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Speaker 1: All right, clan you with us. It's Friday, and I

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Speaker 1: am guessing if you're like me, you're thinking, huh, I

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Speaker 1: can't wait for the weekend. Eight hundred. Linda's laughing. I

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Speaker 1: know I see you, even though I don't see you

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Speaker 1: because you're socially distant. But I think everybody agrees, not

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Speaker 1: easy days, not long times, long hard days, books, long

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Speaker 1: hard days. And that's why someone just send Ellen like

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Speaker 1: some of Nancy Pelosi's ice cream for me do something,

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Speaker 1: because it's it's that crazy, it's that insane, it is

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Speaker 1: that mad. I know I mentioned this yesterday. I think

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Speaker 1: it bears repeating here. Is that you know I've done

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Speaker 1: this now for thirty one years talk radio, when I

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Speaker 1: got first started my journey, and now my twenty fourth

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Speaker 1: year at Fox. Even I'm surprised I'm still there in

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Speaker 1: the sense that you know, I didn't have any TV

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Speaker 1: experience when I started, and I'm very honored to be

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Speaker 1: able to do this with all of you every day.

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Speaker 1: And it's certainly you have your your your tough times,

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Speaker 1: your harder times, and you know there's always an election year.

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Speaker 1: I try to always warn people that it's going to

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Speaker 1: be an emotional rollercoaster, and you don't know until election

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Speaker 1: day what the result's going to be. And there's ups

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Speaker 1: and downs, and times you're gonna be feeling good about

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Speaker 1: where you are and the and the people that you

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Speaker 1: think are gonna win, and and other times you're gonna doubt.

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Speaker 1: And you know, I'm kind of used to that. I'm

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Speaker 1: actually pretty steady about going through all of those cycles.

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Speaker 1: And this nobody expected. The response of some people is

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Speaker 1: just downright repulsive. It is predictably the same people that

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Speaker 1: always that for the last three and a half years

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Speaker 1: have lied, smeared, slandered, besmirched, attacked, advanced more psychotic conspiracy

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Speaker 1: theories than you would ever think could happen in America.

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Speaker 1: I never thought in my lifetime that we would see

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Speaker 1: such a dramatic drift, this hard left by the by

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Speaker 1: the the other party in the country. I mean, you

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Speaker 1: could say we're not a two parties. We're basically two parties.

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Speaker 1: It's Republican and it's democrat. It's not like we have

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Speaker 1: a parliamentary system of government. You want to talk about

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Speaker 1: a mad electoral system, Let's look at Israel. It's nuts

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Speaker 1: three elections, so we get a you know, finally get

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Speaker 1: a coalition government up and running there and h Prime

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Speaker 1: Minister net Yahoo now in that position for the next

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Speaker 1: eighteen months, Thank goodness. But it's hard to go through

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Speaker 1: nearly an entire year without a government. But that's happening.

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Speaker 1: I look at the New York Times. I don't really

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Speaker 1: have words for them anymore except stay tuned and today's

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Speaker 1: disaster by them. And it's so interesting when you actually

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Speaker 1: look at their timeline and you know, the Trump virus

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Speaker 1: at the end of February and them saying that if

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Speaker 1: you're feeling awful, you know who to blame. Specific articles

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Speaker 1: that I won't regurgitate now here this minute. Hope everybody

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Speaker 1: there has a good weekend, but I will tell you that,

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Speaker 1: you know, I look at this and I'm like, Donald

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Speaker 1: Trump puts the travel van in effect, everybody criticizes it.

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Speaker 1: Now in retrospect, nobody will give him credit for anything.

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Speaker 1: And it's even worse than that because you add to

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Speaker 1: that the subsequent travel bans, the quarantine for the first

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Speaker 1: time in fifty plus years, then the largest fastest, quickest

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Speaker 1: medical mobilization in the history of this country by far,

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Speaker 1: and successfully. When you start out, you know, with models

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Speaker 1: showing two and a half million people dead in this

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Speaker 1: and it doesn't happen, And you would think it would

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Speaker 1: be reason for people to say, hey, job well done.

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Speaker 1: How did you build those those twenty five thirty thousand

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Speaker 1: hospital beds in four weeks? How did you get the

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Speaker 1: Javit Center up? How did you get the Navy hospital

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Speaker 1: ships in place? How did you how did you end

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Speaker 1: up getting all the ventilators? Nobody was short of a ventilator,

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Speaker 1: that needed a ventilator. How did you mitigate it? What

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Speaker 1: did you do? You know it, if history is honest,

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Speaker 1: it's going to it's going to look very favorable at

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Speaker 1: what is really transformational approaches towards everything from how we

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Speaker 1: protect Americans, travel bands, public private partnerships, um, the you know,

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Speaker 1: the ability of a country to function when one small,

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Speaker 1: when a small when part of the country geographically speaking,

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Speaker 1: has had to shut down, we're sustained by the rest

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Speaker 1: of the society. New different the challenge lenges specifically for

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Speaker 1: the medical equipment that was needed, the challenges to keep

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Speaker 1: grocery stores, you know, stopped and full with needed food

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Speaker 1: and supplies and medical supplies and pharmaceutical issues. And you know,

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Speaker 1: twenty iterations of testing. I mean, it's it's it's fairly

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Speaker 1: you know, it's so exhaustively extensive, and yet there's no

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Speaker 1: credit given at all to the people that were able

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Speaker 1: to pull it off in record time, having rewritten the

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Speaker 1: books on pandemics and having rewritten the books on any

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Speaker 1: type of need for any medical mobilization. And then even

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Speaker 1: worse than that, even though you end up mitigating the

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Speaker 1: models that predicted high numbers of death, not only do

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Speaker 1: you get no credit for this, then you get called

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Speaker 1: the murderer pretty much. That's that's now happening more and

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Speaker 1: more and more every day. I mean, we had this

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Speaker 1: with Joe Scarborough yesterday, you know, screaming about the president,

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Speaker 1: and you know, I just I don't even have words

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Speaker 1: to describe how repulsive some of these people are, but

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Speaker 1: they are that repulsive. And I'm almost to the point

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Speaker 1: where I'm like, it's sort of like a Jesus on

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Speaker 1: the Cross moment. Forgive them, Father, for they know not

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Speaker 1: what they do in the sense that they're so angry,

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Speaker 1: they're so out of touch with reality, they're so psychotic,

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Speaker 1: they're so full of rage that I think for some

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Speaker 1: maybe it's the ends justifies the means that their agenda

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Speaker 1: is that important. For a lot of them, it's just

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Speaker 1: rooted in a psychotic hatred of all things Trump or

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Speaker 1: any Trump supporter. It's never been this bad, at least

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Speaker 1: that I have seen in my lifetime. And then there's

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Speaker 1: a whole level of ignorance that you just want to

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Speaker 1: believe alternative realities and an alternative universe and alternative facts.

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Speaker 1: New York Times today, how Republicans became the party of death.

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Speaker 1: That's the headline, that is the New York Times. The

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Speaker 1: same New York Times February fifth, who says it's not

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Speaker 1: safe to travel to China, the same New York Times

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Speaker 1: Trump virus. If you're feeling awful, you know who to blame. Unbelievable,

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Speaker 1: multiple articles suggesting that individuals that you know, well, you

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Speaker 1: know basically are responsible for murder. Wow, I supported the

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Speaker 1: travel band. Not many people did. Those that did were

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Speaker 1: called xenophobic, racist, hysterical fearmongers. Well, that travel band incalculable.

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Speaker 1: How many lives were protected from contracting the virus, subsequently

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Speaker 1: dying from this virus, etc. And then when you say

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Speaker 1: it's a hoax, well, if you if you say it's

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Speaker 1: a hoax. But you've been warning people for months about

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Speaker 1: asymptomatic people and talking to the experts and the doctors

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Speaker 1: and everybody in between, and way ahead of the curve,

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Speaker 1: understanding that there is real danger here. Would would negate

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Speaker 1: that if logic, reason, common sense were to prevail. But

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Speaker 1: it's not prevailing. You know, you think through history, how

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Speaker 1: is it that human beings and we've seen this over

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Speaker 1: and over again. There are I mean, the world is

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Speaker 1: littered with a history of mass psychosis, hypnosis, madness that

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Speaker 1: you know, human beings desire to be accepted and a

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Speaker 1: part of something, you know, showing the greater allegiance than

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Speaker 1: others because of a fear that drives them. It's littered

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Speaker 1: with these stories. It's not a new phenomenon. Not a

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Speaker 1: lot of new things here anyway. I look at the

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Speaker 1: numbers every day, sometimes every hour, Timothy Egan, the writer

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Speaker 1: in the New York Times, sometimes before dawn. China is

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Speaker 1: not to be trusted. Nor is Russia. I'm always curious

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Speaker 1: about the latest death toll out of Sweden. Sweden followed

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Speaker 1: the Herd approach, which we had spoken about at length,

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Speaker 1: a country with a riskier, more self regulated approach to

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Speaker 1: keeping people apart. Then he goes on to their etcetera, etcetera,

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Speaker 1: about the drop in this and all of us want

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Speaker 1: the same thing, a roadmap to the way out. Scientific

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Speaker 1: consensus is clear, it's not complicated. We need a significant

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Speaker 1: upgrade of testing, contact, tracing, track the infected nuance, dutiful

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Speaker 1: social isolation all the by time until a vaccine is developed.

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Speaker 1: But the political way out reveals a stark divide and

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Speaker 1: some true madness for Republicans. That pro life slogan of

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Speaker 1: theirs is just another term for nothing left to lose.

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Speaker 1: They are now the party of death, the party of death.

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Speaker 1: And then they go into this and really what some

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Speaker 1: are suggesting is if you open the country. And this

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Speaker 1: is now becoming a bit of a talking point. Number one.

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Speaker 1: I won't give Donald Trump credit for what he's done. Ever,

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Speaker 1: Trump can do nothing right in their eyes. The next

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Speaker 1: thing is if you want to open the country safely.

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Speaker 1: We have discussed the Hannity plan to open New York

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Speaker 1: City exhaustively. Gomez yells at me, Linda, because you have

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Speaker 1: to say it again. I'm like, well, the reason is

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Speaker 1: is because I'm trying to get the right sweet spot formula.

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Speaker 1: That is safe and yet allows people you know, back

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Speaker 1: to do what they do. And I think it's a

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Speaker 1: reasonable plan for New York City. All right, everyone in

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Speaker 1: a big building, half the workers stay home, let them

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Speaker 1: tell a work. I think that's reasonable. That means you're

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Speaker 1: creating in every building in New York, you're building in

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Speaker 1: social distancing guidelines. Then I take it a step further. Okay,

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Speaker 1: every building in New York you at least get a

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Speaker 1: temperature check, and when enough tests come online, you can

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Speaker 1: make that a part of it as well. The next

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Speaker 1: thing is everybody that does go it to work must

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Speaker 1: wear masks and gloves and have that again, because half

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Speaker 1: the working population is home, you'll have the social distance

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Speaker 1: even built into that. I think it's reasonable. I think

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Speaker 1: it's safe. I'm asking doctors, I'm asking professionals, and then

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Speaker 1: everyone gets to get back to work. And what's ironic

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Speaker 1: here about the we can't open up crowd. It's murder,

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Speaker 1: it's the party of death. Is that? Well? Um, if

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Speaker 1: we close the country down, New York and New Yorkers

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Speaker 1: and New York is to say, the right way, if

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Speaker 1: you're from New York, they're not real New York is

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Speaker 1: Governor Cuomo's gonna say, sound like Cuomo, I know, but

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Speaker 1: all of this is true. Well, New york Is would

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Speaker 1: have died. They would have all been dead but for

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Speaker 1: the farmers farming, the packers packing, the truckers trucking, and

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Speaker 1: the guys stocking the shelves stocking. Because the only reason

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Speaker 1: New Yorkers got to eat, and I'm in New York

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Speaker 1: is because of those people. And those stockers stocking were

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Speaker 1: risking their lives, but they did it safely. I've not read.

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Speaker 1: I don't know if it's the case about a high

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Speaker 1: incidence of people stocking with masks and gloves contracting COVID.

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Speaker 1: And when I go to the store, I kind of

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Speaker 1: go out of my way to say thank you to

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Speaker 1: these people, the people that were manufacturing. If we closed down,

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Speaker 1: there wouldn't many ventilators made new ventilators, no respirators, no masks,

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Speaker 1: no gloves. There would be no gowns, there would be

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Speaker 1: no medicines, there'd be nothing. So you know, it's a

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Speaker 1: it's a great strategy that we all stay indoors and hide.

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Speaker 1: But if that happened in this instance, New York was

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Speaker 1: wouldn't eat, wouldn't have any medicine, healthcare, frontline healthcare workers

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Speaker 1: would not the heroes and all this would not have

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Speaker 1: the protective equipment and gear, the pharmaceuticals and the ventilators

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Speaker 1: that they needed to do their job every day. There

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Speaker 1: are smart, intelligent people in this country, the doctors, the scientists.

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Speaker 1: You know, let's do it safely and figure it out.

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Speaker 1: The other thing is otherwise we can't afford to do

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Speaker 1: this forever, and there will be poverty and poverty resulting

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Speaker 1: eventually in sickness, impossible death as a result of that.

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Speaker 1: By the way, coronavirus patients you want to talk about

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Speaker 1: New York, not only would they totally ill prepared, no ventilators, nothing.

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Speaker 1: You can thank Donald Trump, Comrade Dablasia, we bailed your

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Speaker 1: sur ass out anyway. Coronavirus patients admitted to Queen's nursing

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Speaker 1: home with body bags, with body bags. By the way,

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Speaker 1: I've read the timeline in March of the Plazio and Cuomo.

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Speaker 1: They didn't see it coming in March. We'll talk about timelines.

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Speaker 1: They screwed it up bad and still had nothing. All right,

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Speaker 1: as we've been doing now for a number of fridays,

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Speaker 1: Doctor Oz will take your questions at eight hundred and

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Speaker 1: nine for one sean, if you want to get on

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Speaker 1: the line now, you can huge blow up in New

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Speaker 1: York now. And it's amazing when you think of Governor

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Speaker 1: Cuomo and nine forty thousand menta laters, and they were

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Speaker 1: prepared for nothing. Same with Comrade d Blasio. The headline

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Speaker 1: of this article is new patients and body bags. Cuomo

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Speaker 1: order stained strains nursing homes anyway. They quote a nursing

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Speaker 1: home in Queens, New York, under a state mandate to

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Speaker 1: take in COVID nineteen positive patients, also got a supply

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Speaker 1: of bodybags. I'm reading from the New York Post, and

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Speaker 1: executive at the facility, previously free of the deadly disease,

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Speaker 1: said the bags were in shipment of personal protective equipment

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Speaker 1: received the same day the home was forced to begin

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Speaker 1: treating two people with COVID nineteen who had been discharged

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Speaker 1: from hospitals. My colleague noticed that one of the boxes

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Speaker 1: was extremely heavy. Curious as to what could possibly be

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Speaker 1: making that particular box much heavier than the rest, he

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Speaker 1: opened it, the exact told the Post on Thursday. The

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Speaker 1: first two coronavirus patients were accompanied by five bodybags. Governor

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Speaker 1: Cuomo's comments literally now are exploding and if the standard

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Speaker 1: he set for Donald Trump holds for him, it's not

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Speaker 1: going to be good. And read d Blasio in this too,

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Speaker 1: will explain I had twenty five now till the top

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Speaker 1: of the hour, eight hundred and nine four one sean

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Speaker 1: top of the hour, full hour. Doctor Oz will take

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Speaker 1: any questions. You have. Really come to admire him a

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Speaker 1: lot as somebody. I mean, he's I love his line.

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Speaker 1: It's like you got to go into battle with the

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Speaker 1: army you have, not the army you wish you have,

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Speaker 1: and all in to save lives, and it is you know,

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Speaker 1: you would think that that would be people's focus. Earlier

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Speaker 1: this week I did highlight the success of Governor Ronda

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Speaker 1: Santis down in Florida. So the incidents comparatively like Michigan.

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Speaker 1: I'm not comparing it even to New York, but because

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Speaker 1: of their their high percentage of elderly folks retired down there,

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Speaker 1: from the villages on all throughout South Florida, frankly, all

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Speaker 1: over Florida. You know a lot of retirees go down

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Speaker 1: there and you know they have great times and the

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Speaker 1: weather is better, etc. Etc. But um I was Again

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Speaker 1: we knew and this held throughout the entire thing. For example,

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Speaker 1: the in New York, ninety four percent in the hospital

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Speaker 1: with COVID had pre existing conditions. Sixty four percent of

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Speaker 1: New York State deaths were over age seventy. So again

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Speaker 1: there was a moment in time when we actually thought

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Speaker 1: that younger that we didn't think younger people was susceptible

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Speaker 1: at all than that change and change it just didn't

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Speaker 1: work out in terms of mortality, etc. Etc. Though there

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Speaker 1: are terrible stories out there. One really heartbreaking story I

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Speaker 1: saw somewhere about a firefighter lost his young baby to coronavirus.

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Speaker 1: I mean, it just it just breaks your heart on

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Speaker 1: every level. Anyway, So the the comfort we know made

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Speaker 1: it to New York. If I can open this up

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Speaker 1: on my application on the thirtieth of March. Okay, then

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Speaker 1: remember the president also built the Javit Center. What was that?

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Speaker 1: I think that that Javit Center was open on three

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Speaker 1: twenty four. So that's why I'm looking at this report

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Speaker 1: in the New York Post today. And remember, you know,

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Speaker 1: everyone's got the answer for their own timelines, their own questions,

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Speaker 1: their own their own comments, their own stupidity. A lot

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Speaker 1: of it though, is you know, well, what were the

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Speaker 1: experts telling us? And I say this with great respect

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Speaker 1: for doctor Fauci, I really do this. People lived because

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Speaker 1: of doctor Fauci's life work. They just did. There is

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Speaker 1: a big component in this, which is that China lied,

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Speaker 1: and that China knew how bad it was, and that

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Speaker 1: China would not allow travel out of Wuhan to anywhere

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Speaker 1: else in China or anyone from China going into Wuhan

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Speaker 1: that wasn't from Wuhan. But they didn't keep open flights

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Speaker 1: internationally to the rest of the world. They knew how

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Speaker 1: bad it was. They only protected themselves. Then the more

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Speaker 1: recent reports is that once they saw it was really bad,

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Speaker 1: then they're going around the world gobbling up all of

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Speaker 1: the medical equipment they can and report this week that

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Speaker 1: they're actually profiteering from all of this and the fact

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Speaker 1: that they lied. I mean, it's I am more angry

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Speaker 1: at China every single solitary day. It is outrageous to me.

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Speaker 1: And but again, you look at the timeline when you

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Speaker 1: start getting into later, the later time period here, and

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Speaker 1: you look at for example, doctor Fauci, you know, February

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Speaker 1: twenty ninth, the country as a whole still remains at

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Speaker 1: low risk. He says that eat you remember the ninth

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Speaker 1: of March, he said, if you're young and healthy, you

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Speaker 1: can go on a cruise. Think of that. Wuhan efforts

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Speaker 1: have been draconi draconian, he said March eighth. The risk

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Speaker 1: of getting into trouble with this infection mainly if you're

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Speaker 1: infected as overwhelmingly weighted towards people with underlying conditions and

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Speaker 1: the elderly. And he was saying that on Meet the

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Speaker 1: Press on March the eighth, and he said about the efforts,

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Speaker 1: for example in China, he said that their efforts have

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Speaker 1: been draconian, something we would never be able to do here,

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Speaker 1: even suggesting that we would never be able to do

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Speaker 1: the things that we ultimately ended up doing at and

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Speaker 1: around the same time. So, you know, a lot of

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Speaker 1: people said a lot of things. And it's not to

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Speaker 1: be critical so much of doctor Fauci. It's that's not

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Speaker 1: the purpose of me bringing this up here. Now, those

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Speaker 1: in the mob and the media that are out there

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Speaker 1: politicizing this and have been from day one, while we

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Speaker 1: were right in calling them out. Wasn't hard to see,

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Speaker 1: you know, wasn't me saying coronavirus is scary, but the

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Speaker 1: flu is you know, hang on, get a grip America.

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Speaker 1: This was the Washington Post of flu is much bigger,

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Speaker 1: a much bigger threat than coronavirus. Really, Oh okay, I'm

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Speaker 1: I'm I'm reading you know Washington Post past pandemics, prough

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Speaker 1: Fighting coronavirus with a travel ban is a mistake. Well,

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Speaker 1: we would have listened to them. That wouldn't have been

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Speaker 1: too smart, would it. Just like we have the New

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Speaker 1: York Times who says it's not safe to travel to China. Now,

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Speaker 1: I guess based on the logic of the New York Times,

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Speaker 1: their advice to their readers would mean, if you you know,

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Speaker 1: you're telling people at that time it's safe to go

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Speaker 1: to China. Wow, okay, late February, let's call it the

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Speaker 1: Trump virus. If you're feeling awful, you know who to blame.

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Speaker 1: And and it's it's so outrageous how people have politicized

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Speaker 1: all of this, and those of us that called that

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Speaker 1: out somehow a wrong. But it's obvious because it's the

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Speaker 1: same groups of people that have been lying to the

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Speaker 1: American people for years, the same people that smear, lie, slander,

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Speaker 1: besmirched Trump for three and a half years. The same

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Speaker 1: people that spread conspiracy theories, outright lies, falsehoods, and hoaxes.

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Speaker 1: They're the worst in all of this. You got the

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Speaker 1: Democratic Party, their leaders. Nancy Pelosi comedy shows last week,

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Speaker 1: twenty four thousand dollars freezers, two of them gourmet ice cream,

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Speaker 1: in the comfort of her gated community mansion. While she

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Speaker 1: delays two bills to help people with small businesses and

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Speaker 1: workers and hospital supplies, et cetera. She held them both up,

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Speaker 1: you know it. Demands to change election laws, and demands

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Speaker 1: that we're going to change immigration law, with demands that

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Speaker 1: we pay seventy five million for the National Endowment for

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Speaker 1: the Arts, another seventy five million National down for the Humanities.

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Speaker 1: She gets twenty five million for the Kennedy Center for

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Speaker 1: the Arts. It's unconscionable to me. And then you look

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Speaker 1: at New York in particular, and I'm gonna get back

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Speaker 1: to this New York Post story in a second. You know,

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Speaker 1: by the way, the first COVID nineteen positive case in

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Speaker 1: the United States was January twenty first, the first one

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Speaker 1: in New York, according to Governor Cuomo was. You know,

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Speaker 1: he's quoted as saying, March first, this evening we learned

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Speaker 1: of the first positive case of coronavirus or COVID nineteen

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Speaker 1: in New York State. The patient, a woman in her

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Speaker 1: late thirties, contracted the virus while traveling aboard and abroad

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Speaker 1: in Iran and currently is isolated, etc. Etc. There's no

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Speaker 1: cause for surprise. This was expected. As I said from

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Speaker 1: the beginning, Well, I have a particular bone to pick

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Speaker 1: with all these politicians in New York because well, they're

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Speaker 1: the top terror target in the world. They are, you know,

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Speaker 1: with the highest concentration of people, the most densely populated,

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Speaker 1: the smallest geographical area. And you have a New York

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Speaker 1: City study in a New York State study study, the

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Speaker 1: city study in two thousand and six, the state November

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Speaker 1: twenty fifteen telling the city to get ten thousand, ven

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Speaker 1: the laters telling the state to get fifteen thousand, seven

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Speaker 1: hundred eighty three ventilators point four percent of what the

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Speaker 1: New York State budget would be. And they never did it.

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Speaker 1: They never did it. The fact that the President again,

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Speaker 1: this is the biggest medical mobilization in history, and I

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Speaker 1: will give Cuomo credit in this sense, Cuomo, you know

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Speaker 1: at times he was reluctant, but he did thank the

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Speaker 1: President appropriately enough. What do I need to send him

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Speaker 1: a cake? You know, if there were times they had

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Speaker 1: their run ins. But I think in the end, Donald

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Speaker 1: Trump got it done for New York, and the idiot

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Speaker 1: mayor's out there, you're going to suit the New York

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Speaker 1: drop dead when he bailed them out. If you don't

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Speaker 1: have Trump's personnel at the Javit Center building, the three

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Speaker 1: thousand beds and the comfort and the personnel also there,

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Speaker 1: and all your ventilators because you guys didn't buy them,

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Speaker 1: and all the gowns, mass respirators, shields, gloves, you name it, medicines,

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Speaker 1: you don't have it. You guys have nothing. And if

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Speaker 1: you don't have these other people working stocking shelves and

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Speaker 1: going into grocery stores and everybody else in the country

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Speaker 1: producing all of this, New York has nothing. The country

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Speaker 1: stood up for New York again. They did it after

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Speaker 1: nine to eleven. They did it again. Everybody in New

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Speaker 1: York needs to know that the rest of the country

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Speaker 1: was all in to help save New York as we

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Speaker 1: would be there for them just the way. That's how

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Speaker 1: we roll. We're there for the rest of the world.

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Speaker 1: We're going to be there for our own family, even

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Speaker 1: if we have political fights that are any dramatic. But

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Speaker 1: even as late as March second, you know, you know,

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Speaker 1: we had Governor Cuomo. Remember they had no ventilators, they

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Speaker 1: had no they weren't prepared for anything. And he's saying,

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Speaker 1: we have the best healthcare system. He says, we're extrapolating

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Speaker 1: what happened in China and other countries. We have the

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Speaker 1: best healthcare system in the world right here. And excuse

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Speaker 1: our arrogance as New Yorkers, I speak for the mayor

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Speaker 1: also on this one. We think we have the best

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Speaker 1: healthcare system on the planet right here in New York.

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Speaker 1: So when you're saying what happened in other countries versus

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Speaker 1: what happened here, we don't even think it's gonna be

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Speaker 1: as bad as it was in other countries. How wrong

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Speaker 1: they were, and you know it is the mayor. He's

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Speaker 1: even worse. I don't even know what to say about

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Speaker 1: this guy. March first, he's tweeting out, Okay, New York

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Speaker 1: confronts first coronavirus case. We have been preparing for jarring

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Speaker 1: to see Mayor Bloomberg at Mike Bloomberg pay millions to

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Speaker 1: rewrite history. Well, Bloomberg at least bought five ventilators. The

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Speaker 1: guy that didn't maintain them was the Blasio. The guy

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Speaker 1: that sold him at auction to some unknown person was

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Speaker 1: the Blasio. He had none, only what the hospitals had.

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Speaker 1: Since I'm encouraging New Yorkers March second, to go on

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Speaker 1: with your lives, get out on the town despite coronavirus,

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Speaker 1: I thought I would offer some suggestions. You know, here's

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Speaker 1: the first through Thursday three to five. Go see The Trader.

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Speaker 1: If The Wire was a true story and set in Italy,

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Speaker 1: it would be this film. March tenth, the Blasio. Go

425
00:27:41,960 --> 00:27:46,399
Speaker 1: about your life as you normally would. Transmission is not

426
00:27:46,640 --> 00:27:52,000
Speaker 1: that easy. I'm not making it up either, and it's

427
00:27:52,320 --> 00:27:57,200
Speaker 1: you know, look, it's it's frustrating. Then now we're learning

428
00:27:57,320 --> 00:28:00,240
Speaker 1: why did Ron de Santa save How did Ron the

429
00:28:00,240 --> 00:28:02,720
Speaker 1: Santis do it? He got the crap beat out of

430
00:28:02,760 --> 00:28:05,800
Speaker 1: him over the spring Breakers. Okay, maybe fair criticism, maybe

431
00:28:05,920 --> 00:28:09,159
Speaker 1: to some degree at the time, in fairness for listening

432
00:28:09,200 --> 00:28:12,040
Speaker 1: to Fauci, he's saying, yeah, young people, he was saying

433
00:28:12,040 --> 00:28:15,200
Speaker 1: March ninth. Young people healthy can go on cruises, So

434
00:28:15,960 --> 00:28:18,359
Speaker 1: I think he'd have a way to say that the

435
00:28:18,440 --> 00:28:20,720
Speaker 1: experts were saying young people are gonna be okay. Anyway,

436
00:28:20,760 --> 00:28:23,040
Speaker 1: back to this piece in the New York Post today

437
00:28:23,240 --> 00:28:26,680
Speaker 1: new patients body bags. My colleague noticed one of the

438
00:28:26,720 --> 00:28:31,240
Speaker 1: boxes was extremely heavy. This is right after Governor Cuomo

439
00:28:31,680 --> 00:28:37,600
Speaker 1: ordered nursing homes to take on COVID nineteen patients, and

440
00:28:37,720 --> 00:28:42,160
Speaker 1: he goes within within days, three of the bags held

441
00:28:42,680 --> 00:28:46,960
Speaker 1: the first thirty residents who would die there after Governor

442
00:28:47,000 --> 00:28:50,480
Speaker 1: Cuomo's Department of Health and Mental Hygiene handed down It's

443
00:28:50,520 --> 00:28:54,640
Speaker 1: March twenty fifth directed directive that would bar nursing homes

444
00:28:54,640 --> 00:28:59,520
Speaker 1: from refusing to admit medically stable coronavirus patients according to

445
00:28:59,560 --> 00:29:03,080
Speaker 1: the direct Then he goes on to say, like clockwork,

446
00:29:03,200 --> 00:29:06,600
Speaker 1: the nursing home received five body bags a week every

447
00:29:06,640 --> 00:29:10,400
Speaker 1: week from city officials. Quote Cuomo has blood on his hands.

448
00:29:11,120 --> 00:29:14,120
Speaker 1: There's no way to sugarcoat this. Why in the world

449
00:29:14,160 --> 00:29:17,200
Speaker 1: would you be sending coronavirus patients to a nursing home

450
00:29:18,400 --> 00:29:23,320
Speaker 1: where they're where the most vulnerable population of this disease resides.

451
00:29:24,800 --> 00:29:28,080
Speaker 1: How do you answer that? Anyway? Since March twenty fifth,

452
00:29:28,080 --> 00:29:31,200
Speaker 1: the Queen's nursing home had admitted seventeen such patients from

453
00:29:31,240 --> 00:29:35,640
Speaker 1: hospitals testing positive for corona. But in a bitter irony,

454
00:29:36,160 --> 00:29:40,719
Speaker 1: most of them fared well. Those who have died passed

455
00:29:40,720 --> 00:29:44,440
Speaker 1: away without a test while awaiting results, etc. Etc. You

456
00:29:44,480 --> 00:29:47,160
Speaker 1: should have known, I guess by that point though, the

457
00:29:47,200 --> 00:29:49,720
Speaker 1: rest of the people are dropping like flies. Most of

458
00:29:49,720 --> 00:29:53,120
Speaker 1: them have been with us for years. Then he goes,

459
00:29:53,120 --> 00:29:57,160
Speaker 1: that's what he describes here. Now as you go through,

460
00:29:57,200 --> 00:29:59,360
Speaker 1: there's a lot of finger pointing in all of this,

461
00:30:00,320 --> 00:30:03,200
Speaker 1: and you know, they go into more details about officials

462
00:30:03,200 --> 00:30:07,080
Speaker 1: all around the state of New York. And remember this

463
00:30:07,160 --> 00:30:11,600
Speaker 1: was a dictate from from the government of New York.

464
00:30:12,800 --> 00:30:15,600
Speaker 1: Now what the governor said. Now there's another fight with

465
00:30:15,640 --> 00:30:20,480
Speaker 1: the Blasio and Cuomo. The Blasio is now saying Cuomo

466
00:30:21,560 --> 00:30:24,320
Speaker 1: and his assertion that it's not our job to supply

467
00:30:24,480 --> 00:30:27,520
Speaker 1: nursing homes with coronavirus safety gear, saying that there's a

468
00:30:27,600 --> 00:30:31,600
Speaker 1: moral imperative to protect our seniors. Look, protecting senior citizens,

469
00:30:31,640 --> 00:30:34,600
Speaker 1: protecting people in nursing homes is for all of us.

470
00:30:34,640 --> 00:30:38,680
Speaker 1: It's our job, it's our responsibility. It's a little ironic

471
00:30:38,720 --> 00:30:42,120
Speaker 1: considering you know, because Cuomo said that if nursing homes

472
00:30:42,120 --> 00:30:45,400
Speaker 1: can't properly quarantine and treat COVID patients, the homes were

473
00:30:45,400 --> 00:30:48,800
Speaker 1: supposed to move them to facilities. But then the mandate

474
00:30:48,840 --> 00:30:53,160
Speaker 1: comes down, and then Cuomo doubles down on his remark

475
00:30:54,120 --> 00:30:56,320
Speaker 1: that this is the rule and that's the regulation and

476
00:30:56,360 --> 00:30:59,719
Speaker 1: they have to comply. And then he's saying, well, I'm

477
00:30:59,760 --> 00:31:03,320
Speaker 1: not responsible. The nursing homes are responsible. Imagine if Trump

478
00:31:03,360 --> 00:31:06,400
Speaker 1: said that to New York. You guys should have prepared

479
00:31:06,440 --> 00:31:09,480
Speaker 1: for this. I think there would have been a lot

480
00:31:09,480 --> 00:31:13,280
Speaker 1: of screaming from everybody in New York. But it is.

481
00:31:14,360 --> 00:31:19,000
Speaker 1: It's just sad because the one thing that we learned here,

482
00:31:19,040 --> 00:31:22,480
Speaker 1: now there's a learning curve, there is, But we knew

483
00:31:22,520 --> 00:31:26,640
Speaker 1: all along it was older people that never changed. Older

484
00:31:26,680 --> 00:31:31,280
Speaker 1: people underlying conditions, compromised immune systems. That was always the case,

485
00:31:32,400 --> 00:31:34,800
Speaker 1: how you know, And what they did so brilliantly down

486
00:31:34,800 --> 00:31:38,800
Speaker 1: in Florida is they targeted that population like a laser beat.

487
00:31:40,000 --> 00:31:42,200
Speaker 1: It turned out to save lives down in Florida on

488
00:31:42,320 --> 00:31:46,959
Speaker 1: a mass skew. It turned out to be in many ways,

489
00:31:47,600 --> 00:31:52,280
Speaker 1: the dumbest, most dangerous, horrific thing choice that I have

490
00:31:52,360 --> 00:31:55,880
Speaker 1: seen to date on in all of this. All right,

491
00:31:55,880 --> 00:31:58,360
Speaker 1: glad you with us our two eight hundred and ninety

492
00:31:58,360 --> 00:32:00,440
Speaker 1: four one. Sean you want to be at of this

493
00:32:00,520 --> 00:32:04,320
Speaker 1: extravaganza as we've now been doing for a few weeks now.

494
00:32:04,840 --> 00:32:09,280
Speaker 1: Doctor Oz doesn't sleep, doesn't rest. His calling in life

495
00:32:09,560 --> 00:32:11,400
Speaker 1: is what it is. I've learned a lot about him

496
00:32:11,400 --> 00:32:17,320
Speaker 1: and have come to admire his work, ethic, his calling,

497
00:32:17,400 --> 00:32:22,160
Speaker 1: his passion, which is the health of everybody. I think

498
00:32:22,200 --> 00:32:25,040
Speaker 1: we've learned a lot from him. More importantly, you go

499
00:32:25,080 --> 00:32:27,640
Speaker 1: to war with the army you have, not the army

500
00:32:27,640 --> 00:32:30,280
Speaker 1: you wish you had, which is it's true, you do

501
00:32:30,360 --> 00:32:35,200
Speaker 1: the best you can. He's been right so often on

502
00:32:35,240 --> 00:32:38,920
Speaker 1: a lot of this, and I just appreciate him being here.

503
00:32:38,920 --> 00:32:41,000
Speaker 1: And we're going to take your calls for the hour.

504
00:32:41,040 --> 00:32:44,280
Speaker 1: How are you, sir, Welcome back, Thank you very much.

505
00:32:44,280 --> 00:32:46,960
Speaker 1: I'm doing very well. Thank you really a lot for

506
00:32:47,000 --> 00:32:49,840
Speaker 1: doing this. All right. So now we have the lowest

507
00:32:49,880 --> 00:32:52,720
Speaker 1: death toll in New York since March thirty first today,

508
00:32:52,880 --> 00:32:56,920
Speaker 1: still too many people, four hundred and twenty two. We

509
00:32:57,000 --> 00:33:02,320
Speaker 1: have the hospitalization number at fourteen thousand and seven hundred

510
00:33:02,720 --> 00:33:05,280
Speaker 1: below fifteen thousand for the first time in twenty days.

511
00:33:05,400 --> 00:33:09,600
Speaker 1: Net decrease hospital hospitalizations for eleven straight days, net decrease

512
00:33:10,040 --> 00:33:14,560
Speaker 1: intubations twelve straight days, still hovering around thirteen hundred new

513
00:33:14,560 --> 00:33:20,720
Speaker 1: coronavirus hospitalizations per day. And then the big big question

514
00:33:20,880 --> 00:33:23,240
Speaker 1: is how do you open a city like New York?

515
00:33:23,520 --> 00:33:26,960
Speaker 1: I think you know I you know the Hannity plan.

516
00:33:27,000 --> 00:33:28,640
Speaker 1: I don't want to repeat it. You know the Hannity

517
00:33:28,720 --> 00:33:32,200
Speaker 1: plan for stadiums that I have Am I am I there?

518
00:33:32,560 --> 00:33:34,480
Speaker 1: Or is it something that we can look at in

519
00:33:34,600 --> 00:33:38,200
Speaker 1: June July? What are your thoughts? And I don't want

520
00:33:38,240 --> 00:33:40,360
Speaker 1: to wrote either of us into a date because it's

521
00:33:40,400 --> 00:33:42,400
Speaker 1: really about data. And we're going to learn eight tons

522
00:33:42,840 --> 00:33:45,360
Speaker 1: from the states that are opening, even starting this weekend,

523
00:33:45,880 --> 00:33:47,920
Speaker 1: over the next few weeks, because New York City is

524
00:33:47,920 --> 00:33:49,880
Speaker 1: not going to open. New York State, I don't think

525
00:33:49,880 --> 00:33:52,200
Speaker 1: their plans and even the northern parts of the state

526
00:33:52,240 --> 00:33:54,600
Speaker 1: to open, So we're going to watch what happens in

527
00:33:54,680 --> 00:33:56,280
Speaker 1: parts of the the country they have not been hard hit.

528
00:33:56,560 --> 00:33:58,000
Speaker 1: It's for those of you listening for the parts of

529
00:33:58,040 --> 00:34:00,520
Speaker 1: three country. It's to see what on and I saw

530
00:34:00,520 --> 00:34:03,560
Speaker 1: on this part in New York area in particular, it's stunning,

531
00:34:03,560 --> 00:34:06,000
Speaker 1: and we have the mortalities here, have the case. They're here.

532
00:34:06,560 --> 00:34:10,120
Speaker 1: You see, you know how how it could have been elsewhere.

533
00:34:10,120 --> 00:34:12,040
Speaker 1: And thankfully we don't think we're gona hit anywhere close

534
00:34:12,040 --> 00:34:13,880
Speaker 1: these numbers in other parts of the country. But we

535
00:34:13,920 --> 00:34:15,640
Speaker 1: want to be cautious. But the most important thing of

536
00:34:15,719 --> 00:34:18,920
Speaker 1: all the things happening now is more testing and making

537
00:34:18,920 --> 00:34:21,200
Speaker 1: sure that we don't miss hotspots. And by learning from

538
00:34:21,239 --> 00:34:23,799
Speaker 1: those experiences, we're gonna for the first time really know

539
00:34:23,920 --> 00:34:26,000
Speaker 1: for sure if you put your mask on before you

540
00:34:26,040 --> 00:34:27,799
Speaker 1: go to a restaurant where you're not packed on top

541
00:34:27,840 --> 00:34:30,719
Speaker 1: of each other and it's venerated, and you've got, you know,

542
00:34:30,719 --> 00:34:32,360
Speaker 1: the right kinds of soldiers in your air, does that

543
00:34:32,400 --> 00:34:34,480
Speaker 1: make a difference, Because if it does, then you can

544
00:34:34,520 --> 00:34:36,319
Speaker 1: go one step further. It's only march your way down

545
00:34:36,400 --> 00:34:38,239
Speaker 1: the road. Because we have to work out all those

546
00:34:38,320 --> 00:34:40,840
Speaker 1: kinks in places that are not as crowded. Because in

547
00:34:40,840 --> 00:34:43,200
Speaker 1: New York City we have unique problems. Right, We've got

548
00:34:43,200 --> 00:34:45,120
Speaker 1: subways to get to the stadium, so you can go

549
00:34:45,120 --> 00:34:46,719
Speaker 1: in the stadium. They might decide we might be even

550
00:34:46,800 --> 00:34:48,600
Speaker 1: more of a problem than sitting in the stadium. So

551
00:34:48,880 --> 00:34:50,960
Speaker 1: those kinds of things that we don't have all the

552
00:34:50,960 --> 00:34:53,400
Speaker 1: answers too. We ought to get pretty concrete on before

553
00:34:53,400 --> 00:34:55,840
Speaker 1: we start, you know, getting to plan the third stage

554
00:34:55,840 --> 00:34:58,640
Speaker 1: of opening the country. I spend a lot of time

555
00:34:58,719 --> 00:35:02,680
Speaker 1: this week not knowing this sorry existed about New York

556
00:35:02,920 --> 00:35:07,719
Speaker 1: and the mandate that they had March twenty fifth that

557
00:35:07,920 --> 00:35:11,680
Speaker 1: details how the state of New York forced nursing homes

558
00:35:11,680 --> 00:35:17,840
Speaker 1: to take COVID nineteen positive patients in Florida was very interesting,

559
00:35:17,840 --> 00:35:21,080
Speaker 1: and I know the governor down there got criticized for,

560
00:35:21,480 --> 00:35:25,239
Speaker 1: you know, the spring break issue, and but interestingly, I mean,

561
00:35:25,760 --> 00:35:30,359
Speaker 1: I'm making no excuses, I didn't like it, but we

562
00:35:30,360 --> 00:35:33,640
Speaker 1: were told in the beginning and mostly throughout this that

563
00:35:33,760 --> 00:35:36,480
Speaker 1: this was not a life and death issue for young

564
00:35:36,520 --> 00:35:39,239
Speaker 1: people by and large. It was where for example, H

565
00:35:39,320 --> 00:35:41,640
Speaker 1: one N one infected young people more than old people.

566
00:35:41,640 --> 00:35:43,960
Speaker 1: I mean, these viruses are you know, I'm learning so

567
00:35:44,040 --> 00:35:49,000
Speaker 1: much about him and and anyway, but he they early

568
00:35:50,160 --> 00:35:54,000
Speaker 1: on in the process in Florida targeted nursing homes. They

569
00:35:54,040 --> 00:35:55,920
Speaker 1: targeted the villages. I don't know, have you ever been

570
00:35:55,960 --> 00:35:59,920
Speaker 1: in the villages, the coolest place America's friendly home hometown?

571
00:36:00,160 --> 00:36:02,879
Speaker 1: You ever go down there at all? I've not been

572
00:36:02,880 --> 00:36:06,120
Speaker 1: there by older populations. Oh my god, it's the coolest thing.

573
00:36:06,200 --> 00:36:08,960
Speaker 1: They got a million golf courses. They got up their pickleball.

574
00:36:09,000 --> 00:36:11,400
Speaker 1: I don't even know what pickleball is. They got tennis,

575
00:36:11,680 --> 00:36:14,720
Speaker 1: they got movies, they got concerts, they got book clubs,

576
00:36:14,719 --> 00:36:17,279
Speaker 1: they got chess clubs. They've got this. I mean, they

577
00:36:17,360 --> 00:36:20,120
Speaker 1: got bars, they drink, they have a blast. It's like,

578
00:36:20,320 --> 00:36:23,080
Speaker 1: you know, it's cool. It's very fun place. And I've

579
00:36:23,120 --> 00:36:25,680
Speaker 1: been down there and I'm very impressed. But they targeted

580
00:36:26,360 --> 00:36:30,799
Speaker 1: specifically the elderly population, which is quite high as you

581
00:36:30,840 --> 00:36:35,280
Speaker 1: know in Florida, and the numbers are so dramatically lower.

582
00:36:35,719 --> 00:36:38,160
Speaker 1: And I'll take New York, New Jersey, Connecticut out of it,

583
00:36:38,600 --> 00:36:42,880
Speaker 1: then say a state like Michigan dramatically because they did that.

584
00:36:42,960 --> 00:36:46,040
Speaker 1: Now in New York we have this story where not

585
00:36:46,080 --> 00:36:49,880
Speaker 1: only where the COVID nineteen patients sent into the nursing homes,

586
00:36:50,760 --> 00:36:54,040
Speaker 1: that body bags were sent with them. How could that

587
00:36:54,160 --> 00:36:57,120
Speaker 1: decision have been made that late in March? And I'm

588
00:36:57,120 --> 00:37:00,440
Speaker 1: again I'm not playing politics here, I'm like, wow, you know,

589
00:37:00,560 --> 00:37:04,920
Speaker 1: you got what a contrast in decision making and literally

590
00:37:04,960 --> 00:37:09,839
Speaker 1: the consequences associated with it. I Honestly, I think the

591
00:37:10,040 --> 00:37:13,200
Speaker 1: entire world and our perspectives changed during the month of March.

592
00:37:13,239 --> 00:37:16,520
Speaker 1: We went from being fairly confident, i'd even say cocky

593
00:37:16,520 --> 00:37:18,720
Speaker 1: and our ability to address the virus that had already

594
00:37:18,760 --> 00:37:21,440
Speaker 1: hurt other parts of the world, to recognize these acts

595
00:37:21,440 --> 00:37:24,040
Speaker 1: exactly how devastating it could be when it's not. In

596
00:37:24,040 --> 00:37:27,400
Speaker 1: this more new data coming out from Northeastern arguing that

597
00:37:27,440 --> 00:37:29,360
Speaker 1: there were hundreds of thousands of cases here before we

598
00:37:29,400 --> 00:37:31,440
Speaker 1: even realized we had a problem. So of course it

599
00:37:31,520 --> 00:37:34,319
Speaker 1: made it much more difficult because you didn't realize that

600
00:37:34,320 --> 00:37:38,680
Speaker 1: the tsunami was about to hit you. Yeah, well, I know,

601
00:37:38,840 --> 00:37:42,200
Speaker 1: but but from the earliest days, I do remember one

602
00:37:42,239 --> 00:37:45,360
Speaker 1: particular press conference I paid close attention to with Cuomo

603
00:37:45,440 --> 00:37:48,440
Speaker 1: when he started saying, yeah, everything we've been telling you

604
00:37:48,440 --> 00:37:51,800
Speaker 1: about young people is wrong. Remember we hit that little

605
00:37:52,440 --> 00:37:56,320
Speaker 1: was there was like a moment where we thought maybe

606
00:37:56,360 --> 00:37:59,400
Speaker 1: young people were more vulnerable than we had believed earlier.

607
00:37:59,800 --> 00:38:01,880
Speaker 1: And I actually had asked him about that because we

608
00:38:01,880 --> 00:38:04,800
Speaker 1: all thought this was, you know, mostly the great threat

609
00:38:04,880 --> 00:38:09,720
Speaker 1: was for older people, underlying health issues and compromised immune systems.

610
00:38:09,760 --> 00:38:12,160
Speaker 1: In the end, it turned out mostly to be that

611
00:38:12,320 --> 00:38:14,359
Speaker 1: I think is a fair statement. But there was a

612
00:38:14,400 --> 00:38:18,200
Speaker 1: period we thought maybe younger people were more susceptible. Then

613
00:38:18,239 --> 00:38:20,120
Speaker 1: I think they ended up being Is that a fair statement,

614
00:38:20,280 --> 00:38:23,480
Speaker 1: right statement, accurate statement, It's a correct statement. I mean

615
00:38:23,480 --> 00:38:25,960
Speaker 1: two percent of the cases are young people. Thankfully most

616
00:38:25,960 --> 00:38:28,920
Speaker 1: of them don't even have life threatening consequences. But I

617
00:38:29,120 --> 00:38:31,080
Speaker 1: had a kid on the show today who did a

618
00:38:31,080 --> 00:38:32,680
Speaker 1: four year old have no idea why? The mother was

619
00:38:32,719 --> 00:38:35,880
Speaker 1: a pediatrician. She went, she went in to stay with

620
00:38:35,880 --> 00:38:37,680
Speaker 1: her son, and of course you know mom's not either

621
00:38:37,840 --> 00:38:40,000
Speaker 1: no child alone the hospital and once you're in the

622
00:38:40,080 --> 00:38:42,280
Speaker 1: room with the child, now you're assumed to be COVID nineteen.

623
00:38:42,320 --> 00:38:44,719
Speaker 1: Now she never got sick, you know, staying in the

624
00:38:44,800 --> 00:38:48,120
Speaker 1: room with the child, never got sick. He was really sick,

625
00:38:48,200 --> 00:38:51,359
Speaker 1: thankfully recovered. His two sisters did not get ill. So

626
00:38:51,640 --> 00:38:55,759
Speaker 1: the viruses there's there's definitely a genetic element. That's why

627
00:38:55,760 --> 00:38:59,160
Speaker 1: we think more men than women have problems with the virus.

628
00:38:58,960 --> 00:39:01,520
Speaker 1: It's not just lifestyle, but lifestyle is part of it

629
00:39:01,560 --> 00:39:04,359
Speaker 1: as well, especially a middle aged it seems to play

630
00:39:04,400 --> 00:39:08,000
Speaker 1: in the disproportionate ruled. The folks from NYU published data

631
00:39:08,080 --> 00:39:10,480
Speaker 1: saying that to be younger people under the age of

632
00:39:10,520 --> 00:39:14,320
Speaker 1: sixty who got sick. Adults had a disroportionally higher percentage

633
00:39:14,320 --> 00:39:17,080
Speaker 1: of being overweight or obese, and so you know, we're

634
00:39:17,080 --> 00:39:19,960
Speaker 1: starting to see some trends. The folks from Northwall published

635
00:39:19,960 --> 00:39:22,480
Speaker 1: their data. Eighty eight percent of the hospitalized patients in

636
00:39:22,480 --> 00:39:25,960
Speaker 1: their hospital had at least two cor mobility issues, so

637
00:39:26,080 --> 00:39:29,200
Speaker 1: they they had overweight and diabetes and hype pretension of

638
00:39:29,280 --> 00:39:32,040
Speaker 1: some combination. So we're starting to see how the virus

639
00:39:32,080 --> 00:39:34,080
Speaker 1: picked on us. It was able to get into our

640
00:39:34,080 --> 00:39:37,839
Speaker 1: bodies more readily. In some cases, it was able to reproduce,

641
00:39:37,960 --> 00:39:41,319
Speaker 1: probably because our bodies were being overwhelmed with inflammation, and

642
00:39:41,360 --> 00:39:44,319
Speaker 1: so you're starting to understand how how devastating it was.

643
00:39:44,400 --> 00:39:46,680
Speaker 1: The good news, if there is any good news, some

644
00:39:46,719 --> 00:39:49,640
Speaker 1: of this antibody data that we're seeing now that's highlighting

645
00:39:49,719 --> 00:39:52,480
Speaker 1: here in New York, for example, ten times more identified

646
00:39:52,880 --> 00:39:55,800
Speaker 1: people who who have had the virus than actually tested

647
00:39:55,800 --> 00:39:58,239
Speaker 1: positive at the time, and in the West Coast it

648
00:39:58,400 --> 00:40:01,200
Speaker 1: was fifty to eighty times more people. These are all

649
00:40:01,239 --> 00:40:03,680
Speaker 1: bad the way projections. May you think these numbers are hold?

650
00:40:03,880 --> 00:40:07,200
Speaker 1: Are you think there maybe there'll be somewhere around there

651
00:40:07,200 --> 00:40:08,920
Speaker 1: because it was that period of time. I think it

652
00:40:08,960 --> 00:40:11,520
Speaker 1: was what they thought there would be a mortality rate

653
00:40:11,520 --> 00:40:14,560
Speaker 1: of what three point four percent? Yeah, yeah, that was

654
00:40:14,600 --> 00:40:17,279
Speaker 1: the number thrown around right now. The governor New York

655
00:40:17,320 --> 00:40:19,759
Speaker 1: quoted the mortality rate if these numbers hold, would be

656
00:40:19,800 --> 00:40:22,279
Speaker 1: closer to half a percent, which are still a lot.

657
00:40:22,320 --> 00:40:24,040
Speaker 1: I mean, that's five times more than the flu, but

658
00:40:24,080 --> 00:40:26,239
Speaker 1: it's you know, it's not three point four percent. And

659
00:40:26,360 --> 00:40:27,919
Speaker 1: just as if you asked me to answer your question

660
00:40:27,960 --> 00:40:30,360
Speaker 1: more directly, I think the New York numbers are going

661
00:40:30,400 --> 00:40:33,279
Speaker 1: to hold because Howard Zucker, who's is a great health

662
00:40:33,280 --> 00:40:36,160
Speaker 1: commissioner of the state, worked with the federal government to

663
00:40:36,200 --> 00:40:39,239
Speaker 1: make sure that we had really meticulous antibody testing the

664
00:40:39,280 --> 00:40:41,839
Speaker 1: West Coast tests. We don't know if there is good

665
00:40:41,920 --> 00:40:44,439
Speaker 1: and a little difference in the quality those tests, because

666
00:40:44,440 --> 00:40:47,600
Speaker 1: you're strapped leading from three thousand people to millions, you could,

667
00:40:47,640 --> 00:40:49,239
Speaker 1: you know, a small difference makes a big error, so

668
00:40:49,400 --> 00:40:51,279
Speaker 1: it may not be as much. But I think I

669
00:40:51,320 --> 00:40:53,960
Speaker 1: think if it was ten times more than we knew,

670
00:40:54,200 --> 00:40:56,759
Speaker 1: that sort of makes sense because everyone listening right now

671
00:40:56,800 --> 00:41:00,120
Speaker 1: probably thinks they may have had the coronavirus, right who

672
00:41:00,160 --> 00:41:03,759
Speaker 1: had a little kafra? You know, it'll eight little testinal thing.

673
00:41:04,200 --> 00:41:06,440
Speaker 1: They weren't sure they were smelling normally mean, but we

674
00:41:06,480 --> 00:41:08,440
Speaker 1: had they had one of the symptoms because they're common,

675
00:41:08,719 --> 00:41:10,600
Speaker 1: and so you didn't get tested because you didn't want

676
00:41:10,600 --> 00:41:12,000
Speaker 1: to take a risk of going to the ear to

677
00:41:12,000 --> 00:41:14,440
Speaker 1: get tested, or they weren't any available. So they're probably

678
00:41:14,480 --> 00:41:16,080
Speaker 1: in that fair number of people who may have had

679
00:41:16,239 --> 00:41:20,239
Speaker 1: minor symptoms or none who did who did convert having

680
00:41:20,239 --> 00:41:22,239
Speaker 1: out of bodies. But the fact if they even at

681
00:41:22,239 --> 00:41:24,600
Speaker 1: ten to one, it's eye opening because it shows you

682
00:41:24,640 --> 00:41:27,160
Speaker 1: that there's a big difference in how humans respond to

683
00:41:27,239 --> 00:41:31,000
Speaker 1: this virus. Yeah, amazing. You know, we learn a lot

684
00:41:31,080 --> 00:41:33,839
Speaker 1: and I know more about viruses now than I've ever

685
00:41:33,960 --> 00:41:37,640
Speaker 1: wanted to know, ever thought i'd know. Um, but I

686
00:41:37,680 --> 00:41:40,560
Speaker 1: will tell you it's um, it's scary. And you know,

687
00:41:40,880 --> 00:41:42,719
Speaker 1: we lose people from the flu every year. And I

688
00:41:42,719 --> 00:41:45,839
Speaker 1: know you get killed for saying that, but we lose

689
00:41:45,880 --> 00:41:48,360
Speaker 1: tens of thousands of people in this country. Hundreds of

690
00:41:48,360 --> 00:41:51,719
Speaker 1: thousands get hospitalized every year. Um, all those things. I

691
00:41:51,719 --> 00:41:53,440
Speaker 1: wish we had cures for cancer. I wish we had

692
00:41:53,440 --> 00:41:55,680
Speaker 1: cures for everything. I've said that many times before. All Right,

693
00:41:56,040 --> 00:41:58,719
Speaker 1: we've taken your calls for the hour, Doctor Oz is

694
00:41:58,760 --> 00:42:01,840
Speaker 1: with us. You know this. I'm looking at this question

695
00:42:02,080 --> 00:42:06,879
Speaker 1: Chrissy in California asymptomatic carriers. Chrissy, it's funny you say

696
00:42:06,920 --> 00:42:10,680
Speaker 1: that because I brought this up with doctor Fauci in

697
00:42:10,719 --> 00:42:14,920
Speaker 1: my early interviews the end of January and February tenth,

698
00:42:14,960 --> 00:42:17,320
Speaker 1: because that was the one thing that stood out in

699
00:42:17,400 --> 00:42:20,400
Speaker 1: my mind. And it's a fascinating question. You're on with

700
00:42:20,480 --> 00:42:23,160
Speaker 1: doctor Ozz. I want you to ask it, Hisan Hi,

701
00:42:23,280 --> 00:42:26,799
Speaker 1: Doctor Ross. Yes, My question is is their data to

702
00:42:26,920 --> 00:42:32,600
Speaker 1: tell us how long asymptomatic carrier is actually contagious to others?

703
00:42:32,760 --> 00:42:36,520
Speaker 1: And if a contagious period is up to fourteen days,

704
00:42:36,800 --> 00:42:45,040
Speaker 1: why are we still on lockdown? So the period that

705
00:42:45,080 --> 00:42:47,440
Speaker 1: we think you're contagious is up to fourteen days. But

706
00:42:47,560 --> 00:42:50,080
Speaker 1: let me explain a couple couple of things. First off,

707
00:42:50,120 --> 00:42:53,480
Speaker 1: they have definitely been cases where people have been contagious

708
00:42:53,480 --> 00:42:56,600
Speaker 1: for longer. But you have to pick a number that's rational,

709
00:42:56,719 --> 00:42:58,359
Speaker 1: and you can't get nine. You know, I'm not gonna

710
00:42:58,360 --> 00:43:00,400
Speaker 1: get everybody because there's always going to be a few options.

711
00:43:00,480 --> 00:43:03,120
Speaker 1: So the data is based on CDC and other information,

712
00:43:03,960 --> 00:43:08,319
Speaker 1: arguing that the vast majority behind nineties percentile would be

713
00:43:08,360 --> 00:43:11,319
Speaker 1: through the course of their illness within fourteen days. Now,

714
00:43:11,640 --> 00:43:14,799
Speaker 1: most people are not going to have the ability to

715
00:43:14,840 --> 00:43:18,000
Speaker 1: infect others for the first two days, let's say, because

716
00:43:18,000 --> 00:43:20,040
Speaker 1: they're still making a virus in their body. Then from

717
00:43:20,160 --> 00:43:23,359
Speaker 1: days two or let's say three on, you're infectious, but

718
00:43:23,400 --> 00:43:26,560
Speaker 1: you might not have symptoms depending on how your body reacts,

719
00:43:26,640 --> 00:43:30,440
Speaker 1: until day five, which is sort of the average. It's

720
00:43:30,480 --> 00:43:32,000
Speaker 1: the average, of course, to means that you know, most

721
00:43:32,000 --> 00:43:33,600
Speaker 1: people have it then, but you know, a bunch you're

722
00:43:33,640 --> 00:43:35,399
Speaker 1: going to have it less and a bunch more so

723
00:43:35,880 --> 00:43:37,800
Speaker 1: by five days, you know, but by day five or

724
00:43:37,840 --> 00:43:39,640
Speaker 1: six you're going to have symptoms. And one of those

725
00:43:39,680 --> 00:43:42,480
Speaker 1: symptoms might be that could be very subtle, like losing

726
00:43:42,480 --> 00:43:44,960
Speaker 1: a sense of taste and smell, which the CDC just

727
00:43:45,000 --> 00:43:48,960
Speaker 1: added to the symptomless today is present according to the

728
00:43:49,000 --> 00:43:51,840
Speaker 1: European researchers two different studies, either two thirds at a

729
00:43:51,880 --> 00:43:54,120
Speaker 1: time or up to eighty five percent at a time.

730
00:43:54,400 --> 00:43:56,400
Speaker 1: That's a lot of people, and that's that's something we

731
00:43:56,520 --> 00:43:59,000
Speaker 1: even thought about as a symptom earlier on. So those

732
00:43:59,080 --> 00:44:00,759
Speaker 1: kinds of things might be the only clue that you

733
00:44:00,800 --> 00:44:02,439
Speaker 1: have it, and they're going to definitely be some people

734
00:44:02,440 --> 00:44:05,040
Speaker 1: who have absolutely no symptoms. People getting off the cruise

735
00:44:05,040 --> 00:44:08,080
Speaker 1: ships who where we tested every single person, a quarter

736
00:44:08,120 --> 00:44:10,680
Speaker 1: of them were, you know, healthy. One lady told me

737
00:44:10,719 --> 00:44:12,520
Speaker 1: I was interviewing her, says she was doing pilates when

738
00:44:12,520 --> 00:44:15,799
Speaker 1: they studied her, so she clearly wasn't symptomatic, and yet

739
00:44:15,840 --> 00:44:19,399
Speaker 1: she tries tested positive. So in those populations, we still

740
00:44:19,400 --> 00:44:21,040
Speaker 1: think they have a lot of virus. They have a

741
00:44:21,120 --> 00:44:25,319
Speaker 1: similar course of viral excretion, they just don't seem to

742
00:44:25,360 --> 00:44:28,080
Speaker 1: have the symptoms to go along with it, and by

743
00:44:28,120 --> 00:44:30,080
Speaker 1: two weeks out, we think they're done. Part of the

744
00:44:30,120 --> 00:44:32,520
Speaker 1: reason that we say that once you've had symptoms, it's

745
00:44:32,560 --> 00:44:35,879
Speaker 1: seven more days is the belief that those first seven

746
00:44:35,960 --> 00:44:38,359
Speaker 1: days of your fourteen have already you've already gone through them.

747
00:44:38,600 --> 00:44:40,680
Speaker 1: By the time you have symptoms, you're about this, you

748
00:44:40,719 --> 00:44:43,719
Speaker 1: know about that many days in. I was shocked when

749
00:44:43,719 --> 00:44:45,839
Speaker 1: I went back and looked at my old transcripts, how

750
00:44:45,920 --> 00:44:49,560
Speaker 1: fixated I was on asymptomatic you know, carriers of this,

751
00:44:50,120 --> 00:44:52,120
Speaker 1: because that's what scared me. You know what my problem is,

752
00:44:52,120 --> 00:44:53,720
Speaker 1: I have too many friends of mine that of doctors,

753
00:44:53,719 --> 00:44:56,280
Speaker 1: and I read Google too much. My own doctor, doctor

754
00:44:56,440 --> 00:44:58,840
Speaker 1: Jell loved this. You know, I'll call them and I'll

755
00:44:58,880 --> 00:45:01,200
Speaker 1: start telling them this, assist this and this, and he's like,

756
00:45:01,239 --> 00:45:03,080
Speaker 1: do you want do you want doctor Google? Or do

757
00:45:03,120 --> 00:45:05,439
Speaker 1: you want me? Which I think is a great line.

758
00:45:05,760 --> 00:45:07,640
Speaker 1: I'm sure you probably have thought that or said that

759
00:45:07,680 --> 00:45:10,280
Speaker 1: to a patient occasionally, because we think we know everything.

760
00:45:10,920 --> 00:45:13,880
Speaker 1: I've researched it on Google. Charlie, Texas your home with

761
00:45:13,960 --> 00:45:18,799
Speaker 1: doctor Les. Glad you cult sir, yes, um, pleasure to

762
00:45:18,840 --> 00:45:21,520
Speaker 1: speak to both of you. My question is about a

763
00:45:21,560 --> 00:45:25,640
Speaker 1: compound called triethling glycoll that I know in the about

764
00:45:25,640 --> 00:45:28,040
Speaker 1: the mid eighties and before, they were pumping through the

765
00:45:28,080 --> 00:45:32,560
Speaker 1: air system in hospitals to keep one patient from contracting

766
00:45:32,880 --> 00:45:36,480
Speaker 1: what another patient had. And I was just wondering if

767
00:45:36,520 --> 00:45:39,040
Speaker 1: they still do that, and if that's a viable option

768
00:45:39,160 --> 00:45:43,480
Speaker 1: for many businesses to pump through their air systems to

769
00:45:43,520 --> 00:45:48,200
Speaker 1: open things up again. So it's interesting you know about that.

770
00:45:48,239 --> 00:45:51,120
Speaker 1: It's it is an air sanitizer, and there's some commercial

771
00:45:51,120 --> 00:45:54,640
Speaker 1: products that use it. It's not something that I've thought

772
00:45:54,680 --> 00:45:58,640
Speaker 1: about much for large scale purification. There was a bit

773
00:45:58,640 --> 00:46:01,239
Speaker 1: of an alarming article from China that I'll share with

774
00:46:01,280 --> 00:46:03,680
Speaker 1: everybody because in the place of this question you're asking.

775
00:46:03,960 --> 00:46:08,480
Speaker 1: They look back at a restaurant that had about eighty

776
00:46:08,520 --> 00:46:11,359
Speaker 1: people sitting in it, and there was a woman who

777
00:46:11,360 --> 00:46:14,439
Speaker 1: went there who was just beginning to feel symptoms, and

778
00:46:14,520 --> 00:46:17,640
Speaker 1: she sat a table away from the air conditioner, and

779
00:46:17,680 --> 00:46:19,800
Speaker 1: they mapped out what happened, and the air conditions a

780
00:46:19,880 --> 00:46:23,440
Speaker 1: closed environment, no ventilation. The air conditioner blew the air

781
00:46:23,480 --> 00:46:27,759
Speaker 1: across this woman around the room and infected nine people. Now,

782
00:46:27,880 --> 00:46:30,200
Speaker 1: a couple of things are interesting, Right, seventy one people

783
00:46:30,320 --> 00:46:34,080
Speaker 1: roughly I get the match right, didn't have any symptoms afterwards,

784
00:46:34,080 --> 00:46:36,279
Speaker 1: didn't get sick that we know of. That nine people

785
00:46:36,320 --> 00:46:38,120
Speaker 1: did get sick, and they weren't directly next to her.

786
00:46:38,160 --> 00:46:40,560
Speaker 1: So obviously the air condition blewed around and some people

787
00:46:40,560 --> 00:46:43,799
Speaker 1: were more susceptible than others. So when we open restaurants

788
00:46:44,880 --> 00:46:46,960
Speaker 1: in this country, we're gonna want to do a couple

789
00:46:47,000 --> 00:46:49,239
Speaker 1: of things. First off, that's a cautionary note, right, there's

790
00:46:49,280 --> 00:46:51,239
Speaker 1: things we can do about that. One is ventilate the

791
00:46:51,320 --> 00:46:53,640
Speaker 1: room well, so anything that comes out of that woman's

792
00:46:53,880 --> 00:46:55,719
Speaker 1: nose could have been carried out so it doesn't keep

793
00:46:55,719 --> 00:46:59,120
Speaker 1: bouncing around the walls to get everyone multiple doses. Second

794
00:46:59,239 --> 00:47:01,759
Speaker 1: is intead of bringing an air conditioner like that, you

795
00:47:01,840 --> 00:47:06,520
Speaker 1: might take a purification systems. Yeah, I don't know. Look,

796
00:47:06,560 --> 00:47:09,399
Speaker 1: that's not gonna that's not the panacee. And I want

797
00:47:09,400 --> 00:47:11,440
Speaker 1: people to hear doctor Oz. Clearly he's not saying that.

798
00:47:11,600 --> 00:47:17,200
Speaker 1: He's he's saying something totally different about ventilation being looked

799
00:47:17,200 --> 00:47:20,000
Speaker 1: at for other reasons and health reasons. I you know,

800
00:47:20,080 --> 00:47:21,480
Speaker 1: I don't know anything about it, but I want to

801
00:47:21,480 --> 00:47:23,759
Speaker 1: be clear. Quick break right back. I twenty five to

802
00:47:23,920 --> 00:47:25,759
Speaker 1: the top of the hour, eight hundred and nine four

803
00:47:25,840 --> 00:47:30,240
Speaker 1: one sewn. You want to be a part of this extravaganza,

804
00:47:30,719 --> 00:47:34,920
Speaker 1: Doctor Oz with us for the full hour taking your calls.

805
00:47:36,000 --> 00:47:39,880
Speaker 1: Let us say hi to Elizabeth in Colorado. Elizabeth apparently

806
00:47:39,920 --> 00:47:43,399
Speaker 1: a flight attendant. UM, well, first of all, I know

807
00:47:43,600 --> 00:47:45,880
Speaker 1: it's probably tough on you right now. Thanks for calling,

808
00:47:45,920 --> 00:47:50,520
Speaker 1: and I hope we're protecting as airlines open up. Our

809
00:47:50,600 --> 00:47:53,359
Speaker 1: flight attendants are pilots everybody in between. They have these

810
00:47:53,400 --> 00:47:55,839
Speaker 1: anti virals, as I understand it, Elizabeth, that they can

811
00:47:55,840 --> 00:47:58,160
Speaker 1: spray in planes. I don't know how effective they are.

812
00:47:58,239 --> 00:48:01,640
Speaker 1: Just read about it. Yeah, I don't know how effective

813
00:48:01,680 --> 00:48:05,200
Speaker 1: they are. I do work. I'm not afraid I have

814
00:48:05,360 --> 00:48:07,880
Speaker 1: my face if I die tomorrow, I'm okay with that.

815
00:48:08,440 --> 00:48:10,440
Speaker 1: No no, no, no no, no, no no no. We don't

816
00:48:10,480 --> 00:48:11,959
Speaker 1: want you to die and just stick around a little

817
00:48:12,000 --> 00:48:14,920
Speaker 1: longer with we all. We all believe that there's a heaven.

818
00:48:15,120 --> 00:48:17,200
Speaker 1: I believe in God with all my heart, Jesus, the

819
00:48:17,239 --> 00:48:19,560
Speaker 1: whole thing. I believe at all. God's the creator of

820
00:48:19,560 --> 00:48:22,120
Speaker 1: the heaven and heavens and the earth, not now, and

821
00:48:22,160 --> 00:48:25,960
Speaker 1: he's running this road not now. But okay, my question

822
00:48:26,160 --> 00:48:28,759
Speaker 1: is here in Colorado, there are two lamps right now

823
00:48:29,040 --> 00:48:34,120
Speaker 1: that are offering the antibody test. Apparently they're not FDA approved,

824
00:48:34,520 --> 00:48:37,879
Speaker 1: But I still believe I've continued to fly through this

825
00:48:37,920 --> 00:48:42,400
Speaker 1: whole virus. I'm pretty sure I already had it. Should I?

826
00:48:42,600 --> 00:48:44,680
Speaker 1: So my question for ductor lives is do I go

827
00:48:44,840 --> 00:48:48,680
Speaker 1: take the antibody test or do I rate another three

828
00:48:48,719 --> 00:48:51,000
Speaker 1: weeks or however long it's going to take for the

829
00:48:51,040 --> 00:48:57,719
Speaker 1: FDA to approve specific tests. Well, the FDA has gotten overwhelmed,

830
00:48:57,760 --> 00:49:01,480
Speaker 1: and so in order to allow access to testing, they've

831
00:49:01,719 --> 00:49:04,799
Speaker 1: done something called the Emergency Used Authorization. Doesn't mean the

832
00:49:04,800 --> 00:49:07,520
Speaker 1: tests aren't good. It means that the companies are responsible

833
00:49:07,840 --> 00:49:11,040
Speaker 1: for telling the government how good they're performing and so

834
00:49:11,120 --> 00:49:13,000
Speaker 1: that way Americans can get tested. I don't think there's

835
00:49:13,000 --> 00:49:15,560
Speaker 1: any urgency here getting tested. It's not going to change

836
00:49:15,560 --> 00:49:17,480
Speaker 1: your day to day life, other than you'll feel more

837
00:49:17,480 --> 00:49:20,200
Speaker 1: comfortable that you got through it already, and as a

838
00:49:20,200 --> 00:49:22,840
Speaker 1: fight attendant that that might make your you're feel a

839
00:49:22,840 --> 00:49:25,520
Speaker 1: little more comfortable as you get on the plane. So personally,

840
00:49:25,560 --> 00:49:28,280
Speaker 1: I think i'd wait. I personally haven't gotten the antibody

841
00:49:28,320 --> 00:49:30,200
Speaker 1: test yet. I may have been exposed. I didn't. I

842
00:49:30,200 --> 00:49:32,360
Speaker 1: didn't have any symptoms, but there are many of us

843
00:49:32,400 --> 00:49:34,920
Speaker 1: who probably didn't have any symptoms. So if I were you,

844
00:49:34,920 --> 00:49:37,200
Speaker 1: I'd wait. Let the people who need the test urgently,

845
00:49:37,600 --> 00:49:41,000
Speaker 1: especially first responders and emergency rooms hospitals. I let getting

846
00:49:41,000 --> 00:49:42,760
Speaker 1: to get the tests. They're doing that at my hospital

847
00:49:42,840 --> 00:49:45,319
Speaker 1: now so that folks who are on the front line

848
00:49:45,360 --> 00:49:46,880
Speaker 1: have a little more comfort. But we're not even one

849
00:49:46,960 --> 00:49:49,640
Speaker 1: hundred percent sure that you're not going to be able

850
00:49:49,680 --> 00:49:52,560
Speaker 1: to get an infection again, even if you have antibodies right,

851
00:49:52,600 --> 00:49:57,360
Speaker 1: that's still being worked out. Good call, Elizabeth, Thank you

852
00:49:57,400 --> 00:49:58,719
Speaker 1: so much for being on. One thing I'll say to

853
00:49:58,800 --> 00:50:02,080
Speaker 1: Elizabeth too, is I think testing is with lab core

854
00:50:02,320 --> 00:50:07,239
Speaker 1: and quest. I think and Linda might be able to

855
00:50:07,280 --> 00:50:10,279
Speaker 1: clarify this for me that we think as early as

856
00:50:10,520 --> 00:50:15,440
Speaker 1: next week, with a doctor's prescription maybe or approval or

857
00:50:15,560 --> 00:50:19,080
Speaker 1: letter or ask um, you can go and you can.

858
00:50:19,120 --> 00:50:21,239
Speaker 1: I think beginning next week you might be able to

859
00:50:21,239 --> 00:50:23,680
Speaker 1: get your doctor to give you that. Yeah, supposedly by

860
00:50:23,719 --> 00:50:25,720
Speaker 1: next week. Some of the sources that I've been talking

861
00:50:25,760 --> 00:50:28,560
Speaker 1: to at HHS and other doctors in the field on

862
00:50:28,600 --> 00:50:31,080
Speaker 1: the front lines with COVID have been saying that as

863
00:50:31,080 --> 00:50:33,279
Speaker 1: of next week there will be an anybody test that

864
00:50:33,360 --> 00:50:35,720
Speaker 1: you can buy for between eighty to one hundred bucks,

865
00:50:36,120 --> 00:50:38,200
Speaker 1: and then you can take it to your local lab

866
00:50:38,239 --> 00:50:41,160
Speaker 1: core and have them draw blood and test it. And

867
00:50:41,400 --> 00:50:43,200
Speaker 1: we don't want to rush on it, maybe for people

868
00:50:44,640 --> 00:50:46,359
Speaker 1: that that needed. By the way, I did not mean

869
00:50:46,400 --> 00:50:48,320
Speaker 1: to interrupt you. By the way, at the end of

870
00:50:48,360 --> 00:50:50,319
Speaker 1: the last hour, I just didn't want. I had cut

871
00:50:50,320 --> 00:50:52,520
Speaker 1: you short because we had a hard break as you

872
00:50:52,560 --> 00:50:55,520
Speaker 1: were talking about ventilation systems, and I just wanted to

873
00:50:55,520 --> 00:50:57,520
Speaker 1: be clear that you you know, you were speaking more

874
00:50:57,560 --> 00:51:01,319
Speaker 1: in the abstract in terms of air elation systems being

875
00:51:01,440 --> 00:51:05,200
Speaker 1: generally good, and I did not want because in this environment,

876
00:51:05,200 --> 00:51:08,799
Speaker 1: everyone's taking everything anybody says out of context. Anybody to

877
00:51:08,840 --> 00:51:11,200
Speaker 1: interpret it other than how you were expressing it. But

878
00:51:11,239 --> 00:51:13,200
Speaker 1: I'm the one that cut you short, and that's why

879
00:51:13,520 --> 00:51:16,239
Speaker 1: I wanted to clarify that, Doctor oz Well. I appreciate

880
00:51:16,239 --> 00:51:18,960
Speaker 1: it very much, and I also suspected there must be

881
00:51:19,280 --> 00:51:21,439
Speaker 1: a hard out, which means I was quing a commercial vote.

882
00:51:22,840 --> 00:51:25,000
Speaker 1: At least you know what a hard out is. Oh,

883
00:51:25,080 --> 00:51:28,120
Speaker 1: some people have no idea. It's funny. Tucker throws to

884
00:51:28,200 --> 00:51:31,520
Speaker 1: me at night and some nights is fifteen seconds early.

885
00:51:31,600 --> 00:51:34,720
Speaker 1: Some nights it is fifteen seconds seconds late. I'm like, Tucker,

886
00:51:34,800 --> 00:51:37,200
Speaker 1: I work in radio. You gotta hit the post And

887
00:51:37,239 --> 00:51:39,759
Speaker 1: he's like, what does that mean? And it's actually a

888
00:51:39,840 --> 00:51:43,720
Speaker 1: joke between us. All right, back to our phones. Let's

889
00:51:43,840 --> 00:51:47,160
Speaker 1: say hi to Paul and New Hampshire. Paul, you're on

890
00:51:47,280 --> 00:51:51,200
Speaker 1: with doctor Osword. Glad you called, sir Hollo. Gentlemen aren't

891
00:51:51,239 --> 00:51:54,280
Speaker 1: speak to you, doctor oz question. I go into the

892
00:51:54,320 --> 00:51:56,920
Speaker 1: grocery store some we time. Besides the work, I'm a

893
00:51:56,920 --> 00:52:00,239
Speaker 1: trucker for mail, so I have to wear it every

894
00:52:00,239 --> 00:52:04,080
Speaker 1: post office I go into, and when I go into

895
00:52:04,239 --> 00:52:08,480
Speaker 1: the supermarkets, I also wear goggles so I don't see

896
00:52:08,480 --> 00:52:11,680
Speaker 1: anyone else wearing them, so I look stupid. And I

897
00:52:11,760 --> 00:52:13,600
Speaker 1: feel stupid, but I'm wearing them because I don't want

898
00:52:13,600 --> 00:52:15,520
Speaker 1: to infect my family. They've been home for three weeks

899
00:52:15,600 --> 00:52:17,919
Speaker 1: or actually two and a half months now, so they're safe.

900
00:52:17,960 --> 00:52:19,120
Speaker 1: I don't want to be the one to give it

901
00:52:19,160 --> 00:52:22,320
Speaker 1: to them. Is wearing goggles a necessity, a good idea

902
00:52:22,480 --> 00:52:25,919
Speaker 1: or is it overkill? I think it's a good idea,

903
00:52:26,200 --> 00:52:28,560
Speaker 1: But I got to say something because you bring it up.

904
00:52:29,280 --> 00:52:31,400
Speaker 1: We were laughing at people wearing masks in this country

905
00:52:31,400 --> 00:52:33,840
Speaker 1: six weeks ago, right, so we thought, you know, come on,

906
00:52:33,880 --> 00:52:35,440
Speaker 1: that's what are you doing. I mean, you're a little paranoid.

907
00:52:35,440 --> 00:52:37,799
Speaker 1: In fact, we were telling people not to bother. The

908
00:52:37,880 --> 00:52:41,480
Speaker 1: world changes because we change our appreciation of exactly what

909
00:52:41,800 --> 00:52:44,880
Speaker 1: the virus does, how it's transmitted. It's clearly, from our belief,

910
00:52:45,440 --> 00:52:48,799
Speaker 1: usually not always, usually transmitted in a virus particle from

911
00:52:48,840 --> 00:52:50,840
Speaker 1: person to person, which means anything you can do to

912
00:52:50,840 --> 00:52:55,000
Speaker 1: slow that process down and works. Doctors where I protection

913
00:52:55,160 --> 00:52:57,239
Speaker 1: in the emergency room taking care patients, Why are we

914
00:52:57,320 --> 00:52:59,600
Speaker 1: doing that because it might help? Is that the most

915
00:52:59,640 --> 00:53:02,000
Speaker 1: important thing we do? The mask is more important, But

916
00:53:02,200 --> 00:53:04,200
Speaker 1: the goggles are in our best and just we had

917
00:53:04,239 --> 00:53:06,200
Speaker 1: face shields there as all kinds of technologies that we

918
00:53:06,320 --> 00:53:08,920
Speaker 1: use in the operating room, we'd likewise always wear eye protection,

919
00:53:09,040 --> 00:53:11,480
Speaker 1: so yours. Why to do that? I think a lot

920
00:53:11,480 --> 00:53:14,040
Speaker 1: of Americans would be well served as their high risk

921
00:53:14,120 --> 00:53:16,360
Speaker 1: to do it, even though it's not the most important

922
00:53:16,400 --> 00:53:18,040
Speaker 1: thing that you will be wearing. What you know, it's

923
00:53:18,080 --> 00:53:21,080
Speaker 1: a belt and suspender solution. Go do it. Thanks for

924
00:53:21,120 --> 00:53:24,000
Speaker 1: the call. We appreciate it. Dan in Kentucky. You're next

925
00:53:24,040 --> 00:53:26,680
Speaker 1: on the Sean Hannity Show with Doctor Oz. Glad you called, sir,

926
00:53:26,800 --> 00:53:30,279
Speaker 1: Happy Friday. Happy to you both of you two. Thank

927
00:53:30,320 --> 00:53:33,279
Speaker 1: you so much for taking the call. Is there any

928
00:53:34,000 --> 00:53:36,279
Speaker 1: any data being collective for those who get the flu

929
00:53:36,360 --> 00:53:39,040
Speaker 1: vaccine every year where they are more or less likely

930
00:53:39,080 --> 00:53:42,000
Speaker 1: to get the COVID nineteen and or those who get

931
00:53:42,000 --> 00:53:45,040
Speaker 1: the COVID nineteen if they got the flu shot, are

932
00:53:45,080 --> 00:53:50,279
Speaker 1: there symptoms or illness any less aggrevated that makes work

933
00:53:50,400 --> 00:53:52,400
Speaker 1: or less not as serious as those who did not

934
00:53:52,440 --> 00:53:55,520
Speaker 1: get VECCI. Yeah, it's a question that when we get

935
00:53:55,520 --> 00:53:57,640
Speaker 1: asked many many times. You're the first who have asked

936
00:53:57,640 --> 00:53:59,440
Speaker 1: it directly that I'm aware of it on the show,

937
00:53:59,719 --> 00:54:02,040
Speaker 1: and I gotta say that they are. They should be

938
00:54:02,160 --> 00:54:06,120
Speaker 1: completely separate issues that make the data may change, but

939
00:54:06,200 --> 00:54:08,920
Speaker 1: for right now, there are such separate viruses that for

940
00:54:09,040 --> 00:54:13,160
Speaker 1: sure the immunization that's aimed at the flu should not

941
00:54:13,200 --> 00:54:15,319
Speaker 1: protect you against COVID nineteen that there may be other

942
00:54:15,320 --> 00:54:17,680
Speaker 1: things that happen independent of that that may help you.

943
00:54:17,719 --> 00:54:20,439
Speaker 1: But the single biggest benefit is if you get sick

944
00:54:20,520 --> 00:54:23,319
Speaker 1: next December, you're not going to know why, and it'd

945
00:54:23,360 --> 00:54:25,160
Speaker 1: be sort of nice to know that if you least

946
00:54:25,160 --> 00:54:27,279
Speaker 1: got the flu shot, so there's less of a chance

947
00:54:27,320 --> 00:54:29,440
Speaker 1: that you have the flu, even though it's still possible

948
00:54:30,080 --> 00:54:32,359
Speaker 1: since we won't have a COVID vaccination. And I gotta

949
00:54:32,400 --> 00:54:34,080
Speaker 1: say this, if you haven't gotten a flu shot before.

950
00:54:34,080 --> 00:54:36,200
Speaker 1: I get it every year as a physician. We're obliged

951
00:54:36,200 --> 00:54:38,319
Speaker 1: to because we don't want to spread viruses to our

952
00:54:38,360 --> 00:54:40,520
Speaker 1: patients who or who are many of them critically ill.

953
00:54:40,880 --> 00:54:45,160
Speaker 1: So it isn't it about forty percent effective annually? I

954
00:54:45,200 --> 00:54:47,319
Speaker 1: get it every year as well, But that's mine. Some

955
00:54:47,320 --> 00:54:49,759
Speaker 1: people are so anti vaccine, and I don't criticize them,

956
00:54:50,360 --> 00:54:53,359
Speaker 1: you know, I love I believe in people are having

957
00:54:53,400 --> 00:54:55,960
Speaker 1: their own thoughts on things. But I get it. How

958
00:54:56,000 --> 00:54:58,879
Speaker 1: effective is it usually? Like thirty forty percent? I usually read. Yeah,

959
00:54:59,000 --> 00:55:01,279
Speaker 1: I think forty percent out the right number. It's you

960
00:55:01,360 --> 00:55:03,840
Speaker 1: roughly half is likely to have a problem, and the

961
00:55:03,920 --> 00:55:05,480
Speaker 1: half is likely to align your back for a week

962
00:55:05,560 --> 00:55:09,560
Speaker 1: or have more serious complications. And I just especially next year, well,

963
00:55:09,560 --> 00:55:11,239
Speaker 1: we're just not going to be able to tell people

964
00:55:11,239 --> 00:55:13,759
Speaker 1: apart that often. Just get the vaccine, guys. It's if

965
00:55:13,760 --> 00:55:16,000
Speaker 1: you haven't done it before. I don't think that there's

966
00:55:16,040 --> 00:55:18,160
Speaker 1: significant risk associate with it. I know there's always a

967
00:55:18,160 --> 00:55:21,040
Speaker 1: complication to give one hundred million people anything. You'll have issues,

968
00:55:21,239 --> 00:55:23,000
Speaker 1: but you know what I like about it though, it's

969
00:55:23,040 --> 00:55:25,200
Speaker 1: worth it. Yeah. I just go to my local write

970
00:55:25,200 --> 00:55:28,239
Speaker 1: age and the same person as a wonderful a woman

971
00:55:28,280 --> 00:55:30,120
Speaker 1: to write any where I live. I mean, she gives

972
00:55:30,120 --> 00:55:31,759
Speaker 1: it to me every year and we catch up. How

973
00:55:31,800 --> 00:55:35,200
Speaker 1: are your kids? How's this? I mean? And it's it's

974
00:55:35,239 --> 00:55:38,200
Speaker 1: literally in and out, one, two, three. Um. Anyway, good call.

975
00:55:38,280 --> 00:55:41,440
Speaker 1: That was a good question, Dan, Thank you, Tony. Well,

976
00:55:41,480 --> 00:55:46,160
Speaker 1: let's go to Maria first in Jacksonville WOKV. Maria, you're

977
00:55:46,200 --> 00:55:50,160
Speaker 1: on with doctor Oz. Glad you called him. My question

978
00:55:50,280 --> 00:55:53,440
Speaker 1: is are we going to compromise or weaken our children's

979
00:55:53,840 --> 00:56:00,520
Speaker 1: immune systems by creating a society of thermophobes. Well, you know,

980
00:56:00,920 --> 00:56:03,640
Speaker 1: kids benefit from being exposed to Germans, I know is

981
00:56:03,680 --> 00:56:06,240
Speaker 1: the intent of your question. And he had kids around

982
00:56:06,239 --> 00:56:09,000
Speaker 1: pets for example, seem to help. And we've always allowed

983
00:56:09,000 --> 00:56:11,560
Speaker 1: our kids to rumble around, but you know, I don't

984
00:56:11,560 --> 00:56:13,840
Speaker 1: want them exposed to a virus that this species hasn't

985
00:56:13,840 --> 00:56:17,759
Speaker 1: seen before, and potentially because of that, hurt people who

986
00:56:17,760 --> 00:56:20,080
Speaker 1: are very dear to them, like my in laws. So

987
00:56:20,120 --> 00:56:21,840
Speaker 1: I think this is a little bit of an exception.

988
00:56:22,320 --> 00:56:24,560
Speaker 1: I'm not doing things with our kids at home that

989
00:56:24,600 --> 00:56:26,359
Speaker 1: are out of the ordinary. You know, we have got

990
00:56:26,360 --> 00:56:28,000
Speaker 1: the grandkids here with us as well. They go out

991
00:56:28,040 --> 00:56:30,120
Speaker 1: and play in the dirt, and my grandson makes a

992
00:56:30,160 --> 00:56:32,759
Speaker 1: mess of everything like he's supposed to. So I just

993
00:56:32,840 --> 00:56:34,719
Speaker 1: it's a little different. However, taking him to the store

994
00:56:34,760 --> 00:56:37,480
Speaker 1: and exposing him because he probably wouldn't have symptoms, but

995
00:56:37,640 --> 00:56:39,839
Speaker 1: makes it that much more concerning because I won't know

996
00:56:39,920 --> 00:56:42,879
Speaker 1: if he's about the past of somebody else. I hope

997
00:56:42,880 --> 00:56:46,600
Speaker 1: that answers your question. Raise Thank you, Tony Iowa. Next

998
00:56:46,680 --> 00:56:50,279
Speaker 1: on with doctor Oz Glad you called hi, Thanks for

999
00:56:50,320 --> 00:56:54,000
Speaker 1: taking my call. My question is I'm wondering if a

1000
00:56:54,120 --> 00:56:57,600
Speaker 1: valid antibodies specific to COVID nineteen. If they could be

1001
00:56:58,040 --> 00:57:01,080
Speaker 1: harvested and maybe are assoled a lot of people vapor

1002
00:57:01,520 --> 00:57:03,200
Speaker 1: if it could be put into some kind of product

1003
00:57:03,280 --> 00:57:05,640
Speaker 1: like that to where people could breathe the men is

1004
00:57:05,680 --> 00:57:09,759
Speaker 1: that even possible. Well, the antibodies that were harvesting now,

1005
00:57:10,160 --> 00:57:12,160
Speaker 1: so you just set them in the chair, you pull

1006
00:57:12,200 --> 00:57:13,920
Speaker 1: them blood out, you take out the yellow stuff which

1007
00:57:13,960 --> 00:57:16,320
Speaker 1: is the serum, and then you purify the antibodies. It's

1008
00:57:16,400 --> 00:57:18,880
Speaker 1: best if you put that back into someone's blood. That

1009
00:57:18,960 --> 00:57:21,280
Speaker 1: way we know exactly what the immune response is going

1010
00:57:21,320 --> 00:57:24,240
Speaker 1: to do. We haven't. I have not thought of putting

1011
00:57:24,280 --> 00:57:26,520
Speaker 1: it in the lungs. There are many medications that once

1012
00:57:26,560 --> 00:57:28,560
Speaker 1: they work in the blood, we've proven everything, you can

1013
00:57:28,560 --> 00:57:30,760
Speaker 1: then begin to think about them and other parts of

1014
00:57:30,760 --> 00:57:32,240
Speaker 1: the body. But I think for right now, we still

1015
00:57:32,280 --> 00:57:34,720
Speaker 1: have to prove that it works. I just interviewed Ian

1016
00:57:34,800 --> 00:57:37,439
Speaker 1: Lipkin today on my show, who's the famous virus hunter,

1017
00:57:37,480 --> 00:57:39,560
Speaker 1: and he's one of the big leaders in this movement.

1018
00:57:39,800 --> 00:57:42,080
Speaker 1: But you know, there's this technique of taking plasmas. You know,

1019
00:57:42,120 --> 00:57:45,160
Speaker 1: it's one hundred and plus years old. So I'm hop

1020
00:57:45,320 --> 00:57:48,160
Speaker 1: he's optimistic. But let's prove that first thing. Clinical trials

1021
00:57:48,160 --> 00:57:49,600
Speaker 1: that are going and then we'll take you to the

1022
00:57:49,600 --> 00:57:51,360
Speaker 1: next level, which is looking at heasier ways of putting

1023
00:57:51,400 --> 00:57:55,000
Speaker 1: it into people. All right, good call Tony, We appreciate it.

1024
00:57:55,560 --> 00:58:00,720
Speaker 1: Let's go to North Carolina. Jonathan's next Jonathan, Happy Friday

1025
00:58:00,760 --> 00:58:03,040
Speaker 1: to you. Glad you called. You're on with doctor Oz.

1026
00:58:04,160 --> 00:58:07,080
Speaker 1: Happy Friday to you too, Thanks for having me on. Hey,

1027
00:58:07,480 --> 00:58:10,320
Speaker 1: doctor Oz, I have kind of an observation and I

1028
00:58:10,400 --> 00:58:12,640
Speaker 1: was wondering if you think that this is going to

1029
00:58:12,680 --> 00:58:17,840
Speaker 1: apply to the COVID case. Also, historically speaking, anytime you

1030
00:58:17,880 --> 00:58:21,880
Speaker 1: introduce a new virus or anything along those lines to

1031
00:58:22,000 --> 00:58:28,080
Speaker 1: a population, it tends to have a massive effect initially,

1032
00:58:28,400 --> 00:58:31,640
Speaker 1: like the first time it goes around. But then once

1033
00:58:31,720 --> 00:58:35,080
Speaker 1: the general population has the people that are going to

1034
00:58:35,160 --> 00:58:37,560
Speaker 1: die off have died off, the people that have survived

1035
00:58:37,600 --> 00:58:42,280
Speaker 1: have survived, and they've built up the antibodies, it tends

1036
00:58:42,320 --> 00:58:45,120
Speaker 1: to not be as even if it's something like the

1037
00:58:45,160 --> 00:58:47,400
Speaker 1: flu where you can get it, you know, every year

1038
00:58:47,600 --> 00:58:49,760
Speaker 1: or so on. So for as, it never seems to

1039
00:58:49,800 --> 00:58:53,080
Speaker 1: be as bad as it goes on over time because

1040
00:58:53,120 --> 00:58:55,840
Speaker 1: people are building up an immune system to it. My

1041
00:58:55,960 --> 00:58:58,960
Speaker 1: point with this is everybody keeps talking about well, what

1042
00:58:59,000 --> 00:59:01,240
Speaker 1: if this comes back, if this comes back, and getting

1043
00:59:01,240 --> 00:59:04,680
Speaker 1: worried about it. Even if this does come back, do

1044
00:59:04,760 --> 00:59:08,600
Speaker 1: you think it's going to I'm feeling like this first

1045
00:59:08,680 --> 00:59:10,760
Speaker 1: round of it is the worst that we're going to

1046
00:59:10,880 --> 00:59:14,040
Speaker 1: see and it should actually, in fact not be as

1047
00:59:14,040 --> 00:59:20,440
Speaker 1: bad even if it comes back. Do you think that's correct. Well, unfortunately,

1048
00:59:20,480 --> 00:59:22,920
Speaker 1: you pay a big price to figure that out, and

1049
00:59:23,080 --> 00:59:25,480
Speaker 1: our country has decided, I think appropriately, not to pay

1050
00:59:25,520 --> 00:59:29,480
Speaker 1: that price. There are other countries, as Scandinavia Sweden in particular,

1051
00:59:29,960 --> 00:59:33,080
Speaker 1: who are taking that approach. I think the loss of

1052
00:59:33,120 --> 00:59:35,120
Speaker 1: life is so great with the virus of this nature,

1053
00:59:35,200 --> 00:59:37,520
Speaker 1: as contagious as it is, as devastating it as to

1054
00:59:37,520 --> 00:59:40,320
Speaker 1: the lungs of people, especially if they have co morbid issues,

1055
00:59:41,120 --> 00:59:44,400
Speaker 1: that it's not an experiment we can do. Herd immunity,

1056
00:59:44,480 --> 00:59:48,040
Speaker 1: which is what you're describing so aloqually, Johnson is only

1057
00:59:48,080 --> 00:59:50,480
Speaker 1: going to be seen at sixty five seventy percent of

1058
00:59:50,480 --> 00:59:53,480
Speaker 1: the population being infected, and we're talking right now about

1059
00:59:53,480 --> 00:59:56,120
Speaker 1: low single digits in most of America that's already been

1060
00:59:56,200 --> 00:59:58,160
Speaker 1: hit hard. If it in New York City, where a

1061
00:59:58,320 --> 01:00:00,280
Speaker 1: New York State, rather you know, many part to the

1062
01:00:01,000 --> 01:00:02,840
Speaker 1: county aren't going to have high numbers that you know,

1063
01:00:02,960 --> 01:00:05,160
Speaker 1: the city itself is at twenty percent, so we're still

1064
01:00:05,240 --> 01:00:07,400
Speaker 1: quite a bit away from the numbers that we require.

1065
01:00:07,440 --> 01:00:10,240
Speaker 1: The easiest way to get hurt immunity is to get

1066
01:00:10,520 --> 01:00:12,320
Speaker 1: a vaccine, because then you can get up to ninety

1067
01:00:12,360 --> 01:00:15,080
Speaker 1: five ninety seven percent where you truly can suffocate the virus.

1068
01:00:15,400 --> 01:00:17,280
Speaker 1: And that's what we're going to do eventually. But in

1069
01:00:17,360 --> 01:00:19,760
Speaker 1: the meantime, I think the smarter tactic for us is

1070
01:00:19,800 --> 01:00:22,280
Speaker 1: a reduced number of people are infected and waited out.

1071
01:00:22,440 --> 01:00:25,240
Speaker 1: We're going to recreate what you're describing in a safe

1072
01:00:25,280 --> 01:00:28,320
Speaker 1: way with a vaccine, that tent that gets our immune

1073
01:00:28,360 --> 01:00:31,880
Speaker 1: system to wake up but doesn't cause pathology while doing that.

1074
01:00:33,000 --> 01:00:36,280
Speaker 1: Thanks for the call, Jonathan Judy, Nevada Next with doctor

1075
01:00:36,360 --> 01:00:42,520
Speaker 1: Oz Glad you called. Hi. I'm wondering if you get

1076
01:00:42,600 --> 01:00:46,000
Speaker 1: your pneumonia shots on a regular basis. I'm seventy five

1077
01:00:46,080 --> 01:00:48,680
Speaker 1: and I've been getting them for quite some time. Will

1078
01:00:48,760 --> 01:00:51,440
Speaker 1: that help you if you come down with this virus

1079
01:00:51,560 --> 01:00:58,800
Speaker 1: and get pneumonia, Well, what would help is preventing you

1080
01:00:58,960 --> 01:01:03,120
Speaker 1: from having both having both a very bad bacterial infection

1081
01:01:03,160 --> 01:01:05,360
Speaker 1: of your lung and at the same time having COVID nineteen,

1082
01:01:05,400 --> 01:01:07,120
Speaker 1: which would do other things that are bad for your

1083
01:01:07,200 --> 01:01:09,520
Speaker 1: lung So this is a good year to make sure

1084
01:01:09,520 --> 01:01:11,320
Speaker 1: you're up to date in your vaccination so you can

1085
01:01:11,360 --> 01:01:15,440
Speaker 1: at least what you remove the pathology, the damaging of

1086
01:01:16,040 --> 01:01:18,960
Speaker 1: infections that could hurt your body, particularly your lungs. So

1087
01:01:19,080 --> 01:01:21,880
Speaker 1: if you already get COVID nineteen, you could weather the storm.

1088
01:01:22,520 --> 01:01:25,640
Speaker 1: I've never even heard of a pneumonia shot. Were barely

1089
01:01:25,720 --> 01:01:28,400
Speaker 1: heard of it. Um is that something that has a

1090
01:01:29,320 --> 01:01:32,400
Speaker 1: Is that something that you find effective? Oh? Yeah, that's

1091
01:01:32,480 --> 01:01:34,760
Speaker 1: very effective. It's it's a it's a vaccine against the

1092
01:01:34,800 --> 01:01:39,600
Speaker 1: bacteria that causes pneumonia. Is an annual or uh, well

1093
01:01:41,240 --> 01:01:42,880
Speaker 1: you don't use you need an annually, but it's a

1094
01:01:43,040 --> 01:01:46,760
Speaker 1: it's a it's a protection against a bacteria that's different

1095
01:01:46,840 --> 01:01:50,680
Speaker 1: from influenza, and it's it's given most people are operative

1096
01:01:50,680 --> 01:01:52,320
Speaker 1: as you as they get older. It doesn't that that

1097
01:01:52,440 --> 01:01:55,000
Speaker 1: bacteria doesn't tend to cause problems in younger people as much,

1098
01:01:55,040 --> 01:01:57,600
Speaker 1: but in some parts of population we offer it. But

1099
01:01:57,840 --> 01:01:59,400
Speaker 1: this is not just that. I mean, frankly, i'd get

1100
01:01:59,400 --> 01:02:01,880
Speaker 1: a shingles back right now, I get on the vaccine.

1101
01:02:01,920 --> 01:02:04,360
Speaker 1: I could just to remove those things, because if he

1102
01:02:04,400 --> 01:02:08,640
Speaker 1: gets splotches on your skin and aches and pains, people

1103
01:02:08,640 --> 01:02:10,920
Speaker 1: are gonna start thinking they've got COVID nineteen even though

1104
01:02:10,920 --> 01:02:13,200
Speaker 1: they just the beginning of her disaster. Which let me,

1105
01:02:13,320 --> 01:02:14,840
Speaker 1: let me ask you this question. And I only have

1106
01:02:14,960 --> 01:02:17,000
Speaker 1: thirty seconds, and you've been so generous with your time,

1107
01:02:17,040 --> 01:02:20,040
Speaker 1: doctor Os. Look, I don't want to open up a

1108
01:02:20,080 --> 01:02:24,160
Speaker 1: Pandora's box here. I have friends that are very anti vaccine,

1109
01:02:24,520 --> 01:02:28,400
Speaker 1: and I don't I'm not anti vaccine and I but

1110
01:02:28,480 --> 01:02:31,040
Speaker 1: I want to respect their points of view. And I

1111
01:02:31,160 --> 01:02:34,720
Speaker 1: do you get into some very you know, now you

1112
01:02:34,880 --> 01:02:39,320
Speaker 1: hit some ethical territories here. You know, well, for example,

1113
01:02:39,360 --> 01:02:42,400
Speaker 1: a polio vaccine, nor mumps or whatever we're talking about. Um,

1114
01:02:42,560 --> 01:02:46,800
Speaker 1: it gets complicated. If you believe personal freedom, etc. And

1115
01:02:47,160 --> 01:02:50,640
Speaker 1: the rights to protect others from outbreaks of things. You

1116
01:02:50,720 --> 01:02:52,720
Speaker 1: probably don't even want to walk into that fire, right.

1117
01:02:52,800 --> 01:02:54,600
Speaker 1: I don't blame you if you if you do, don't,

1118
01:02:56,800 --> 01:02:58,640
Speaker 1: well I do. I'll walk into it. I'm walking into

1119
01:02:58,720 --> 01:03:01,240
Speaker 1: many times. I mean, I have this conflict, you know,

1120
01:03:01,280 --> 01:03:03,560
Speaker 1: with members of my family who know people. He's what

1121
01:03:03,640 --> 01:03:07,440
Speaker 1: I found effective. I don't want to treat people like chattel.

1122
01:03:07,840 --> 01:03:10,080
Speaker 1: What really bothers people is when you tell them they're

1123
01:03:10,120 --> 01:03:12,120
Speaker 1: fools for not getting back to it. That is not

1124
01:03:12,240 --> 01:03:13,720
Speaker 1: the right way to go, and I don't think it's

1125
01:03:13,720 --> 01:03:16,200
Speaker 1: an honorable way of dealing with it. Since the first

1126
01:03:16,280 --> 01:03:19,440
Speaker 1: time vaccines have ever been offered, humans have felt that

1127
01:03:19,560 --> 01:03:21,600
Speaker 1: it wasn't in their best interests. They didn't want to

1128
01:03:21,600 --> 01:03:23,720
Speaker 1: take the risk, it wasn't worth it. I respect that

1129
01:03:24,120 --> 01:03:26,920
Speaker 1: personally in my family, I want people vaccinated. I think

1130
01:03:26,960 --> 01:03:28,800
Speaker 1: it's best for them. That's how strongly I feel about it.

1131
01:03:28,920 --> 01:03:31,280
Speaker 1: But it's your choice. You done about it, You'll do

1132
01:03:31,400 --> 01:03:35,760
Speaker 1: the research, doctor Oz. As always, we really appreciate you

1133
01:03:35,880 --> 01:03:38,360
Speaker 1: being with us. You know, so many good questions today,

1134
01:03:38,480 --> 01:03:40,680
Speaker 1: really good, amazing. All right. Eight hundred thank you sir,

1135
01:03:41,640 --> 01:03:43,240
Speaker 1: eight hundred nine four one sewn you want to be

1136
01:03:43,280 --> 01:03:45,320
Speaker 1: a part of the program. The latest on the media mob.

1137
01:03:45,440 --> 01:03:49,160
Speaker 1: Joel Pollock is the Bright Bart Senior editor at large,

1138
01:03:49,840 --> 01:03:52,560
Speaker 1: and well, he's going to talk about the mob in

1139
01:03:52,600 --> 01:03:54,320
Speaker 1: the media when we come back off and try and

1140
01:03:54,520 --> 01:03:56,800
Speaker 1: sort of stay away from our colleagues in the business.

1141
01:03:56,920 --> 01:04:00,040
Speaker 1: But Fox News has several puppets for this president and

1142
01:04:00,800 --> 01:04:06,320
Speaker 1: constantly going on the air, constantly repeating what he says verbatim,

1143
01:04:06,840 --> 01:04:11,080
Speaker 1: these people are working for Trump behind the scenes. We

1144
01:04:11,240 --> 01:04:13,200
Speaker 1: try and stay away from it. We try and hope

1145
01:04:13,240 --> 01:04:16,360
Speaker 1: that Fox News will do their best, that there are

1146
01:04:16,440 --> 01:04:19,240
Speaker 1: other hosts on the network that really step up and

1147
01:04:19,320 --> 01:04:22,280
Speaker 1: do the right thing, and we hope that prevails. We

1148
01:04:22,440 --> 01:04:25,440
Speaker 1: hope that goodness prevails, and we hope that ability to

1149
01:04:25,520 --> 01:04:29,240
Speaker 1: be objective prevails and try and put the facts first.

1150
01:04:29,280 --> 01:04:33,040
Speaker 1: But we repeatedly see it not happening on certain shows,

1151
01:04:33,080 --> 01:04:35,720
Speaker 1: and last night Sean Handy went after Joe at the

1152
01:04:35,800 --> 01:04:39,920
Speaker 1: top of his show. For quite a long time, perhaps

1153
01:04:40,200 --> 01:04:44,000
Speaker 1: it was too tough to take the president's ridiculous ideas

1154
01:04:44,320 --> 01:04:46,720
Speaker 1: and make them into a reality for his viewers and

1155
01:04:47,280 --> 01:04:50,400
Speaker 1: put viewers at risk. Perhaps it was even too much

1156
01:04:50,440 --> 01:04:52,840
Speaker 1: for Sean Hannity, so he had to find some sort

1157
01:04:52,880 --> 01:04:56,080
Speaker 1: of foil to go after. It's just it's got to

1158
01:04:56,120 --> 01:05:01,320
Speaker 1: stop at some point. Something both tragic and stic and

1159
01:05:01,480 --> 01:05:05,360
Speaker 1: ironic about the fact that it took a you know,

1160
01:05:05,520 --> 01:05:10,600
Speaker 1: color blind, gender blind, state you know, state line blind

1161
01:05:11,200 --> 01:05:15,240
Speaker 1: virus to sort of have all of the president's sins

1162
01:05:15,400 --> 01:05:17,280
Speaker 1: from his first three years catch up with him. You

1163
01:05:17,320 --> 01:05:20,280
Speaker 1: can't stand there and lie, You can't contradict your scientists,

1164
01:05:20,320 --> 01:05:22,320
Speaker 1: because they're the ones that stand at sixty six and

1165
01:05:22,440 --> 01:05:25,720
Speaker 1: sixty eight percent public trust, not you, He's down at

1166
01:05:25,760 --> 01:05:28,200
Speaker 1: thirty eight percent. Pence is lower than him. I mean,

1167
01:05:28,240 --> 01:05:30,880
Speaker 1: he needs those people, whether he likes what they say

1168
01:05:31,640 --> 01:05:34,919
Speaker 1: or not. And I wonder what you think about whether

1169
01:05:35,000 --> 01:05:37,360
Speaker 1: or not there's some silver lining there that some of

1170
01:05:37,440 --> 01:05:39,480
Speaker 1: the things that that we've been talking about for three

1171
01:05:39,520 --> 01:05:42,480
Speaker 1: years may be finally catching up with him. You mean

1172
01:05:42,560 --> 01:05:45,680
Speaker 1: the lies for three years. You mean the conspiracy theories,

1173
01:05:46,000 --> 01:05:50,040
Speaker 1: you mean the hoaxes, the let's see, the character assassination,

1174
01:05:50,400 --> 01:05:56,160
Speaker 1: the libel slander. I don't even know what to say anymore.

1175
01:05:57,120 --> 01:06:01,200
Speaker 1: The mob in the media is nuts. What Mika was

1176
01:06:01,320 --> 01:06:04,680
Speaker 1: talking about. And still I don't even hate Joe, but

1177
01:06:04,880 --> 01:06:08,320
Speaker 1: Joe lost his mind and accused the president pretty much

1178
01:06:08,320 --> 01:06:12,640
Speaker 1: a murder any confarenty thousand people. Remember, we're gonna lose

1179
01:06:12,720 --> 01:06:16,840
Speaker 1: two point two million people. And what's so unbelievable here,

1180
01:06:16,920 --> 01:06:19,200
Speaker 1: And it's something that I've said now for a long time.

1181
01:06:19,440 --> 01:06:23,040
Speaker 1: If Donald Trump cured cancer, they'd impeach him procuring cancer.

1182
01:06:24,280 --> 01:06:28,600
Speaker 1: They can't even acknowledge the travel band Wow was ten

1183
01:06:28,720 --> 01:06:34,080
Speaker 1: days after the first identified case of coronavirus. You know

1184
01:06:34,200 --> 01:06:39,280
Speaker 1: what that prevented untold tens of thousands of Americans likely

1185
01:06:39,360 --> 01:06:44,400
Speaker 1: from contracting the disease, untold numbers of Americans from exponentially

1186
01:06:44,720 --> 01:06:50,720
Speaker 1: mathematically than dying. And this being you know, exponentially worse

1187
01:06:51,360 --> 01:06:53,440
Speaker 1: on a level I don't even think we can imagine

1188
01:06:55,080 --> 01:06:59,600
Speaker 1: and not a word, you know, I go back and

1189
01:06:59,680 --> 01:07:02,840
Speaker 1: I go through the timelines, and you know, fake news CNN.

1190
01:07:03,320 --> 01:07:07,120
Speaker 1: You know, Anderson Cooper, the virus is you worry more

1191
01:07:07,120 --> 01:07:09,560
Speaker 1: about the flu? He said that on March fourth. I

1192
01:07:09,720 --> 01:07:13,240
Speaker 1: went over the statements in great detail in the last

1193
01:07:13,320 --> 01:07:16,040
Speaker 1: hour about the things doctor Fauci was telling Well, if

1194
01:07:16,080 --> 01:07:18,560
Speaker 1: you're generally healthy and young, sure go on a cruise.

1195
01:07:18,800 --> 01:07:23,440
Speaker 1: March ninth. That's late if you go to him, and

1196
01:07:23,600 --> 01:07:26,040
Speaker 1: we interviewed him a lot throughout this, going back to

1197
01:07:26,160 --> 01:07:31,640
Speaker 1: January twenty seventh, of February tenth, etc. You know, February

1198
01:07:31,680 --> 01:07:35,000
Speaker 1: twenty ninth. You know, you know it's we still remain

1199
01:07:35,120 --> 01:07:37,600
Speaker 1: the risk is as a whole, the country as a

1200
01:07:37,640 --> 01:07:41,280
Speaker 1: whole still remains a low risk. February twenty ninth. If

1201
01:07:41,360 --> 01:07:44,640
Speaker 1: you want to look at the politicians and the things

1202
01:07:44,760 --> 01:07:48,320
Speaker 1: that they were saying, they were wrong on a level

1203
01:07:48,480 --> 01:07:54,840
Speaker 1: that is. It was an epics spectacular fail on so

1204
01:07:55,040 --> 01:07:59,640
Speaker 1: many different levels. The politicizing of this New York Times

1205
01:08:00,280 --> 01:08:02,960
Speaker 1: calling it the you know, it's hypocrisy, calling it the

1206
01:08:03,080 --> 01:08:07,960
Speaker 1: Chinese virus. Okay, but they themselves did well. Lilie's Fake

1207
01:08:08,040 --> 01:08:12,160
Speaker 1: News accosted it over at CNN or January I'm sorry

1208
01:08:12,200 --> 01:08:16,599
Speaker 1: February fifth, who says it's not safe to travel to China. Oh,

1209
01:08:16,680 --> 01:08:20,280
Speaker 1: there's some genius advice. Maybe we'll follow that advice. And

1210
01:08:20,400 --> 01:08:23,120
Speaker 1: what would the ramifications of that be? And you have

1211
01:08:23,280 --> 01:08:28,400
Speaker 1: your your incredibly genius politicians that couldn't have been more

1212
01:08:28,520 --> 01:08:33,160
Speaker 1: wrong on so many different levels that it is. It

1213
01:08:33,360 --> 01:08:37,719
Speaker 1: is so scary from having what's on Nancy Pelosi February

1214
01:08:37,760 --> 01:08:41,920
Speaker 1: twenty four, Come to Chinatown, really, come to Chinatown. What

1215
01:08:42,160 --> 01:08:44,800
Speaker 1: was she doing when the president was implementing the travel ban?

1216
01:08:45,040 --> 01:08:47,559
Speaker 1: She was impeaching the president. What was she doing when

1217
01:08:47,600 --> 01:08:49,519
Speaker 1: he was talking about it at the State of the Union.

1218
01:08:49,640 --> 01:08:52,920
Speaker 1: She was pre ripping the papers for her made for

1219
01:08:53,080 --> 01:09:00,400
Speaker 1: television preplanned, well orchestrated temper tantrum. That's what she was doing. Um,

1220
01:09:01,000 --> 01:09:03,840
Speaker 1: you know, I for the Governor of New York March second,

1221
01:09:03,960 --> 01:09:06,160
Speaker 1: to be saying the things that he was saying, Oh,

1222
01:09:06,400 --> 01:09:09,240
Speaker 1: we're New Yorkers, you know, you know, we're New Yorkers.

1223
01:09:09,720 --> 01:09:13,040
Speaker 1: We're ready for this sort of thing. We're not like

1224
01:09:13,160 --> 01:09:15,240
Speaker 1: these other countries. If you don't mind me, I don't

1225
01:09:15,320 --> 01:09:17,920
Speaker 1: I speak for the mayor on this. That's what you're saying.

1226
01:09:18,160 --> 01:09:20,800
Speaker 1: And then the idiotic you know, tweets going out to

1227
01:09:21,240 --> 01:09:24,640
Speaker 1: March tenth by Comrade de Blasio. They were prepared for

1228
01:09:24,760 --> 01:09:27,839
Speaker 1: nothing in New York. You know, it was the biggest

1229
01:09:27,960 --> 01:09:32,760
Speaker 1: medical mobilization in history, nearly thirty thousand hospital beds. You know,

1230
01:09:32,840 --> 01:09:37,479
Speaker 1: the Javit Center staffed, built, staffed by Trump. Every ventilator

1231
01:09:37,560 --> 01:09:41,880
Speaker 1: New York had came from Trump. The comfort staffed by Trump,

1232
01:09:42,320 --> 01:09:45,599
Speaker 1: converted COVID nineteen, not the original plan by the president.

1233
01:09:46,920 --> 01:09:50,400
Speaker 1: The mass, the shields, the respirators, the ventilators, the gowns,

1234
01:09:50,479 --> 01:09:54,439
Speaker 1: the gloves, the medicines. Trump, it doesn't matter. You get

1235
01:09:54,479 --> 01:09:59,599
Speaker 1: the foremost expert on the issue of hydroxy chloroquin they

1236
01:09:59,640 --> 01:10:03,160
Speaker 1: don't even want for Daniel Wallace forty two years, four

1237
01:10:03,320 --> 01:10:07,720
Speaker 1: hundred peer review studies. You know, it doesn't then none

1238
01:10:07,760 --> 01:10:10,639
Speaker 1: of that seems to matter. And I and him saying

1239
01:10:10,680 --> 01:10:14,160
Speaker 1: that the risk is nil for thirty to sixty days

1240
01:10:14,240 --> 01:10:16,960
Speaker 1: at the at the at the dosage level, people were

1241
01:10:17,000 --> 01:10:19,559
Speaker 1: talking about what's the first role of medicine, do no harm?

1242
01:10:20,520 --> 01:10:23,920
Speaker 1: You know, hydroxy chloroquin is a very safe drug his words.

1243
01:10:24,720 --> 01:10:27,960
Speaker 1: It's been in use since nineteen fifty five, sixty five years,

1244
01:10:28,600 --> 01:10:31,320
Speaker 1: and in forty two years of practice, no patient of

1245
01:10:31,360 --> 01:10:34,519
Speaker 1: mine has ever been hospitalized for eight CQ complications. This

1246
01:10:34,640 --> 01:10:38,879
Speaker 1: guy wrote the book on lupus, four hundred peer reviewed,

1247
01:10:40,160 --> 01:10:44,920
Speaker 1: you know papers this guy's written, including anti malarials too.

1248
01:10:45,439 --> 01:10:48,320
Speaker 1: This is the drug he uses for rheumatoid arthritis and

1249
01:10:48,720 --> 01:10:53,200
Speaker 1: for lupus. Anyway, Joel Pollock is with US editor Senior

1250
01:10:53,320 --> 01:10:56,360
Speaker 1: Editor at Large, Bright Bart, author of How Trump Won,

1251
01:10:56,400 --> 01:11:01,120
Speaker 1: The Inside Story of a Revolution, And you know he's

1252
01:11:01,160 --> 01:11:04,439
Speaker 1: been reporting this disgusting news that you know, I would

1253
01:11:04,439 --> 01:11:06,320
Speaker 1: look at the greatness of the American people, then I

1254
01:11:06,400 --> 01:11:08,640
Speaker 1: see the same people that live for three years and

1255
01:11:08,800 --> 01:11:11,120
Speaker 1: hated Trump for three years, the Democrats on the mob,

1256
01:11:11,200 --> 01:11:13,920
Speaker 1: And it's the same thing. Even during a national emergency,

1257
01:11:15,920 --> 01:11:19,920
Speaker 1: it's absolutely right, and in fact, immediate surgains de regency

1258
01:11:20,200 --> 01:11:24,160
Speaker 1: as the opportunity to take Trump out rather than unifying

1259
01:11:24,240 --> 01:11:28,360
Speaker 1: the country behind the war against the invisible enemy, the

1260
01:11:28,680 --> 01:11:32,919
Speaker 1: mainstream and the White House Press Court as their opportunity. Finally,

1261
01:11:33,360 --> 01:11:37,719
Speaker 1: impeachment didn't work. Russia collusion didn't work, twenty fifth Amendment

1262
01:11:37,760 --> 01:11:40,759
Speaker 1: didn't work, Michael Cohen didn't work. None of their schemes worked,

1263
01:11:40,840 --> 01:11:43,760
Speaker 1: Stormy Daniels, Michael Evanati. But this was going to be it,

1264
01:11:44,280 --> 01:11:48,040
Speaker 1: and they put the interests of the country behind getting

1265
01:11:48,160 --> 01:11:52,200
Speaker 1: rid of Donald Trump because in their minds, it's in

1266
01:11:52,280 --> 01:11:53,840
Speaker 1: the best interest of the country to get rid of

1267
01:11:53,920 --> 01:11:55,760
Speaker 1: Donald Trump. So they think they're doing the right thing,

1268
01:11:56,160 --> 01:12:00,320
Speaker 1: and they put all their energy into attacking him rather

1269
01:12:00,400 --> 01:12:06,719
Speaker 1: than unifying the country. Is it the ends justified the means?

1270
01:12:06,800 --> 01:12:08,720
Speaker 1: Do they know they're lying? In your view? Because I

1271
01:12:08,760 --> 01:12:11,320
Speaker 1: can't tell. I think there are true believers. I think

1272
01:12:11,360 --> 01:12:14,040
Speaker 1: there are people that you know, they're in a state

1273
01:12:14,080 --> 01:12:16,240
Speaker 1: of psychosis. They wake up in the morning, How can

1274
01:12:16,280 --> 01:12:17,800
Speaker 1: I hate Trump today? And they don't even know what

1275
01:12:17,840 --> 01:12:20,120
Speaker 1: they're doing. Then you got other people that know damn

1276
01:12:20,160 --> 01:12:23,240
Speaker 1: well what they're doing, but they want the power back,

1277
01:12:23,840 --> 01:12:26,760
Speaker 1: and then there's a combination somewhere in the middle. Where

1278
01:12:26,800 --> 01:12:30,479
Speaker 1: are your thoughts on it? I agree with you, there

1279
01:12:30,479 --> 01:12:33,280
Speaker 1: are different people. So there are some people who are

1280
01:12:33,400 --> 01:12:36,120
Speaker 1: just determined to get rid of him regardless. It doesn't

1281
01:12:36,160 --> 01:12:38,800
Speaker 1: matter whether it's right or wrong. They just want him out.

1282
01:12:38,880 --> 01:12:41,120
Speaker 1: They want their power back, you see, because he hasn't

1283
01:12:41,120 --> 01:12:44,320
Speaker 1: just undermined the Democrats. What he really did was undermine

1284
01:12:44,479 --> 01:12:46,680
Speaker 1: the power of the media to choose our leaders for

1285
01:12:46,880 --> 01:12:50,519
Speaker 1: us by defeating Hillary Clinton and doing it without the

1286
01:12:50,560 --> 01:12:53,320
Speaker 1: support of the media, without paying for all the advertisements

1287
01:12:53,720 --> 01:12:55,960
Speaker 1: on CNN and so forth. He got them to cover

1288
01:12:56,080 --> 01:12:59,919
Speaker 1: him without paying for the airtime, and that really frustrates

1289
01:13:00,160 --> 01:13:01,760
Speaker 1: So some of them just want him out. But then

1290
01:13:01,800 --> 01:13:03,840
Speaker 1: there are those who think they're doing their civic duty.

1291
01:13:04,040 --> 01:13:07,719
Speaker 1: They're so brainwashed by their peers and by the constant

1292
01:13:07,800 --> 01:13:10,280
Speaker 1: drum of fake news that they think it's in the

1293
01:13:10,400 --> 01:13:13,880
Speaker 1: national interest in their rhythm. That's why they pounce on

1294
01:13:14,040 --> 01:13:18,040
Speaker 1: every little mistake, they use every gaff, every error. The

1295
01:13:18,120 --> 01:13:21,840
Speaker 1: guy's been up, you know, he Inpens twenty four hours

1296
01:13:21,880 --> 01:13:24,519
Speaker 1: a day for the last six weeks working on this problem,

1297
01:13:25,040 --> 01:13:27,640
Speaker 1: and they've done a stellar job of delivering. There's no

1298
01:13:28,240 --> 01:13:31,599
Speaker 1: response in American history like this one. And they did

1299
01:13:31,680 --> 01:13:33,800
Speaker 1: it in a conservative way that was more effective. They

1300
01:13:33,800 --> 01:13:38,000
Speaker 1: didn't centralize government, they didn't build new government agencies, they deregulated,

1301
01:13:38,040 --> 01:13:40,719
Speaker 1: they decentralized, they let the private sector and the states

1302
01:13:40,760 --> 01:13:43,880
Speaker 1: take the initiative. It's an amazing achievement, and the media

1303
01:13:44,000 --> 01:13:46,639
Speaker 1: is so frustrated by that that they simply will pounce

1304
01:13:46,720 --> 01:13:51,360
Speaker 1: on anything, any small, minor ridiculous nonsense to try to

1305
01:13:51,840 --> 01:13:54,160
Speaker 1: out to the president. They're talking about the twenty fifth

1306
01:13:54,160 --> 01:13:56,960
Speaker 1: Amendment today because there's some comments he made it a

1307
01:13:57,040 --> 01:13:59,320
Speaker 1: press conference, and they've been talking about the twenty fifth

1308
01:13:59,320 --> 01:14:01,519
Speaker 1: Amendment since before he took office. It's just the same

1309
01:14:01,600 --> 01:14:04,320
Speaker 1: thing over and over again. And the American people are

1310
01:14:04,360 --> 01:14:07,080
Speaker 1: tired of it. I think they're tired of it. But

1311
01:14:07,720 --> 01:14:10,880
Speaker 1: it's never gonna end. You know, I was saying for

1312
01:14:10,920 --> 01:14:13,120
Speaker 1: a while that if he cured cancer, that impeach him

1313
01:14:13,360 --> 01:14:16,439
Speaker 1: for curing cancer. If he gave every American five million,

1314
01:14:16,479 --> 01:14:19,519
Speaker 1: it would be why didn't you give them six? And

1315
01:14:20,200 --> 01:14:22,800
Speaker 1: so how does this all play out? Because we're one

1316
01:14:22,880 --> 01:14:25,559
Speaker 1: hundred and ninety three days away from election day. As

1317
01:14:25,640 --> 01:14:28,479
Speaker 1: you examine the landscape, it's obviously very different than what

1318
01:14:28,560 --> 01:14:32,240
Speaker 1: we thought it would be. This is a whole new equation.

1319
01:14:32,439 --> 01:14:35,280
Speaker 1: Then we're seeing, you know, the ever so forgetful Joe

1320
01:14:35,840 --> 01:14:39,360
Speaker 1: would by basically useless. Probably the best thing that can

1321
01:14:39,439 --> 01:14:42,960
Speaker 1: happen is hiding him for now. Do you see anyway

1322
01:14:43,000 --> 01:14:47,040
Speaker 1: they try to wrestle this nomination away from him. Yeah,

1323
01:14:47,080 --> 01:14:49,600
Speaker 1: they may try, because he's really been stuck in his

1324
01:14:49,680 --> 01:14:53,400
Speaker 1: bunker in Wilmington, Delaware, not able to do anything. He's

1325
01:14:53,400 --> 01:14:55,800
Speaker 1: a very handsy guy, as we know, for better or worse.

1326
01:14:56,080 --> 01:14:58,759
Speaker 1: Can't shake hands, can't kiss the babies, can't hug people.

1327
01:14:59,200 --> 01:15:01,120
Speaker 1: He's just tucking to basement trying to learn how to

1328
01:15:01,160 --> 01:15:03,760
Speaker 1: live stream, and he's not very good at it, so

1329
01:15:04,479 --> 01:15:06,800
Speaker 1: they may try to find someone else. On the other hand,

1330
01:15:07,560 --> 01:15:10,519
Speaker 1: all of these endorsements coming in and this effect of

1331
01:15:10,720 --> 01:15:13,599
Speaker 1: rallying everybody in the Democratic Party against Trump is helping

1332
01:15:13,680 --> 01:15:17,280
Speaker 1: Biden hang in there, so it may get hard for

1333
01:15:17,400 --> 01:15:20,240
Speaker 1: them to replace him. As to what the race looks like,

1334
01:15:20,840 --> 01:15:23,519
Speaker 1: you know, if this crisis had happened in September and

1335
01:15:23,600 --> 01:15:27,519
Speaker 1: October instead of February and March and April, things might

1336
01:15:27,560 --> 01:15:29,720
Speaker 1: look very different. But we've got a long way to

1337
01:15:29,800 --> 01:15:32,160
Speaker 1: go still before the fall, we've got to have the

1338
01:15:32,280 --> 01:15:35,200
Speaker 1: economy reopen. We've got to see where it's moving if

1339
01:15:35,240 --> 01:15:37,600
Speaker 1: it's harder than the right direction. We've also got to

1340
01:15:37,640 --> 01:15:39,240
Speaker 1: think about whether this thing's going to start to come

1341
01:15:39,280 --> 01:15:40,640
Speaker 1: back in the fall, whether you're going to see a

1342
01:15:40,680 --> 01:15:44,360
Speaker 1: resurgence of the writer's infections, if the Trump administration can

1343
01:15:44,479 --> 01:15:48,599
Speaker 1: handle the virus and the economy, which is a tall order,

1344
01:15:48,640 --> 01:15:50,880
Speaker 1: but Trump's done it pretty well so far. If he

1345
01:15:50,920 --> 01:15:54,000
Speaker 1: can do that, then I think he's in pretty good shape.

1346
01:15:54,040 --> 01:15:56,160
Speaker 1: People will judge him on his performance over the next

1347
01:15:56,200 --> 01:15:59,000
Speaker 1: six months. The media will get more hysterical than ever.

1348
01:15:59,120 --> 01:16:01,400
Speaker 1: As you said, Sean, it never stops, but it is

1349
01:16:01,439 --> 01:16:05,160
Speaker 1: going to get worse. You're going to see craziness increase

1350
01:16:05,320 --> 01:16:07,840
Speaker 1: rather than decrease. And even if he gets reelected, it's

1351
01:16:07,880 --> 01:16:10,559
Speaker 1: not going away. But this has always been about results

1352
01:16:10,600 --> 01:16:13,120
Speaker 1: with Trump. It's always about what he does over and

1353
01:16:13,160 --> 01:16:16,160
Speaker 1: above what he says. And I think if people are

1354
01:16:16,200 --> 01:16:19,760
Speaker 1: impressed prior to results, he'll be reelected. If not, well

1355
01:16:20,560 --> 01:16:22,080
Speaker 1: we'll talk about it then. But there's going to be

1356
01:16:22,160 --> 01:16:25,800
Speaker 1: a resistance, a real resistance from the conservative side and

1357
01:16:25,880 --> 01:16:28,360
Speaker 1: from the American people, frankly, because they know what the

1358
01:16:28,439 --> 01:16:30,800
Speaker 1: media and the Democratic Party have tried to do to

1359
01:16:30,880 --> 01:16:32,960
Speaker 1: this him. They've been behind what amounts to a coup

1360
01:16:33,280 --> 01:16:35,439
Speaker 1: since before he took office, and we're finding more out

1361
01:16:35,439 --> 01:16:41,040
Speaker 1: about that every day. Stay tuned on all of that anyway,

1362
01:16:41,160 --> 01:16:43,720
Speaker 1: and you guys get your share of hits as well

1363
01:16:43,760 --> 01:16:46,200
Speaker 1: as us. I mean, it's unbelievable the environment out here.

1364
01:16:46,200 --> 01:16:48,960
Speaker 1: I've never seen it this bad, and I've been at this.

1365
01:16:49,280 --> 01:16:51,799
Speaker 1: I'm an old person thirty one years since I started

1366
01:16:51,840 --> 01:16:54,599
Speaker 1: my radio journey, twenty four years of Fox, and it's

1367
01:16:54,640 --> 01:16:57,080
Speaker 1: never been this bad. And it's none of it. As

1368
01:16:57,120 --> 01:17:00,040
Speaker 1: I said, even before this whole mess. You know, what

1369
01:17:00,080 --> 01:17:03,439
Speaker 1: they're doing is destructive to the country, Joel. It's sad

1370
01:17:03,520 --> 01:17:07,680
Speaker 1: to watch and it's an all hands on deck to

1371
01:17:07,800 --> 01:17:11,240
Speaker 1: save the Republic moment in the sense that their plans

1372
01:17:11,360 --> 01:17:15,880
Speaker 1: to restructure the country are so dangerous for everybody. But anyway,

1373
01:17:15,920 --> 01:17:17,519
Speaker 1: great to talk to you, Great to catch up, Joel

1374
01:17:17,560 --> 01:17:21,360
Speaker 1: Pollock Bright Part Senior editor at Large, author of the

1375
01:17:21,400 --> 01:17:24,080
Speaker 1: book How Trump Won The Inside Story of a Revolution

1376
01:17:24,200 --> 01:17:25,920
Speaker 1: up on We'll put it up on Hannity dot com,

1377
01:17:26,080 --> 01:17:30,479
Speaker 1: Amazon dot com hopefully soon bookstores near you. Hi twenty

1378
01:17:30,520 --> 01:17:32,400
Speaker 1: five downs to the top of the Hour, eight hundred

1379
01:17:32,400 --> 01:17:34,439
Speaker 1: and nine four one sewn. You want to be a

1380
01:17:34,640 --> 01:17:39,040
Speaker 1: part of this extravaganza. Um, We're just gonna take calls

1381
01:17:39,040 --> 01:17:41,880
Speaker 1: at some point. I think they'll have the Coronavirus task Force.

1382
01:17:42,080 --> 01:17:46,320
Speaker 1: If it happens, we'll let you know. As we've been doing.

1383
01:17:46,760 --> 01:17:48,800
Speaker 1: UM want to remind you if you want to sleep better,

1384
01:17:48,840 --> 01:17:51,400
Speaker 1: our friends at My Pillow, there's no better products. And

1385
01:17:51,600 --> 01:17:54,640
Speaker 1: Mike Lindell and all the workers at My Pillow. And

1386
01:17:54,840 --> 01:17:58,000
Speaker 1: by the way, they're all in Minnesota. These are jobs

1387
01:17:58,040 --> 01:18:00,920
Speaker 1: in the United States. They make the best pillows, the

1388
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Speaker 1: best pillow products, the best sheet skis of dreamsheets, the

1389
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Speaker 1: world's best cotton. They have the best deals. When you

1390
01:18:06,520 --> 01:18:09,479
Speaker 1: go to my pillow dot Com and the Sean Hannity Square,

1391
01:18:09,520 --> 01:18:12,519
Speaker 1: you get deep discounts. Buy one, get one free, buy

1392
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Speaker 1: one set of GISA dreamsheets, get another free every day.

1393
01:18:15,280 --> 01:18:19,880
Speaker 1: Great great discounts. But they're also building those n ninety

1394
01:18:19,920 --> 01:18:23,599
Speaker 1: five masks. They've they've reconfigured it to help the country

1395
01:18:23,640 --> 01:18:26,639
Speaker 1: out in the time of need. How to get workers

1396
01:18:26,760 --> 01:18:28,960
Speaker 1: to transition to do that in the right way. And

1397
01:18:29,280 --> 01:18:31,439
Speaker 1: all these people everyone thinks you can snap your fingers. Oh,

1398
01:18:31,479 --> 01:18:34,639
Speaker 1: I'll just gonna make ninety five masks. GMO make ventilators,

1399
01:18:34,680 --> 01:18:36,680
Speaker 1: will have hundreds of thousands of them in seconds. No,

1400
01:18:37,640 --> 01:18:40,240
Speaker 1: you know it was That's why makes this so amazing

1401
01:18:40,320 --> 01:18:42,240
Speaker 1: what people have done and how they pulled it off.

1402
01:18:42,280 --> 01:18:43,640
Speaker 1: And my Pillow is a big part of it. And

1403
01:18:43,680 --> 01:18:46,240
Speaker 1: I want to congratulate Michaelndell and his team over there

1404
01:18:46,280 --> 01:18:49,479
Speaker 1: for everything more great partners of ours, my Pillow dot Com,

1405
01:18:49,600 --> 01:18:53,200
Speaker 1: Sean Hannity Square, You're gonna fall asleep faster, stay a

1406
01:18:53,240 --> 01:18:55,040
Speaker 1: sleep longer. And by the way, we all need a

1407
01:18:55,080 --> 01:18:57,400
Speaker 1: little extra sleep. Right, all right, let's get to our

1408
01:18:57,439 --> 01:19:00,519
Speaker 1: phones here um for stations along the Sean Hannity Show Network.

1409
01:19:00,560 --> 01:19:03,240
Speaker 1: We're gonna continue our format that we have had now

1410
01:19:03,320 --> 01:19:06,280
Speaker 1: for the last number of weeks. If the Coronavirus Task

1411
01:19:06,360 --> 01:19:09,479
Speaker 1: Force starts during this half hour, we'll go to it.

1412
01:19:09,520 --> 01:19:13,120
Speaker 1: We'll take it right straight to the end. Let's say

1413
01:19:13,439 --> 01:19:17,840
Speaker 1: hi two. Let's see Ben and Delaware. What's up, Ben?

1414
01:19:17,920 --> 01:19:21,479
Speaker 1: How are you? Sir? Glad you called Happy Friday? Crazy times,

1415
01:19:21,800 --> 01:19:25,080
Speaker 1: rough times, But we see great things in the American people,

1416
01:19:25,160 --> 01:19:28,080
Speaker 1: don't we. Yes, we do, show and I see it

1417
01:19:28,160 --> 01:19:30,720
Speaker 1: every day. I'm blessed my family company. We have a

1418
01:19:30,760 --> 01:19:33,320
Speaker 1: construction company, Greg and Frere. We're still in business seventy

1419
01:19:33,400 --> 01:19:35,800
Speaker 1: years in Delaware and we're open right now. Fortunately. But

1420
01:19:35,920 --> 01:19:37,439
Speaker 1: I got a real heart for the people that are

1421
01:19:37,439 --> 01:19:40,400
Speaker 1: out of work right now. And you know, I've got

1422
01:19:40,520 --> 01:19:43,000
Speaker 1: five simple facts that a Delaware that would blow your mind.

1423
01:19:43,520 --> 01:19:45,800
Speaker 1: You know, here in Delaware, we have thirty three hundred

1424
01:19:45,840 --> 01:19:50,520
Speaker 1: coronavirus cases. That's point three percent of our one million population.

1425
01:19:50,920 --> 01:19:53,680
Speaker 1: We have two hundred and ninety hospitalizations, and I take

1426
01:19:53,720 --> 01:19:56,720
Speaker 1: every life seriously, okay, but this is point zero to

1427
01:19:57,280 --> 01:20:01,120
Speaker 1: nine percent of our population. I had ninety two tragic,

1428
01:20:01,200 --> 01:20:05,080
Speaker 1: sad deaths, most of those unfortunately we're elderly with existing complications.

1429
01:20:05,400 --> 01:20:08,200
Speaker 1: But just a fact here, this is point zero zero

1430
01:20:08,640 --> 01:20:11,880
Speaker 1: nine percent of our population. Okay. If you look at

1431
01:20:11,920 --> 01:20:15,000
Speaker 1: that and overlay that against the very real economic crisis

1432
01:20:15,080 --> 01:20:17,320
Speaker 1: that we have. We have thirty million dollars right now.

1433
01:20:17,720 --> 01:20:20,840
Speaker 1: This is today's numbers, thirty million dollars a week being

1434
01:20:20,920 --> 01:20:24,160
Speaker 1: spent on unemployment numbers. And every month we have another

1435
01:20:24,280 --> 01:20:28,759
Speaker 1: seventy thousand new claims of unemployment. We have an economic crisis,

1436
01:20:28,840 --> 01:20:31,240
Speaker 1: not a medical one. Our medical infrastructure. We have over

1437
01:20:31,280 --> 01:20:34,040
Speaker 1: twenty two hundred hospital bids in Delaware, and I talk

1438
01:20:34,080 --> 01:20:37,639
Speaker 1: to many people in our medical profession and there simply

1439
01:20:37,760 --> 01:20:42,600
Speaker 1: is not any overwhelming or crisis. Well, look, let me

1440
01:20:42,640 --> 01:20:44,840
Speaker 1: say it a little differently than you. And I'm listening

1441
01:20:44,960 --> 01:20:47,320
Speaker 1: very closely to everything you're saying, and you're thinking along

1442
01:20:47,400 --> 01:20:49,639
Speaker 1: the lines that most Americans are, and that is hard.

1443
01:20:49,680 --> 01:20:51,519
Speaker 1: How do we get back to work? It's amazing because

1444
01:20:51,680 --> 01:20:54,880
Speaker 1: everywhere across the country you see people protesting whycause they

1445
01:20:54,880 --> 01:20:57,519
Speaker 1: want to get back to work. I go back to

1446
01:20:57,800 --> 01:21:00,599
Speaker 1: the same example I've been using, and I'm not trying

1447
01:21:00,600 --> 01:21:05,400
Speaker 1: to repeat myself, but I'll go New York grocery stores.

1448
01:21:06,720 --> 01:21:08,960
Speaker 1: I've been in New York City, I have been out

1449
01:21:09,000 --> 01:21:12,160
Speaker 1: in Long Island, right in the epicenter of this, and

1450
01:21:12,880 --> 01:21:17,280
Speaker 1: the store shelves are full. There's not been a time

1451
01:21:18,000 --> 01:21:20,800
Speaker 1: in the last number of weeks that I have gone

1452
01:21:21,600 --> 01:21:24,840
Speaker 1: to my local grocery store and I go. You know,

1453
01:21:24,880 --> 01:21:27,320
Speaker 1: people always say, I don't know why people say this

1454
01:21:27,439 --> 01:21:29,720
Speaker 1: to me. I say, what are you doing here? I'm

1455
01:21:29,760 --> 01:21:33,360
Speaker 1: like shopping? What are you doing here? People must think that.

1456
01:21:33,439 --> 01:21:35,280
Speaker 1: I guess you're talking to your host. You have peoples

1457
01:21:35,320 --> 01:21:37,479
Speaker 1: that does shopping up. No. I like to do my

1458
01:21:37,520 --> 01:21:40,800
Speaker 1: own shopping, my own cooking. Jeez cracks me up. And

1459
01:21:41,040 --> 01:21:45,519
Speaker 1: but I but I see every single time, Ben, I

1460
01:21:45,720 --> 01:21:50,960
Speaker 1: see the guy stock in the shelves, and I'm telling you.

1461
01:21:51,200 --> 01:21:54,800
Speaker 1: They're they're in their mask, they're in their gloves. And

1462
01:21:54,960 --> 01:21:56,479
Speaker 1: the one time I saw a guy with his mask,

1463
01:21:56,960 --> 01:21:59,320
Speaker 1: please put it on. Please for yourself. We care about you.

1464
01:22:00,120 --> 01:22:03,720
Speaker 1: And most people you know now are wearing their masks. Yeah,

1465
01:22:03,760 --> 01:22:05,720
Speaker 1: in a few weeks back they weren't, but now they are.

1466
01:22:06,880 --> 01:22:11,280
Speaker 1: And absolutely, I'm building a twelve million dollar roadway project

1467
01:22:11,400 --> 01:22:14,280
Speaker 1: right now, and we've adapted to improvised and overcome by

1468
01:22:14,320 --> 01:22:17,080
Speaker 1: supporting each other. We social distance, we wear masks. The

1469
01:22:17,160 --> 01:22:20,000
Speaker 1: American people are resilient. I swore note that this country

1470
01:22:20,080 --> 01:22:22,720
Speaker 1: is a special operations veteran, and I'll never let it go.

1471
01:22:22,960 --> 01:22:26,160
Speaker 1: We the people are capable of making choice, living out

1472
01:22:26,160 --> 01:22:28,439
Speaker 1: our freedoms and protecting each other. The American people have

1473
01:22:28,560 --> 01:22:32,400
Speaker 1: proven that the social distance. The President just stood up

1474
01:22:32,400 --> 01:22:34,120
Speaker 1: to the microphone. Let me just say this and we'll

1475
01:22:34,120 --> 01:22:36,360
Speaker 1: start it at the beginning here in a second. Yeah,

1476
01:22:36,479 --> 01:22:39,160
Speaker 1: I hear everything you're saying. But if those guys can

1477
01:22:39,240 --> 01:22:42,120
Speaker 1: stock the shelves or else we've starve and they can

1478
01:22:42,200 --> 01:22:45,320
Speaker 1: do it safely, the key is safely social distancing of

1479
01:22:45,400 --> 01:22:48,360
Speaker 1: half the New York City buildings stay working from home.

1480
01:22:49,160 --> 01:22:52,120
Speaker 1: Were masks and gloves. You have temperature checks. When you

1481
01:22:52,200 --> 01:22:55,000
Speaker 1: get more tests, you have more testing. Got to do

1482
01:22:55,120 --> 01:22:58,120
Speaker 1: it safely. I understand people's fears, but it can be

1483
01:22:58,240 --> 01:23:04,719
Speaker 1: done anyway. Listen, stay well, stay healthy, cling to your families,

1484
01:23:04,760 --> 01:23:07,760
Speaker 1: your God and your Bibles. Oh yeah, we're one of

1485
01:23:08,040 --> 01:23:12,479
Speaker 1: those bitter Walmart shoppers. But those are the things that matter.

1486
01:23:13,280 --> 01:23:15,280
Speaker 1: And we'll see you on Monday. This is now the

1487
01:23:15,320 --> 01:23:22,559
Speaker 1: President taken to the podium. Number. Thank you very much, everyone,

1488
01:23:27,200 --> 01:23:31,480
Speaker 1: Thank you. We continue to see evidence that our aggressive

1489
01:23:31,600 --> 01:23:36,400
Speaker 1: strategy is working and working at a very high level. Nationwide.

1490
01:23:36,680 --> 01:23:40,080
Speaker 1: To percent of tests that come back positive has declined

1491
01:23:40,320 --> 01:23:44,120
Speaker 1: very significantly. Last week, roughly thirty eight percent of the

1492
01:23:44,200 --> 01:23:47,400
Speaker 1: tests in New York were positive. This week that number

1493
01:23:47,479 --> 01:23:50,479
Speaker 1: is down to twenty eight percent. New cases in New

1494
01:23:50,560 --> 01:23:54,040
Speaker 1: York are down fifty percent compared to a week ago,

1495
01:23:54,680 --> 01:23:58,040
Speaker 1: and fatalities are down forty percent over the same period.

1496
01:23:58,520 --> 01:24:03,200
Speaker 1: In Louisiana, the rate a positive test resulted decline from

1497
01:24:03,280 --> 01:24:06,000
Speaker 1: twenty five percent down to fifteen percent in the last

1498
01:24:06,080 --> 01:24:10,680
Speaker 1: seven days alone. Eighteen states now show a decline in

1499
01:24:10,800 --> 01:24:13,880
Speaker 1: a number of positive tests in the last seven days.

1500
01:24:13,960 --> 01:24:16,240
Speaker 1: So over the last seven day has been very very

1501
01:24:16,320 --> 01:24:21,120
Speaker 1: significant progress. Half of all Americans live in states that

1502
01:24:21,240 --> 01:24:25,839
Speaker 1: have now taken steps to open their economies. Just yesterday,

1503
01:24:25,920 --> 01:24:30,519
Speaker 1: Governors Gavin Newsom California, Tim Waltz of Minnesota, and Bill

1504
01:24:30,560 --> 01:24:35,000
Speaker 1: Lee of Tennessee announced additional plans to restart certain sectors.

1505
01:24:36,000 --> 01:24:40,960
Speaker 1: We ask every American to maintain vigilance and hygiene, social distancing,

1506
01:24:41,080 --> 01:24:45,839
Speaker 1: and voluntary use of face coverings. We're opening our country.

1507
01:24:45,880 --> 01:24:48,640
Speaker 1: It's very exciting to see. We have a lot of

1508
01:24:48,760 --> 01:24:54,400
Speaker 1: talent involved, from governors down to people that just stand

1509
01:24:54,479 --> 01:24:58,120
Speaker 1: there and help you with the doors. There's been tremendous

1510
01:24:58,200 --> 01:25:02,840
Speaker 1: talent involved and tremendous from our country. Country is a

1511
01:25:02,960 --> 01:25:06,519
Speaker 1: great place, and it's going to be greater than ever before.

1512
01:25:06,600 --> 01:25:08,439
Speaker 1: I really believe that. I think there's going to be

1513
01:25:08,960 --> 01:25:12,719
Speaker 1: a tremendous upward shift. I spoke with Tim Cook today

1514
01:25:12,800 --> 01:25:15,519
Speaker 1: of Apple, and they have a good sense of the

1515
01:25:15,640 --> 01:25:17,360
Speaker 1: market and he feels it's going to be a v

1516
01:25:17,600 --> 01:25:21,880
Speaker 1: The V is sharply upward later on as we actually

1517
01:25:21,920 --> 01:25:26,559
Speaker 1: get it fully open. Today I signed the Paycheck Protection

1518
01:25:26,680 --> 01:25:30,880
Speaker 1: Program and Healthcare Enhancement Act, providing three hundred and twenty

1519
01:25:30,920 --> 01:25:34,880
Speaker 1: billion dollars to keep American workers on the payroll. Thirty

1520
01:25:34,960 --> 01:25:38,160
Speaker 1: billion dollars of the paycheck protection funds will be reserved

1521
01:25:38,240 --> 01:25:42,720
Speaker 1: for small financial institutions, including those that serve minority and

1522
01:25:42,840 --> 01:25:47,799
Speaker 1: distressed communities, extending vital relief to thousands of African American

1523
01:25:47,840 --> 01:25:53,840
Speaker 1: and Hispanic American small business owners and their employees. The

1524
01:25:53,960 --> 01:25:57,600
Speaker 1: bill also deliver seventy five billion dollars for hospitals so

1525
01:25:57,800 --> 01:26:01,439
Speaker 1: badly needed. For hospitals, they've taken a big hit, and

1526
01:26:01,640 --> 01:26:05,800
Speaker 1: medical providers in areas less affected by the virus. Hospitals

1527
01:26:05,840 --> 01:26:08,320
Speaker 1: and doctors should work with their state and local health

1528
01:26:08,400 --> 01:26:14,800
Speaker 1: officials on ways to safely resume elective medical treatments and care.

1529
01:26:15,720 --> 01:26:19,519
Speaker 1: Under the Cares Act, we're sending direct payments to millions

1530
01:26:19,560 --> 01:26:22,679
Speaker 1: of American workers. More than eighty million Americans have already

1531
01:26:22,760 --> 01:26:27,080
Speaker 1: received their payment three four hundred dollars for a typical

1532
01:26:27,200 --> 01:26:31,040
Speaker 1: family of four three thousand, four hundred dollars. That's great

1533
01:26:31,560 --> 01:26:34,800
Speaker 1: and you deserve it. The Cares Act requires that the

1534
01:26:34,960 --> 01:26:38,640
Speaker 1: federal government send out a notice of what benefits Americans

1535
01:26:38,720 --> 01:26:42,439
Speaker 1: are receiving. To fulfill the requirement, the Treasury Department is

1536
01:26:42,479 --> 01:26:45,679
Speaker 1: mailing a letter to me. It will include the amount

1537
01:26:46,280 --> 01:26:51,960
Speaker 1: their economic impact payment, how it will arrive, direct deposit check,

1538
01:26:52,520 --> 01:26:55,880
Speaker 1: or prepaid debit card, as well as a message to

1539
01:26:56,280 --> 01:26:59,519
Speaker 1: the nation letting each American know that we are getting

1540
01:26:59,560 --> 01:27:03,479
Speaker 1: through the challenged together as one American family. That's what's

1541
01:27:03,520 --> 01:27:05,920
Speaker 1: been happening. The whole world is watching us. You have

1542
01:27:05,920 --> 01:27:08,040
Speaker 1: one hundred and eighty four countries out there that have

1543
01:27:08,160 --> 01:27:11,720
Speaker 1: been hit, and now it's probably higher than that. But

1544
01:27:12,600 --> 01:27:15,679
Speaker 1: they're all watching us. They're all watching, and they're calling,

1545
01:27:15,760 --> 01:27:19,040
Speaker 1: and they respect what we're doing so much. I spoke

1546
01:27:19,120 --> 01:27:21,920
Speaker 1: with the leaders of numerous countries today. They're asking if

1547
01:27:21,960 --> 01:27:24,400
Speaker 1: we can send them ventilators, and I'm agreeing to do it.

1548
01:27:24,520 --> 01:27:30,360
Speaker 1: We have tremendous capacity now, over capacity of ventilators. We're

1549
01:27:30,400 --> 01:27:35,080
Speaker 1: filling up stockpiles for our states and for ourselves. Federal

1550
01:27:35,120 --> 01:27:38,120
Speaker 1: government is over ten thousand ventilators, and we could have

1551
01:27:38,200 --> 01:27:39,800
Speaker 1: a lot more if we wanted to do that. But

1552
01:27:39,920 --> 01:27:46,320
Speaker 1: we're helping Mexico, Honduras, Indonesia, France. We're sending to France,

1553
01:27:46,360 --> 01:27:49,280
Speaker 1: We're sending to Spain, We're sending to Italy, and we'll

1554
01:27:49,360 --> 01:27:52,639
Speaker 1: probably be sending to Germany should they need them. Over

1555
01:27:52,680 --> 01:27:55,439
Speaker 1: the last three years, we built the strongest economy and

1556
01:27:55,479 --> 01:27:59,160
Speaker 1: the most successful country the world has ever seen. Greatest

1557
01:27:59,200 --> 01:28:03,360
Speaker 1: economy that has ever seen. Nobody's ever done anything like

1558
01:28:03,520 --> 01:28:06,759
Speaker 1: what we were able to do, and we will rebuild

1559
01:28:06,800 --> 01:28:11,400
Speaker 1: that economy, our economy in the not too distant future.

1560
01:28:11,479 --> 01:28:14,479
Speaker 1: I really believe, with all that we've learned and all

1561
01:28:14,520 --> 01:28:17,479
Speaker 1: that we've done, will be just as strong and maybe

1562
01:28:17,560 --> 01:28:20,960
Speaker 1: stronger than ever before, even stronger than it was just

1563
01:28:21,360 --> 01:28:25,599
Speaker 1: two months ago. Some interesting note is that the FDA

1564
01:28:25,720 --> 01:28:30,120
Speaker 1: approved the first at home COVID nineteen test kit just

1565
01:28:30,240 --> 01:28:34,880
Speaker 1: got approved, and doctor Stephen, we're as Stephen Stephen Hans

1566
01:28:34,960 --> 01:28:37,760
Speaker 1: Steven is going to say a couple of words about

1567
01:28:37,800 --> 01:28:39,920
Speaker 1: that and some other things. I want to thank Stephen.

1568
01:28:39,960 --> 01:28:43,360
Speaker 1: The FDA has been incredible. They've been approving not only this,

1569
01:28:43,640 --> 01:28:46,320
Speaker 1: but they've been approving many things at a pace that's

1570
01:28:46,400 --> 01:28:50,560
Speaker 1: never happened before. And they're being very safe about it,

1571
01:28:50,680 --> 01:28:53,800
Speaker 1: as Stephen told me, he told me very strongly. But

1572
01:28:54,080 --> 01:28:57,120
Speaker 1: at the same time, they're approving things at record numbers

1573
01:28:57,280 --> 01:29:00,280
Speaker 1: in a record at a record rate, and it's really

1574
01:29:00,360 --> 01:29:04,080
Speaker 1: been helpful. Many tests are going on, many vaccine tests

1575
01:29:04,240 --> 01:29:09,080
Speaker 1: and tests of every different guide and things are happening

1576
01:29:09,160 --> 01:29:11,600
Speaker 1: just like this event. Things are happening very rapidly, and

1577
01:29:11,680 --> 01:29:13,680
Speaker 1: i'd like to have Stephen tell you a little bit

1578
01:29:13,720 --> 01:29:18,880
Speaker 1: about it. Thank you very much, stateful, Thank you, mister President.

1579
01:29:20,439 --> 01:29:22,519
Speaker 1: Appreciate the opportunity to tell you about what's happening at

1580
01:29:22,560 --> 01:29:25,120
Speaker 1: the FDA. We have a team of more than eighteen

1581
01:29:25,200 --> 01:29:30,240
Speaker 1: thousand employees, including ten thousand scientists, doctors, pharmacists, and nurses,

1582
01:29:30,640 --> 01:29:33,160
Speaker 1: and they've been working around the clock because, as you

1583
01:29:33,280 --> 01:29:35,920
Speaker 1: probably know, many of the medical products that are being

1584
01:29:36,040 --> 01:29:38,759
Speaker 1: used for the COVID nineteen outbreak are in fact regulated

1585
01:29:38,800 --> 01:29:42,040
Speaker 1: by FDA. The staff have been hard at work authorizing

1586
01:29:42,120 --> 01:29:46,679
Speaker 1: tests and other medical products as part of these efforts

1587
01:29:46,760 --> 01:29:51,080
Speaker 1: to support diagnostic test development during this global pandemic. The

1588
01:29:51,160 --> 01:29:54,240
Speaker 1: President has asked us in under its leadership, to actually

1589
01:29:54,320 --> 01:29:56,680
Speaker 1: cut down as many barriers as who possibly could to

1590
01:29:56,760 --> 01:30:00,560
Speaker 1: get medical products into the medical community, and we have

1591
01:30:00,720 --> 01:30:03,960
Speaker 1: done that the course, recognizing the urgency of the situation.

1592
01:30:04,479 --> 01:30:06,840
Speaker 1: I do want to emphasize what the President said is

1593
01:30:06,880 --> 01:30:09,479
Speaker 1: that we are very much paying attations to safety and

1594
01:30:09,600 --> 01:30:12,519
Speaker 1: with respect to tests, validity and reliability of those tests,

1595
01:30:13,240 --> 01:30:15,519
Speaker 1: and I think it's really important to understand how far

1596
01:30:15,640 --> 01:30:20,280
Speaker 1: we've come in just a few short months. The academic community,

1597
01:30:20,680 --> 01:30:24,559
Speaker 1: which I come from the private sector, the government. We've

1598
01:30:24,640 --> 01:30:28,400
Speaker 1: come together to develop diagnostics for a completely new infectious disease,

1599
01:30:29,240 --> 01:30:32,080
Speaker 1: and it's really important. We've heard from many test developers,

1600
01:30:32,160 --> 01:30:36,120
Speaker 1: both in academia and in the manufacturing world. This normally

1601
01:30:36,200 --> 01:30:39,160
Speaker 1: takes years to develop. You've heard doctor Burke's talk about

1602
01:30:39,200 --> 01:30:42,040
Speaker 1: the fact that HIV tests have taken many, many years

1603
01:30:42,080 --> 01:30:45,960
Speaker 1: to develop. This has happened in weeks and months. We've

1604
01:30:46,000 --> 01:30:49,160
Speaker 1: been laser focused on working with both industry and academia

1605
01:30:49,200 --> 01:30:52,400
Speaker 1: to actually make this happen. To date, under our Emergency

1606
01:30:52,520 --> 01:30:56,759
Speaker 1: Use Authorization approach, we've quickly reviewed and authorized sixty three tests,

1607
01:30:57,439 --> 01:30:59,920
Speaker 1: both diagnostic as well as zero logic, that is, the

1608
01:31:00,040 --> 01:31:03,240
Speaker 1: antibody test. We've had several point of care tests and

1609
01:31:03,360 --> 01:31:06,280
Speaker 1: that's important because those can be done in the emergency room,

1610
01:31:06,479 --> 01:31:09,400
Speaker 1: where in a doctor's office, etc. And much more convenient

1611
01:31:09,439 --> 01:31:11,920
Speaker 1: for the patient. And this week, as the President said,

1612
01:31:11,960 --> 01:31:14,719
Speaker 1: we authorized the first at home test by a company

1613
01:31:14,760 --> 01:31:18,600
Speaker 1: called lab Corps. This is a test where, under certain circumstances,

1614
01:31:18,640 --> 01:31:21,280
Speaker 1: with a doctor's supervision, a test can be mailed to

1615
01:31:21,360 --> 01:31:23,960
Speaker 1: a patient and the patient can perform the self swab

1616
01:31:24,200 --> 01:31:26,200
Speaker 1: and then mail it back and get the results after

1617
01:31:26,320 --> 01:31:29,559
Speaker 1: that time. All under the guidance of a licensed physician,

1618
01:31:30,360 --> 01:31:32,439
Speaker 1: and we're not just letting up with the sixty three

1619
01:31:32,520 --> 01:31:35,960
Speaker 1: tests we've approved. We are working with more than four

1620
01:31:36,120 --> 01:31:40,600
Speaker 1: hundred test developers who are pursuing authorization for their diagnosed agnostics.

1621
01:31:40,760 --> 01:31:44,800
Speaker 1: Under our current policies and under our regulatory approach, which

1622
01:31:44,840 --> 01:31:48,320
Speaker 1: is quite flexible, many other tests are becoming available. We

1623
01:31:48,800 --> 01:31:51,360
Speaker 1: have heard and have reported to US two hundred and

1624
01:31:51,439 --> 01:31:54,840
Speaker 1: twenty labs around the country have begun patient testing using

1625
01:31:54,920 --> 01:31:58,799
Speaker 1: their own validated tests. This has allowed us to increase

1626
01:31:58,840 --> 01:32:02,800
Speaker 1: significantly tests around the country. I updated you earlier this

1627
01:32:02,920 --> 01:32:05,720
Speaker 1: week on serologic tests, these antibody tests that are used

1628
01:32:05,760 --> 01:32:08,960
Speaker 1: to detect natural immunity, and the FDA's approach to help

1629
01:32:09,000 --> 01:32:11,920
Speaker 1: make these tests available. While these are just one part

1630
01:32:12,000 --> 01:32:14,280
Speaker 1: of our larger response effort, they can play a role

1631
01:32:14,360 --> 01:32:17,959
Speaker 1: in helping move our economy forward by helping healthcare professionals

1632
01:32:18,000 --> 01:32:23,040
Speaker 1: identify those who have immunity to the COVID nineteen And

1633
01:32:23,200 --> 01:32:25,760
Speaker 1: just finally, when it comes to therapeutics, we are leaving

1634
01:32:25,800 --> 01:32:29,720
Speaker 1: no stone unturned in finding treatments for COVID nineteen. You

1635
01:32:29,840 --> 01:32:32,680
Speaker 1: do know that we don't have any approved currently therapeutics

1636
01:32:32,760 --> 01:32:35,559
Speaker 1: for COVID nineteen, but we are actively involved with both

1637
01:32:35,640 --> 01:32:39,439
Speaker 1: the academic and the commercial and private sector to find those.

1638
01:32:40,000 --> 01:32:42,840
Speaker 1: Seventy two trials of therapeutics are underway in the United

1639
01:32:42,880 --> 01:32:46,439
Speaker 1: States under FDA oversight, and two hundred and eleven are

1640
01:32:46,479 --> 01:32:49,000
Speaker 1: in the planning stages, so we expect to see more.

1641
01:32:49,080 --> 01:32:53,559
Speaker 1: This includes convalescent plasma as well as antiviral therapies. Work

1642
01:32:53,720 --> 01:32:56,840
Speaker 1: continues on vaccines and two firms have announced that the

1643
01:32:56,960 --> 01:32:59,840
Speaker 1: FDA has authorized their trials to go forward, one of

1644
01:33:00,000 --> 01:33:02,920
Speaker 1: which we've mentioned here before. And finally, in response to

1645
01:33:03,000 --> 01:33:05,120
Speaker 1: the Presidence and Test Force requests, we've stood up the

1646
01:33:05,160 --> 01:33:09,200
Speaker 1: coronavirus Treatment Acceleration Program. We are leaving no stone unturned,

1647
01:33:09,240 --> 01:33:10,920
Speaker 1: as I said, and we're working around the clock to

1648
01:33:11,000 --> 01:33:16,320
Speaker 1: develop these therapeutics for the American people. Thank you very much, doctor,

1649
01:33:17,160 --> 01:33:23,800
Speaker 1: about question, probably, and it's timely because just about an

1650
01:33:23,840 --> 01:33:28,040
Speaker 1: hour ago, a subcommittee with oversight release some findings that

1651
01:33:28,120 --> 01:33:32,120
Speaker 1: the FDA doesn't have any review of the antibody tests

1652
01:33:32,160 --> 01:33:35,160
Speaker 1: that are on the market. There are no guidelines to

1653
01:33:35,360 --> 01:33:37,720
Speaker 1: tell which one should be out there, and there's no

1654
01:33:37,880 --> 01:33:41,360
Speaker 1: way to test their accuracy. They're quite worried that these

1655
01:33:41,400 --> 01:33:45,639
Speaker 1: are jump tests on the market because they weren't reviewed

1656
01:33:45,800 --> 01:33:48,720
Speaker 1: before they were approved. Is that true? So under our

1657
01:33:48,800 --> 01:33:52,160
Speaker 1: policy and we provide a flexibility, what we've told manufacturers

1658
01:33:52,400 --> 01:33:54,880
Speaker 1: is that in order to market in the US they

1659
01:33:55,000 --> 01:33:57,880
Speaker 1: have to validate their tests. They have to tell us

1660
01:33:57,960 --> 01:34:00,920
Speaker 1: that they validated their tests, and then the package insert

1661
01:34:01,000 --> 01:34:03,920
Speaker 1: they have to let people know and users, labs, etc.

1662
01:34:04,640 --> 01:34:08,280
Speaker 1: That those tests were not authorized by FDA. We've authorized

1663
01:34:08,320 --> 01:34:11,679
Speaker 1: for as I mentioned more in the pipeline, and these

1664
01:34:11,760 --> 01:34:15,559
Speaker 1: tests that have come in without any information to us,

1665
01:34:15,680 --> 01:34:18,280
Speaker 1: but have been self validated. As I mentioned at the

1666
01:34:18,320 --> 01:34:20,240
Speaker 1: podium a couple of days ago, we are working with

1667
01:34:20,280 --> 01:34:23,479
Speaker 1: the National Cancer Institute as well as CDC to perform

1668
01:34:23,560 --> 01:34:26,240
Speaker 1: our own validation of the tests that have been sent

1669
01:34:26,320 --> 01:34:28,560
Speaker 1: to us. So we'll provide as much information as we

1670
01:34:28,680 --> 01:34:32,120
Speaker 1: possibly can, and there is transparency on our website about

1671
01:34:32,160 --> 01:34:35,360
Speaker 1: those tests and also the tests that we have authorized.

1672
01:34:35,560 --> 01:34:46,920
Speaker 1: Thank you, as President. From early in this effort, President

1673
01:34:46,960 --> 01:34:50,720
Speaker 1: Trump is called forth a whole of government response to

1674
01:34:50,840 --> 01:34:54,759
Speaker 1: the coronavirus epidemic in America, and by that the President

1675
01:34:54,880 --> 01:34:56,920
Speaker 1: made clear when he asked me to lead the White

1676
01:34:56,920 --> 01:35:00,600
Speaker 1: House Coronavirus Task Force, not merely a whole of the

1677
01:35:00,680 --> 01:35:04,200
Speaker 1: federal government, but a full partnership with state and local

1678
01:35:04,280 --> 01:35:08,040
Speaker 1: governments across the country, and today we renewed that with

1679
01:35:08,280 --> 01:35:14,200
Speaker 1: our latest conference call with governors all across America. We've

1680
01:35:14,280 --> 01:35:17,160
Speaker 1: met with them today specifically to speak about the progress

1681
01:35:17,320 --> 01:35:21,120
Speaker 1: that our governors are making expanding testing across the country,

1682
01:35:21,400 --> 01:35:25,160
Speaker 1: and we were pleased to hear about extraordinary and rapid

1683
01:35:25,880 --> 01:35:30,400
Speaker 1: progress that governors are making. At the outset of the call,

1684
01:35:30,479 --> 01:35:32,559
Speaker 1: where we had more than fifty of our nation's governors,

1685
01:35:32,560 --> 01:35:36,679
Speaker 1: we of course had Pete Gainer of FEMA report on progress.

1686
01:35:36,800 --> 01:35:39,360
Speaker 1: More than thirty five thousand National guards stood up five

1687
01:35:39,439 --> 01:35:44,160
Speaker 1: thousand active duty military deployed in ten states, and we

1688
01:35:44,280 --> 01:35:48,400
Speaker 1: were also pleased to report that FEMA, HHS and the

1689
01:35:48,479 --> 01:35:53,000
Speaker 1: private sector have coordinated the delivery of shipments to states

1690
01:35:53,080 --> 01:35:56,759
Speaker 1: around the country, including nearly sixty seven million and ninety

1691
01:35:56,800 --> 01:36:03,280
Speaker 1: five masks, one hundred and five million surgical masks, surgical gowns, shields, gloves,

1692
01:36:03,360 --> 01:36:06,639
Speaker 1: more than ten thousand ventilators, and more than eight thousand

1693
01:36:07,600 --> 01:36:12,280
Speaker 1: federal field medical station beds. Beyond the report that we

1694
01:36:12,400 --> 01:36:15,800
Speaker 1: provided to the governors, we assured them that at the

1695
01:36:15,880 --> 01:36:21,360
Speaker 1: President's direction, this is one team, one mission, and we've

1696
01:36:21,560 --> 01:36:24,160
Speaker 1: made it clear to the governors that we know we're

1697
01:36:24,200 --> 01:36:27,439
Speaker 1: all in this together, and the partnership that we have

1698
01:36:27,640 --> 01:36:32,479
Speaker 1: foraged together really begins with mitigation efforts. It moves to

1699
01:36:32,680 --> 01:36:35,160
Speaker 1: making sure our healthcare workers have to support they need,

1700
01:36:35,280 --> 01:36:38,080
Speaker 1: but also testing is in the forefront of all of

1701
01:36:38,120 --> 01:36:41,400
Speaker 1: our minds. We're working to make it possible for every

1702
01:36:41,520 --> 01:36:45,280
Speaker 1: governor to access the existing capacity to enable our states

1703
01:36:45,320 --> 01:36:49,280
Speaker 1: to be able to reopen responsibly under the phased approach

1704
01:36:49,360 --> 01:36:52,600
Speaker 1: that the President unveiled one week ago. A little bit

1705
01:36:52,640 --> 01:36:57,320
Speaker 1: of context, you may recall that one month ago all

1706
01:36:57,439 --> 01:36:59,800
Speaker 1: of the testing that have been done in America, eighty

1707
01:36:59,840 --> 01:37:03,280
Speaker 1: thousand Americans had been tested, but as of this morning,

1708
01:37:03,400 --> 01:37:07,720
Speaker 1: five point one million Americans have been tested for the coronavirus.

1709
01:37:08,400 --> 01:37:11,920
Speaker 1: A quick reminder to our fellow Americans, and this was

1710
01:37:12,000 --> 01:37:14,560
Speaker 1: something from our scientists today at the Task Force. We

1711
01:37:14,680 --> 01:37:19,120
Speaker 1: reminded governors of this as well that as testing increases

1712
01:37:19,240 --> 01:37:25,600
Speaker 1: dramatically across the country, cases will increase as well, but

1713
01:37:26,160 --> 01:37:30,840
Speaker 1: people should not be discouraged by those numbers. We are

1714
01:37:30,920 --> 01:37:37,559
Speaker 1: looking at very positive trends in hospitalization in emergency room entrances,

1715
01:37:37,960 --> 01:37:40,040
Speaker 1: and we continue to see as we've said at this

1716
01:37:40,160 --> 01:37:44,200
Speaker 1: podium every day over the last several weeks, we continue

1717
01:37:44,240 --> 01:37:46,920
Speaker 1: to see positive progress, not just on the West Coast,

1718
01:37:47,360 --> 01:37:51,640
Speaker 1: but even where the coronavirus epidemic has most deeply impacted,

1719
01:37:52,120 --> 01:37:55,839
Speaker 1: in areas of the Greater New York City area, New Orleans, Detroit,

1720
01:37:56,439 --> 01:37:59,799
Speaker 1: and elsewhere. On our nearly two hour phone call today

1721
01:38:00,120 --> 01:38:03,439
Speaker 1: with those governors, we heard of the progress governors were

1722
01:38:03,479 --> 01:38:07,479
Speaker 1: making in implementing the resources that we've been working to

1723
01:38:07,560 --> 01:38:10,439
Speaker 1: provide them, not just the medical equipment, but also as

1724
01:38:10,520 --> 01:38:14,160
Speaker 1: you recall that map a week ago that showed where

1725
01:38:14,240 --> 01:38:17,360
Speaker 1: all of the equipment is all across the country in

1726
01:38:17,439 --> 01:38:21,400
Speaker 1: all fifty states. Governor Cuomo joined us for the call today.

1727
01:38:21,439 --> 01:38:23,880
Speaker 1: He spoke favorably of his meeting here at the White House,

1728
01:38:23,920 --> 01:38:28,680
Speaker 1: mister President, and his recognition that testing is a partnership

1729
01:38:29,560 --> 01:38:34,320
Speaker 1: between the federal and state governments. As Governor Cuomo said

1730
01:38:34,360 --> 01:38:37,200
Speaker 1: today that he understood that the federal government works with

1731
01:38:37,360 --> 01:38:41,040
Speaker 1: national manufacturing and supply chain and the governors deal with

1732
01:38:41,200 --> 01:38:45,559
Speaker 1: the labs to expand and implement testing at the state level.

1733
01:38:46,320 --> 01:38:49,919
Speaker 1: Governor Cuomo also explained how he's using his licensing authority

1734
01:38:50,000 --> 01:38:52,720
Speaker 1: as a governor to stand up the more than three

1735
01:38:52,840 --> 01:38:55,639
Speaker 1: hundred labs that can do coronavirus testing in the state

1736
01:38:56,439 --> 01:38:59,639
Speaker 1: of New York, and we congratulated him for his leadership

1737
01:38:59,720 --> 01:39:03,839
Speaker 1: in urged other governors to use their authority. Similarly, in Tennessee,

1738
01:39:03,960 --> 01:39:06,160
Speaker 1: Governor Bill Lee told us that he's deployed the National

1739
01:39:06,240 --> 01:39:10,000
Speaker 1: Guard to stand up more than twenty drive through test sites.

1740
01:39:10,080 --> 01:39:13,679
Speaker 1: They're testing ten thousand people a day. Have already tested

1741
01:39:13,720 --> 01:39:16,560
Speaker 1: more than one hundred and thirty thousand people in Tennessee,

1742
01:39:16,640 --> 01:39:19,840
Speaker 1: and they expect to surge another fifteen thousand people in

1743
01:39:19,960 --> 01:39:24,240
Speaker 1: testing sites this weekend. In Tennessee, Massachusetts, and Ay, we're

1744
01:39:24,280 --> 01:39:29,000
Speaker 1: continuing to watch very closely as cases have not yet stabilized.

1745
01:39:29,040 --> 01:39:32,759
Speaker 1: And Governor Charlie Baker, after he thanked US Mister President

1746
01:39:32,840 --> 01:39:35,879
Speaker 1: for the Army Corps of Engineers deployment of four field hospitals,

1747
01:39:36,640 --> 01:39:39,000
Speaker 1: he described how they have rapidly expanded