 2: all the executive office are pointed political individuals. They're all

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Speaker 2: appointed no scientific expertise whatsoever. Imagine if you had an

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Speaker 2: aircraft carrier and the top twelve people and that aircraft

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Speaker 2: carrier command, we're all just appointed politically individuals. How confident

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Speaker 2: would you be in that? And so I think, Chuck,

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Speaker 2: we surely want to talk about the long term, because

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Speaker 2: it's inevitable we're going to have that, But I think

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Speaker 2: we have to also recognize even in the short term.

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Speaker 2: Right now, we're in big trouble.

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Speaker 1: Well, and that's but it also sort of opens up

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Speaker 1: the book implies we haven't had the big one. What

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Speaker 1: was covid?

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Speaker 2: Well, first of all, let me just kind of put

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Speaker 2: into perspective what a pandemic is in the sense of

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Speaker 2: what we saw with COVID or what we saw with flu.

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Speaker 2: Prior to COVID, we really thought that the only virus

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Speaker 2: that was capable of basically changing itself and then infecting

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Speaker 2: people around the world in a very effective way was influenza.

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Speaker 2: We had warning signs that COVID could do this, or

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Speaker 2: a coronavirus at least, And in fact, in the book

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Speaker 2: that Mark and I published in twenty seventeen, Deadliest Enemies

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Speaker 2: Our Wargan's Killer Germs, the actual chapter on coronavirus was

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Speaker 2: a harbinger of things to come, and so that when

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Speaker 2: we saw what happened with COVID, we shouldn't be surprised

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Speaker 2: what else could happen. What do I mean by that, Well,

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Speaker 2: you know when SARS showed up in two thousand and three,

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Speaker 2: remember that was a coronavirus. The severe acute restriatory centrum

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Speaker 2: and I actually worked on that. At that time I

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Speaker 2: was still spending fifty percent of my time at the

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Speaker 2: Department Health Human Service, was probably nine to eleven, and

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Speaker 2: we saw a virus that was not that infectious. A

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Speaker 2: couple of individuals were super spreaders, but basically we were

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Speaker 2: able to contrain that, but about fifteen to twenty percent

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Speaker 2: of the people who got SARS died. Well, then twenty

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Speaker 2: twelve came along and we now had merged middle Eastern

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Speaker 2: of Spriatory Center. We started on the Arabian Peninsula and

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Speaker 2: again I was involved with that investigation as a advisor

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Speaker 2: to the royal family. In the id of the Oar

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Speaker 2: and emericks, we saw a virus that the same way

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Speaker 2: in terms of transmission, wasn't that infectious, with some individuals

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Speaker 2: that were indeed super spreaders, but we could contain that.

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Speaker 2: But now to thirty five percent of the people died

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Speaker 2: who got that infection. With COVID, we had about one

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Speaker 2: and a half percent of the people who got infected died.

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Speaker 2: And today we now have actually documented coronaviruses in the

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Speaker 2: wild that actually have the onboard capability of being transmitted

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Speaker 2: as infectious as COVID was, but also have on board

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Speaker 2: the genetic package to kill at the same level as

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Speaker 2: we saw stars and mers. Now imagine that combination. Instead

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Speaker 2: of one and a half percent of the people dying,

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Speaker 2: we're now talking fifteen to twenty percent. And even in

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Speaker 2: our book we even hypothesize just what would it be

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Speaker 2: like at seven and a half percent deaths among those

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Speaker 2: who got sick. And so you could see, these really

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Speaker 2: are realistic concerns, and they may seem so frightening that

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Speaker 2: we can't do any about them, but we can, we

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Speaker 2: can do a lot about them.

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Speaker 1: It was interesting. So what you're saying is that this

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Speaker 1: coronavirus that we did experience at a one and a

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Speaker 1: half percent death rate doesn't qualify it to be the

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Speaker 1: big one, oh not at.

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Speaker 2: All, not even close. And or an influenza virus like

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Speaker 2: nineteen eighteen, that too, would have killed many, many more

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Speaker 2: people if it were to even happened today, And so

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Speaker 2: that we have to recognize, you know, we could have

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Speaker 2: another COVID like event, but we could have ones that'd

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Speaker 2: be much much more severe. And this isn't movie making.

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Speaker 2: This isn't you know, some kind of scary scenario. These

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Speaker 2: are the realities of what we are dealing with. With

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Speaker 2: these viruses today, you know so much.

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Speaker 1: Of your work before I would well, let me ask

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Speaker 1: you this, how much of your work before twenty twenty

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Speaker 1: was about the virus itself and the science behind it,

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Speaker 1: and less about the sort of the psychology of the

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Speaker 1: public and how it would react to it. You get

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Speaker 1: where I'm going here?

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Speaker 2: Yeah, absolutely, Well, I can't say how much was about

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Speaker 2: the psychology of the public, although I surely was very

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Speaker 2: concerned about that. I actually I wrote an interesting piece

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Speaker 2: back in two thousand and five when H five in

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Speaker 2: one first first showed up and I was able to

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Speaker 2: get the New England journal Medicine, Nature and Science all

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Speaker 2: on the same day to publish the same article that

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Speaker 2: I wrote, so that it was coordinated, calling into question

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Speaker 2: how prepared we were for a future pandemic, and basically

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Speaker 2: laid out all the reasons why we weren't.

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Speaker 1: And didn't you frame that somewhat in bioterrorism, Well, because.

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Speaker 2: Yeah, it wasn't even in two thousand and five. It

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Speaker 2: wasn't even bioterrorism yet, although I surely have talked a

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Speaker 2: lot about the role that bioterrorism could play, and we're

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Speaker 2: very at risk for that very scenario today too. But

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Speaker 2: the point of it was is that we know that

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Speaker 2: these viruses are going to change. Pandemics are inevitable. You know,

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Speaker 2: as I say, the pandemic clock is ticking, we just

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Speaker 2: don't know what time it is. And people may say, well,

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Speaker 2: we just got through a pandemic. We won't have one

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Speaker 2: for a while.

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Speaker 1: Right, It's like a hurricane, is it pandemic season? Michael? Right?

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Speaker 2: Well, or like a hurricane. We just got hit by

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Speaker 2: a hurricanes, so we won't get hit for another twenty

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Speaker 2: or thirty years. Go out and sell the people in

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Speaker 2: the southern United States about that, okay? And so I

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Speaker 2: think that's the challenge we have today is helping people

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Speaker 2: understand one they are going to happen too. They could

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Speaker 2: be a hell of a lot worse than we've already had.

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Speaker 1: Before we get to more on your book, because I

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Speaker 1: am it really does. If it seems to me, you

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Speaker 1: should be busy leading an after action report that is,

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Speaker 1: you know, some sort of joint House, Senate Executive branch.

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Speaker 1: We didn't do it. And I understand our I know

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Speaker 1: why our politics haven't allowed for this to happen, but

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Speaker 1: how much are we just I mean, if I want

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Speaker 1: to prepare for this one. I need to be understanding

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Speaker 1: better what we could have done differently, and did we

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Speaker 1: overreact in some places underreact in others. If you were

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Speaker 1: charged with this after action report, where how would you

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Speaker 1: be focusing your scholarship?

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Speaker 2: Well, first of all, it's really important emphasized that we

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Speaker 2: do have examples for how after action reports can be

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Speaker 2: such important tools for preparing for a future event or

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Speaker 2: even preventing it. For example. You know, I had the

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Speaker 2: good fortune after nine to eleven to spend three years

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Speaker 2: as a fifty percent consultant the Department Health Human Services

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Speaker 2: Tommy Thompson, and was able to get in on the

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Speaker 2: early days of the Bipartisan Commission on nine to eleven,

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Speaker 2: and I watched an event unfold there where it was

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Speaker 2: nonpartisan with incredibly good leadership.

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Speaker 1: This is Tom Kane and Hamilton exactly. Hamilton, Yeah, Lee,

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Speaker 1: Hamilton is two high class guys.

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Speaker 2: Yeah. And you know what, there were a lot of

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Speaker 2: challenges identified worlds efficiencies, but nobody pointed figures. What they

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Speaker 2: did is they added them up. They said what can

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Speaker 2: we do about them? How are we going to deal

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Speaker 2: with them? And you know what, we did A lot

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Speaker 2: that came out of that after after report. Well, now

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Speaker 2: what we have is it's all boiled down to one

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Speaker 2: simple question. We just want to know, why did you

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Speaker 2: lie about Wuhan? And and you know I talked about

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Speaker 2: that in the book and say, we're never going to

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Speaker 2: know whether that virus leak from the lab or whether

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Speaker 2: it was a spillover. I tend to sell personally favor.

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Speaker 2: I think it was a spillover.

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Speaker 1: I was just going to say, I'm an Akham's razor guy.

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Speaker 1: Like you know it the when they when when when

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Speaker 1: the story came out that they found this virus in

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Speaker 1: a remote part of the country, It's like, oh, they

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Speaker 1: were trying to study it. It slipped out. I mean,

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Speaker 1: you know, it feels like, you know, what's the most

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Speaker 1: logical reason, because why would the Chinese want to inflict

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Speaker 1: something that they didn't have a care for exactly.

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Speaker 2: No, I think you're absolutely right. And I think the

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Speaker 2: point being here, though, is that we have to get

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Speaker 2: off of that. You know, I keep saying, there is

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Speaker 2: so much we can do, and and you know.

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Speaker 1: Our friend doctor Fauci would say that it doesn't matter

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Speaker 1: what the origin story is in this in this specific incident,

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Speaker 1: because we've got to We've got to focus on preparation regardless.

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Speaker 2: We got approach. Yeah, we need to prepare for both.

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Speaker 2: And you know, at the very outset, let me just

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Speaker 2: say that this book really has two flavors to it

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Speaker 2: that I don't think are very apparent necessarily. One, it's

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Speaker 2: a love story, and it's a love story to my grandkids,

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Speaker 2: because I sit here and say, oh my god, what

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Speaker 2: kind of world might you experience in the future that

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Speaker 2: we could really do something about. The second thing is

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Speaker 2: I am an optimist at heart. I really believe that

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Speaker 2: we can achieve tremendously important, game changing vaccines in the

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Speaker 2: upcoming years with a really concentrated effort at research, that

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Speaker 2: we could have the vaccines available before the pandemic begins

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Speaker 2: that could be readily deployed, could be highly effective. And

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Speaker 2: if that were the case, we could take pandemics off

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Speaker 2: the table. But we're not doing anything to get there,

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Speaker 2: and that I think is the real challenge, is that

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Speaker 2: it'd be different if we had nothing to do. We

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Speaker 2: don't know what to do. You know, inevitable, we can't

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Speaker 2: stop hurricanes, okay, but in this case, we could stop

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Speaker 2: future pandemics dead in their tracks.

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Speaker 1: Well, let's talk about that. Like, so, I mean, because

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Speaker 1: this is by the way, when you were writing your book,

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Speaker 1: did you assume that there that a Kennedy like figure

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Speaker 1: would purge the CDC the way it's been purged, or

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Speaker 1: did you write this book assuming we wouldn't have something

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Speaker 1: that drastic happened?

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Speaker 2: Well, let's put it this way. It was on the

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Speaker 2: cusp of the intersection of the two. I wrote a

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Speaker 2: piece in November in the New York Times in which

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Speaker 2: I said, my god, world, wake up. This man's going

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Speaker 2: to take our vaccines from us. Okay, go back and

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Speaker 2: look at that piece predicted pretty much of everything is

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Speaker 2: he was going to do has been done, so as

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Speaker 2: I and we were just finishing the book at that point,

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Speaker 2: so we were able to get a little bit of

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Speaker 2: that into the concluding chapters. But I well recognized from

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Speaker 2: the very beginning that he was going to basically destroy

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Speaker 2: public health. Did I have the idea that he would

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Speaker 2: do it as effectively and as quickly as he did? No,

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Speaker 2: I didn't. But I think it's really uh today the

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Speaker 2: biggest challenge public health is faced in fifty years.

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Speaker 1: You know, it's funny I equated. I'm curious of what

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Speaker 1: you think of this metaphor. I equated this sort of

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Speaker 1: surge of anti vax views to what happened. It is

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Speaker 1: not a coincidence now in hindsight, after watching how we

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Speaker 1: behaved during COVID and after COVID as a society to

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Speaker 1: now realize, oh, the pandemic happens in nineteen eighteen, and

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Speaker 1: literally a year later, we're banning alcohol for the next decade,

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Speaker 1: and we sort of lose our minds as a society,

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Speaker 1: and within a decade realized, wait a minute, we're actually

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Speaker 1: killing more people with bootleg alcohol. This is crazy. We

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Speaker 1: just created a criminal syndicates that didn't exist before thanks

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Speaker 1: to bootlegging. Right, is it possible we've we're in the

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Speaker 1: middle of just sort of losing our minds post pandemic.

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Speaker 1: Here is the anti vaxx movement similar to the sort

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Speaker 1: of temperance prohibition movement in that it's always was out there,

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Speaker 1: but it needed a moment to get traction, and COVID

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Speaker 1: was the moment.

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Speaker 2: Well, I think you're right. In fact, while we saw

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Speaker 2: the anti vax activity well before COVID, even ten years

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Speaker 2: ago it started, but in fact, the whole manifestation we

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Speaker 2: see now really I think did come off of COVID.

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Speaker 2: You know, I explained this with the idea that it

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Speaker 2: really is a metaphor for what all the people who

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Speaker 2: thought that the pandemic response was a total failure, if

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Speaker 2: not really a punishment in of itself, now have equated

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Speaker 2: those feelings to the vaccine. Remember, the vaccine initially was

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Speaker 2: heralded as President Trump's great accomplishment, and everybody thought this

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Speaker 2: was going to be the end all of the pandemic. Well,

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Speaker 2: we didn't do a good job explaining that part that

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Speaker 2: it was not going to be, but it was still

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Speaker 2: going to have a major impact. And then when basically

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Speaker 2: the pandemic began to end and no one could complain

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Speaker 2: about what was happening in terms of mandates and things

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Speaker 2: like that, they still needed a way to be angry

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Speaker 2: about it. And so it became the vaccine. And so today,

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Speaker 2: so much I think of what is aimed at anti

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Speaker 2: vaccine overall did come from COVID, And it came from

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Speaker 2: this idea. You know, it's like out of network. You know,

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Speaker 2: I'm really damn mad at about everything.

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Speaker 1: I'm going to be mad, and I'm just going to

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Speaker 1: be mad. Yeah, so we're if we're in a world

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Speaker 1: where the government can't lead on public health. How do

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Speaker 1: you prepare for the next big one?

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Speaker 2: Well, let me give you an example of what I

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Speaker 2: think is just such an apparent mistake right now that's

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Speaker 2: happening to our current capacity to make influenza vaccine, which

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Speaker 2: is a good vaccine, not a great one. It doesn't

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Speaker 2: stop you from getting In fact, it doesn't stop you

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Speaker 2: from even necessarily getting sick, but it has a lot

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Speaker 2: to do with preventing you from having serious illness, hospitalizations,

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Speaker 2: and death, which I'll take any day of the week

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Speaker 2: as an outcome. If we were to have to make

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Speaker 2: of vaccine overnight for an emerging pandemic, using the egg

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Speaker 2: base approach we do for growing the virus as an

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Speaker 2: inberated chicken egg or a little bit of cell culture,

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Speaker 2: we could make enough vaccine in the first year to

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Speaker 2: fifteen months to only vaccinate about a quarter of the world.

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Speaker 2: That's it. mRNA technology, which of course was very important

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Speaker 2: in the COVID response, actually could change that substantially. And

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Speaker 2: in this case, what we're talking about is a vaccine

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Speaker 2: that still is good, not great. We want even better vaccines,

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Speaker 2: but we could make enough COVID vaccine for flu with

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Speaker 2: to vaccinate the world likely in the first year. The

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Speaker 2: difference between those two scenarios is literally millions and millions

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Speaker 2: of deaths, millions of deaths. And yet we just ended

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Speaker 2: a five hundred million dollar investment in trying to make

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Speaker 2: sure that we had the technology available and ready to

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Speaker 2: go to make a COVID flash influenza mRNA vaccine. And

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Speaker 2: why why did we do that? Because it was about ideology.

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Speaker 2: It wasn't about the real science.

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Speaker 1: Yeah, there's the Kennedy never produces science to back up

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Speaker 1: his gut feelings. There's never even like bad scientific research.

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Speaker 1: There's none.

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Speaker 2: It's it's it beyond description of what this is. And

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Speaker 2: I have to tell you last Thursday and Friday, the

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Speaker 2: Advisory Communityanization Practices met at CDCs. You know, this was

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Speaker 2: the advisory group to the CDC.

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Speaker 1: Have you ever been on that group? I have not.

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Speaker 2: I have nourious, but I've advised it for a number

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Speaker 2: of years. But the bottom line was is that I

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Speaker 2: have seen high school student console meetings held with more decorum,

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Speaker 2: practice and effectiveness than I saw at that meeting last week.

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Speaker 1: Wait, but the pharmacist said that she knew four different

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Speaker 1: people who had gotten the vaccine and something bad happened

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Speaker 1: to them.

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Speaker 2: Yeah, it was.

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Speaker 1: It was I'm sorry. That was like really set me off, Like,

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Speaker 1: what the hell are we doing? We literally have just

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Speaker 1: some random pharmacist who may or may not be well trained.

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Speaker 1: I mean there are good pharmacies out there, don't get

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Speaker 1: me wrong. You have to go through real training. But

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Speaker 1: what do they know about the making of these things?

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Speaker 2: They don't. And I think what was really more telling

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Speaker 2: is you have somebody who's an expert in supply chain

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Speaker 2: management out of the business world telling us all about

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Speaker 2: the imminology of mRNA vaccine technology and had no idea

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Speaker 2: what he was talking about. And yet that came across

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Speaker 2: that but it was more important. I mean we actually

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Speaker 2: had an example I can't get I can't make this

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Speaker 2: stuff up where one of the members, on a hot

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Speaker 2: mic moment said, what do we just vote for?

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Speaker 1: What was it?

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Speaker 2: I mean he didn't even know what they voted for.

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Speaker 2: I mean that was emblematic of the entire two Well,

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Speaker 2: what is it?

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Speaker 1: They they voted against recommending the vaccine, but they're not

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Speaker 1: going to force a prescription for it.

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Speaker 2: Well for the chicken pox and MMR vaccine combination. They basically,

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Speaker 2: we've known about this for years and have made recommendation

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Speaker 2: instead of having the combined vaccine for the first dose,

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Speaker 2: give the verasellar or the chicken pox vaccine separate from

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Speaker 2: the MMR and therefore you don't have febrile seizures. These

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Speaker 2: things that racing are benign. But you know it's hard

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Speaker 2: for a parent to see. But that means you're going

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Speaker 2: to get an extra stick and only then make it

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Speaker 2: available for the second dose, where we don't see that

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Speaker 2: phenomenon at all. Well, they voted to take away the

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Speaker 2: ability to use the two or the single vaccine for

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Speaker 2: the young kids, but then they took a vote to

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Speaker 2: have the vaccine for children's program paid for it, which

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Speaker 2: seemed a little inconsistent. Okay, so they had to come

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Speaker 2: back the next day and revote to undo the vote

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Speaker 2: they did the day before. Again, you can't make this

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Speaker 2: stuff up.

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Speaker 1: There's a reason results matter more than promises, just like

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Speaker 1: there's a reason Morgan and Morgan is America's largest injury

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Speaker 1: It includes cases where insurance companies offered next to nothing,

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Speaker 1: Morgan and Morgan fought back ended up winning millions. In fact,

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Speaker 1: which was a staggering forty times the amount that the

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Speaker 1: insurance company originally offered. That original offer six hundred and

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Speaker 1: fifty thousand dollars twenty six million, six hundred and fifty

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Speaker 1: thousand dollars. So with more than one thousand lawyers across

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Speaker 1: the country, they know how to deliver for everyday people.

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Speaker 1: are not the same. So check out Morgan and Morgan.

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Speaker 1: Their fee is free unless they win. No, I mean,

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Speaker 1: it's Keystone Cops. Doesn't really doesn't really doesn't even work

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Speaker 1: as a as a as a good description there, So

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Speaker 1: I go back, let's go back to if we don't

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Speaker 1: have a government essentially getting I mean this moved to

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Speaker 1: Mr nax vaccines and this technology I mean, and the

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Speaker 1: stuff it's doing in cancer treatments and this I mean.

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Speaker 1: To think that we have just pulled all this funding.

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Speaker 1: I mean, it feels like we just It's as if

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Speaker 1: we said, you know what, this whole electricity thing, let's

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Speaker 1: go back to candles. I mean, I where does this

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Speaker 1: research go? Is it all going to be dispersed in

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Speaker 1: universities and if the or are we going to just

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Speaker 1: have less and less of this research and hope that

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Speaker 1: the French and the Koreans have more success.

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Speaker 2: Well, let me just paint a very quick landscape picture

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Speaker 2: of what's happening simultaneously. Because it's not added, it's really

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Speaker 2: in a sense multiplicative in terms of impact. You know,

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Speaker 2: we destroyed basically our ability on an international level to

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Speaker 2: be part of anything as it relates to infectious disease issue.

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Speaker 2: We pulled out, We destroyed USAID, we destroyed PEP far

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Speaker 2: one of the most important programs that this country has

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Speaker 2: ever done in terms of soft diplomacy, you know, bringing

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Speaker 2: the very best of this country to low and middle

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Speaker 2: income countries where now we see thirty million individuals who

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Speaker 2: are HIV infected, who will likely die in the mediate

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Speaker 2: years ahead because we no longer can get them drug treatment. Okay,

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Speaker 2: pennies a day we were spending on this program. We

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Speaker 2: now no longer have contact with the world to understand,

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Speaker 2: for example, what is really happening with ebola in the Congo,

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Speaker 2: what's going on in Africa, And we have an outbreak

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Speaker 2: right now in DRC that is of real importance, and

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Speaker 2: so we're totally out of the picture internationally. And you know,

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Speaker 2: we controlled a lot of infectious diseases over there, so

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Speaker 2: it didn't even get to our border. Now we have

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Speaker 2: to understand our border is going to keep getting hit

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Speaker 2: day after day with these infectious diseases because we're not

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Speaker 2: stopping them on a global basis.

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Speaker 1: Now the tariffs will help. Okay, sorry, you know more

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Speaker 1: about that. I'm trying a little bit of trying a

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Speaker 1: little bit of terror fumor. I guess it didn't worry anyway, No, no,

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Speaker 1: I hear it.

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Speaker 2: So, first of all, that's the first issue. The second

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Speaker 2: issue is is that, you know, again I mentioned it earlier,

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Speaker 2: right now, there is not one single senior scientist in

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Speaker 2: a leadership position at CDC. Do you know, for the

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Speaker 2: first time in decades, we no longer have anyone in

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Speaker 2: the White House that has any biopreparedness expertise, Nobody in

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Speaker 2: the National Security Council. These used to be major activities

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Speaker 2: where basically they were air traffic control for our federal

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Speaker 2: response we had.

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Speaker 1: Correct me if I'm wrong, but I think Bush, the

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Speaker 1: Bush team, and the Obama team together and me did

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Speaker 1: a pandemic simulation. Oh, absolutely right, and I did. Did

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Speaker 1: Obama in fact even do that with Team Trump in

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Speaker 1: the first term. I think anyway, there's these they didn't need.

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Speaker 2: Yeah, I think they say that Team Trump in the

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Speaker 2: first administration actually had a very comprehensive and I think

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Speaker 2: really quite credible plan that just has been thrown away.

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Speaker 1: It's got doctor. I mean, look, I think not enough

436
00:23:07,119 --> 00:23:10,160
Speaker 1: credit is given to rights previous and Mike Pence. They

437
00:23:10,800 --> 00:23:14,760
Speaker 1: put built the first Trump administration, and you know, they've

438
00:23:14,840 --> 00:23:17,359
Speaker 1: gotten a lot of grief from the mainstream world, and

439
00:23:18,960 --> 00:23:21,440
Speaker 1: I think in hindsight, they did a lot of the

440
00:23:22,080 --> 00:23:24,720
Speaker 1: They put in a lot of guardrails that held up

441
00:23:24,880 --> 00:23:26,639
Speaker 1: for a term that were very important.

442
00:23:27,000 --> 00:23:29,040
Speaker 2: And you know, Chuck, you know you've worked with me

443
00:23:29,119 --> 00:23:31,679
Speaker 2: for long enough to know you know, I have served

444
00:23:32,080 --> 00:23:34,040
Speaker 2: in formal roles with every administration.

445
00:23:34,160 --> 00:23:37,000
Speaker 1: Since you're about it's a political of a person that I.

446
00:23:36,920 --> 00:23:39,640
Speaker 2: Know pure you know, and you know, I serve two

447
00:23:39,680 --> 00:23:42,760
Speaker 2: Republican governors, two Democratic governors, won independent wrestler here in

448
00:23:42,760 --> 00:23:47,679
Speaker 2: Minnesota at the state Health Department, and yeah, you know,

449
00:23:47,720 --> 00:23:49,800
Speaker 2: my job is just to be a member of the

450
00:23:49,840 --> 00:23:52,600
Speaker 2: public health army to fight these things. So my comments

451
00:23:52,640 --> 00:23:55,359
Speaker 2: are not at all partisans But what we're seeing happen

452
00:23:55,480 --> 00:23:58,960
Speaker 2: right now is one that is not about partisan. It's

453
00:23:59,000 --> 00:24:03,639
Speaker 2: about destroying the very infrastructure that got us the benefits

454
00:24:03,680 --> 00:24:06,640
Speaker 2: that we have so enjoyed in this country. And we're

455
00:24:06,640 --> 00:24:09,680
Speaker 2: going to see a number of diseases come back that

456
00:24:09,760 --> 00:24:12,040
Speaker 2: we thought we had gotten rid of, and we're not.

457
00:24:13,040 --> 00:24:16,840
Speaker 1: I I have this sneaking suspicion that we've got quite

458
00:24:16,880 --> 00:24:22,960
Speaker 1: a few doctors, family doctors who will not recognize mumps

459
00:24:23,040 --> 00:24:25,520
Speaker 1: or measles at first because it's been so long since

460
00:24:25,560 --> 00:24:28,320
Speaker 1: they've been in circulation. The doctors may not be able

461
00:24:28,320 --> 00:24:32,359
Speaker 1: to diagnose what a child has because of this.

462
00:24:32,800 --> 00:24:35,200
Speaker 2: Well, you know, just this past week, it's been noted

463
00:24:35,359 --> 00:24:39,240
Speaker 2: the Shagu's disease, a type of parasitic disease transmitted by

464
00:24:39,280 --> 00:24:41,920
Speaker 2: a bug called the kissing bug because it tends to

465
00:24:42,119 --> 00:24:44,119
Speaker 2: go to your face when you're sleeping at night and

466
00:24:44,160 --> 00:24:49,600
Speaker 2: bite you, and it actually causes potentially very severe heart disease.

467
00:24:50,119 --> 00:24:53,160
Speaker 2: The vast majority of doctors in this country couldn't tell

468
00:24:53,160 --> 00:24:56,000
Speaker 2: you what Shagu's disease was, let alone diagnose the case.

469
00:24:56,840 --> 00:24:59,119
Speaker 2: And that's all coming in now from the southern border.

470
00:24:59,160 --> 00:25:01,480
Speaker 2: We now have the twelve states in which this bug

471
00:25:01,560 --> 00:25:04,720
Speaker 2: is commonly found. Fifteen twenty years ago, we would never

472
00:25:04,800 --> 00:25:06,960
Speaker 2: talked about this. So do I think this is because

473
00:25:07,000 --> 00:25:09,199
Speaker 2: of the breakdown of public health? Not necessarily, but the

474
00:25:09,359 --> 00:25:14,480
Speaker 2: challenges that we're seeing globally is growing immensely, and I

475
00:25:14,520 --> 00:25:17,160
Speaker 2: think so when I talk about the problems of today,

476
00:25:17,560 --> 00:25:20,400
Speaker 2: there are problems that would have happened anyway, but we're

477
00:25:20,400 --> 00:25:23,000
Speaker 2: making them a lot worse. And of course we're doing nothing,

478
00:25:23,600 --> 00:25:25,800
Speaker 2: as we talk about in the book to prepares for tomorrow.

479
00:25:26,840 --> 00:25:29,320
Speaker 1: Well, and you know, some of the things you talk

480
00:25:29,359 --> 00:25:33,560
Speaker 1: about in here are sort of some I don't know

481
00:25:33,600 --> 00:25:35,280
Speaker 1: if I would call them lifestyle chain I guess I

482
00:25:35,280 --> 00:25:37,840
Speaker 1: would call them architectural changes right where it comes to

483
00:25:38,200 --> 00:25:40,280
Speaker 1: how do you improve airflow and how do you do

484
00:25:40,640 --> 00:25:48,880
Speaker 1: like some preventative things to at least slow the spread

485
00:25:49,160 --> 00:25:51,879
Speaker 1: of a deadly virus goes through some of them, because

486
00:25:52,320 --> 00:25:55,160
Speaker 1: are these things we can do without the government?

487
00:25:55,359 --> 00:25:57,680
Speaker 2: Yeah, well, let me just first of all say that,

488
00:25:58,160 --> 00:26:00,600
Speaker 2: and you know me well enough. Also, this is not

489
00:26:00,840 --> 00:26:04,639
Speaker 2: barely trying to gain favor with the moderator here, but you,

490
00:26:04,960 --> 00:26:06,760
Speaker 2: as I've shared with you in the past, or one

491
00:26:06,760 --> 00:26:10,720
Speaker 2: of the few media people that really understood what you

492
00:26:10,720 --> 00:26:14,199
Speaker 2: were asking and what you were talking about. And you know,

493
00:26:14,240 --> 00:26:17,080
Speaker 2: I can remember one episode on Meet the Press with

494
00:26:17,119 --> 00:26:18,920
Speaker 2: you where I said I thought the darkest days of

495
00:26:18,960 --> 00:26:21,600
Speaker 2: the pandemic were still ahead of its. People like Nate

496
00:26:21,640 --> 00:26:24,159
Speaker 2: Silver and others just nailed me for that. You know,

497
00:26:24,240 --> 00:26:25,199
Speaker 2: here I was scary.

498
00:26:25,200 --> 00:26:25,520
Speaker 1: Again.

499
00:26:25,680 --> 00:26:28,480
Speaker 2: Over half the deaths and the pandemic occurred after that moment.

500
00:26:29,080 --> 00:26:31,400
Speaker 2: You know, it wasn't at the end. And I think

501
00:26:31,440 --> 00:26:33,600
Speaker 2: one of the things that we failed to do was

502
00:26:33,760 --> 00:26:37,000
Speaker 2: have that kind of creative imagination understand what would this

503
00:26:37,119 --> 00:26:39,720
Speaker 2: look like for three or more years. I wrote a

504
00:26:39,760 --> 00:26:43,119
Speaker 2: piece in the Washington Post in early March of twenty

505
00:26:43,160 --> 00:26:46,040
Speaker 2: twenty saying, do not do lockdowns. They won't work. Don't

506
00:26:46,040 --> 00:26:48,800
Speaker 2: do them. And it was all about the fact that

507
00:26:48,840 --> 00:26:50,760
Speaker 2: are we prepared to do that for the next two

508
00:26:50,800 --> 00:26:52,720
Speaker 2: to three years. You know, this is not like a

509
00:26:52,800 --> 00:26:55,240
Speaker 2: hurricane where it's going to blow through and do incredible

510
00:26:55,320 --> 00:26:58,280
Speaker 2: damage in eighteen hours and then we go into recovery.

511
00:26:58,520 --> 00:27:00,680
Speaker 2: We were going to have surge after surge of these

512
00:27:00,720 --> 00:27:02,919
Speaker 2: cases and we had to be prepared for that. And

513
00:27:02,960 --> 00:27:05,320
Speaker 2: so what we proposed, And again just to address the

514
00:27:05,400 --> 00:27:08,119
Speaker 2: question you asked, what can we do a process like

515
00:27:08,200 --> 00:27:11,159
Speaker 2: snow days, Because in fact, the one thing that we

516
00:27:11,200 --> 00:27:14,440
Speaker 2: could do to save lives was to have good medical care.

517
00:27:14,920 --> 00:27:17,679
Speaker 2: And when your hospitals at one hundred and forty percent capacity,

518
00:27:18,000 --> 00:27:21,960
Speaker 2: you don't have healthcare period, let alone good healthcare. And

519
00:27:22,040 --> 00:27:24,160
Speaker 2: so what we should have done is instead of having

520
00:27:24,200 --> 00:27:27,480
Speaker 2: these lockdowns, which by the way, have been grossly overstated

521
00:27:27,480 --> 00:27:29,800
Speaker 2: at what they were. Right, we had forty one states

522
00:27:30,000 --> 00:27:35,119
Speaker 2: that had some information out about minimizing contact for a

523
00:27:35,200 --> 00:27:38,040
Speaker 2: period of two months basically from end of March till

524
00:27:38,119 --> 00:27:40,119
Speaker 2: end of June. By June they were all over with

525
00:27:40,440 --> 00:27:44,199
Speaker 2: a state like Minnesota had a basically stay at home

526
00:27:44,359 --> 00:27:45,880
Speaker 2: order except for essential work.

527
00:27:45,920 --> 00:27:49,200
Speaker 1: Well, well you know what I shout to, Well, well, Michael,

528
00:27:49,240 --> 00:27:51,159
Speaker 1: I'll chuck it up to the fact that DC and

529
00:27:51,200 --> 00:27:54,879
Speaker 1: New York were probably the most small sea conservative metro

530
00:27:54,960 --> 00:27:59,000
Speaker 1: areas in the country in what was closed and what

531
00:27:59,119 --> 00:28:02,119
Speaker 1: was open, and because that's where ninety percent of the

532
00:28:02,200 --> 00:28:05,159
Speaker 1: media people lived. Ye, and you know, I think it

533
00:28:05,200 --> 00:28:09,480
Speaker 1: got an outsize because you're everywhere else it was sort

534
00:28:09,480 --> 00:28:13,320
Speaker 1: of what I would call sensible lockdown, right, which was okay,

535
00:28:13,480 --> 00:28:16,760
Speaker 1: you know, everybody else did it within within sort of

536
00:28:17,400 --> 00:28:20,800
Speaker 1: common sense. This New York City and Washington, d C.

537
00:28:20,920 --> 00:28:24,840
Speaker 1: Were just sort of more elevated than other places. And

538
00:28:24,920 --> 00:28:27,280
Speaker 1: I think it had an impact on the coverage.

539
00:28:27,440 --> 00:28:29,120
Speaker 2: I just did not absolutely right. No, I think you're

540
00:28:29,119 --> 00:28:33,440
Speaker 2: absolutely right. And what we had proposed was do snow days.

541
00:28:33,760 --> 00:28:36,879
Speaker 2: What does that mean if we could let every person

542
00:28:36,960 --> 00:28:39,680
Speaker 2: know every day what our hospital census was for our

543
00:28:39,720 --> 00:28:42,520
Speaker 2: hospitals and our community, and if we got to ninety

544
00:28:42,600 --> 00:28:45,800
Speaker 2: ninety five percent, please for the next two weeks, you know,

545
00:28:46,000 --> 00:28:46,960
Speaker 2: back off public.

546
00:28:47,040 --> 00:28:48,680
Speaker 1: We're not going to work from home. Let's try to

547
00:28:48,720 --> 00:28:49,360
Speaker 1: work from home.

548
00:28:49,520 --> 00:28:52,440
Speaker 2: Let's do a few that schools may be closed temporarily

549
00:28:52,760 --> 00:28:55,680
Speaker 2: remote that number back down so that if you do

550
00:28:55,720 --> 00:28:58,000
Speaker 2: get sick, you can get good medical care, because that's

551
00:28:58,040 --> 00:28:59,400
Speaker 2: all we can really offer. Well.

552
00:28:59,440 --> 00:29:01,959
Speaker 1: And the more thing is, as we learned, I mean,

553
00:29:02,000 --> 00:29:05,920
Speaker 1: we all learned there was COVID seasons plural meaning right,

554
00:29:06,240 --> 00:29:10,000
Speaker 1: it was it was the summer was peak in the south,

555
00:29:10,440 --> 00:29:12,560
Speaker 1: the winter was peak in the north.

556
00:29:12,640 --> 00:29:12,760
Speaker 2: Right.

557
00:29:12,800 --> 00:29:15,800
Speaker 1: We had all these different so it wasn't a one

558
00:29:16,560 --> 00:29:21,520
Speaker 1: We've learned that, it wasn't one set of rules to

559
00:29:21,640 --> 00:29:26,720
Speaker 1: fit all different regions were in different had different capacities

560
00:29:26,760 --> 00:29:29,040
Speaker 1: and different surges.

561
00:29:28,920 --> 00:29:30,640
Speaker 2: Right, and that's what we needed to get across. So

562
00:29:30,640 --> 00:29:32,120
Speaker 2: we're going to be in this for the long haul,

563
00:29:32,520 --> 00:29:34,840
Speaker 2: and so we had to find a way. An example

564
00:29:34,840 --> 00:29:38,160
Speaker 2: of what the lockdown world really was if you did

565
00:29:38,200 --> 00:29:40,560
Speaker 2: it as we all thought we did, would be what

566
00:29:40,600 --> 00:29:43,880
Speaker 2: happened in China. They actually had major areas of China

567
00:29:43,920 --> 00:29:46,640
Speaker 2: that were truly locked out, where people literally had food

568
00:29:46,640 --> 00:29:48,760
Speaker 2: delivered to their homes. They didn't leave their homes for

569
00:29:48,880 --> 00:29:52,880
Speaker 2: months and months, well without vaccinating that crowd. Finally, the

570
00:29:52,920 --> 00:29:55,960
Speaker 2: social pressures got so great that they basically relaxed these

571
00:29:56,440 --> 00:30:00,800
Speaker 2: these lockdowns there and guess what millions of Chinese later

572
00:30:00,840 --> 00:30:03,680
Speaker 2: in the pandemic, not earlier, because once they were not

573
00:30:03,800 --> 00:30:06,400
Speaker 2: no longer in lockdown, they basically had it. So, as

574
00:30:06,440 --> 00:30:09,000
Speaker 2: I've said, multiple times, whether you died the first six months,

575
00:30:09,000 --> 00:30:11,160
Speaker 2: the second six months, the third six months, or the

576
00:30:11,200 --> 00:30:13,000
Speaker 2: four six months. You were pretty much dead at the

577
00:30:13,040 --> 00:30:15,920
Speaker 2: end of the pandemic. And so our job was to

578
00:30:15,920 --> 00:30:18,920
Speaker 2: get us through three years of what was going to

579
00:30:18,960 --> 00:30:22,360
Speaker 2: happen and anticipate that, and we didn't do that, and

580
00:30:22,400 --> 00:30:25,040
Speaker 2: that by itself would be a lesson for the future

581
00:30:25,520 --> 00:30:28,480
Speaker 2: of how do we approach this. Don't do lockdown, talk

582
00:30:28,520 --> 00:30:33,000
Speaker 2: about managing the maximize medical care so it's available. No.

583
00:30:33,120 --> 00:30:35,120
Speaker 1: I mean, in some ways, COVID came right when the

584
00:30:35,160 --> 00:30:39,200
Speaker 1: technology gave us the opportunity to actually not shut off

585
00:30:39,240 --> 00:30:40,960
Speaker 1: our economy at the same time.

586
00:30:41,360 --> 00:30:43,640
Speaker 2: It did And I think that I gave you that,

587
00:30:43,400 --> 00:30:47,600
Speaker 2: But that was vaccines, you know. I've also wrote about

588
00:30:47,600 --> 00:30:50,160
Speaker 2: this and also talked about this with my colleagues off

589
00:30:50,200 --> 00:30:52,920
Speaker 2: it and again was not always necessarily seen as the

590
00:30:53,000 --> 00:30:55,720
Speaker 2: person we wanted to invite to the party. But I

591
00:30:55,800 --> 00:30:59,760
Speaker 2: had indicated early on ninety six percent protection in those

592
00:30:59,760 --> 00:31:02,320
Speaker 2: first two months, which was the data that we had

593
00:31:02,400 --> 00:31:07,240
Speaker 2: from those vaccine trials was remarkable. But we know about coronaviruses.

594
00:31:07,400 --> 00:31:10,560
Speaker 2: They tend to have weaning immunity over time, and we've

595
00:31:10,600 --> 00:31:15,240
Speaker 2: seen that multiple examples with the cold causing coronaviruses. So

596
00:31:15,280 --> 00:31:17,960
Speaker 2: I had actually said, how about every month we put

597
00:31:18,000 --> 00:31:20,880
Speaker 2: a number out for this cohort and we follow up

598
00:31:20,880 --> 00:31:24,040
Speaker 2: and say it's ninety four percent today, next month is

599
00:31:24,080 --> 00:31:26,880
Speaker 2: eighty eight percent, the following month is seventy two percent,

600
00:31:27,320 --> 00:31:29,640
Speaker 2: and you guess what, we're going to need boosters, but

601
00:31:29,720 --> 00:31:32,520
Speaker 2: you'll know the number. We'll tell you. Imagine if we

602
00:31:32,560 --> 00:31:34,920
Speaker 2: had done that then having people assumed that when they

603
00:31:34,920 --> 00:31:36,960
Speaker 2: got their two doses, it was done and over with.

604
00:31:37,560 --> 00:31:40,040
Speaker 1: Now I that for the life of me, you know,

605
00:31:40,080 --> 00:31:42,520
Speaker 1: I went back and racked my brain on this, and

606
00:31:42,600 --> 00:31:44,959
Speaker 1: I really guess we got to blame the politicians because

607
00:31:45,320 --> 00:31:47,920
Speaker 1: I feel like we were all careful in reporting. Hey, look,

608
00:31:49,240 --> 00:31:52,560
Speaker 1: this vaccine is about preventing death, not preventing the virus,

609
00:31:53,080 --> 00:31:55,800
Speaker 1: not preventing symptoms. You are going to get a cold,

610
00:31:56,200 --> 00:31:57,960
Speaker 1: you know it. Maybe it just isn't going to be

611
00:31:58,000 --> 00:31:59,880
Speaker 1: as harsh and it isn't going to kill you, and

612
00:32:00,200 --> 00:32:04,200
Speaker 1: this is what it's for. But you know, I mean,

613
00:32:04,240 --> 00:32:08,760
Speaker 1: this is where the absolutism right of our political conversation

614
00:32:08,960 --> 00:32:11,719
Speaker 1: created the illusion that the virus was going to make

615
00:32:11,720 --> 00:32:16,480
Speaker 1: people immune from COVID. And boy, this is where it's

616
00:32:16,480 --> 00:32:20,320
Speaker 1: obvious our information ecosystem was already broken by the time

617
00:32:20,360 --> 00:32:25,600
Speaker 1: of twenty twenty because mainstream reporting never was implying saying that,

618
00:32:25,720 --> 00:32:28,840
Speaker 1: or even implying it. Only the politician a few politicians.

619
00:32:28,240 --> 00:32:31,400
Speaker 2: Were yeah, well, and I think that's exactly the point.

620
00:32:31,440 --> 00:32:33,800
Speaker 2: So again, preparing for the future, how do we prepare

621
00:32:33,800 --> 00:32:36,880
Speaker 2: the news media as well as the public to understand

622
00:32:36,920 --> 00:32:40,560
Speaker 2: messaging and what that means. And I think that by itself,

623
00:32:40,600 --> 00:32:42,440
Speaker 2: if we just had had that so the things we

624
00:32:42,560 --> 00:32:45,320
Speaker 2: just talked about, if we could actually dramatically improve our

625
00:32:45,400 --> 00:32:48,800
Speaker 2: vaccine capability, which we can do if we just have

626
00:32:49,080 --> 00:32:52,240
Speaker 2: dedicated fun instead of one aircraft carrier. And I'm not

627
00:32:52,240 --> 00:32:54,520
Speaker 2: a defense expert, so I'm not here to bast DoD

628
00:32:54,880 --> 00:33:00,840
Speaker 2: or war doow I guess you know that'll could get

629
00:33:00,920 --> 00:33:04,640
Speaker 2: us the technology for this. And again what's happened is

630
00:33:04,680 --> 00:33:08,040
Speaker 2: not only have we taken the mRNA vaccines off the table,

631
00:33:08,120 --> 00:33:13,000
Speaker 2: but there's one of mister you know, Kennedy's key people

632
00:33:13,040 --> 00:33:15,080
Speaker 2: who is now the head of the NIH who has

633
00:33:15,120 --> 00:33:17,600
Speaker 2: made a decision to put five hundred million dollars into

634
00:33:17,680 --> 00:33:20,880
Speaker 2: an influenza vaccine that we've proven over the past four

635
00:33:20,920 --> 00:33:24,560
Speaker 2: decades doesn't work well. You know what's that about. But

636
00:33:24,640 --> 00:33:26,880
Speaker 2: if we could change that, we could talk about the

637
00:33:26,920 --> 00:33:28,719
Speaker 2: things that we just did about how do you keep

638
00:33:28,760 --> 00:33:31,400
Speaker 2: people from staying out of the hospital, you know, how

639
00:33:31,400 --> 00:33:34,560
Speaker 2: do we convey messaging in a way that isn't about

640
00:33:35,320 --> 00:33:38,320
Speaker 2: lockdowns or not lockdowns? We could I think comes through

641
00:33:38,360 --> 00:33:40,440
Speaker 2: this in a very different way.

642
00:33:40,840 --> 00:33:46,200
Speaker 1: Right there's almost like a very sort of dry way

643
00:33:46,240 --> 00:33:47,920
Speaker 1: of doing this, almost like a you know, like you

644
00:33:47,920 --> 00:33:50,240
Speaker 1: would if this were a department in the military. Okay,

645
00:33:50,640 --> 00:33:52,920
Speaker 1: this is how we will prepare for this battle. And

646
00:33:52,960 --> 00:33:55,000
Speaker 1: we're going to have data on this, and we'll have

647
00:33:55,120 --> 00:33:57,400
Speaker 1: data on this, and we're going to have our hospitalization

648
00:33:57,560 --> 00:34:00,960
Speaker 1: data trigger when we do locked schools shut downs, And

649
00:34:01,520 --> 00:34:04,360
Speaker 1: I mean, all that makes that's that's perfectly logical what

650
00:34:04,880 --> 00:34:08,280
Speaker 1: you're laying out here and exactly what people do expect

651
00:34:08,320 --> 00:34:12,520
Speaker 1: government to be capable of. And Kennedy is just you know,

652
00:34:13,719 --> 00:34:14,960
Speaker 1: he's the virus right now.

653
00:34:15,280 --> 00:34:17,160
Speaker 2: In fact, let me just add a piece to that,

654
00:34:17,239 --> 00:34:19,880
Speaker 2: because I think you and I actually discussed this on

655
00:34:19,920 --> 00:34:24,240
Speaker 2: the air several years ago, was the issue of school kids.

656
00:34:24,719 --> 00:34:27,360
Speaker 2: You know, early on, there was this conclusion that this

657
00:34:27,520 --> 00:34:30,640
Speaker 2: virus was really not that damaging to kids. You know,

658
00:34:30,880 --> 00:34:33,200
Speaker 2: they weren't seeing the same number of desks. For you know,

659
00:34:33,239 --> 00:34:35,799
Speaker 2: a number of people infected, et cetera. And in the

660
00:34:35,840 --> 00:34:38,080
Speaker 2: first year of the pandemic, one hundred and ninety nine

661
00:34:38,160 --> 00:34:41,080
Speaker 2: kids in this country died from COVID, and there were

662
00:34:41,120 --> 00:34:43,680
Speaker 2: a number of studies that came out saying, see, look

663
00:34:43,680 --> 00:34:45,600
Speaker 2: at this is not a big risk compared to what

664
00:34:45,640 --> 00:34:49,040
Speaker 2: we're seeing. But then when the new variants, the delta

665
00:34:49,120 --> 00:34:52,240
Speaker 2: and omicron variants showed up, that changed, and in fact,

666
00:34:52,440 --> 00:34:54,960
Speaker 2: there were six hundred and twelve deaths the second year,

667
00:34:55,239 --> 00:34:57,719
Speaker 2: and they were almost eight hundred desks the third year.

668
00:34:58,320 --> 00:35:01,080
Speaker 2: Eighty seven percent of the dest kids occurred in year

669
00:35:01,120 --> 00:35:04,840
Speaker 2: two and three. Yeah, we were operating by the rules

670
00:35:04,880 --> 00:35:08,040
Speaker 2: of what was year one, and we to get that

671
00:35:08,120 --> 00:35:09,920
Speaker 2: message out to say, wait a minute, we got to

672
00:35:09,920 --> 00:35:12,719
Speaker 2: look at this little carefully. Now. There was a wonderful

673
00:35:12,760 --> 00:35:17,160
Speaker 2: study done in the Boston area basically looking at kids.

674
00:35:17,719 --> 00:35:21,120
Speaker 2: In the most comprehensive study today, about eighty percent of

675
00:35:21,120 --> 00:35:24,920
Speaker 2: the transmission in year two and three in households occurred

676
00:35:24,960 --> 00:35:27,200
Speaker 2: because of a child bringing the virus home from school,

677
00:35:28,200 --> 00:35:30,319
Speaker 2: and we didn't adjust to that. That's the other thing

678
00:35:30,360 --> 00:35:32,880
Speaker 2: we have to do is have situational awareness to say

679
00:35:33,040 --> 00:35:35,880
Speaker 2: this is what it was. Then didn't tell you something wrong,

680
00:35:36,080 --> 00:35:37,440
Speaker 2: But now look what's happened.

681
00:35:37,880 --> 00:35:40,440
Speaker 1: You know, we treat science and this is a I

682
00:35:40,480 --> 00:35:43,760
Speaker 1: guess I would put this in the larger political community

683
00:35:43,760 --> 00:35:46,920
Speaker 1: and I throw the press in there. In this. What

684
00:35:46,960 --> 00:35:51,319
Speaker 1: you're describing is we treat science like it's a politician

685
00:35:51,360 --> 00:35:54,960
Speaker 1: who makes who declares a position on an issue, and

686
00:35:55,000 --> 00:35:57,719
Speaker 1: then when they try to change their position, we call

687
00:35:57,760 --> 00:36:00,799
Speaker 1: them a flip flopper. Well, in the world is science, right,

688
00:36:01,000 --> 00:36:03,960
Speaker 1: what the data says on year one is not necessarily

689
00:36:03,960 --> 00:36:06,359
Speaker 1: going to be the data because you know, nothing is

690
00:36:07,400 --> 00:36:09,919
Speaker 1: nothing is permanent in the world of science, right, there's

691
00:36:09,920 --> 00:36:15,959
Speaker 1: always and our lizard brains, right, our political lizard brain

692
00:36:16,520 --> 00:36:20,760
Speaker 1: can't seem to convey that it's normal for the science

693
00:36:20,840 --> 00:36:24,000
Speaker 1: to change. It's not unusual for the science to change.

694
00:36:24,320 --> 00:36:27,320
Speaker 1: And that seemed to be a huge barrier in conveying

695
00:36:27,360 --> 00:36:28,279
Speaker 1: information to the post.

696
00:36:28,360 --> 00:36:30,240
Speaker 2: You know, Chuck, the one thing I try to instill

697
00:36:30,280 --> 00:36:34,440
Speaker 2: in all my graduate students, science is not truth. Science

698
00:36:34,520 --> 00:36:37,160
Speaker 2: is the pursuit of truth, and that means you need

699
00:36:37,200 --> 00:36:40,160
Speaker 2: to be humble. You need to be able to say, well,

700
00:36:40,200 --> 00:36:43,240
Speaker 2: look what we learned. Now look how that changes exactly

701
00:36:43,280 --> 00:36:45,960
Speaker 2: what you're saying. We need to have much a much

702
00:36:46,120 --> 00:36:49,840
Speaker 2: more open culture to that idea that science is the

703
00:36:49,920 --> 00:36:51,080
Speaker 2: pursuit of them.

704
00:36:51,600 --> 00:36:53,759
Speaker 1: So, for instance, you know, all of a sudden, now

705
00:36:54,800 --> 00:36:58,160
Speaker 1: you can't help I can't help my brain behaving in

706
00:36:58,200 --> 00:37:01,759
Speaker 1: the following way, Bobby Kennedy Junior is going to come

707
00:37:01,800 --> 00:37:05,640
Speaker 1: out and say that Tilan, it might be a cause

708
00:37:05,680 --> 00:37:08,920
Speaker 1: of autism, and I say, might right, And it is

709
00:37:08,960 --> 00:37:11,719
Speaker 1: going to be. I don't want to say it's junk

710
00:37:11,760 --> 00:37:14,640
Speaker 1: science yet. But at the same time, you know, it

711
00:37:14,640 --> 00:37:17,560
Speaker 1: doesn't feel like there's a there's enough to be as

712
00:37:17,600 --> 00:37:20,200
Speaker 1: declarative as that they might be on this. At the

713
00:37:20,239 --> 00:37:24,720
Speaker 1: same time, I, you know, I'm well aware that things

714
00:37:24,719 --> 00:37:26,680
Speaker 1: we thought that were healthy will find out one day

715
00:37:26,680 --> 00:37:29,719
Speaker 1: that they're not right. So it how would you be

716
00:37:29,840 --> 00:37:34,359
Speaker 1: conveying this set of miniferent situation in a more responsible way?

717
00:37:34,840 --> 00:37:37,319
Speaker 2: Well, the first problem we have is that people have

718
00:37:37,440 --> 00:37:41,560
Speaker 2: a horrible time understanding risk benefit. Virtually nothing in this

719
00:37:41,640 --> 00:37:45,200
Speaker 2: world is risk free, and often I love playing.

720
00:37:45,000 --> 00:37:48,040
Speaker 1: The risk game. You know, somebody says ninety five percent.

721
00:37:48,080 --> 00:37:49,440
Speaker 1: I said, would you get on an airplane that I

722
00:37:49,480 --> 00:37:53,279
Speaker 1: had a ninety five percent chance of landing. Yeah, and

723
00:37:53,360 --> 00:37:55,279
Speaker 1: you start to think about it, all, right, how about

724
00:37:55,360 --> 00:37:58,840
Speaker 1: ninety percent? And then it's like, no intent, I wouldn't

725
00:37:58,840 --> 00:38:01,920
Speaker 1: know it right, Like you know, people, it all depends

726
00:38:01,920 --> 00:38:03,719
Speaker 1: on what the risk is. I'm a big fan of

727
00:38:03,719 --> 00:38:06,280
Speaker 1: playing that game because it's a way of teaching people

728
00:38:06,680 --> 00:38:08,520
Speaker 1: what does it ninety five percent really mean?

729
00:38:08,680 --> 00:38:11,240
Speaker 2: Absolutely well, if you look at a set of menifit

730
00:38:11,480 --> 00:38:14,200
Speaker 2: actually one of the other real challenges in pregnant women

731
00:38:14,640 --> 00:38:17,440
Speaker 2: is actually fevers. And you know, I'm not an expert

732
00:38:17,480 --> 00:38:20,080
Speaker 2: as an obg U I n on this issue, but

733
00:38:20,680 --> 00:38:23,200
Speaker 2: a set of minifit has been a very important part

734
00:38:23,520 --> 00:38:27,239
Speaker 2: of reducing fevers. And the issue that that raises with.

735
00:38:27,320 --> 00:38:31,160
Speaker 1: Betime why have had migraines and during the pregnancies she

736
00:38:31,200 --> 00:38:34,040
Speaker 1: couldn't take her migraine medicine, so it was just tiling on.

737
00:38:34,400 --> 00:38:36,279
Speaker 1: I mean, that was all she was allowed to take

738
00:38:37,000 --> 00:38:39,479
Speaker 1: and it only kind of worked.

739
00:38:39,719 --> 00:38:41,920
Speaker 2: Yeah, And so let's just start out with the fact

740
00:38:41,920 --> 00:38:44,400
Speaker 2: that we have to understand risk benefit With the second

741
00:38:44,400 --> 00:38:46,719
Speaker 2: of all, as you pointed out, there's still a lot

742
00:38:46,760 --> 00:38:50,560
Speaker 2: of questions about just what the role of Thailand all

743
00:38:50,680 --> 00:38:53,160
Speaker 2: might be and how much does it account for Is

744
00:38:53,160 --> 00:38:55,520
Speaker 2: it a few percent of all the cases that occur,

745
00:38:55,920 --> 00:38:59,000
Speaker 2: and realizing the data we have to date is very

746
00:38:59,000 --> 00:39:01,279
Speaker 2: incomplete and we're going to learn a lot more. You

747
00:39:01,320 --> 00:39:03,839
Speaker 2: know how many times I say to myself every day, Boy,

748
00:39:03,880 --> 00:39:06,040
Speaker 2: I wish I know today what I'm going to know

749
00:39:06,200 --> 00:39:08,440
Speaker 2: six months from now. You know, wouldn't I be a

750
00:39:08,440 --> 00:39:09,200
Speaker 2: lot better off?

751
00:39:09,560 --> 00:39:10,320
Speaker 1: Be a great gambler?

752
00:39:10,520 --> 00:39:12,640
Speaker 2: Yeah? Yeah, I think you know, once we once we

753
00:39:12,840 --> 00:39:15,520
Speaker 2: better understand this risk of see to benefit my own

754
00:39:15,560 --> 00:39:18,960
Speaker 2: personal belief is it'll account for a very very small

755
00:39:19,320 --> 00:39:22,520
Speaker 2: part of the autism picture. In the meantime, we're going

756
00:39:22,600 --> 00:39:25,840
Speaker 2: to throw out a very important medication from a fever

757
00:39:25,960 --> 00:39:29,280
Speaker 2: standpoint that in pregnancy is in itself a challenge.

758
00:39:29,520 --> 00:39:31,919
Speaker 1: Well half the population is going to accept the premise here.

759
00:39:32,560 --> 00:39:35,560
Speaker 2: They do, they do, They absolutely do. Although I will

760
00:39:35,560 --> 00:39:38,160
Speaker 2: have to say, when red wine was in vogue, everybody

761
00:39:38,160 --> 00:39:40,360
Speaker 2: went with it. When then it wasn't in vogue health wise,

762
00:39:40,520 --> 00:39:43,680
Speaker 2: I'm not sure everybody stopped. That would make county.

763
00:39:43,920 --> 00:39:46,960
Speaker 1: That's true, that's true. It really when it fits your lifestyle, you're,

764
00:39:47,120 --> 00:39:51,319
Speaker 1: oh yeah, red wine healthy for you? Really? Really, you know,

765
00:39:51,400 --> 00:39:53,800
Speaker 1: it's just sort of less unhealthy than the other stuff.

766
00:39:53,880 --> 00:39:56,000
Speaker 1: Is probably the better way it should have been described.

767
00:39:56,080 --> 00:39:56,520
Speaker 2: That's right.

768
00:39:57,040 --> 00:40:01,960
Speaker 1: So when somebody who's listening to us is going to

769
00:40:02,239 --> 00:40:05,080
Speaker 1: hear this a set of minifrin, I mean, is it

770
00:40:05,160 --> 00:40:08,160
Speaker 1: going to impact how your view of a seat of minifrain.

771
00:40:08,800 --> 00:40:10,799
Speaker 2: Well, you know, I first of all will tell you

772
00:40:10,840 --> 00:40:12,600
Speaker 2: that one of the important things is you don't want

773
00:40:12,640 --> 00:40:15,600
Speaker 2: to have armshare quarterbacks like me who do enough to

774
00:40:15,640 --> 00:40:17,799
Speaker 2: be dangerous to be comming on this. I've already been

775
00:40:17,880 --> 00:40:21,000
Speaker 2: contacted this morning by a number of news outlets asking

776
00:40:21,040 --> 00:40:23,120
Speaker 2: if I'll be on today to comment on this. My

777
00:40:23,200 --> 00:40:26,600
Speaker 2: answer is I don't know enough and therefore I'm not

778
00:40:26,719 --> 00:40:29,080
Speaker 2: the voice you want to have. These are the people

779
00:40:29,239 --> 00:40:32,800
Speaker 2: that from the OBGYN world that can really give you

780
00:40:32,920 --> 00:40:35,399
Speaker 2: better information. So I'm going to beg off this one

781
00:40:35,719 --> 00:40:38,000
Speaker 2: and say that I know enough here to say that

782
00:40:38,160 --> 00:40:40,600
Speaker 2: it's not a slam dunk, but at the same time

783
00:40:40,600 --> 00:40:42,480
Speaker 2: as one we have to look at. But like you,

784
00:40:42,600 --> 00:40:45,799
Speaker 2: I worry that it will be misinterpreted and that we're

785
00:40:45,800 --> 00:40:48,880
Speaker 2: going to see damage occur because people aren't taking a

786
00:40:48,920 --> 00:40:50,240
Speaker 2: seat of benifit when they shouldn't.

787
00:40:50,560 --> 00:40:53,800
Speaker 1: Look. The biggest fear I've had about this entire experiment

788
00:40:53,840 --> 00:40:56,600
Speaker 1: that we're on right now in this current political environment

789
00:40:56,680 --> 00:41:00,239
Speaker 1: is that we already had to half the country of

790
00:41:00,719 --> 00:41:05,680
Speaker 1: anti expert okay, and now they took over the expertise lane,

791
00:41:05,760 --> 00:41:07,040
Speaker 1: and now we're gonna have the other half of the

792
00:41:07,040 --> 00:41:10,799
Speaker 1: country no longer believe experts. And you know it's you know,

793
00:41:12,360 --> 00:41:13,480
Speaker 1: I have a friend of mine who used to tell

794
00:41:13,520 --> 00:41:15,800
Speaker 1: this joke. He goes, you know, if the beer companies

795
00:41:16,480 --> 00:41:20,560
Speaker 1: behaved like politicians, you know, Miller Lte says, it's less filling.

796
00:41:20,640 --> 00:41:22,520
Speaker 1: But what they don't tell you is that this is

797
00:41:22,520 --> 00:41:24,759
Speaker 1: in there, he says. Eventually, it's not that people would

798
00:41:24,760 --> 00:41:26,920
Speaker 1: stop drinking Miller Light or stop drinking bud Light. They

799
00:41:27,040 --> 00:41:30,080
Speaker 1: just stop drinking beer. And I think the fear we

800
00:41:30,160 --> 00:41:34,640
Speaker 1: have here is that everybody's just going to like not

801
00:41:34,680 --> 00:41:40,000
Speaker 1: trust anything they hear, which is honestly, I understand if

802
00:41:40,000 --> 00:41:42,319
Speaker 1: they would come to that conclusion given the situation we're

803
00:41:42,360 --> 00:41:42,959
Speaker 1: all living it.

804
00:41:43,560 --> 00:41:45,480
Speaker 2: I think you're right, And I think that's the challenge

805
00:41:45,520 --> 00:41:46,960
Speaker 2: we have trying to get ready for the big one,

806
00:41:47,000 --> 00:41:48,719
Speaker 2: because the first one is nobody wants to believe it

807
00:41:48,719 --> 00:41:52,160
Speaker 2: can happen. It won't happen. Nobody wanted. In two thousand

808
00:41:52,200 --> 00:41:54,919
Speaker 2: and seventeen, when I published eudlist enemies and talked about

809
00:41:55,000 --> 00:41:57,800
Speaker 2: what I had three chapters in that book that pretty

810
00:41:57,880 --> 00:42:00,399
Speaker 2: much played out as the pandemic did, except I used

811
00:42:00,400 --> 00:42:02,840
Speaker 2: an a windsor virus. And I think that that's the

812
00:42:02,960 --> 00:42:05,400
Speaker 2: challenge is how do you get people to understand this

813
00:42:05,520 --> 00:42:08,880
Speaker 2: is what you can do about the future now? And

814
00:42:08,880 --> 00:42:11,839
Speaker 2: and I worry that that's going to get buried in Well,

815
00:42:11,880 --> 00:42:14,280
Speaker 2: everything's that's screwed up, let's do nothing.

816
00:42:28,640 --> 00:42:31,440
Speaker 1: So obviously the big thing you'd be standing up is

817
00:42:31,480 --> 00:42:35,879
Speaker 1: sort of this preventative virus and vaccine research, right, which

818
00:42:35,920 --> 00:42:38,279
Speaker 1: is what we had going at n Eh. It was

819
00:42:38,280 --> 00:42:40,560
Speaker 1: an amazing program. Now it's gone.

820
00:42:41,200 --> 00:42:45,960
Speaker 2: It's it's it's it's absolutely critical that we globally do that.

821
00:42:46,239 --> 00:42:48,319
Speaker 2: I mean, as I said, I'm like, we don't do it?

822
00:42:48,360 --> 00:42:50,240
Speaker 1: Who is? Who is doing it?

823
00:42:50,680 --> 00:42:52,920
Speaker 2: Problems? No, this is one of the problems. Is the

824
00:42:53,040 --> 00:42:55,520
Speaker 2: US is the tail that wags the dog. In fact,

825
00:42:55,520 --> 00:42:57,160
Speaker 2: i'd say the tail that wegs the elephant.

826
00:42:57,280 --> 00:42:59,680
Speaker 1: I had an EU ambassador say this. He goes, if

827
00:42:59,719 --> 00:43:03,600
Speaker 1: I could replicate one thing America does, he says, it

828
00:43:03,640 --> 00:43:08,480
Speaker 1: would be Barta. Yeah, Yeah, I mean I think that's it.

829
00:43:08,800 --> 00:43:12,320
Speaker 2: Yeah. Well, and so from that perspective. I'm very concerned

830
00:43:12,360 --> 00:43:15,400
Speaker 2: that we're going to see on a global basis companies

831
00:43:15,800 --> 00:43:18,799
Speaker 2: countries not willing to get an mRNA technology because if

832
00:43:18,800 --> 00:43:20,919
Speaker 2: the US isn't leading the way on that, or they're

833
00:43:20,960 --> 00:43:24,919
Speaker 2: anti mRNA vaccine technology, there's no market in it for them.

834
00:43:25,440 --> 00:43:28,400
Speaker 2: And so we're already seeing companies on a global basis

835
00:43:28,440 --> 00:43:31,320
Speaker 2: pull out of mRNA research. And as you noted earlier,

836
00:43:31,440 --> 00:43:34,440
Speaker 2: this is not just about COVID or influenza. This is

837
00:43:34,480 --> 00:43:36,880
Speaker 2: about a whole number of other infectious diseases the one

838
00:43:36,920 --> 00:43:37,680
Speaker 2: I just mentioned.

839
00:43:37,840 --> 00:43:43,040
Speaker 3: Can you imagine a vaccine for cancer and cancers? And

840
00:43:43,080 --> 00:43:47,360
Speaker 3: that's real, right, and those vaccines are both prevention, but

841
00:43:47,400 --> 00:43:50,239
Speaker 3: more important, they're also treatment issues. I mean, we can

842
00:43:50,280 --> 00:43:54,280
Speaker 3: actually use these vaccines for very effective treatment. And again,

843
00:43:54,440 --> 00:43:58,239
Speaker 3: you know, it was a situation where the statements that

844
00:43:58,239 --> 00:43:59,880
Speaker 3: were made at the ACIP.

845
00:43:59,480 --> 00:44:03,560
Speaker 2: MEDIU Lanne week they were so off base, they had

846
00:44:03,640 --> 00:44:06,759
Speaker 2: no basis in science whatsoever, but they were stating, with

847
00:44:06,800 --> 00:44:09,840
Speaker 2: this authority voice, look at how bad these vaccines are.

848
00:44:09,880 --> 00:44:11,879
Speaker 2: Look what they do to you, you know, and that's

849
00:44:12,000 --> 00:44:13,120
Speaker 2: that's the challenge we have.

850
00:44:14,560 --> 00:44:17,520
Speaker 1: So so that gets starved, all right, So if we

851
00:44:17,560 --> 00:44:23,920
Speaker 1: can't what are what would besides standing up the mRNA research,

852
00:44:24,520 --> 00:44:28,400
Speaker 1: what else would should we be doing in preparation for

853
00:44:28,480 --> 00:44:31,160
Speaker 1: the big one? I mean, obviously we learned a lot

854
00:44:31,200 --> 00:44:34,960
Speaker 1: about PPE and what we had too much outsourced in

855
00:44:35,000 --> 00:44:38,320
Speaker 1: our reliance in other countries that I think we're getting

856
00:44:39,040 --> 00:44:41,920
Speaker 1: at a minimum that's going to get. That's probably something

857
00:44:41,960 --> 00:44:44,480
Speaker 1: at least in the short term that even this administration

858
00:44:44,560 --> 00:44:46,080
Speaker 1: wants to get right right.

859
00:44:46,120 --> 00:44:48,200
Speaker 2: But unfortunately, I'll tell you right now that we're not

860
00:44:48,239 --> 00:44:51,040
Speaker 2: any better off with manufacturing capacity or what to do.

861
00:44:51,200 --> 00:44:53,200
Speaker 2: But let me back up. In the book we cover this,

862
00:44:54,239 --> 00:44:57,360
Speaker 2: we saw so much miss and disinformation, and public Health

863
00:44:57,440 --> 00:45:00,160
Speaker 2: was really in part to blame for this because as

864
00:45:00,200 --> 00:45:03,200
Speaker 2: we basically kept saying a group of us that it's

865
00:45:03,239 --> 00:45:07,040
Speaker 2: not airborne, meaning these very fine mist like particles that

866
00:45:07,160 --> 00:45:10,680
Speaker 2: fill the entire room, rather than the droplets, those things

867
00:45:10,719 --> 00:45:12,840
Speaker 2: that basically as you if you've ever been in the

868
00:45:12,840 --> 00:45:15,000
Speaker 2: front row of a play or a concert, you see

869
00:45:15,040 --> 00:45:19,120
Speaker 2: those droplets coming out across the stage. Okay, those are

870
00:45:19,160 --> 00:45:21,880
Speaker 2: the ones that people said were causing this. That's the

871
00:45:22,000 --> 00:45:24,960
Speaker 2: kind of thing that hygiene theater all was all about.

872
00:45:25,000 --> 00:45:28,280
Speaker 2: The plexiglass and all of that made no difference whatsoever.

873
00:45:28,640 --> 00:45:32,960
Speaker 2: Bandan has made no different surgical You needed to have

874
00:45:33,000 --> 00:45:35,879
Speaker 2: what we call an N ninety five respirator. Why did

875
00:45:35,920 --> 00:45:38,440
Speaker 2: that work? Because first of all, it was very tight

876
00:45:38,520 --> 00:45:41,200
Speaker 2: face fit. You know how many times you ever use

877
00:45:41,239 --> 00:45:43,600
Speaker 2: swim goggles that leaked through the glass? They did, They

878
00:45:43,680 --> 00:45:46,520
Speaker 2: leaked through the side. The second thing, though, is it

879
00:45:46,560 --> 00:45:49,280
Speaker 2: wasn't just any material in front of your face, because

880
00:45:49,280 --> 00:45:52,560
Speaker 2: something that is airtight around your face, you suffocate quickly

881
00:45:52,560 --> 00:45:54,719
Speaker 2: if you couldn't move air back and forth. And so

882
00:45:54,880 --> 00:45:58,719
Speaker 2: this material had an electro electrostatic charge to it that

883
00:45:58,880 --> 00:46:03,080
Speaker 2: basically trapped virus coming through but let air come through well.

884
00:46:03,080 --> 00:46:06,560
Speaker 2: But they still were very uncomfortable for many people I have,

885
00:46:06,880 --> 00:46:09,080
Speaker 2: and we talked about this in the book. We need

886
00:46:09,120 --> 00:46:14,040
Speaker 2: a major project to develop a consumer friendly, reusable IN

887
00:46:14,160 --> 00:46:17,960
Speaker 2: ninety five rospirator that people would wear and actually find

888
00:46:17,960 --> 00:46:20,640
Speaker 2: it to be comfortable, and one that they would wear

889
00:46:20,640 --> 00:46:23,160
Speaker 2: into public. You know, if you could do that, you

890
00:46:23,160 --> 00:46:25,959
Speaker 2: could stop a lot of transmission for people that had

891
00:46:25,960 --> 00:46:28,600
Speaker 2: to be in the public setting. You know, it was

892
00:46:28,680 --> 00:46:31,759
Speaker 2: hard to watch so many families in this country where

893
00:46:31,880 --> 00:46:35,560
Speaker 2: grandpa and grandma, mom and dad, the kids all lived

894
00:46:35,600 --> 00:46:38,520
Speaker 2: in the same apartment. You know, you couldn't you couldn't

895
00:46:38,520 --> 00:46:40,799
Speaker 2: isolate these people from each other. So if the kid

896
00:46:40,800 --> 00:46:43,560
Speaker 2: brought a virus home from school, Grandpa and grandma could

897
00:46:43,560 --> 00:46:46,880
Speaker 2: have died from it. That's where this kind of increased

898
00:46:46,920 --> 00:46:50,160
Speaker 2: respiratory protection could make just a huge difference. But we're

899
00:46:50,160 --> 00:46:52,399
Speaker 2: doing very little to achieve that right now.

900
00:46:54,520 --> 00:47:00,359
Speaker 1: What about in the public setting, in building codes things

901
00:47:00,400 --> 00:47:02,839
Speaker 1: like this, Are there things we should be doing differently

902
00:47:04,400 --> 00:47:10,040
Speaker 1: in order to essentially be more to help us deal

903
00:47:10,080 --> 00:47:13,080
Speaker 1: with with a with a airborne virus?

904
00:47:13,280 --> 00:47:16,560
Speaker 2: Well, first of all, let me just say that we

905
00:47:16,600 --> 00:47:18,640
Speaker 2: already have an example of what can be done with

906
00:47:18,680 --> 00:47:22,200
Speaker 2: building codes. And look at the earthquake prone areas, look

907
00:47:22,239 --> 00:47:25,440
Speaker 2: at the hurricane prone areas. You know we actually tailor

908
00:47:26,440 --> 00:47:30,520
Speaker 2: building codes to meet those challenges. Well, we never really

909
00:47:30,560 --> 00:47:33,439
Speaker 2: thought about air. I mean, we all talk about safe

910
00:47:33,520 --> 00:47:36,080
Speaker 2: water supplies. You know, we want to make sure our

911
00:47:36,120 --> 00:47:38,120
Speaker 2: food is safe. But when's the last time you heard

912
00:47:38,160 --> 00:47:42,160
Speaker 2: somebody say how safe is our air? And so one

913
00:47:42,160 --> 00:47:43,480
Speaker 2: of the things we need to do is just to

914
00:47:43,560 --> 00:47:47,319
Speaker 2: understand that that is also a very important way for

915
00:47:47,480 --> 00:47:51,160
Speaker 2: virus to be transmitted. You'll appreciate this one I use

916
00:47:51,200 --> 00:47:55,760
Speaker 2: as an example of what airborne viruses are like in

917
00:47:55,800 --> 00:47:58,319
Speaker 2: a previous life at the State Health Department here as

918
00:47:58,320 --> 00:48:02,239
Speaker 2: a state of pheologist I let in investigation of measles

919
00:48:02,400 --> 00:48:05,640
Speaker 2: that occurred in our state associated with the Special Olympics

920
00:48:05,680 --> 00:48:09,279
Speaker 2: and International Special Olympics were here and on opening night

921
00:48:09,400 --> 00:48:12,960
Speaker 2: session in the Hubert Hulphrey Metrodome, sixty five thousand people

922
00:48:13,000 --> 00:48:16,200
Speaker 2: in the stands. We had the entire infield and outfield

923
00:48:16,239 --> 00:48:19,200
Speaker 2: field filled with all of the players from the different

924
00:48:19,200 --> 00:48:22,640
Speaker 2: countries and their coaches, et cetera. Well, the a's by

925
00:48:22,680 --> 00:48:26,040
Speaker 2: alphabet country were on right at home plate and that

926
00:48:26,120 --> 00:48:28,680
Speaker 2: was Argentina, and we had a young boy who was

927
00:48:28,880 --> 00:48:33,040
Speaker 2: just incubating measles, was infectious and the outbreak resulted in

928
00:48:33,080 --> 00:48:36,880
Speaker 2: the entire participant group. But we had many people in

929
00:48:36,920 --> 00:48:41,600
Speaker 2: that sixty five thousand plus visitors that night who had

930
00:48:41,600 --> 00:48:44,759
Speaker 2: no other contact with the Special Olympics. They also had

931
00:48:44,800 --> 00:48:47,759
Speaker 2: an outbreak of measles. Nobody knew each other, but it

932
00:48:47,840 --> 00:48:50,040
Speaker 2: turned out they all sat in the same section in

933
00:48:50,080 --> 00:48:53,400
Speaker 2: the far far right field upper bleachers where Mark McGuire

934
00:48:53,400 --> 00:48:55,440
Speaker 2: at the time couldn't had a home run in steroids

935
00:48:55,600 --> 00:48:58,160
Speaker 2: four hundred and twenty feet away, and it turned out

936
00:48:58,160 --> 00:49:00,480
Speaker 2: that the air came out from behind home home plate,

937
00:49:00,760 --> 00:49:03,840
Speaker 2: across home plate and bounced and literally went all the

938
00:49:03,880 --> 00:49:07,200
Speaker 2: way up to that right field out take up there,

939
00:49:07,520 --> 00:49:09,880
Speaker 2: and everyone who was in that section who had not

940
00:49:09,920 --> 00:49:12,759
Speaker 2: previously had measles got measles that night from that exposure.

941
00:49:13,640 --> 00:49:18,200
Speaker 2: Now that's how dynamic airborne transmission is. So how do

942
00:49:18,280 --> 00:49:20,360
Speaker 2: we improve ventilation there? And that's where we have to

943
00:49:20,400 --> 00:49:22,760
Speaker 2: do a lot of work. We don't have easy answers.

944
00:49:22,920 --> 00:49:26,120
Speaker 2: It's not simple just turn on a fan. We but

945
00:49:26,239 --> 00:49:29,640
Speaker 2: this again should be a very basic research area that

946
00:49:29,680 --> 00:49:30,799
Speaker 2: we're doing very little with.

947
00:49:31,640 --> 00:49:35,359
Speaker 1: Uh. It's funny you use the measles example there, since

948
00:49:35,360 --> 00:49:38,799
Speaker 1: it's it was something you were involved with. I have

949
00:49:38,880 --> 00:49:43,520
Speaker 1: an older relative who's wondering, who's wondered aloud if measles

950
00:49:43,640 --> 00:49:47,000
Speaker 1: is going to be back in circulation? Are there boosters

951
00:49:47,000 --> 00:49:52,160
Speaker 1: that older folks probably never thought they needed but may need,

952
00:49:53,400 --> 00:49:55,560
Speaker 1: you know, are we gonna yeah?

953
00:49:55,360 --> 00:49:55,480
Speaker 2: Uh?

954
00:49:55,640 --> 00:49:59,200
Speaker 1: You know what? What kind of how concerned? What should

955
00:49:59,239 --> 00:50:01,760
Speaker 1: we be for our population over the age of fifty,

956
00:50:02,200 --> 00:50:07,280
Speaker 1: for instance, when it comes to a new outbreak of measles?

957
00:50:07,520 --> 00:50:10,360
Speaker 2: Well, in keeping with my science is not truth, it

958
00:50:10,520 --> 00:50:13,000
Speaker 2: is pursuit of truth. I'll tell you about what data

959
00:50:13,040 --> 00:50:15,400
Speaker 2: we do have is the fact that it says you

960
00:50:15,480 --> 00:50:19,360
Speaker 2: probably have lifelong protection. Okay, that's why measles, mumps, and

961
00:50:19,400 --> 00:50:22,480
Speaker 2: rubella that vaccine is easy for me to talk about

962
00:50:22,520 --> 00:50:26,360
Speaker 2: mandating it because one, it stops transmission, it stops you

963
00:50:26,400 --> 00:50:29,319
Speaker 2: from getting infected, and it's lifelong protection. And this is

964
00:50:29,360 --> 00:50:30,480
Speaker 2: where you then contribute it.

965
00:50:30,480 --> 00:50:33,000
Speaker 1: No boosters necessary, and that doesn't look like it at

966
00:50:33,000 --> 00:50:33,400
Speaker 1: this point.

967
00:50:33,480 --> 00:50:35,640
Speaker 2: We'll continue to follow it. I could be back on

968
00:50:35,719 --> 00:50:38,239
Speaker 2: here tomorrow and say, well, now we have data if

969
00:50:38,280 --> 00:50:40,680
Speaker 2: you're immune compromised the sixty you may need a booster.

970
00:50:41,160 --> 00:50:43,399
Speaker 2: But the bottom line is this is one of those

971
00:50:43,440 --> 00:50:46,759
Speaker 2: examples of a vaccine that is so good that it

972
00:50:46,920 --> 00:50:50,560
Speaker 2: is putting rods in the reaction. You stop community transmission

973
00:50:50,960 --> 00:50:52,880
Speaker 2: when you in fact you know.

974
00:50:53,040 --> 00:50:56,400
Speaker 1: But let's be humble here. What we don't know. We

975
00:50:56,440 --> 00:50:59,839
Speaker 1: didn't know we were going to reintroduce measles into the population.

976
00:51:00,120 --> 00:51:02,399
Speaker 1: So there's going to be a whole new slew of

977
00:51:02,680 --> 00:51:05,479
Speaker 1: people over the age of sixty who even fifty years ago,

978
00:51:06,000 --> 00:51:08,680
Speaker 1: our elderly population was just not as big because we

979
00:51:08,719 --> 00:51:12,960
Speaker 1: didn't keep people right. Now, people live longer, so we're

980
00:51:13,040 --> 00:51:16,680
Speaker 1: going to learn. Okay, what does lifelong protection mean? Is

981
00:51:16,719 --> 00:51:20,640
Speaker 1: lifelong sixty or is life long eighty? Right? And that's

982
00:51:20,680 --> 00:51:24,160
Speaker 1: it again, as you point out, we got to keep

983
00:51:24,160 --> 00:51:25,239
Speaker 1: pursuing this, and we do.

984
00:51:25,440 --> 00:51:27,680
Speaker 2: And the one thing I would say that's in our favor.

985
00:51:27,840 --> 00:51:31,680
Speaker 2: Sixty years ago, we still had a lot of measles around. Okay,

986
00:51:31,960 --> 00:51:35,320
Speaker 2: So you may have gotten vaccinated and then gotten an

987
00:51:35,360 --> 00:51:38,640
Speaker 2: recognized boost by having been exposed to the virus and

988
00:51:38,680 --> 00:51:42,440
Speaker 2: then only reinforced your protection. Where I worry about is

989
00:51:42,480 --> 00:51:45,160
Speaker 2: more in the forty year olds, where in fact, there

990
00:51:45,160 --> 00:51:47,480
Speaker 2: were a number of them that never were exposed to measles,

991
00:51:47,520 --> 00:51:50,040
Speaker 2: because by the time forty years ago we were really

992
00:51:50,040 --> 00:51:52,480
Speaker 2: starting to improve on this. Let me just point out

993
00:51:52,480 --> 00:51:55,600
Speaker 2: I had never seen congenital measles in my life until

994
00:51:55,640 --> 00:51:59,440
Speaker 2: this recent year. Congeneral measles occurs when a young pregnant

995
00:51:59,440 --> 00:52:03,399
Speaker 2: woman gets infect with measles. Why pregnant? Okay, Well, why

996
00:52:03,440 --> 00:52:06,799
Speaker 2: did we not see that before? Because prior to vaccination,

997
00:52:07,239 --> 00:52:09,799
Speaker 2: virtually everybody under age twenty had already.

998
00:52:09,560 --> 00:52:12,880
Speaker 1: Had music, so it was it was a heard immunity,

999
00:52:13,200 --> 00:52:13,880
Speaker 1: heard immunity.

1000
00:52:14,040 --> 00:52:18,360
Speaker 2: Then after that period, even in the transition years of

1001
00:52:18,400 --> 00:52:21,640
Speaker 2: where we saw vaccine there was enough people that did

1002
00:52:21,680 --> 00:52:25,279
Speaker 2: get vaccinated that we just didn't see sustained measles. Now

1003
00:52:25,320 --> 00:52:29,319
Speaker 2: we've got enough measles circulating. When twenty and twenty five

1004
00:52:29,440 --> 00:52:32,000
Speaker 2: year olds who have never had measles vaccine, or who

1005
00:52:32,160 --> 00:52:35,720
Speaker 2: never had measles itself, who are now getting infected whild pregnant.

1006
00:52:36,040 --> 00:52:39,280
Speaker 2: This is a new phenomenon because of the unique nature

1007
00:52:39,280 --> 00:52:42,319
Speaker 2: of what you were just describing of. You know what

1008
00:52:42,520 --> 00:52:44,839
Speaker 2: happens with time, and how does time change them?

1009
00:52:45,600 --> 00:52:47,640
Speaker 1: Would you take your grand kids in Disney World right now?

1010
00:52:50,040 --> 00:52:52,880
Speaker 2: Well, right now, I might because there's very little evidence

1011
00:52:52,880 --> 00:52:55,840
Speaker 2: of measles down there beyond what we're seeing anywhere in

1012
00:52:55,840 --> 00:52:56,240
Speaker 2: the country.

1013
00:52:56,320 --> 00:52:58,840
Speaker 1: Yeah, well Florida is about to go Florida's about to

1014
00:52:58,840 --> 00:52:59,960
Speaker 1: go anti vacs.

1015
00:53:00,520 --> 00:53:02,880
Speaker 2: In the future, and I've said this, I wouldn't take

1016
00:53:02,920 --> 00:53:06,600
Speaker 2: them in the future. I think that's that's a huge issue.

1017
00:53:06,760 --> 00:53:09,080
Speaker 2: And of course the other thing is happening here.

1018
00:53:08,960 --> 00:53:11,560
Speaker 1: By the way, as it aside. This is my I

1019
00:53:11,600 --> 00:53:15,480
Speaker 1: suspect that at some point the people that own theme

1020
00:53:15,560 --> 00:53:19,120
Speaker 1: parks in Orlando, yep, and are going to put real

1021
00:53:19,160 --> 00:53:22,200
Speaker 1: pressure on government because this is going to have a

1022
00:53:22,280 --> 00:53:24,520
Speaker 1: huge business hit. You're going to have more and more

1023
00:53:24,560 --> 00:53:26,200
Speaker 1: people not coming because of this.

1024
00:53:26,520 --> 00:53:28,160
Speaker 2: Well, let me add on to that if I can

1025
00:53:28,239 --> 00:53:33,360
Speaker 2: pile on right now, almost five thousand kids in Canada

1026
00:53:33,400 --> 00:53:37,120
Speaker 2: have had musles this year. Remember we're talking about twenty

1027
00:53:37,160 --> 00:53:40,160
Speaker 2: five hundred and three thousand cases here. But remember they

1028
00:53:40,200 --> 00:53:43,400
Speaker 2: only have forty million people population. We have three hundred for.

1029
00:53:43,520 --> 00:53:46,359
Speaker 1: That per capita. Something else, and Europe.

1030
00:53:46,040 --> 00:53:48,560
Speaker 2: Is even worse. Well, how many kids are going to

1031
00:53:48,600 --> 00:53:52,240
Speaker 2: Disney World right now from walt from Canada or from Europe?

1032
00:53:52,680 --> 00:53:55,560
Speaker 2: And so these theme parks are even becoming a greater

1033
00:53:55,719 --> 00:53:58,640
Speaker 2: risk issue because not only is it the United States

1034
00:53:58,680 --> 00:54:02,839
Speaker 2: contributing to it all these foreign born individuals when we're

1035
00:54:02,840 --> 00:54:06,480
Speaker 2: seeing these huge outbreaks of measles around the world, and

1036
00:54:06,520 --> 00:54:08,839
Speaker 2: so this is again as a global issue. What are

1037
00:54:08,880 --> 00:54:10,960
Speaker 2: we doing to deal with it on a global basis?

1038
00:54:11,239 --> 00:54:13,600
Speaker 2: Very little? We're pulling out of the who.

1039
00:54:13,960 --> 00:54:15,680
Speaker 1: I do want to land this plane because we can.

1040
00:54:16,320 --> 00:54:18,759
Speaker 1: We can. We can go doom and gloom for quite

1041
00:54:18,760 --> 00:54:20,200
Speaker 1: some time. But I got to ask about H five

1042
00:54:20,280 --> 00:54:24,319
Speaker 1: N one right where we are on that and the

1043
00:54:24,440 --> 00:54:27,440
Speaker 1: concern that it can you know, it hasn't jumped to humans,

1044
00:54:27,520 --> 00:54:29,360
Speaker 1: and that's that's thank goodness.

1045
00:54:29,560 --> 00:54:31,839
Speaker 2: Well, let me just say we the bird flu. I'm

1046
00:54:31,840 --> 00:54:34,759
Speaker 2: going to have another influenza pandemic. There's no question about that.

1047
00:54:34,920 --> 00:54:37,719
Speaker 2: Will it be h five in one? Well a year

1048
00:54:37,960 --> 00:54:39,680
Speaker 2: and a half ago when it first showed up in

1049
00:54:39,760 --> 00:54:42,239
Speaker 2: dairy cattle, I was very conservative and said I'm not

1050
00:54:42,239 --> 00:54:43,799
Speaker 2: sure this is going to do it. And people looked

1051
00:54:43,840 --> 00:54:45,319
Speaker 2: at me, like, what do you mean this is your

1052
00:54:45,560 --> 00:54:49,520
Speaker 2: baby pandemic? Well, I said, you know, I've been involved

1053
00:54:49,560 --> 00:54:52,120
Speaker 2: with this since two thousand and three. When it re

1054
00:54:52,200 --> 00:54:55,160
Speaker 2: emerged in Asia after the nineteen ninety seven outbreak in

1055
00:54:55,239 --> 00:54:58,480
Speaker 2: Hong Kong. I was actually in Indonesia and Malaysia working

1056
00:54:58,560 --> 00:55:01,480
Speaker 2: on this. Okay, well, all thought this was it, this

1057
00:55:01,640 --> 00:55:04,799
Speaker 2: coming any day. I watched it go through the next

1058
00:55:04,840 --> 00:55:09,319
Speaker 2: ten years and actually caused very limited problems. Over time,

1059
00:55:09,400 --> 00:55:12,560
Speaker 2: it dropped and dropped, and then we had I was

1060
00:55:12,600 --> 00:55:15,480
Speaker 2: on the National Science Advisor Board for Biosecurity in the US,

1061
00:55:15,520 --> 00:55:19,000
Speaker 2: the group that was supposed to oversee BacT research safety

1062
00:55:19,000 --> 00:55:22,840
Speaker 2: in our country, and we had two very important researchers

1063
00:55:22,840 --> 00:55:25,200
Speaker 2: come to our group and said, we're one mutation away

1064
00:55:25,239 --> 00:55:28,040
Speaker 2: from age five in one causing the next pandemic. Oh my,

1065
00:55:28,800 --> 00:55:32,600
Speaker 2: nothing happened twenty fifteen sixteen, we had a major outbreak

1066
00:55:32,640 --> 00:55:36,200
Speaker 2: in the Nile River Valley one hundred and forty some doubts.

1067
00:55:36,520 --> 00:55:39,960
Speaker 2: Then it disappeared, nothing happened. Now we're here with the

1068
00:55:40,040 --> 00:55:42,239
Speaker 2: dairy cattle. I don't know what it's going to do.

1069
00:55:42,680 --> 00:55:44,600
Speaker 2: Anyone that can tell you what age five in one's

1070
00:55:44,640 --> 00:55:46,920
Speaker 2: going to do, good luck. But I will tell you

1071
00:55:47,080 --> 00:55:50,160
Speaker 2: there will be another flu virus that will emerge, so

1072
00:55:50,239 --> 00:55:51,480
Speaker 2: we need to be prepared for it.

1073
00:55:52,360 --> 00:55:57,520
Speaker 1: And is it still you know, the uncomfortable relationship with China?

1074
00:55:57,600 --> 00:56:00,520
Speaker 1: I mean, is China still the is it feels like

1075
00:56:00,600 --> 00:56:05,000
Speaker 1: Asia is the place where this incubates more it actually

1076
00:56:05,480 --> 00:56:07,480
Speaker 1: is that true or is that just perception?

1077
00:56:07,880 --> 00:56:10,360
Speaker 2: Well, I think it's true to the extent that it

1078
00:56:10,400 --> 00:56:13,040
Speaker 2: should show up anywhere. I mean, look at two thousand

1079
00:56:13,080 --> 00:56:15,960
Speaker 2: and nine, h one end one showed up in the

1080
00:56:16,000 --> 00:56:19,640
Speaker 2: pork industry in central Mexico. You know, it's showed up

1081
00:56:19,680 --> 00:56:22,560
Speaker 2: in the pigs. There could occur anywhere. But one of

1082
00:56:22,600 --> 00:56:25,000
Speaker 2: the things we have to understand is, for example, today

1083
00:56:25,080 --> 00:56:28,799
Speaker 2: the fastest conversion of energy to protein is poultry, and

1084
00:56:28,840 --> 00:56:32,920
Speaker 2: so globally we're producing more poultry ever than ever before

1085
00:56:33,080 --> 00:56:36,280
Speaker 2: to feed our eight billion people. Bush meat has become

1086
00:56:36,440 --> 00:56:40,640
Speaker 2: much more commonly consumed in parts of the Africa, Asia,

1087
00:56:40,760 --> 00:56:43,719
Speaker 2: et cetera. That never before happened. Now people are being

1088
00:56:43,719 --> 00:56:47,239
Speaker 2: exposed to that, so there's a lot of opportunity for exposure.

1089
00:56:47,560 --> 00:56:51,040
Speaker 2: We just recently recovered a virus from a bat cave

1090
00:56:51,120 --> 00:56:53,560
Speaker 2: in China that is like the one I talked about

1091
00:56:53,560 --> 00:56:56,680
Speaker 2: with covid on steroids, you know, one that had the

1092
00:56:56,920 --> 00:57:00,120
Speaker 2: infectiousness and the ability to kill that was isolate it

1093
00:57:00,200 --> 00:57:03,359
Speaker 2: from a bad and so I think, yeah, it's still there,

1094
00:57:03,440 --> 00:57:05,919
Speaker 2: It's still going to happen. I just like I said

1095
00:57:05,920 --> 00:57:07,800
Speaker 2: that the pandemic clock is ticking. I just don't know

1096
00:57:07,840 --> 00:57:09,279
Speaker 2: what time it is. Well, but I know there's a

1097
00:57:09,320 --> 00:57:09,960
Speaker 2: lot we can do.

1098
00:57:10,520 --> 00:57:13,200
Speaker 1: And it sounds like we should be thinking about vaccinating

1099
00:57:13,239 --> 00:57:16,080
Speaker 1: some of our the animals that are part of our

1100
00:57:16,120 --> 00:57:16,680
Speaker 1: food supply.

1101
00:57:17,360 --> 00:57:20,360
Speaker 2: Absolutely, and that is surely on the table now. That

1102
00:57:20,520 --> 00:57:23,400
Speaker 2: was a big trade issue because they didn't want to

1103
00:57:23,440 --> 00:57:26,840
Speaker 2: have to acknowledge that they had vaccinated proof of it.

1104
00:57:26,920 --> 00:57:29,520
Speaker 2: In the US really opposed it. I think that's changing

1105
00:57:29,920 --> 00:57:34,240
Speaker 2: because the wild bird migratory season moves a virus so quickly,

1106
00:57:34,600 --> 00:57:37,600
Speaker 2: so many operations have been hit hard. With age five

1107
00:57:38,040 --> 00:57:40,360
Speaker 2: both dairy and birds, and so I think you're going

1108
00:57:40,400 --> 00:57:42,360
Speaker 2: to see more of that, absolutely.

1109
00:57:42,200 --> 00:57:48,800
Speaker 1: And you don't view bioterrorism or naturally occurring pandemics as

1110
00:57:48,840 --> 00:57:51,240
Speaker 1: sort of any differently, do you like the preparation is

1111
00:57:51,840 --> 00:57:55,160
Speaker 1: in your mind, the preparation should be identical.

1112
00:57:55,720 --> 00:57:59,040
Speaker 2: You know, I had the opportunity recently to have dinner

1113
00:57:59,080 --> 00:58:02,600
Speaker 2: with a group of four or intelligence people from the

1114
00:58:02,680 --> 00:58:06,840
Speaker 2: United States, people really on the cutting edge and stay there,

1115
00:58:07,200 --> 00:58:09,919
Speaker 2: and they'll tell you that we've never been at more

1116
00:58:10,040 --> 00:58:14,320
Speaker 2: risk for a bioterrorism bio event as we are now

1117
00:58:14,480 --> 00:58:15,919
Speaker 2: because of everything that's been.

1118
00:58:15,840 --> 00:58:19,960
Speaker 1: Torn down completely again and about and the countries know this.

1119
00:58:20,160 --> 00:58:22,840
Speaker 2: Other countries know this, of course. And if we had

1120
00:58:22,880 --> 00:58:27,040
Speaker 2: a major event today, the CDC Shore couldn't respond, Nobody

1121
00:58:27,040 --> 00:58:29,560
Speaker 2: in HHS could respond. Maybe DO O D could have

1122
00:58:29,600 --> 00:58:32,360
Speaker 2: some response, But how's that going to go? Uh? And

1123
00:58:32,920 --> 00:58:35,760
Speaker 2: it would be a real disaster. And again I want

1124
00:58:35,800 --> 00:58:41,080
Speaker 2: to emphasize the Trump one administration had very detailed, comprehensive

1125
00:58:41,120 --> 00:58:44,160
Speaker 2: plans for that, and so it's not a partisan issue.

1126
00:58:44,160 --> 00:58:47,120
Speaker 2: It's just that this administration has elected to throw them out.

1127
00:58:47,520 --> 00:58:50,120
Speaker 1: No. Well, look, the book is the big one, and

1128
00:58:50,200 --> 00:58:53,000
Speaker 1: yes it's it is a little bit. It's a little

1129
00:58:53,040 --> 00:58:53,520
Speaker 1: bit scary.

1130
00:58:53,560 --> 00:58:56,640
Speaker 2: Michael, Well, I just tried to tell the truth, you know,

1131
00:58:56,760 --> 00:58:58,720
Speaker 2: and I did that. You know, you saw how many.

1132
00:58:58,600 --> 00:59:00,800
Speaker 1: Times why you were always the best guests to have

1133
00:59:00,920 --> 00:59:03,680
Speaker 1: because but it was direct. I mean, I do think

1134
00:59:04,640 --> 00:59:08,000
Speaker 1: in some ways the you know, we tried so hard,

1135
00:59:08,040 --> 00:59:11,560
Speaker 1: you know, everybody tried so hard to it's it's it's

1136
00:59:11,600 --> 00:59:13,680
Speaker 1: something I did in the past, which I call rounding

1137
00:59:13,760 --> 00:59:15,680
Speaker 1: the edges, because you want to make everybody feel a

1138
00:59:15,720 --> 00:59:19,760
Speaker 1: little bit better, and ultimately, you know, you just got

1139
00:59:19,800 --> 00:59:23,360
Speaker 1: to be matter of fact. Yep, particularly when it comes

1140
00:59:23,440 --> 00:59:23,920
Speaker 1: to science.

1141
00:59:24,160 --> 00:59:27,280
Speaker 2: Chuck, You've always done that, and I so appreciate you

1142
00:59:27,360 --> 00:59:29,640
Speaker 2: for that, and I hope you continue to have a voice.

1143
00:59:29,800 --> 00:59:30,520
Speaker 2: It's important.

1144
00:59:30,840 --> 00:59:32,680
Speaker 1: I appreciate you saying that, and I'm glad you're out

1145
00:59:32,720 --> 00:59:37,640
Speaker 1: there one of people. I really hope somebody currently at

1146
00:59:37,800 --> 00:59:40,680
Speaker 1: HHS is reading and to see and this stuff. That's

1147
00:59:40,880 --> 00:59:43,240
Speaker 1: you know, I'm never going to give up hope that

1148
00:59:43,280 --> 00:59:46,880
Speaker 1: there are people in positions of responsibility who won't eventually

1149
00:59:46,920 --> 00:59:47,520
Speaker 1: do the right thing.

1150
00:59:48,160 --> 00:59:48,800
Speaker 2: I'm with you.

1151
00:59:48,720 --> 00:59:51,480
Speaker 1: Because you know that that, like, you can't one hundred

1152
00:59:51,480 --> 00:59:53,560
Speaker 1: percent give up on somebody because you never know when

1153
00:59:53,560 --> 00:59:54,440
Speaker 1: they might be your ally.

1154
00:59:55,000 --> 00:59:57,760
Speaker 2: Yeah, and again I have hope because I have to

1155
00:59:57,760 --> 01:00:00,320
Speaker 2: have it because of my grandkids. I'm going to of it.

1156
01:00:00,880 --> 01:00:03,200
Speaker 1: If you don't have hope, what's the point that's right,

1157
01:00:03,840 --> 01:00:06,520
Speaker 1: you know, to get really dark, right and so gosh,

1158
01:00:06,720 --> 01:00:09,720
Speaker 1: you know we're going to have it, Michael Oster. Home

1159
01:00:09,760 --> 01:00:10,480
Speaker 1: is always a pleasure.

1160
01:00:10,520 --> 01:00:12,120
Speaker 2: Thank you, Thank you, sir. It's a great hone to

1161
01:00:12,120 --> 01:00:13,400
Speaker 2: be with you. Thank you very much.

1162
01:00:17,440 --> 01:00:17,480
Speaker 1: M