episodes/(2023-12-01) Ep 246.1 - Interview w Jessica Hockett (Wood House 76) on 2020 New York City health data (and more)/(2023-12-01) Ep 246.1 - Interview w Jessica Hockett (Wood House 76) on 2020 New York City health data (and more).vtt

WEBVTT

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Hello, it is two oh six to now two oh seven p.m. Eastern standard time on Thursday November 30th year two thousand and twenty three

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This is episode

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731 a fusatonic live not including the shorts of course and today we are

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Lest and with the opportunity to have a discussion with a Jessica Hockett who I've been introduced to on Twitter

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This is her Twitter account. It's wood house

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76 and you see the

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Underscore between wood underscore house 76

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She is a

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Bicentennial baby as her profile says please reach out and follow her on Twitter

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The other way that you can follow her amazing work is on sub stack and she was smart enough to go out and get the wood house

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76.com domain so you don't have to worry about remembering the specific username on

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Substack it will just link directly to there and should something ever happen in the future of where she needs to change

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Where her blog posts are being written she can always then redirect the URL

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So with that said welcome to the show Jessica

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I'm just reading your the profile that you have a grown-up bicentennial baby writing from a wood house

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And I think that's a reference to hunger games. Do I have that right or is that another?

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So my original

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COVID focused Twitter account was an eponym

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Emma wood house and that is the titular character of Jane Austen's

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Emma

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Which is one of my favorite books and I'm a huge Jane Austen fan Jane Austen's my daughter's middle name actually

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So yeah, I use I used that name after I had

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Deactivated my other Twitter account under my name that it was for a different purpose

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But then when COVID madness came down

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I and my kids came came home from school and they were locked out of school

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I had I deleted that account and wasn't gonna do Twitter anymore and then I

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Mean as you know as we all know things were not adding up with COVID at all

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I'm like I got to go back on Twitter because that's where people tend to know what's up

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So there are where those people tend to be so I didn't want people to find me under my real name

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Like in my other account. So that's why I created an eponym. I never I never aimed to amass like

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53,000 followers or whatever it is that it has right now

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But I went ahead earlier this year and changed it to my my real name

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It wasn't really a secret who I was anyway

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I was sometimes on Chicago radio and they would say Emma Woodhouse, you know Jessica Hockett aka Emma Woodhouse

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So I didn't really have a hidden identity. I just I more had a a pen name is what I would say

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So yeah, that's that's what I do live in a woodhouse

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It's a cedar shingled house. So that it goes it goes with that as well. So it's sort of a throwback to the old

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Pen name, right, but it makes sense with where I live. So

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Just a curiosity were you in the and I don't mean business in terms of

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Getting rich because none of us is doing this to get rich, but were you in the business of blogging before?

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COVID-19

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No, no, not at all

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So my background is in a K-12 education years ago

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I started out as a K-12 as a middle school teacher for five years

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and then I went to University of Connecticut and then University of Virginia is where my PhD is from my background my

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specialty was gifted education and

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I was gonna go into academia

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I actually was hired for a ten-year track position

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I accepted it and then I turned it down two weeks later. That was one of the best decisions

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I've ever made in my life. I just felt like the weight of all the the rules and expectations of

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Academia, I'm like I can't I can't do it. I can't do it

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I just want to do what I want to do and that's what I ended up doing for a while 15 plus years

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I did a lot of consulting work in K-12 education did a lot of teaching of teachers

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I had certain specialties and I mean still do really within education did a lot of traveling worked with state agencies did some program evaluation

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Wrote some books. So so yeah, that's what I did for a while until March March 2020 when you know when everything went crazy and shut down

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So no, so no, I wasn't doing that that I was I've always been a writer

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Okay, you know art of books and things like that, but not not a not a blogger

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University Connecticut, I went to University Connecticut if you knew that or not. Yeah. Yeah, my degree in computer

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Engineering and I don't even remember what you're graduated 96. I think it was 96

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So okay. Yeah, I wasn't a graduate like a summer an interesting

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Graduate program called three summers and so and I was when I was still a classroom teacher

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So I would go in the summer and for like an intensive with another like a cohort of people and then during the

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Year, it was actually at the beginning of online learning. I and I was really a fan of online learning back in the day. I also taught

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Graduate courses for University of Virginia online graduate courses

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My view of online learning has changed a little bit since they tried to foist it all on to you know K-12 kids

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But in the graduate space it was great

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Dedicated people offered that that flexibility, but yeah

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I was physically on campus at at UConn and stores and those those were magical times

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I really enjoyed it really enjoyed it. So yeah, I didn't know we had that connection. That's cool

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What what just out of curiosity what pulled you to University Connecticut?

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I know different schools have

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Expertise like they have a supposedly a very strong agricultural school which I was there something about their their K through 12

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Or their special education program. That's right. And so my my field was gifted education

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So University of Connecticut University of Virginia

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College of William and Mary those are just a few of the the universities that have

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You know the the big names in the small field. It's fantastic

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It was a great great time in my life for sure and then went from there to

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University of Virginia

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So I left my my full-time teaching job

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This was before my husband. I had kids who've been married 25 years, but we moved from the Chicago area to

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Charlottesville for Virginia

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And so I did my my program there for a couple years and then we moved back

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Charlottesville Virginia, that's not really a big city is it?

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No, and there's a lot that I really appreciated about Charlottesville

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But it's funny to think back on now because we used to go drive up to DC all the time

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Because we're city people really at at heart. So we're like, oh my gosh. There's nothing going on here. Things are closed on on Mondays

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So but I but I enjoyed it the whole the Jeffersonian vibe all of that the history you you can't you can't beat it

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But we we were we were never planning to stay there long-term just because it was more rural in our in our view

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But yeah, I really benefited from that from that program really appreciated it

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You didn't happen to pump into David Martin while you were there. Did you because no, it's funny though

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Right all these people that that later later come up. Although I will say and I don't know what David Martin's background is

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is fully but University of Virginia is

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Along with Yale well known for secret societies and and things like that

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So it would not surprise me if David Martin was part of the seven society or the z society or any number that we're crawling about on campus

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See he seems like that sort of character, but I but I really don't know. I'm making I'm making this up

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You know, we've looked into it a little bit

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There's like this Charlottesville business council and it's just one of those areas where

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There's there's multiple people have congregated with respect to the topic of patents and intellectual property

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And I don't know

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I mean, I'm sure it's a beautiful town but

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Usually there's something else something else that anchors these particular things to one area

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So yeah, we my husband I used to joke that it seemed like charlotte's phil was where like young rich people go to retire

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It so it had that sort of a vibe. There's a very clubby kind of old money south vibe

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And I I just realized recently Robert Malone has not really ever been on my radar

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I've always sort of seen him as a 1980s like soap opera star or something

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I just haven't paid much attention to him

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but

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Recently I was like oh wait this horse farm thing. It's in Madison, Virginia. I know I know where that is

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So I I find that that interesting. Yeah, nothing to really say about that

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Just that you know duly noted

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South of charlotte's phil for several years before buying the the horse farm

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I think and there's there's a lot of horses on that farm. So so let's get down the business

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So the one thing the one look there's many topics that you've covered related to the pandemic

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There's one thing in particular though. Everyone's got there one area of of focus where they're just and

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You're at the lead as far as I'm concerned regarding this

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Uh, it is a casualty data mass casualty data in the year 2020 and in particularly you've done extensive work on New York City

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Um, and there's just no one else that has even come close to doing the you know

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The research that you have on that

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But I would love if you could just walk us through your little journey

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Because I'm always encouraging people don't think that just because someone isn't questioning narratives now that they can't in the future

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Right. So you're mining your own business

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It's uh, January February

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You couldn't miss the news reports about what was coming what everyone seemed to expect in the media

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What was that first year like of something's not quite right? And then you you turned around and it actually started to invest your time into research

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And what led you to?

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Focusing on New York City. Please share that journey

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Great great question

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I mean, January, February 2020 with these reports that were coming out of china and then the diamond princess cruise ship

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Um, I just remember people women in my bible study

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Honestly talking about this and a few of them being concerned and some of them are sort of prone to worrying about things like this

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Anyway, right and I was sort of known for not being like that as you might imagine

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So, oh, what's going on in china people falling down on the streets? Oh this cruise ship. I'm like

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That this is nothing like and like it's china like who knows what who knows what's going on there

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And I looked into the cruise ship a little bit like

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There's old people on cruise ships like they they die. I mean what what is the big what is the big deal with this?

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I just I just thought it was a nothing burger

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And then in march as the tension started to build

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And especially when you know the 15 days to slow the spread

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I was like what the heck is going on here a huge alarm for me

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Was when you know the governor governor jb pritzker went up from you know the pritzker family one of the richest families in the world

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um when he

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ordered churches to close

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I was like what wait what what like it and churches were doing it

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And I was questioning my christian friends and like this this doesn't seem constitutional to me

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This seems completely out of out of line

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um

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And I got a lot of pushback honestly from from christian christian friends. It's only two weeks

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It's you know, it's an emergency. We just don't know

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Um, he's not only shutting down churches

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And I thought well, yeah, he's also shutting down restaurants and my husband's in the restaurant industry

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But target is staying open. So I mean so for I can honestly say even though

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I did I thought there might be a new virus something spreading around

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I was skeptical from the very beginning and in cook county where I was living at where we were living in the time and had been

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So that's you know, chicago. We were in evanston where north western is

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Every death that goes through the medical examiner

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Is public and at the time then included deaths that were determined to be from this novel virus

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So I was every day looking at line by line by line. I'm like, okay

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85-year-old person who has coronary heart disease diabetes kidney failure

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Dies, okay, so I I was going through that we had 12

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Long-term care facilities in evanston alone

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So the local paper was tracking those and I tried I remember this so vividly

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I tried to get a local reporter to kind of look at some things. He called me a covid denier

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He canceled my subscription to his online message message board

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Um, I emailed my mayor mayor of evanston put put out a mask mandate mid april

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I'm still still have the email. I responded right away. I was basically like, what are you doing?

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This is you know, this is ridiculous. This doesn't make any this doesn't make any sense at all

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So the questioning I can honestly say that I was doing that from the very beginning got back on twitter in may 2020

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Started that account. I'm just trying to find out like, okay, is anybody else really questioning this because even though there was a lot

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You probably remember this there was some rah-rah energy at the beginning right like the first two weeks

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Maybe even the first month we had Broadway performers on tv and on the internet being like yay

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You know stay home save lives there there was some positive energy in those days

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Which I think is part of the propaganda and it's it's really dark and scary to look back on it now

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But you know then as this starts dragging on it's like what is really happening here

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And with new york in in particular I try to remind people about this all the time

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New york was part of really the justification for locking down

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the specter of

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Look at what's happening in new york. The hospitals are overrun

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Look, they're calling in the travel cadre of nurses and doctors and we don't want to be in new york

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Without new york

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I would say americans would never have agreed that there was an emergency or or something actually

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going on

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So new york is kind of burned in my brain as a key part for getting the us on

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On board. Um, I would say and and it'll be I can walk the sequence back

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But new york was like the linchpin and then that was it

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That that that was it and I don't know when maybe my first tweets about it were but I know for sure in 2021

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That I was asking like because the more the data was out right more of the finalized death data

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And I mean, I I asked pretty consistently within a dm group

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I was in at the time and then on twitter itself, but what the heck happened here

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This makes no sense and I could never really get a lot of traction around it

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It was sort of like well vent ventilators, right or or they messed up or the nursing home policy

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Like there were a lot of pat answers around it some of which I agreed with

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Initially, especially with the nursing home policy, which I now realize is not really part of the picture

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Um, so yeah, I just I kept pursuing that that and the alleged disappearance of flu

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Uh, which I I now realize are related, but those were two things that always bothered me

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But I was also fighting mandates at the time

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And my kids were home and I pulled them out in my homeschooled them and there was all of that going on

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So as you remember like when you're when you're actually fighting what's going on day-to-day

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And I'm getting kicked out of the grocery store

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You know police came and like, you know, basically threatened to arrest me denied my grocery purchase

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Like when that stuff is going on

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You can't attend to every every little data issue that that you that you have

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Especially when your homeschooling is as well. So it when I was kicked off of twitter more more permanently in july 2022

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That is when I was like, okay now now I now I have some more time to delve more

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Specifically into this new york event. I can and I already had been submitting public records requests for data

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But now I couldn't could do that more intensely with some other consulting work that I was doing

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So that that's when I really dove in and that may now it's been well over a year of of that

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Um, but yet I I I like doing it

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I like like doing it, but there's there's still a long way to go

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There's still a long way to go. The more I find the more questions I have and the more bizarre

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Whatever app actually happened there becomes

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So it was something about in the area of chicago. You were looking at specific deaths or records

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uh, the profiles of them and that was a good match for the type of

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skepticism and

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Critical approach that was required to go back to new york city

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Now having the perspective that it was such a big part of the narrative and I think you frequently

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Remind the audience that new york city is I think 7.8 million

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People and new york city proper and then the metropolitan area of new york city. I think it's around 15 or 18 million

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Uh and us is 330 million people

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Right. Yeah, it depends on population numbers you look at for the five boroughs

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Actually, the the cdc numbers and the city of new york numbers are not the same. I think there's some shenanigans there

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But it's between the five boroughs proper is eight between 8.3 and 8.8 million

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The 20 the 2020 population and yes, if you're talking about greater

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Metro, it's bigger than that

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But in spring 2020 for that what I would call 11 week of event from mid-march 2020 to the end

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May 2020

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The new new york city

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proper is 19 percent

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of the total covid deaths in the us

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And what do I mean by covid death? I mean we could go into that at length, but for data purposes

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It's the deaths that attribute covid 19

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as underlying cause

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So 19 percent of the deaths that do that in the us in that period in that along with period are in new york city

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Even though new york city only comprises less than 3 percent of the total population

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Does anyone have questions about that?

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I do just a curiosity

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How would you describe the profile of of of deaths related to covid in new york city met the entire metropolitan area

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Have you noticed like a major drop-off as soon as you cross the hudson river like people just stop dying in jersey city in new work

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or

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That those areas have higher high rates of death also

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They did too. They did too. I mean I can pull it up if you want to it's it's really interesting to look at county

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Level each burrow is a county and york's kind of weird like that

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But then you look at the other counties and then if you sort the counties in that

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Period it's it's new york new jersey cook county

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Is is up there um detroit is up there

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You know relatively relatively speaking

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But by and large, I think the metro area if i'm not mistaken that that tri-state area is about 50 to 55

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Of the total covid attributed deaths in the whole country

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Connecticut which is only 3 million people

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Right on a good day

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So I mean again, it's it's kind of by different counties in there

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So I I like to think in terms of like like city so new york city, new york city metro area

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Boston metro area, chicago metro detroit

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New Orleans right those those were the key

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locations that saw the most increase but nobody saw what what the new york city new york city metro is

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I mean five five burrows alone. I mean we we see a six to seven hundred percent

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Increase in all cause mortality in a matter of a few weeks

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It's not an event that's indicative of viral spread

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Let me let me put it that way. It's not it. It's not anything like a disease spread event

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It's it's like you would see with a bomb or with um multiple like an earthquake and aftershocks

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Afterwards the the mortality equivalent of 10

20:51.060 --> 20:54.500
9-11 events, you know, whatever you think about 9-11

20:54.900 --> 20:58.740
You know, if whatever they said the mortality was about 10 times that

20:59.380 --> 21:00.180
um

21:00.180 --> 21:02.180
And and nobody seems to have any

21:02.420 --> 21:06.100
Questions about it. There's no real investigation about it

21:06.660 --> 21:08.660
Nobody's asking if

21:08.660 --> 21:15.380
This event really occurred in the way that it's claimed in some ways. I find the silence

21:16.260 --> 21:19.140
More disturbing than the actual

21:20.020 --> 21:23.860
Casualties as they're depicted on paper so to speak

21:25.460 --> 21:27.460
So what we see here

21:27.460 --> 21:32.020
So what we see here is I'm associated with a group called international group called panda

21:32.900 --> 21:38.500
Introduce a plenary group of people from different places in the world. That's uh chaired by nip hudson

21:38.980 --> 21:41.940
And we recently put out on multiple

21:42.900 --> 21:46.100
Candles the panda website and then the panda sub stack included

21:46.580 --> 21:50.980
This um this article does new york city 2020 make any sense and it's eight

21:51.060 --> 21:55.380
We spelled out eight reasons to doubt the official data. Now these aren't the only reasons

21:55.700 --> 22:01.140
These are just some eight uh some reasons that sort of lay the foundation for it and the first

22:01.540 --> 22:06.820
Uh graph. So I think this is what you're referring to is uh daily daily

22:07.220 --> 22:10.100
I know it it's it's just absurd

22:10.660 --> 22:14.980
But this is daily deaths from the beginning of 2019

22:15.780 --> 22:18.260
All the way to the end of 2020

22:18.660 --> 22:25.780
Uh just a reminder that death is a daily event right your your death when you die when I die will be recorded as occurring on a day

22:26.580 --> 22:31.780
In a particular location in a particular setting and there will be some causes listed

22:32.100 --> 22:36.260
Uh by a medical examiner or by a doctor or whomever and the dates down below

22:36.500 --> 22:41.460
Uh on the x-axis those are looks like one week apart. So those are weeks

22:41.940 --> 22:47.380
No, they're not this is daily data. It's just that to make the the font a reasonable size

22:47.460 --> 22:53.060
You necessarily kind of cut out some days, but this is daily dates each of these points is daily

22:53.620 --> 22:57.620
So, you know, what something I point out to people is we see

22:58.500 --> 23:03.860
Uh, and I've looked at this data in about a trillion different ways different slices, uh age group

23:04.500 --> 23:06.900
Uh setting of death cause of death

23:07.620 --> 23:11.460
We see basically the claim that nothing is going on

23:12.420 --> 23:14.100
Mortality wise

23:14.100 --> 23:15.780
No, nothing

23:15.780 --> 23:17.140
nothing

23:17.140 --> 23:22.500
And then at around uh on the 18th or so, which is a couple days after

23:22.900 --> 23:28.020
15 days to slow the spread was announced. Oh my gosh. Why did I just get balloons?

23:28.020 --> 23:30.260
Did you see the balloons on my screen? Anyway, I did

23:31.380 --> 23:31.700
I

23:31.700 --> 23:34.340
I was celebrating 15 days to slow the spread

23:34.820 --> 23:36.980
15 days to slow the spread

23:37.940 --> 23:42.020
That didn't happen again. That was fascinating. It's the fbi watching

23:42.580 --> 23:43.540
um

23:43.540 --> 23:45.860
I'm just kidding. So we see that

23:46.900 --> 23:50.020
Massive, I mean just the speed of this

23:50.500 --> 23:51.700
alone

23:51.700 --> 23:54.580
Is I realized a huge red flag

23:55.220 --> 23:57.140
Huge red flag

23:57.140 --> 23:59.060
based to peak here about

23:59.700 --> 24:03.460
21 days ish if i'm not mistaken, maybe 22 days

24:03.940 --> 24:05.460
go from about

24:05.460 --> 24:07.460
120

24:08.260 --> 24:15.860
150 ish deaths a day to this is 1200 deaths in a single day

24:17.060 --> 24:21.060
So the the sense of scale here, I think is something that people still don't grasp

24:21.060 --> 24:25.460
They think well, there's 8.5 million people that live in New York city

24:26.180 --> 24:28.740
Sure, you know a lot of people died

24:28.820 --> 24:33.700
But you have to think about the baseline or the claim to baseline anyway

24:34.260 --> 24:38.580
That you know really we don't have a thousand people a day dying in New York city

24:39.620 --> 24:44.420
We have fewer than 200 people a day dying in New York city

24:44.980 --> 24:47.620
And then we're being asked to believe that

24:48.340 --> 24:49.700
There was no

24:49.700 --> 24:54.980
Signal whatsoever in all cause mortality and this is true in New York city, but everywhere

24:54.980 --> 24:57.380
There's no signal of this super spreading

24:59.380 --> 25:05.220
Deadly or risk additive pathogen in the data until after

25:06.100 --> 25:10.340
mass testing in hospitals has commenced and

25:11.220 --> 25:17.460
The government has given this pathogen permission to show up apparently i mean being facetious

25:17.540 --> 25:23.620
But permission to show up in all cause mortality and then we see it literally go off like a bomb

25:24.580 --> 25:26.580
in New York city like

25:26.820 --> 25:29.300
Nearly no place else in the world except

25:30.420 --> 25:35.300
Northern some select provinces in northern, Italy a couple weeks before

25:35.940 --> 25:40.820
Their their events started first. They also started testing in their hospitals first

25:41.460 --> 25:47.460
So we have northern Italy and New York and then nobody else ever comes close to this scale

25:48.500 --> 25:49.860
again

25:49.860 --> 25:51.700
Or the speed

25:51.700 --> 25:52.820
again

25:52.820 --> 25:54.820
These are New York city

25:55.460 --> 25:56.740
death

25:56.740 --> 25:57.940
Certificates like

25:57.940 --> 25:59.940
Where does one get this number?

26:00.100 --> 26:02.420
Great great question. So this particular data

26:02.740 --> 26:03.460
I

26:03.460 --> 26:10.580
Requested via foya from the New York city department of health and mental hygiene their bureau vital statistics produces

26:11.060 --> 26:14.740
Reports for each year the 2020 report came out

26:15.460 --> 26:18.100
In april 2023 so a little bit delayed

26:18.820 --> 26:23.300
And so I requested this this data from them so they send me

26:24.260 --> 26:25.620
Frequencies

26:25.620 --> 26:32.100
So they sent me the date and just a simple excel spreadsheet the date and then the number of deaths

26:32.900 --> 26:33.780
that

26:33.780 --> 26:35.380
They are claiming

26:35.380 --> 26:38.500
I mean you have you have to think of it this way what what what they're saying is

26:39.300 --> 26:46.740
On this day we had 125 deaths and there are 125 death certificates that

26:48.020 --> 26:51.860
We could show we're not going to because they're not subject to foil

26:51.860 --> 26:55.300
But we could show or should be able to show that

26:55.940 --> 26:58.500
125 people in the city died on that day

26:59.700 --> 27:04.980
So this graph and this is something I've I've said to deni rank or actually in others

27:05.460 --> 27:09.620
Is that these are not records that this is not proof

27:10.660 --> 27:12.660
It's a representation

27:13.140 --> 27:18.740
Of records that are claimed to exist, but it's not the records themselves

27:19.220 --> 27:26.020
But this is day of occurrence not day of report or day of processing. It's day of occurrence

27:26.980 --> 27:33.300
So something that I am my colleagues have said is that we doubt or we question

27:34.420 --> 27:37.300
If this event actually occurred

27:38.020 --> 27:43.220
In the way that is that it's claimed did the number of people that are claimed to have died

27:43.780 --> 27:45.940
on each day

27:45.940 --> 27:50.900
In the settings that they're claimed to have died. So by setting, I mean hospital nursing home

27:51.540 --> 27:58.820
Personal home hospital facility that data is elsewhere in the article, but did this happen in real time

27:59.380 --> 28:00.740
and

28:00.740 --> 28:02.180
We doubt it

28:02.180 --> 28:04.580
We doubt it. We're not going to say absolutely that it didn't

28:05.140 --> 28:09.300
But we have many reasons why we doubt that this occurred

28:10.100 --> 28:14.100
weren't newspapers reporting those numbers on a

28:14.740 --> 28:15.940
day-to-day basis

28:15.940 --> 28:20.740
Like if you went through the the daily news in New York times, would you find like on a Tuesday?

28:20.740 --> 28:25.700
Wednesday thursday section like the updated number and it's somewhat correlating to that

28:25.780 --> 28:30.740
Or these numbers come out like sort of after this mass casualty event

28:30.900 --> 28:35.300
Well, it's it's interesting because the data that was being reported at the time

28:35.300 --> 28:38.500
And this is true actually all across the us whether you're looking at the

28:39.140 --> 28:41.300
Johns Hopkins dashboard

28:41.300 --> 28:47.540
Right or the reports coming out of your state health department that were being announced in press conferences every day

28:48.180 --> 28:51.860
Those numbers were not day of death. They were day of report

28:52.340 --> 28:59.140
So if you go back and you start to look through the New York times, you know, they're they're reporting numbers every day

28:59.700 --> 29:06.260
Something interesting that happened on april 14th 2020 is they started adding in

29:07.220 --> 29:09.220
probable covet deaths

29:10.020 --> 29:10.820
And

29:10.820 --> 29:17.460
They added I think on that day about 3,700 deaths that they said were like probable covet deaths

29:18.100 --> 29:24.420
And then between that day and I think june first they added I think 4,500 or so total

29:25.060 --> 29:26.660
4,700 of these

29:26.660 --> 29:30.980
Probable covet deaths to the toll so there was kind of a massive sudden dump

29:31.540 --> 29:32.900
In that time

29:32.900 --> 29:37.780
But but something that's really important I think to realize a a colleague in panda brought this up once that

29:38.260 --> 29:39.860
This idea

29:39.860 --> 29:43.540
for this phenomenon of real-time death reporting

29:44.180 --> 29:50.980
Is is sort of ridiculous if you if you think about it. We we we should not expect

29:52.020 --> 29:54.740
That deaths that occur each day

29:55.620 --> 29:59.220
Would or should be reported in real in real time

29:59.300 --> 30:03.300
And so we have to ask ourselves like where were these numbers?

30:04.020 --> 30:05.540
coming from

30:05.540 --> 30:10.260
A lot of them were at the time and andro quomo even said this in later april

30:10.580 --> 30:15.380
They were maybe it was earlier april that he said this but they were getting some direct

30:16.100 --> 30:18.100
reporting from hospitals

30:18.900 --> 30:21.140
directly into the

30:21.140 --> 30:22.420
health department

30:22.420 --> 30:30.260
So a lot of what people were hearing was what was ostensibly being reported from hospitals, but not other places of death

30:31.220 --> 30:37.780
But again, I don't know that the speed of the reporting in that time necessarily

30:38.500 --> 30:40.500
matches

30:40.500 --> 30:41.700
reality

30:41.700 --> 30:43.700
you can imagine maybe

30:43.940 --> 30:46.020
projections

30:46.020 --> 30:47.540
and models

30:47.540 --> 30:51.220
You know that we were being fed at that time maybe getting out of hand

30:52.180 --> 30:54.020
a little bit

30:54.020 --> 30:59.860
Right and maybe so some people have theorized that this is actually what we're seeing on this graph is like

31:00.580 --> 31:03.300
Almost a model and they messed they messed up

31:04.020 --> 31:06.820
and then maybe they had to pull deaths from the past

31:07.700 --> 31:09.060
and from

31:09.060 --> 31:10.820
the future

31:10.820 --> 31:17.620
Because the the other thing we see with this curve as shocking if not more shocking than this dramatic

31:18.340 --> 31:20.500
You know almost like finger pointing up to god

31:21.220 --> 31:22.820
um

31:22.820 --> 31:28.500
Maybe maybe there's something prophetic there. It doesn't level off. It just goes up and then it immediately goes

31:29.380 --> 31:32.100
It goes down and it drops to baseline

31:32.660 --> 31:37.380
Even below baseline a little bit, but it does kind of depend what slice of the data

31:37.380 --> 31:41.300
You're looking at but just daily all cause drops back down

31:41.940 --> 31:43.940
and never even creeps up again

31:44.820 --> 31:45.940
until

31:45.940 --> 31:48.020
the normal respiratory illness

31:48.660 --> 31:51.940
Season it's also very smooth curve. I mean it just

31:52.740 --> 31:54.900
You would you would expect maybe some days

31:55.780 --> 31:59.460
If everything is genuine to be high and then the next day

32:00.260 --> 32:02.420
Maybe for whatever reason it goes down

32:02.820 --> 32:05.940
20% and then up because you could see normally

32:06.820 --> 32:11.140
Uh, there could be an increase or a decrease of from day to day 40 50

32:11.700 --> 32:15.300
And that wouldn't be unusual. Maybe one day there's

32:16.580 --> 32:18.580
240 deaths on

32:18.900 --> 32:22.260
If you look at it before April the next day, maybe there's 120

32:22.660 --> 32:27.140
So it's but the average is definitely around 180 or so. It looks like

32:27.700 --> 32:28.580
It is noisy

32:28.580 --> 32:34.900
I mean if you if you take out this curve if you take out this spike you would see the noise that you're talking about right random

32:35.060 --> 32:36.740
variation just

32:36.740 --> 32:42.740
You know like up and up and down up and down what I think we see here is what I would call a fauci and fantasy

32:43.700 --> 32:50.980
I mean it's actually the peak is actually double if you adjust for population in 1918 that this is actually double

32:51.620 --> 32:55.540
What's claimed to have occurred in New York City in october 1918

32:56.500 --> 32:57.460
which

32:57.460 --> 32:59.460
That that's a heck of a claim

32:59.460 --> 33:03.700
Um, and we could you know talk sometime about 1918 right and there's reasons to

33:04.340 --> 33:08.980
Kind of question what the factors were back then as well, but but this is double the rate

33:09.940 --> 33:16.660
Of october 1918 when you look at new york versus new york new york 1918 versus new york 2020

33:16.660 --> 33:18.020
So that alone

33:18.020 --> 33:21.460
But but also I think if you would ask people

33:22.260 --> 33:28.580
Without showing this graph like what they would expect to see with something that is purported to be spreading

33:29.460 --> 33:31.460
And that can kill a lot of people

33:32.020 --> 33:34.900
You would expect something more gradual here

33:35.780 --> 33:37.220
in in my opinion

33:37.220 --> 33:44.020
You would expect to see signs of it somewhere, but for some reason people are okay with this idea

33:44.820 --> 33:45.620
of

33:45.620 --> 33:49.620
Okay, they announced the first case in new york on march first

33:50.820 --> 33:52.820
Right, you know right right here

33:53.700 --> 33:57.620
And then it like spread in two weeks to millions of people

33:58.740 --> 34:01.460
Like that that that's that's what you have to believe

34:02.180 --> 34:05.540
Like the the r value on this has to be astronomical

34:06.420 --> 34:09.940
Not not only that it has to be astronomical, but it has to have been

34:10.900 --> 34:16.260
Behaving differently in new york city and bergamot, italy then it did anyplace else

34:18.100 --> 34:20.100
Yeah, it's if one person

34:20.740 --> 34:22.740
brought the disease in

34:23.460 --> 34:30.180
They must have had needed to have immediate contact with everyone else just based upon what's described as the uh time for

34:30.820 --> 34:33.300
onset of severe symptoms and then

34:34.420 --> 34:36.420
We don't see pathogenicity

34:36.820 --> 34:40.980
From each of those people giving it to someone else because it just stops

34:41.620 --> 34:44.340
Yeah, it's like something out of it's like something out of a movie

34:44.980 --> 34:48.900
Not only that in a recent interview when when Andrew komo was on bill mar

34:49.380 --> 34:55.300
Who knows what that was really about but when he was on bill mar he's like oh covid had been circulating for months

34:56.260 --> 35:02.900
Okay, fine. Let's let's go with that. So it was circulating for months, but had no impact

35:03.620 --> 35:05.620
The non lethal version

35:05.620 --> 35:11.700
So it's the non lethal version and and actually j about a charia still says this he said it on on jonathan kui's

35:12.100 --> 35:15.380
broadcast a couple weeks ago like oh, yeah, covid was here

35:16.340 --> 35:21.780
So then what what happened here then what was the what was the trigger?

35:22.420 --> 35:23.380
like

35:23.380 --> 35:28.340
I don't I don't know. I don't know how people explain the and i'm not a biologist, right?

35:28.660 --> 35:31.940
But just it doesn't for me past the smell test

35:32.820 --> 35:40.420
What whatsoever you also don't hear new yorkers, you know looking back and say yeah, everybody became sick all at once

35:41.460 --> 35:46.100
You know like oh, I was sick as a dog. Yeah in and march. We don't we don't hear that

35:46.500 --> 35:49.380
We hear people talking about this flu season some

35:50.180 --> 35:56.900
That they were sick in you know ball nut 2019 or they were sick in in january and they had the flu for a few days

35:56.900 --> 35:58.740
And they you know they were knocked out and that

35:59.620 --> 36:02.900
Oh sicker than i've ever been those kinds of reports

36:03.380 --> 36:09.220
But even then if you go back and you look on twitter or you look in different contemporaneous sources

36:10.260 --> 36:16.260
It's not like people said oh, yeah my my grandma died from the flu in october 2019

36:16.740 --> 36:20.180
Do you do you see what i'm saying? We didn't hear that then

36:20.980 --> 36:25.860
So I have proposed that perhaps there was excess death

36:26.740 --> 36:29.940
In this period not just new york, but a lot of places

36:30.980 --> 36:33.940
I have questions about the flu shot. Maybe that's for another time

36:34.020 --> 36:38.260
But um that there was excess death here, but they pushed it forward

36:39.140 --> 36:44.660
Everywhere around the and you could do that everywhere around the world with some ease meaning it was delayed

36:45.620 --> 36:48.580
If the processing of deaths is delayed anyway

36:49.540 --> 36:50.580
So

36:50.580 --> 36:52.900
Yes, or they were intentionally held back

36:53.780 --> 36:59.460
A lot of death coding and death processes are a lot of countries follow the flu

37:00.180 --> 37:02.180
Protocols and the icd classification

37:03.220 --> 37:04.340
System

37:04.340 --> 37:08.820
So there's a lot of ways that deaths could be held back

37:09.140 --> 37:12.340
Reclassified dumped in as probable deaths

37:12.820 --> 37:18.180
Those new york city ones i talked about earlier that started to be added on april 14th 2020

37:18.580 --> 37:22.260
They said they were probable covid deaths, but nobody ever said when they occurred

37:23.780 --> 37:26.820
Nobody said when they occurred. Did they happen in january

37:27.940 --> 37:29.940
Uh, did they happen in december?

37:29.940 --> 37:33.620
What was the date that it was advised to

37:34.260 --> 37:38.980
Reclassify anything that could possibly be covid to covid

37:39.620 --> 37:44.180
There's a series of things that happened in february and march in april

37:45.220 --> 37:54.260
Regarding that i should make a timeline of it kind of how to classify death certificates, etc. The code for covid 19

37:55.460 --> 37:57.460
uo 7.1

37:57.700 --> 37:59.700
debuted on april first

38:00.660 --> 38:02.660
The same day that the vaping

38:03.300 --> 38:04.340
death

38:04.340 --> 38:05.860
uh, valley

38:05.860 --> 38:09.460
Death code was debuted by the way, they're right next to each other

38:10.500 --> 38:15.460
But who also debuted i think on that day or maybe a couple weeks later i have to check that

38:15.940 --> 38:20.580
But they debuted uo 7.2, which is probable

38:22.420 --> 38:24.580
So but the us

38:24.580 --> 38:30.500
Says that they never really used that and you can't look up probables like that in wonder

38:31.380 --> 38:33.860
So i so i have questions about

38:34.980 --> 38:41.540
That but when different so new york added probables illinois i remember when illinois added probables

38:41.540 --> 38:48.740
It might have been a little later more like in the fall, but there wasn't really clarity about when those deaths occurred

38:48.740 --> 38:50.260
So, you know

38:50.260 --> 38:52.660
If i could ask androkoma one question

38:53.700 --> 38:59.380
I that that's what it would be remember those probable deaths that u announced on april 14th

38:59.460 --> 39:01.460
When did those happen

39:01.460 --> 39:03.860
When it went to what what's the day of death on those

39:05.300 --> 39:11.300
Because i i would like like to know and art did did those get pulled forward into that that spike

39:12.260 --> 39:18.020
I mean and i guess along these lines just to move forward a second in this this article what i also find

39:19.940 --> 39:21.780
incredible

39:21.780 --> 39:26.340
Is that if you take out the deaths that blamed covid as underlying cause

39:27.300 --> 39:29.300
And only look at non-covid

39:29.860 --> 39:35.460
So everything else size covid you see a six week non-covid death event

39:36.740 --> 39:41.380
And then no more non-covid access for the rest of the year

39:42.820 --> 39:49.540
That i i'm sorry in a year with ongoing mitigations civil unrest

39:50.980 --> 39:52.420
Mental health

39:52.420 --> 40:01.460
Challenges for you know who among us would not say that we struggled in one way or another churches are closed right all all of this school still closed

40:02.660 --> 40:06.980
There's no more non-covid access death except in that six week period

40:08.260 --> 40:11.780
I might might call that super sus. It's super sus

40:12.420 --> 40:20.020
Do you have any profile available of what those non-covid access deaths typically i do i don't have them ready to pull up right here

40:20.020 --> 40:24.180
i'm working on an analysis with the young deaths i mean we can look at

40:25.140 --> 40:28.180
Actually, let's look at the young deaths just all cause mortality

40:29.060 --> 40:30.660
We see

40:30.660 --> 40:38.100
All age groups in this article we have the younger adult what we call in the article younger adult age groups and then we have older adult age groups

40:38.100 --> 40:40.820
Okay, the simultaneous rise

40:41.780 --> 40:47.540
Of all cause mortality in all adult age groups at one time is a red flag

40:48.260 --> 40:55.940
It's it's a huge red flag if there's a disease spread event with a disease purported to disproportionately affect

40:57.220 --> 40:59.460
Older people than younger people

41:00.420 --> 41:02.500
You should start to see a rise

41:03.460 --> 41:05.460
In in older age groups

41:06.180 --> 41:10.580
Well for the other age groups, but that's not really what we see here

41:11.540 --> 41:16.660
We see in 85 plus, you know, we see a bump during regular flu season

41:16.980 --> 41:20.340
And I don't have this on this on this graph all the way back to 2018

41:20.420 --> 41:22.740
But if I if I did and this is weekly by the way

41:23.380 --> 41:28.580
If I did you would see that there's nothing unusual about people in the 85 plus group

41:28.980 --> 41:33.700
You know more of them dying during the winter months that that's not that's not unusual whatsoever

41:34.660 --> 41:38.580
But we see the young adult age groups go up right away

41:38.820 --> 41:41.620
So when people have all overdosed deaths actually no

41:42.500 --> 41:49.380
Actually, no, and we we wouldn't expect overdose deaths to go up immediately not not in a two-week time period

41:50.020 --> 41:52.740
Right, but we see these these groups

41:53.860 --> 41:55.940
More than double and then more than double again

41:57.060 --> 42:04.020
We also see a rise and a drop in the youngest younger adult age group

42:04.980 --> 42:06.740
First

42:06.740 --> 42:11.380
If you zoom in on this it actually starts to go up with them a little bit sooner and a little bit harder

42:11.860 --> 42:15.780
A little bit faster, but then look at how it comes down for them first

42:16.820 --> 42:18.820
I think that's interesting

42:19.540 --> 42:21.540
Really interesting

42:21.540 --> 42:27.060
Most of the excess in this age group was in hospitals hospital inpatient

42:28.340 --> 42:30.340
And those hospital inpatient deaths

42:30.980 --> 42:36.580
Mostly blame covid in these age groups actually I think we have that down down here if you don't mind

42:37.460 --> 42:39.460
Me scrolling down here a bit. Look at this

42:40.100 --> 42:44.180
This is 20. So this is the 25 to 54 as one age band

42:45.300 --> 42:47.060
right

42:47.060 --> 42:52.260
Most of the spike is blamed on covid underlying cause

42:54.260 --> 42:57.860
And most of that look this is hospital inpatient. Sorry. That's the other thing I should say

42:57.860 --> 43:00.580
So these were 25 to 54 year olds

43:01.460 --> 43:03.460
who were in the hospital as inpatients

43:04.660 --> 43:05.860
And died

43:05.860 --> 43:07.940
New York City is a global outlier with this

43:09.460 --> 43:13.700
Global outlier, Italy did not have high young deaths

43:14.420 --> 43:17.460
Certainly not young high young deaths played blamed on

43:18.820 --> 43:20.820
Something called covid-19

43:22.420 --> 43:25.860
And even just to compare this is similar with all age groups

43:25.860 --> 43:28.420
But down here we show in this age group

43:29.380 --> 43:31.380
New York City has 3%

43:32.340 --> 43:38.580
Of the population of the whole united states, you know if you look at 25 to 54 year olds

43:39.300 --> 43:42.340
This is how many New York has this is how many the whole us has

43:43.460 --> 43:45.460
But yet

43:45.540 --> 43:47.860
They had a quarter of the country's

43:48.740 --> 43:51.300
covid deaths in this in this time frame

43:51.940 --> 43:55.940
Of of the whole country. I mean, I so why

43:57.220 --> 43:59.220
For me, it's like even if you

43:59.940 --> 44:07.540
Even if you believe in the sudden spread of a novel deadly virus from Wuhan. Okay. Let's let's just say that you're on that on that train. Okay, fine

44:08.740 --> 44:11.620
Can we at least say that there should be an investigation

44:12.420 --> 44:14.420
into this

44:14.420 --> 44:18.980
Right because don't we all agree that covid's not really a young person thing

44:19.380 --> 44:22.820
Can we can we agree about that even by the government's narrative

44:23.460 --> 44:26.260
Who were these people were these homeless people

44:27.300 --> 44:34.020
I'm speculating here, but I'm just this is my my thought process after you know met a long time looking at this for these homeless people

44:34.500 --> 44:38.500
Were these mentally adults in you know homes for mentally

44:39.460 --> 44:41.460
Troubled or mentally ill people

44:42.420 --> 44:47.300
Were these people already in the hospital. They were admitted in January and February

44:48.260 --> 44:50.900
And then they were used to effectively stage

44:51.700 --> 44:54.260
The sudden spread of a novel virus in New York City

44:54.820 --> 45:00.660
This is what we have to speculate about because we don't have any answers about this and nobody cares

45:00.740 --> 45:05.540
I mean, you might have watched the interview that we did Jonathan angler and I did with Naomi wolf

45:06.260 --> 45:09.380
I mean Naomi wolf didn't think that there was a story here yet

45:10.660 --> 45:15.780
I I think there's a story. I think it's being ignored and I'm not sure why it's being ignored

45:17.940 --> 45:19.940
Now just to be clear

45:20.500 --> 45:22.980
You you are not making a statement that

45:24.100 --> 45:30.020
All of these excess deaths were were fraudulent or or didn't exist you you have seen

45:31.220 --> 45:38.020
Some data correct that there legitimately was an increase in overall all cause mortality

45:39.620 --> 45:45.620
We are we are questioning unlike deni rancor who who's work. I love and respect that by the way

45:46.020 --> 45:48.580
But what one thing that deni has said

45:49.540 --> 45:51.540
repeatedly is that

45:52.580 --> 45:59.380
I'm paraphrasing him that or their team has assumed and I and I think it's a has been a fairly safe assumption

45:59.700 --> 46:06.020
Especially for scientists to make that all cause mortality is unassailable

46:07.380 --> 46:14.500
Or that at least it's more reliable than cause of death because you keep like okay dead is dead

46:14.660 --> 46:15.780
You know

46:15.780 --> 46:17.780
Your your cause can be fudged

46:17.780 --> 46:24.820
But the fact that I can't be and I agree with him and that's why I've tended to focus on all cause mortality as well

46:25.380 --> 46:26.980
But I think it's

46:26.980 --> 46:33.140
I think it's a mistake or I've come to realize that it's it may be a mistake to assume

46:33.780 --> 46:37.620
At the government agencies that have lied about everything in this mess

46:38.580 --> 46:39.860
left

46:39.860 --> 46:42.660
left all cause mortality unmanipulated

46:43.540 --> 46:49.780
And part of the reason that I say that is because I very much doubt the speed of this

46:50.580 --> 46:51.460
event

46:51.460 --> 46:53.460
especially in hospitals

46:53.860 --> 46:57.060
The peak occupancy I don't think I have this graph right here

46:57.060 --> 47:04.100
But the peak occupancy that New York City hospitals report in this 11 week period is 20,000

47:05.460 --> 47:12.020
Patients in embed so that the peak number which is the equivalent of every every single bed

47:12.980 --> 47:15.700
Normally available in New York New York City

47:17.860 --> 47:21.220
That is roughly the number of inpatients that they say died

47:21.860 --> 47:24.020
in the same period

47:24.020 --> 47:31.140
So I'm not my background's on hospitals. I've only ever been in a hospital a handful of time as as a patient and twice was to have babies

47:31.940 --> 47:35.940
But I'm from a restaurant family and my husband's in restaurants and I worked in restaurants

47:36.500 --> 47:40.580
So I think about the turnover of the bodies

47:42.740 --> 47:48.180
New York City is saying that they lost the equivalent of every inpatient bed

47:49.220 --> 47:54.980
In 11 weeks actually a little yeah, and the bulk of it was in like six weeks five or six weeks

47:56.100 --> 47:57.060
So

47:57.060 --> 48:02.660
I don't think that matches what was actually happening on on the ground and at minimum

48:02.820 --> 48:09.620
Even if it was you have to say how many of those people who died in hospitals entered the hospital

48:10.260 --> 48:12.260
Before this event began

48:13.060 --> 48:15.060
And why were they admitted?

48:15.300 --> 48:18.180
Right how many of those people were already in the hospital

48:18.980 --> 48:23.620
On march 1st and had been admitted in January or February

48:24.260 --> 48:30.260
That's good for us to know don't you think because in real time what were you and I led to believe

48:30.580 --> 48:35.940
We were led to believe that New York City was experiencing an onslaught of patients

48:36.340 --> 48:41.300
And people coming to the hospital, but in fact mark that part's not even true

48:42.260 --> 48:47.300
That part's not even true the pink here represents emergency department visits

48:48.420 --> 48:52.260
Those peaked in January January early February

48:53.540 --> 48:55.540
And look what happens

48:55.700 --> 49:01.460
During this alleged disease spread event they plummet more than 60 percent

49:02.420 --> 49:05.940
Simultaneous to hospital deaths going up

49:07.380 --> 49:16.500
So one of my theories is that what we're seeing here are people who entered the hospital back here

49:17.380 --> 49:19.380
And who maybe died back here

49:20.340 --> 49:24.980
So if if we have some pushed forward deaths literally then

49:26.820 --> 49:28.820
That would be fraud

49:29.220 --> 49:35.620
That would be fraud so like should this curve actually this black line should it actually look higher back here

49:36.820 --> 49:39.700
But insofar as completely faked deaths

49:40.340 --> 49:47.460
That's not something that I've alleged yet, but I have said I can't exclude the the likelihood

49:47.620 --> 49:53.220
In fact, I've had a lot of people say to me good good analysts actually say don't you think they just hit an extra zero

49:53.700 --> 49:55.700
Like wouldn't that just be the easiest don't you think

49:56.340 --> 49:59.940
Don't don't you think that could have happened and yeah, I do think that could that could happen

50:00.420 --> 50:04.420
There could also be confusion between New York City and New York State

50:05.140 --> 50:09.060
Right, there could be some double counting of deaths that occurred at home

50:10.420 --> 50:13.220
And then they double counted it for the hospital numbers

50:14.020 --> 50:18.420
Right, so there there's a lot of things that can happen that would be easier than you think

50:18.980 --> 50:22.420
A lot easier than you think and not everybody would have to be involved in it

50:23.060 --> 50:27.380
But again without real answers or people demanding answers

50:27.540 --> 50:34.100
We're sort of left to to speculate a bit and just I just keep gathering data to try to put the pieces together

50:34.820 --> 50:41.380
I think you've mentioned that total was it total COVID deaths or total excess deaths in New York City for

50:42.660 --> 50:46.500
April of the year 2020 was 20,000. Was that the number?

50:47.460 --> 50:51.060
The increase I don't like saying excess because excess is modeled but

50:51.380 --> 50:55.220
um the increase over 2019 in those weeks is between

50:55.780 --> 50:58.580
27 to 26,000 27

50:58.820 --> 51:05.060
No, I'm sorry 26 and 27,000 depending on if you look at federal numbers or or the city's numbers

51:05.700 --> 51:08.500
So just just a completely massive

51:09.780 --> 51:11.620
Increase that

51:11.620 --> 51:20.420
Nobody wants to talk about and you might remember that the narrative was that and still is that the virus hit New York City harder

51:21.300 --> 51:26.180
But New York defeated the virus and then everybody could learn from New York City

51:26.660 --> 51:29.460
Well, that that that makes no sense whatsoever

51:30.180 --> 51:37.300
No, no sense whatsoever, but it just doesn't seem like anybody wants to revisit those those assumptions

51:38.260 --> 51:42.180
Or that narrative. I mean, I'm really Cuomo Fauci

51:43.780 --> 51:50.340
Donald Trump a lot of anti mandate people on our side. They're kind of all telling the same story

51:50.900 --> 51:57.940
And it doesn't I'm with I'm with you and you and JJ. It doesn't matter if it was a lab leak or a wet market

51:58.260 --> 52:00.260
That's not even important

52:00.340 --> 52:03.300
And at all. I don't even get that whole thing is a root

52:04.260 --> 52:09.540
What's the the key claim is about that there was sudden spread of a novel

52:10.180 --> 52:17.220
Risk additive pathogen that started in Wuhan and made it with lightning speed

52:18.020 --> 52:24.900
Creating geopolitically strategic mass casualty events around the world before it descended on New York City

52:24.900 --> 52:28.740
I mean, it just it's it's straight out of a movie and it doesn't make sense

52:29.620 --> 52:31.620
I

52:32.980 --> 52:34.980
Back at the time I was

52:36.100 --> 52:42.180
Deep into that in those discussions into those battles of where where the origins of the

52:43.060 --> 52:45.700
deadly novel virus came from didn't even

52:46.500 --> 52:48.500
occur to me that there could have been

52:49.540 --> 52:53.380
Potential fraudulent anyways. We haven't proved anything yet in the death

52:54.340 --> 52:59.220
The profile of the x of these deaths in the year 2020

52:59.860 --> 53:04.180
You know and at the very least the fraud with New York that has occurred

53:04.900 --> 53:11.860
And I'd be I mean I could testify about this on a witness stand at least according to the data is their hospitals were not overrun with people

53:12.660 --> 53:14.660
And and they presented a vision

53:15.220 --> 53:19.780
Of their hospitals being overrun with patients and that the data are like nope

53:20.420 --> 53:23.060
That that's not that's not what happened at all

53:23.700 --> 53:31.460
So we we were I think New Yorkers especially, but really everybody was defrauded in that way in that New York City was used as

53:32.340 --> 53:39.540
Propaganda really to stage and I think stage is the right word to stage an event that

53:40.580 --> 53:48.020
Quite possibly did not occur. I think the the only thing more horrifying than this number of people actually dying in real time

53:48.500 --> 53:50.500
Is that they didn't

53:50.500 --> 53:55.060
And that doesn't mean that there's death certificates without bodies attached to it. That's not what I'm saying

53:55.300 --> 53:58.180
But there's a lot of ways that this could be

54:00.340 --> 54:08.180
Pumped let's let's put it put it that way. So I just just declare just want to clarify like when I say it's fraudulent

54:08.420 --> 54:09.940
I mean it's a

54:09.940 --> 54:15.780
It's a fraudulent representation of the number of deaths that occurred real time according to where they occurred

54:16.580 --> 54:18.580
Now

54:18.820 --> 54:24.180
Obviously there's going to be a much here. You couldn't you you can't share but has

54:24.980 --> 54:29.540
Anyone in the medical community who might have some insights on this

54:30.660 --> 54:36.100
reached out to you now, I know that you know, they could be totally lying about what they said so everything has

54:36.660 --> 54:38.420
lots of salt here

54:38.420 --> 54:41.060
What this date if has anyone reached out to you to give you

54:41.860 --> 54:45.860
Some insights on what it might have actually been like in those hospitals and how it

54:46.420 --> 54:49.540
They might have said it does line up with official narratives or

54:50.260 --> 54:52.260
descriptions or perhaps

54:53.780 --> 54:56.180
There were empty floors. Has anyone reached out to you to

54:57.860 --> 55:00.580
Question, you know, of course I've heard this whole year

55:00.580 --> 55:05.220
I've heard from, you know, some what I would call tick-dock doctors and celebrity doctors

55:05.220 --> 55:09.380
You know yelling at me. You don't know you weren't there. You weren't in our reality, right?

55:09.860 --> 55:13.060
So they're their story is, you know, well represented, right?

55:13.060 --> 55:17.620
It's the story we were hearing from march 2020 onward. So there's that

55:18.420 --> 55:22.900
But I have spoken with a couple of of doctors

55:23.460 --> 55:27.700
Um, I'm hoping to put one of their views out there

55:28.660 --> 55:31.540
Soon, it'll it'll it'll be under a pseudonym

55:31.940 --> 55:36.820
Of course, but yes, I've talked to some and it's really important. I think too to talk to

55:37.780 --> 55:39.780
doctors who are employees

55:40.820 --> 55:47.540
That there are people like, um, pure quarry. I always get his first and last name of verse. It's it's pure quarry, right?

55:48.100 --> 55:49.220
I believe so

55:49.220 --> 55:50.980
pure pure quarry

55:50.980 --> 55:52.420
nurse erin

55:52.420 --> 56:01.540
Nicole serotics or sort of these these people were quote in new york city hospitals, but they came after mid april

56:02.660 --> 56:05.060
So that so they came around here

56:05.860 --> 56:07.860
Around this time

56:08.180 --> 56:13.860
Exposed facto in so far as the mortality the the crux of the mortality event

56:14.340 --> 56:16.100
Happened, right?

56:16.100 --> 56:23.540
What we don't hear as much from besides of the you know celebrity types that were elevated from the very beginning are

56:24.100 --> 56:27.620
People who are who are and and or were at the time

56:28.260 --> 56:33.300
New York City health care workers or emps who are actually

56:34.100 --> 56:36.580
In hospitals during the event

56:37.220 --> 56:40.180
I'm so far. I've spoken with a couple

56:40.980 --> 56:46.740
Um, and they it's interesting. I'll just I'll just say that they've been they've been helpful

56:47.380 --> 56:52.340
But remember these people too were they can report on their experience

56:53.220 --> 56:59.700
In that in that hospital, right? But these hospitals were divided up. There were different wards

57:00.180 --> 57:04.500
COVID I see you ward it was there was a lot of shuffling of people around

57:04.980 --> 57:06.980
reassignment of duties

57:07.140 --> 57:11.220
Lot lots of things were going on and so it's really indicative of

57:12.020 --> 57:15.380
I'm not sure ever anybody really knows all of what was going on

57:16.260 --> 57:17.620
at at the time

57:17.620 --> 57:22.580
But both of the doctors I've spoken with talked independently independent of one another

57:23.140 --> 57:25.300
Both talked about military presence

57:26.260 --> 57:29.460
In their in their hospitals one doctor called them the visitors

57:30.820 --> 57:36.820
Gotta find euphemism. Um, the other doctor thought they might have been naval health officers

57:37.220 --> 57:39.220
So I thought it was interesting

57:39.300 --> 57:44.020
But they they both reported that that presence in their in their hospitals

57:44.260 --> 57:48.420
I've tweeted a little bit about that the military in New York at that time

57:49.060 --> 57:53.540
The people that came in on the us and as comfort the national guard

57:54.260 --> 57:56.260
That was was brought in

57:56.260 --> 57:57.380
um

57:57.380 --> 57:59.380
DoD trucks that were

58:00.340 --> 58:06.580
Allegedly sent to New York City via FEMA that I'm still waiting for a foyer response about

58:07.140 --> 58:10.900
So that there was there was military involvement

58:11.460 --> 58:20.260
Um, so that's one thing that they've that they've talked that they've independently have both both talked about but it's it's it's interesting to listen to those doctors

58:20.980 --> 58:23.940
Versus the the celeb you doctor

58:24.500 --> 58:29.060
Crowd or even though where I would call the doctors that emerged and became part of the early treatment crowd

58:29.860 --> 58:33.060
Right like pia or cori just just a different

58:33.620 --> 58:41.140
Different vibe that that early march period to mid apo period is what I call the black box where

58:42.020 --> 58:44.020
nobody's talking

58:44.020 --> 58:46.420
Wait, we don't hear from a lot of people who were there

58:47.220 --> 58:49.380
And that and I wonder and I wonder why

58:50.340 --> 58:54.980
I don't know why exactly but but I but I wonder it seems that a vow of america

58:55.700 --> 59:01.780
You know implicit or explicit like an america code is kind of hiding what happened and

59:02.420 --> 59:06.980
Again, the only thing worse than this didn't have you know, this did happen is it didn't

59:07.460 --> 59:12.260
But I I believe that if we knew the truth about what occurred especially in hospitals

59:12.500 --> 59:17.780
It actually might exonerate a lot of doctors and the perception that doctors were killing people

59:18.660 --> 59:20.660
um

59:20.660 --> 59:24.820
It's especially military presence was not like some questions about that

59:25.460 --> 59:31.620
But and something to add to you know, why would it be bad if if this didn't happen?

59:32.260 --> 59:34.260
I mean that can sound cold, but

59:34.980 --> 59:39.300
Much of our response in the united states worldwide actually is based upon

59:40.100 --> 59:42.740
What is purported to have happened?

59:43.220 --> 59:45.220
um, there are many

59:45.300 --> 59:47.300
committees right now

59:47.620 --> 59:49.620
talking about the

59:49.860 --> 59:52.020
efficacy the safety of the

59:52.660 --> 59:54.660
countermeasures which were used or

59:55.860 --> 59:57.220
vaccines

59:57.220 --> 59:58.340
for

59:58.340 --> 01:00:00.180
That were given, you know

01:00:00.180 --> 01:00:05.140
emergency use authorization that are of course still in use today still being pushed or still boosters coming out

01:00:05.780 --> 01:00:07.780
based off of

01:00:08.020 --> 01:00:11.860
This data not just New York City, but it's a big part of the story. So

01:00:12.660 --> 01:00:14.660
if we are to believe that

01:00:15.380 --> 01:00:18.900
Uh, perhaps as some do not going to give my opinion

01:00:18.980 --> 01:00:20.980
I think most people can guess what it is

01:00:21.300 --> 01:00:23.860
But these vaccines are causing a lot of harm

01:00:24.500 --> 01:00:27.940
And they should be pulled. Well, if you wanted to do that

01:00:28.580 --> 01:00:30.580
Wouldn't you want to investigate?

01:00:31.380 --> 01:00:35.860
The underlying reasons why they were encouraged to be used in the first places

01:00:36.260 --> 01:00:40.020
Because the total number of injuries and potentially deaths from that

01:00:40.900 --> 01:00:42.900
Is actually far greater now

01:00:42.980 --> 01:00:47.860
So that is one of the reasons why I know it can sound cold, but

01:00:48.260 --> 01:00:50.420
uh, the the consequences of

01:00:51.300 --> 01:00:55.460
This data not being 100% legitimate are extraordinary

01:00:56.180 --> 01:01:00.980
Um, yeah, they're huge and that that's such a great point because I think a lot of people

01:01:01.460 --> 01:01:04.260
Including a lot of what I would call anti mandate people

01:01:04.820 --> 01:01:05.700
You know

01:01:05.700 --> 01:01:10.420
Things that they have said and things that they've assumed and I used to say and assume some of those things as well

01:01:10.420 --> 01:01:15.060
So I don't want to make it out like I've been onto this the whole time or I've discovered the secret

01:01:15.700 --> 01:01:20.100
All right, I mean we're just we're we're inquiring minds that want to know right

01:01:20.180 --> 01:01:27.060
But some people are very happy to just kind of sit there and assume that there was sudden spread of a novel deadly

01:01:27.700 --> 01:01:32.580
Pathogen right that there was something novel that required novel tr new treatments

01:01:33.300 --> 01:01:35.300
That weren't already being done

01:01:36.020 --> 01:01:38.980
Right, but my my contention is like what you've said

01:01:38.980 --> 01:01:42.900
Yeah, I I agree that that even though it's not my area of specific focus and interest

01:01:43.540 --> 01:01:49.540
I agree that the vaccine has harmed people. I I completely agree

01:01:49.540 --> 01:01:55.780
I mean even just moral injury if nothing else, but I I believe the reports of the injuries and and the deaths

01:01:56.180 --> 01:01:58.580
However, let's go back to 2020

01:01:59.620 --> 01:02:03.300
There this was used to justify the need

01:02:04.260 --> 01:02:08.500
For a shot, which was already in development anyway, right? I mean we we know we know that

01:02:08.820 --> 01:02:10.820
It was a solution to need of a problem

01:02:11.940 --> 01:02:13.060
So

01:02:13.060 --> 01:02:18.740
That's why when people say to me what what's really important is the vaccine. Okay, that's fine

01:02:18.820 --> 01:02:21.700
You know to borrow line from star wars, you worry about the fighters

01:02:21.780 --> 01:02:25.060
I'm going to worry about the tower here that this being a tower

01:02:25.540 --> 01:02:27.460
like this was used

01:02:27.460 --> 01:02:30.740
to justify there is something that we need

01:02:31.620 --> 01:02:33.620
a shot for and

01:02:34.020 --> 01:02:39.460
If this is fraudulent, you better believe that this is not the only place that it happened

01:02:39.940 --> 01:02:44.660
I don't think that only New York messed up that there was a coordinated response

01:02:45.860 --> 01:02:47.860
Coordinated response

01:02:47.860 --> 01:02:52.580
And people say to me well, you know, are you are you saying that the world governments coordinated?

01:02:52.980 --> 01:02:58.260
I'm saying they're already coordinated when it comes to disease surveillance

01:02:58.740 --> 01:03:01.940
participation in the who's flu surveillance program

01:03:02.900 --> 01:03:06.100
Using the international classification of diseases

01:03:06.660 --> 01:03:09.140
You know chapters. It's like the dewy decimal system

01:03:09.140 --> 01:03:12.420
If you will of death and medical billing classification

01:03:12.820 --> 01:03:18.100
These things are already uniform and these countries already march in lobster

01:03:18.500 --> 01:03:20.820
So all it takes is a switch

01:03:21.540 --> 01:03:23.700
Okay, everybody now do this

01:03:24.340 --> 01:03:25.540
Right

01:03:25.540 --> 01:03:28.980
Right that that that's all it that's all it takes

01:03:28.980 --> 01:03:34.820
I mean, my governor was calling for a coordinated response on january 24th 2020

01:03:35.220 --> 01:03:38.340
In a press conference and tweets. We need a coordinated response

01:03:38.420 --> 01:03:42.820
It's like that somebody should do research just on that term january 24th

01:03:43.780 --> 01:03:47.060
january 24th 2020 jb pritzker governor of illinois

01:03:47.780 --> 01:03:51.540
When the first case in chicago was announced a nurse

01:03:52.180 --> 01:03:55.060
return this is echoes of snohamish man here, but the

01:03:55.700 --> 01:03:57.700
a nurse returning from muhan

01:03:58.180 --> 01:04:00.180
That happened in chicago, too

01:04:00.900 --> 01:04:04.180
Oh, yeah, yeah, I thought it was just a snow homish man

01:04:04.820 --> 01:04:05.860
Oh, no

01:04:05.860 --> 01:04:14.260
No, that so yeah, I mean not even a week later after snohomish man was the announcement of the the chicago the chicago case

01:04:14.820 --> 01:04:15.380
um

01:04:15.380 --> 01:04:17.860
I detailed that somewhere on my my sub-staff

01:04:17.860 --> 01:04:23.460
But just completely bizarre and and that day the our our governor announced

01:04:23.940 --> 01:04:26.500
Coordinated response in fact if any of your listeners

01:04:27.380 --> 01:04:28.420
viewers

01:04:28.420 --> 01:04:33.860
Can find an earlier reference to coordinated response or or a us official

01:04:34.340 --> 01:04:41.140
Using that term. I would love to know who it is that that's the earliest I found but I also haven't done an exhaustive search

01:04:41.860 --> 01:04:43.220
um

01:04:43.220 --> 01:04:47.540
But yeah, that that was the refrain people have forgotten coordinated response

01:04:48.260 --> 01:04:54.180
Was the the bat the battle cry in in those days? It I think it's something of a signal

01:04:54.820 --> 01:04:56.820
um

01:04:56.820 --> 01:05:02.180
But that that's just my that's just my opinion now. This is a question. I've been I've been

01:05:02.900 --> 01:05:08.020
Uh, I was going to say dying to ask you, but that's I shouldn't say I love fun. No, please

01:05:08.740 --> 01:05:11.060
Is that there was a change in

01:05:11.700 --> 01:05:13.940
Protocol some protocols in new york city

01:05:14.580 --> 01:05:16.580
for april of

01:05:16.580 --> 01:05:17.940
2020

01:05:17.940 --> 01:05:23.540
Such as responses to people who might have been suffering from cardi cardiac event

01:05:24.340 --> 01:05:26.340
um, yeah

01:05:27.060 --> 01:05:31.940
How would you characterize those changes and uh what if people were to

01:05:32.820 --> 01:05:36.740
Question this uh, where can they find evidence to to back this up?

01:05:37.380 --> 01:05:38.980
All right, this is I'm glad you brought that up

01:05:38.980 --> 01:05:44.740
So pretty soon. Hopefully within the next couple weeks myself and some colleagues are going to put out an article on this

01:05:45.620 --> 01:05:49.220
Using we we spent a lot of time analyzing the ambulance dispatch data

01:05:49.780 --> 01:05:54.260
in this time, but something people don't realize was was going on in

01:05:54.980 --> 01:05:56.580
New york is

01:05:56.580 --> 01:05:58.820
There were and actually this was in other places too

01:05:59.460 --> 01:06:03.620
but there were orders or directives to

01:06:04.180 --> 01:06:06.180
ems emergency medical services

01:06:07.140 --> 01:06:10.980
regarding how to handle cardiac arrest calls

01:06:12.020 --> 01:06:15.940
And we'll we'll show the documentation of it in in the article, but

01:06:16.500 --> 01:06:19.460
Basically, they were directed to do

01:06:20.580 --> 01:06:22.580
not as much as they would normally do

01:06:23.460 --> 01:06:28.660
to administer life's full life-saving measures to people in cardiac arrest

01:06:29.620 --> 01:06:33.780
and to not bring they were encouraged to not bring them in the hospital

01:06:34.420 --> 01:06:37.940
Or excuse me put them in the ambulance and bring them to

01:06:38.820 --> 01:06:41.940
the hospital for two reasons one spread

01:06:42.900 --> 01:06:44.660
There's that word again

01:06:44.660 --> 01:06:46.820
might spread the virus

01:06:46.820 --> 01:06:49.780
and two because our hospitals are overwhelmed

01:06:51.460 --> 01:06:55.860
And so if you look at the time series data, it's actually super scary

01:06:56.420 --> 01:06:58.420
when you plot these orders

01:06:58.660 --> 01:07:00.660
along with the dispatch data

01:07:01.540 --> 01:07:05.620
And the number of patients pronounced dead at the scene of pickup

01:07:06.580 --> 01:07:07.780
the

01:07:07.780 --> 01:07:16.260
Transport data showing that there was a huge drop in patients being transported from point of pickup to other places hospital or wherever

01:07:17.220 --> 01:07:19.220
and home deaths

01:07:19.700 --> 01:07:23.700
How many is there any evidence? I'm sorry to cut you off, but uh,

01:07:25.220 --> 01:07:29.780
Is there any evidence that this might also include encouragement to

01:07:30.660 --> 01:07:32.660
uh

01:07:32.660 --> 01:07:37.940
To to reduce the likelihood of using Narcan for people who are suffering from an overdose

01:07:38.740 --> 01:07:43.300
That you know what that's a great question. I I have not that would be worth looking into

01:07:44.100 --> 01:07:51.300
There is that would explain the the young deaths that would explain you're a young desk young deaths at home surging at that time

01:07:52.020 --> 01:07:54.020
uh, there's

01:07:54.740 --> 01:07:58.100
The only reason we have a granddaughter is because of Narcan. Let's put it that way

01:07:58.580 --> 01:08:01.140
Um, so people who are struggling with addiction

01:08:01.860 --> 01:08:03.540
oftentimes

01:08:03.540 --> 01:08:09.220
Uh, will receive Narcan at least once or twice during their their years or more

01:08:09.780 --> 01:08:15.380
Uh, that could very easily explain a sudden surge in at-home deaths of ages

01:08:15.620 --> 01:08:17.620
20 to 45

01:08:17.620 --> 01:08:23.700
I completely agree with you on that. It's interesting and I have another article in development on just the young deaths

01:08:24.100 --> 01:08:28.820
In in New York City. And so I've been analyzing the home like the home death data

01:08:29.380 --> 01:08:31.140
most of the deaths at home

01:08:32.580 --> 01:08:38.180
Are our heart if i'm not mistaken are in the heart chapter right of of icd

01:08:39.380 --> 01:08:41.380
There's also um

01:08:41.380 --> 01:08:46.020
A good number that are blamed on covid, which doesn't really make sense. Right?

01:08:46.980 --> 01:08:49.780
Who's the young person that's dying at home of covid?

01:08:50.580 --> 01:08:56.900
Unless covid has another meaning which I think i've told you I I kind of have a theory about that about what the oh and covid might stand

01:08:56.900 --> 01:08:58.740
might really stand for

01:08:58.740 --> 01:08:59.620
um

01:08:59.620 --> 01:09:02.180
Opioid I mean it could be that covid stands for

01:09:02.820 --> 01:09:05.940
coronavirus opioid and vaccine induced death

01:09:06.900 --> 01:09:08.900
or vaccine induced death

01:09:09.540 --> 01:09:10.660
That's

01:09:10.660 --> 01:09:12.340
That would be interesting

01:09:12.340 --> 01:09:16.820
And you could classify and reclassify a bunch of deaths under that ad nauseam

01:09:17.460 --> 01:09:24.420
You know forever forever and ever so I I will look into that what you just said because I think that that's important

01:09:25.620 --> 01:09:30.260
Some of the ambulance orders suggest that people were

01:09:31.060 --> 01:09:36.660
That there were directives or the suggestion that people should be sedated

01:09:37.540 --> 01:09:41.620
In ambulances or that there was a need for sedation

01:09:42.260 --> 01:09:43.540
Heavy sedation

01:09:43.540 --> 01:09:50.660
So one thing I've wondered about these reports in new york city that you never heard anywhere else about young people showing up to the hospital

01:09:50.660 --> 01:09:52.900
Not being able to breathe

01:09:52.900 --> 01:09:57.300
I wonder if some younger aged people

01:09:57.860 --> 01:10:01.380
You can imagine this happening with homeless people actually but others too

01:10:02.180 --> 01:10:06.260
Were sedated heavily with medazalam, etc

01:10:07.140 --> 01:10:09.140
In the in the ambulance

01:10:09.140 --> 01:10:16.340
And then the impact of that i've seen some studies on this actually but the the impact of that was showing up not being able to breathe

01:10:16.580 --> 01:10:18.660
Like they became hypoxic

01:10:18.660 --> 01:10:20.740
So that would um the receiving end

01:10:21.620 --> 01:10:24.500
Give this like we had so so the the

01:10:25.380 --> 01:10:32.740
The doctors aren't lying the doctors and nurses aren't lying about what they heard, but there's another reason for it

01:10:33.700 --> 01:10:39.460
But yeah, I I agree with that idea that you just put forward that would be interesting to see

01:10:39.620 --> 01:10:46.660
That would be interesting data to to see but even the even the directives I have seen would discourage narkan

01:10:47.700 --> 01:10:49.460
Correct

01:10:49.460 --> 01:10:55.860
Well, I mean narkan that the hardest stop the hardest stopped or it's it's very very slow rate

01:10:55.940 --> 01:10:56.980
So

01:10:56.980 --> 01:10:59.620
You could describe it as a cardiac event

01:11:00.580 --> 01:11:02.580
And it is a

01:11:03.460 --> 01:11:05.460
A way to revive someone

01:11:07.220 --> 01:11:10.900
Wow, I never thought I did not think about this jessica until this show

01:11:11.460 --> 01:11:18.340
I'm just I like this. I like this. It's the young people that young at the profile of young people at home dying

01:11:18.420 --> 01:11:19.540
I've not

01:11:19.540 --> 01:11:22.660
Actually considered this this angle and it's not

01:11:23.460 --> 01:11:26.900
This is not you know like 50 of the 20,000

01:11:27.700 --> 01:11:34.180
26,000 excess excess deaths if you will I know that's not the term you would prefer to use but

01:11:34.980 --> 01:11:40.180
It is statistically significant and and it is a major contributor to

01:11:41.940 --> 01:11:46.740
Uh, if anyone was providing data on um from the york city on

01:11:48.020 --> 01:11:51.540
Average age of death or changes in life expectancy during that month

01:11:52.180 --> 01:11:54.180
um

01:11:54.180 --> 01:11:55.460
Wow

01:11:55.460 --> 01:11:59.940
Well, here's something else that you see actually this this view doesn't show it and this is you know

01:11:59.940 --> 01:12:03.540
This is all causes all ages but by setting of death or place of death

01:12:04.020 --> 01:12:10.420
But one thing that you see or don't don't see here is you don't see an increase on uh dead on arrival

01:12:11.780 --> 01:12:14.900
So which makes sense with the ambulance dispatch data

01:12:15.620 --> 01:12:22.500
Right, so you would expect that during some kind of disease spread event or even some kind of biological

01:12:23.460 --> 01:12:27.700
Or bioterror attack, okay, like if we want to call it call it that i'm just entertaining that

01:12:28.180 --> 01:12:30.900
You know that speculation that that some have have made

01:12:31.860 --> 01:12:33.860
You would expect to see

01:12:34.180 --> 01:12:37.700
Actually in this graph, I combined deo a hospice and other places

01:12:37.780 --> 01:12:42.260
But if I if you disaggregate those actually hospice, I think goes down

01:12:43.700 --> 01:12:48.020
With or or it's it's very it barely goes up at all if it does

01:12:48.500 --> 01:12:56.660
Doa too that does not so that's another indicator that at least on paper people were not being brought to the hospital

01:12:58.180 --> 01:12:58.980
in

01:12:58.980 --> 01:13:00.980
Levels that you would expect

01:13:01.380 --> 01:13:06.980
The other the other data that goes along with this that we'll put in the article is 911 call data

01:13:08.020 --> 01:13:09.140
So

01:13:09.140 --> 01:13:12.420
All of a sudden it's so sudden it's it's weird

01:13:13.460 --> 01:13:16.260
15 days to stop the spread is announced on march 16

01:13:17.140 --> 01:13:23.460
2020 and then 911 call data for life threatening situation spikes

01:13:24.980 --> 01:13:31.220
I used to think that it was like just people panicking on that day on on the march 15th or after the 15 days

01:13:32.180 --> 01:13:38.580
In that week in that week starting march up. I you know, I maybe could pull it up if you want to see it

01:13:39.460 --> 01:13:42.580
Um, you know, so many graphs in my head. Um

01:13:42.580 --> 01:13:44.580
I

01:13:44.580 --> 01:13:49.060
Don't know if I have it at the ready. Oh, here we go. Actually. This is a little complicated

01:13:50.740 --> 01:13:53.620
These are different call types to 911 in New York City

01:13:54.660 --> 01:14:01.780
and uh, this isn't my annotated version, but something you have to understand what happens. This is for this is calls to

01:14:02.420 --> 01:14:03.860
fdny

01:14:03.860 --> 01:14:05.860
and empt

01:14:05.860 --> 01:14:08.660
Different classifications broad broad categories

01:14:09.140 --> 01:14:17.860
Something that happened in early march is that fdny was taken off of certain responding to certain calls

01:14:19.620 --> 01:14:21.620
They were taken off of calls

01:14:22.180 --> 01:14:27.700
Asma and like other things that were said to be associated potentially with covid

01:14:29.540 --> 01:14:30.820
So

01:14:30.820 --> 01:14:35.940
It's interesting right because that's why you see the blue line here the light blue line

01:14:36.660 --> 01:14:40.420
in weekly calls to fdny medical emergencies go down

01:14:41.540 --> 01:14:43.540
and they were redirected

01:14:44.500 --> 01:14:49.220
To empt non-life threatening you see that so you see this go down

01:14:50.180 --> 01:14:51.860
And you see this go up

01:14:51.860 --> 01:14:58.340
See I used to think before I had this data below here. I used to think that this was people starting to panic

01:15:00.420 --> 01:15:03.620
But I now realize that it's a call redirection

01:15:04.580 --> 01:15:06.580
That occurred here

01:15:07.700 --> 01:15:10.660
Right here for empt life threatening

01:15:13.380 --> 01:15:16.420
We have this massive jump

01:15:17.860 --> 01:15:20.900
After 15 days to slow the spread is announced

01:15:22.500 --> 01:15:24.660
So like I told Naomi wolf

01:15:26.020 --> 01:15:28.020
People were calling

01:15:28.180 --> 01:15:33.700
Like the idea that and I used to think this too like people were staying away from the hospital because they were afraid

01:15:33.700 --> 01:15:39.220
They were afraid of covid and then they died. Oh, I do think there was some of that. I mean there there's no question about it

01:15:40.260 --> 01:15:44.180
Um, well, there is a question, but I you know, it's it's plausible

01:15:44.180 --> 01:15:47.460
Especially in New York where things are very tense. You've got you know

01:15:47.460 --> 01:15:53.860
My example is like ernie goldstein who lives in a rent control department on the upper east side and lives alone

01:15:54.260 --> 01:15:58.580
You tell him to stay home. He can't go out. He doesn't he loses his routines

01:15:59.380 --> 01:16:05.300
Right like and the guy dies of a heart attack like you could imagine that that scenario, right?

01:16:05.860 --> 01:16:09.700
But the calls this is people calling 911

01:16:11.220 --> 01:16:13.140
So they call

01:16:13.140 --> 01:16:19.540
Ambulance dispatches did go up commensurate with these 911 just like you would expect

01:16:20.500 --> 01:16:26.900
Except the transports that the dispatches that are moving patients from one place to another plummet

01:16:27.860 --> 01:16:29.860
and patients pronounce dead

01:16:30.340 --> 01:16:32.340
skyrockets

01:16:32.740 --> 01:16:38.900
Again coincidental to these ambulance orders that were issued around cardiac arrest

01:16:40.980 --> 01:16:42.100
So

01:16:42.100 --> 01:16:44.100
Basically a dnr

01:16:44.100 --> 01:16:46.260
That's how the orders read as like a dnr

01:16:46.260 --> 01:16:50.420
Especially when you look at it alongside these data. So when people say well, I was in New York

01:16:50.420 --> 01:16:52.340
I heard the ambulances. Yes, you did

01:16:52.900 --> 01:16:57.860
There there were a lot of ambulances going out, but they weren't a lot of them weren't taking people

01:16:59.220 --> 01:17:02.340
People people were calling for help and help wasn't helping

01:17:02.980 --> 01:17:06.820
That's what the that's the story the data tell anyway the multiple data points

01:17:06.900 --> 01:17:11.460
So we'll we'll put that we'll spell that out in the article that we're working on related to that

01:17:11.540 --> 01:17:13.700
But it's a pretty it's pretty grim

01:17:14.180 --> 01:17:19.700
It's pretty grim and it all it actually wasn't just in New York. I've found it. I found some from

01:17:21.780 --> 01:17:26.740
I want to say Pennsylvania had similar orders or philadelphia

01:17:27.460 --> 01:17:30.020
CMS the federal agency

01:17:30.820 --> 01:17:35.380
put out something in later march 2020 that said that

01:17:36.180 --> 01:17:43.540
under these kinds of orders that ambulance companies would still be reimbursed as though they brought the

01:17:43.700 --> 01:17:45.700
Patient to the hospital

01:17:47.300 --> 01:17:49.940
That's really scary to me

01:17:50.900 --> 01:17:55.700
I guess as a matter of course, I didn't I'm not in the medical billing. I don't know all the ins and outs of it

01:17:55.700 --> 01:18:01.380
But I guess ambulance companies get reimbursed or paid in some way when they bring a patient to the hospital

01:18:01.460 --> 01:18:04.340
Okay, that's fine. Well, that was just that because

01:18:05.140 --> 01:18:07.140
with these kinds of orders

01:18:07.700 --> 01:18:09.700
They were still reimbursed

01:18:10.660 --> 01:18:15.860
So that goes to the death count. I'm sort of wondering was there a double count

01:18:16.420 --> 01:18:19.860
Of deaths that occurred in hospitals and deaths that occurred at home

01:18:21.620 --> 01:18:25.460
Do you see what I'm saying? Like I could almost imagine that happening

01:18:26.740 --> 01:18:28.980
Right to substantiate

01:18:28.980 --> 01:18:35.860
Something on on both ends or you know, who knows? Maybe they'll say there was an error right that we we know that's going to happen

01:18:35.940 --> 01:18:39.540
We know that's coming in the future, right? That's that's the first line of defense

01:18:40.020 --> 01:18:42.900
That will happen. This is failure. We had an error

01:18:43.780 --> 01:18:45.780
Cerebral error, right

01:18:46.100 --> 01:18:52.340
Do you have any data that breaks out um or shows that there was an an increase in

01:18:53.060 --> 01:18:59.060
Maybe it wasn't listed as a cardi cardiac event being the primary cause of death, but cardiac events overall

01:19:00.020 --> 01:19:04.740
um in that time period late march april 2020 new york city and

01:19:05.540 --> 01:19:07.540
I asked because

01:19:08.980 --> 01:19:10.500
Uh

01:19:10.500 --> 01:19:12.500
Many have commented that

01:19:14.180 --> 01:19:21.060
Since cardiac events were related or or increased in the united states in early 2020

01:19:21.860 --> 01:19:23.860
that it is evidence that the

01:19:24.980 --> 01:19:26.420
deadly novel

01:19:26.420 --> 01:19:28.420
spreading pathogen

01:19:29.220 --> 01:19:31.220
Also causes

01:19:31.220 --> 01:19:33.220
cardiac events and because

01:19:33.700 --> 01:19:35.220
And therefore

01:19:35.220 --> 01:19:41.700
That is why the vaccine to it also seems to be correlated with the increase is in

01:19:42.260 --> 01:19:44.420
uh, cardiac events, but if some

01:19:45.460 --> 01:19:48.580
Of the increases in cardiac events might have been related to

01:19:49.220 --> 01:19:51.220
Changes in the way

01:19:51.220 --> 01:19:54.020
Uh, uh, people who are suffering from a cardiac event were

01:19:54.580 --> 01:19:56.580
Um, were treated well

01:19:57.140 --> 01:20:02.180
That would again mean that we are responding to something in a way that does not

01:20:03.380 --> 01:20:05.780
match the what the underlying risk

01:20:06.900 --> 01:20:08.900
Uh was of that thing

01:20:09.700 --> 01:20:11.700
So my belief is

01:20:12.500 --> 01:20:14.180
that

01:20:14.180 --> 01:20:16.180
Whatever happened in new york city

01:20:17.140 --> 01:20:19.140
Around this around this time

01:20:20.420 --> 01:20:21.380
That

01:20:21.380 --> 01:20:23.220
What I would call the myth

01:20:23.220 --> 01:20:24.020
About

01:20:24.020 --> 01:20:28.820
COVID's of cardiac or vascular disease is actually rooted in this

01:20:29.380 --> 01:20:32.820
Is actually rooted in what happened in new york

01:20:33.460 --> 01:20:39.620
So here's I so this isn't every I don't have external causes and I don't have every cause of death

01:20:39.940 --> 01:20:41.940
These are bigger chapters

01:20:42.980 --> 01:20:44.980
For for viewers

01:20:45.380 --> 01:20:50.900
The cause of death classification system it you can think of it as like the dewy decimal system in a library

01:20:50.980 --> 01:20:54.580
Well, that's school libraries, but or library of congress system, right? There's this

01:20:55.300 --> 01:20:56.900
These chapters

01:20:56.900 --> 01:20:58.900
Of causes of of death

01:20:59.220 --> 01:21:03.380
Medical bill billing uses them too and they're determined by the the who the w h o

01:21:04.100 --> 01:21:07.460
So here's here's some of those. Why do I have

01:21:09.460 --> 01:21:11.300
I have something mislabeled on here

01:21:12.100 --> 01:21:15.620
Something is mislabeled on here. What is it? Why do I have the

01:21:19.060 --> 01:21:24.820
Um, okay ignore where it's that ignore the first thing on the legend where it says disease is a circulatory system

01:21:24.820 --> 01:21:27.940
I think that's on there errantly. Sorry. This isn't a finalized graph

01:21:28.500 --> 01:21:33.940
For publication. I was just showing somebody else. Okay. So the weeks are at the bottom. This is weekly deaths

01:21:34.580 --> 01:21:36.180
And at home

01:21:36.180 --> 01:21:40.820
So all ages, okay weekly deaths at home. We see cardiac

01:21:42.580 --> 01:21:44.100
Go way up

01:21:44.100 --> 01:21:45.620
Right

01:21:45.620 --> 01:21:50.260
It spikes first. It spikes more than more than anything else

01:21:51.300 --> 01:21:53.460
And then notice too

01:21:53.460 --> 01:22:00.100
That the deaths that list covet 19 is underline cause have the same shape

01:22:01.540 --> 01:22:03.380
Do you see that? Yeah, I find that

01:22:03.860 --> 01:22:05.860
Between that blue line, which is

01:22:06.740 --> 01:22:07.700
You

01:22:07.700 --> 01:22:09.540
Zero seven point one or coven 19

01:22:10.340 --> 01:22:15.220
Those are deaths. So this is underlying cause. So that means those blue line deaths. Those are

01:22:16.580 --> 01:22:19.940
Deaths that blame covet 19 as underlying cause

01:22:20.500 --> 01:22:25.860
Not as contributing cause but underlying cause. Okay. So there's no overlap in the deaths in this chart, right?

01:22:25.940 --> 01:22:27.860
Every death is only represented

01:22:27.860 --> 01:22:34.180
The deaths are only represented once but this this isn't every cause category either. I don't have external causes on on here

01:22:34.980 --> 01:22:36.980
Um or some smaller categories

01:22:37.380 --> 01:22:42.100
So but those ambulance orders begin at the end of

01:22:42.980 --> 01:22:47.940
You know toward the actually the ambulance orders sequence starts to go out in early march. Okay

01:22:48.660 --> 01:22:52.900
Of different kinds, but the cardiac order. I think was march

01:22:54.580 --> 01:22:57.780
Oh, I don't know. I'm gonna have to look march 27th

01:22:58.660 --> 01:22:59.860
Can't remember

01:22:59.860 --> 01:23:02.100
But that that's those spike up

01:23:02.900 --> 01:23:09.220
And then the orders end the cardiac or what I call the cardiac DNR order ends. I think April 24th

01:23:11.220 --> 01:23:13.300
If I remember correctly

01:23:13.300 --> 01:23:18.980
Deaths at home do stay elevated for the rest of the year. By the way, I don't have that picture on this graph

01:23:19.060 --> 01:23:21.060
But they do they do stay elevated

01:23:21.940 --> 01:23:23.940
What I think we see here

01:23:24.500 --> 01:23:29.620
And the reason I think that covet mirrors the heart deaths at home is

01:23:30.660 --> 01:23:37.380
I think that the the blue line is all the deaths that occurred in a home setting

01:23:38.260 --> 01:23:40.260
Could even be a group home setting

01:23:41.140 --> 01:23:43.940
Which they were able to get a positive covet test

01:23:46.340 --> 01:23:48.340
See what i'm saying

01:23:49.460 --> 01:23:54.020
And then those that couldn't were attributed to other causes

01:23:55.860 --> 01:24:02.900
So yes, I mean sort of answer to your sort of question is yeah, I I think what i'm saying

01:24:03.700 --> 01:24:06.100
Really challenges that assumption

01:24:06.820 --> 01:24:13.780
About covet causes heart attacks. I mean and and again if if it does and this thing was spreading in new york

01:24:14.500 --> 01:24:16.500
Right. Why don't we see it

01:24:17.540 --> 01:24:21.300
In the data. Why don't we see it in the weeks leading up?

01:24:22.020 --> 01:24:25.300
Why is it only when the government issues of proclamation?

01:24:25.780 --> 01:24:31.700
Is it because of the prescience of the us governments? I mean come on people know

01:24:32.660 --> 01:24:36.340
No, but I but I do think that some of these deaths do reflect

01:24:36.820 --> 01:24:38.420
um

01:24:38.420 --> 01:24:42.180
You know, yeah people just having heart attacks for other reasons

01:24:42.180 --> 01:24:46.820
I'm not you know for fear and and things like that or not being able to call 911

01:24:47.620 --> 01:24:50.340
I do think that there is some of that there could have been some

01:24:51.060 --> 01:24:54.900
In especially as you get to the later weeks i'm choosing to die at home

01:24:55.620 --> 01:24:58.900
Instead of in the hospital or coming home from the hospital

01:24:59.620 --> 01:25:02.020
Right, so that there could be some of that

01:25:02.980 --> 01:25:06.500
But it's it's that a lot of these deaths are young deaths that is like

01:25:07.540 --> 01:25:12.900
You know people like oh opioid overdoses, but it's very the increase is so fast

01:25:13.700 --> 01:25:14.980
So fast

01:25:14.980 --> 01:25:17.780
So along along the lines of what you were kind of speculating

01:25:18.100 --> 01:25:21.540
I I kind of wonder and maybe you know more about this than I do

01:25:22.020 --> 01:25:26.340
I wonder about the street drugs that were put out there in march

01:25:27.140 --> 01:25:29.780
You know, I mean like you have people who are already using

01:25:30.500 --> 01:25:34.340
There was a release of prisoners at the time. I don't know if you worry that

01:25:35.460 --> 01:25:37.140
um

01:25:37.140 --> 01:25:39.140
I have a question about that

01:25:40.020 --> 01:25:46.260
You know or maybe street drugs had higher doses of something at that time like if we were getting nefarious about it

01:25:46.260 --> 01:25:48.260
I'm just no I

01:25:48.260 --> 01:25:50.260
Through some possibilities

01:25:50.260 --> 01:25:54.580
Um, you know which people are going to call me all kinds of names for that, but I I think

01:25:55.220 --> 01:25:58.820
This is tangent, but one thing that people have been loath to do

01:25:59.540 --> 01:26:02.180
is to speculate or it is to brainstorm

01:26:03.060 --> 01:26:04.100
and

01:26:04.100 --> 01:26:11.060
I I think people should do that. I'm not trying to put out missing misinformation. No. No, we're just we're thinking out loud

01:26:12.260 --> 01:26:18.180
It could this be possible. That's not wrong. That's not misinformation. It's

01:26:19.140 --> 01:26:20.980
It's how humans think

01:26:20.980 --> 01:26:24.020
Right. It's how scientists think shouldn't it be? I don't know

01:26:24.020 --> 01:26:29.220
We've been discouraged from that from doing that. I still have a video up from 2021

01:26:30.100 --> 01:26:32.100
noting that there was

01:26:32.180 --> 01:26:35.380
I mean we had anecdotal evidence that there was a major surge in

01:26:36.180 --> 01:26:38.740
Fentanyl lace repressed pills on the streets

01:26:39.700 --> 01:26:44.340
It was just winding up and all kinds of different things. I wasn't observing that

01:26:45.620 --> 01:26:47.620
Because of our sons

01:26:47.780 --> 01:26:49.860
Because he was you know in and out of programs

01:26:50.820 --> 01:26:52.820
during that time

01:26:52.820 --> 01:26:53.860
and

01:26:54.260 --> 01:26:59.300
You know, I got a certain number of views on it. That was the middle of 2021

01:27:01.060 --> 01:27:02.420
And

01:27:02.420 --> 01:27:05.380
nationwide the drug overdose is total which includes

01:27:05.940 --> 01:27:12.980
Other things but predominantly opioids which also includes fentanyl and card fental in 2020. It was 91,800

01:27:14.020 --> 01:27:16.020
Whereas in

01:27:16.180 --> 01:27:18.180
2019 it was

01:27:18.180 --> 01:27:20.340
70,600 so it was

01:27:20.980 --> 01:27:24.100
And it started to spike in March in May 2020, right?

01:27:24.900 --> 01:27:26.900
That's what it really

01:27:27.140 --> 01:27:31.380
I have that data. It started in 2020 and then it got

01:27:32.260 --> 01:27:34.420
much worse in 21

01:27:34.420 --> 01:27:36.420
I see me 106,000

01:27:36.420 --> 01:27:41.140
1 to 79 and 109,980 in 2022 so

01:27:42.100 --> 01:27:44.100
nationwide the that's

01:27:45.060 --> 01:27:48.100
310,000 in three years whereas the

01:27:49.060 --> 01:27:50.980
average number of

01:27:50.980 --> 01:27:52.980
Fatal drug overdoses

01:27:53.460 --> 01:27:55.460
in the year

01:27:55.540 --> 01:27:57.540
2000 was

01:27:57.540 --> 01:27:59.540
20,000 per year

01:28:00.420 --> 01:28:03.700
And this is I mean, I don't mean to to change the subject but

01:28:04.740 --> 01:28:06.740
I mean it is related

01:28:07.460 --> 01:28:09.940
If you use a baseline of 60,000

01:28:11.620 --> 01:28:14.740
As which is actually closer to a record level

01:28:15.220 --> 01:28:18.180
as the as the baseline and that's like

01:28:19.060 --> 01:28:25.220
Maybe that's a a base if you use the years between 2000 and 16 to 2019

01:28:25.700 --> 01:28:27.540
average that out and use that as your baseline

01:28:28.580 --> 01:28:30.580
That would mean that we have a hundred and

01:28:31.620 --> 01:28:35.380
15,000 excess deaths in three years of drug overdoses

01:28:37.780 --> 01:28:43.060
Yeah, I have questions about that because I am not I'm not not that I'm not questioning those death

01:28:43.380 --> 01:28:46.100
That's not what I'm saying. What I wonder about

01:28:47.540 --> 01:28:49.540
is

01:28:49.540 --> 01:28:52.260
Maybe there was some pretty heavy excess

01:28:53.300 --> 01:28:55.300
in drug overdoses

01:28:55.300 --> 01:29:00.580
Opioid, benzol, may be stuff. I mean, maybe maybe there wasn't an attack of a different kind

01:29:01.540 --> 01:29:07.780
That that that's something that I would encourage people to sort of think about because it would be easy

01:29:08.660 --> 01:29:14.980
Because opioid deaths and and deaths from external causes take longer to process

01:29:15.780 --> 01:29:17.140
always

01:29:17.140 --> 01:29:18.580
right

01:29:18.580 --> 01:29:23.140
It would be very easy to do what I would call some death certificate swapping

01:29:24.260 --> 01:29:26.260
So you had some delayed death

01:29:26.820 --> 01:29:30.340
Six-month lag on the end of deaths that are happening in

01:29:31.380 --> 01:29:34.980
November 2019 December 2019 January 2019

01:29:35.300 --> 01:29:37.300
Do you see what I'm saying?

01:29:37.300 --> 01:29:42.100
And then you could do some re some swapping and some reclassification

01:29:42.740 --> 01:29:43.700
There

01:29:43.700 --> 01:29:50.180
It would probably happen on the federal level though is is where that that kind of thing would would happen

01:29:50.820 --> 01:29:55.940
Um, and I don't know if it's you or somebody else has I know people have speculated that

01:29:56.420 --> 01:30:02.580
Part of what maybe governments were trying to hide or the us government is trying to hide is how many

01:30:03.540 --> 01:30:06.340
fentanyl deaths there were or

01:30:07.060 --> 01:30:11.860
Whatever, but yeah, the New York City curve, you know could be a signal about that

01:30:12.340 --> 01:30:18.980
Honestly, and this this ambulance thing could be these deaths at home these young cardiac deaths at home

01:30:20.100 --> 01:30:27.060
It's going to be hard for the government to get around that. How do you explain these young cardiac deaths at home?

01:30:28.020 --> 01:30:33.860
Well, I don't know what the ratio is, but I would estimate again anecdotal data

01:30:35.540 --> 01:30:36.900
that if

01:30:36.900 --> 01:30:39.540
Uh, let's say a hundred thousand people

01:30:40.340 --> 01:30:43.780
Had died to an overdose in one year

01:30:44.660 --> 01:30:46.660
That there were probably

01:30:47.540 --> 01:30:50.980
300,000 people who didn't die because of Narcan

01:30:52.420 --> 01:30:54.420
I think the number really is that high

01:30:54.740 --> 01:30:57.540
It is uh, Narcan is it uses

01:30:58.180 --> 01:30:59.780
extensive and

01:30:59.780 --> 01:31:05.700
It's one of the only reasons why it's not even worse right now. Um, with that said

01:31:06.260 --> 01:31:14.500
We can get that data if you can't can't we can't we foil that that data? I bet we can't but that would mean

01:31:15.460 --> 01:31:20.660
That if you just take New York city and say no, no Narcan for two or three weeks

01:31:21.380 --> 01:31:27.380
All right, you will uh affected the effective result of that will be during those two or three weeks

01:31:28.100 --> 01:31:30.580
Probably a four x increase in drug overdose deaths

01:31:31.060 --> 01:31:33.460
Yeah, and you would not even have to say no Narcan

01:31:34.180 --> 01:31:37.460
Yes, right. Isn't that kind of what we're saying together? We're saying

01:31:38.020 --> 01:31:42.500
I here's here's one way of putting it. I think jonathan angler has posed this question to me

01:31:42.500 --> 01:31:44.500
Or maybe thomas verdine and in panda

01:31:45.300 --> 01:31:48.500
How many or is there a way of finding out how many?

01:31:49.460 --> 01:31:53.300
People New York city EMTs save a day

01:31:54.740 --> 01:32:00.260
Right or we're saving a day. And so just by issuing this order

01:32:01.060 --> 01:32:03.060
Which you know

01:32:03.060 --> 01:32:05.060
You don't have to say was intentional

01:32:05.780 --> 01:32:11.620
Or I would say that I would I would say that how many how many deaths could you create?

01:32:12.420 --> 01:32:16.820
Simply by doing that and some would be from drug overdose

01:32:16.980 --> 01:32:20.580
Some would be just because you didn't save somebody or you didn't bring them to the hospital

01:32:21.460 --> 01:32:27.140
Like you like you normally would you were afraid you created fear among EMTs about spread

01:32:28.260 --> 01:32:34.260
Right like you you could imagine that and is that really what we see but in real time

01:32:34.820 --> 01:32:37.220
It was blamed on covid deaths at home

01:32:38.180 --> 01:32:40.180
Well

01:32:40.180 --> 01:32:44.100
Which is absurd it's absurd to think about now. Yeah, no way

01:32:44.740 --> 01:32:48.980
And I'm so appreciative to have a chance to talk about this with you because

01:32:49.700 --> 01:32:52.980
I respect your audience and I'm hoping that they can

01:32:53.540 --> 01:32:59.460
Now access or maybe this can give them some ideas about some other things which might have happened as part

01:33:00.740 --> 01:33:02.980
As part of this uh this tragedy is

01:33:06.260 --> 01:33:10.420
Um people who succumb to pneumonia many of the people who

01:33:10.980 --> 01:33:14.580
Aside from perhaps that one month in New York city are listed as covid

01:33:15.460 --> 01:33:17.780
those average ages of death are actually

01:33:18.500 --> 01:33:19.700
older

01:33:19.700 --> 01:33:21.700
than the average

01:33:21.860 --> 01:33:24.500
Then then then what life expectancy was

01:33:25.220 --> 01:33:26.100
um

01:33:26.100 --> 01:33:28.660
It would it's it's a funny thing to say but

01:33:29.380 --> 01:33:32.100
uh if the average age of a covid death was 84

01:33:33.460 --> 01:33:40.100
You could say you know what it would be good news to discover that you'll die of covid because that means you're going to live a longer than average life

01:33:40.580 --> 01:33:42.580
Because life expectancy was 78

01:33:43.540 --> 01:33:47.380
Now if life expectancy had gone up during coronavirus

01:33:48.740 --> 01:33:51.220
That doesn't look like a pandemic

01:33:52.020 --> 01:33:55.140
That's that's impacting people of all of all ages

01:33:55.860 --> 01:33:58.660
um, however, life expectancy went down

01:33:59.540 --> 01:34:02.340
um by about two years or so

01:34:03.380 --> 01:34:05.380
um between 2000

01:34:05.380 --> 01:34:06.420
uh

01:34:06.420 --> 01:34:08.420
19 to 20 and 21

01:34:08.660 --> 01:34:10.660
And that hasn't happened

01:34:10.900 --> 01:34:14.180
In the united states for the last 80 90 years or so

01:34:15.300 --> 01:34:15.940
um

01:34:15.940 --> 01:34:19.460
And the only reason why that's happened is because of the opioid epidemic

01:34:20.260 --> 01:34:22.020
And that's it. So

01:34:22.020 --> 01:34:24.020
While the opioid epidemic is happening

01:34:24.900 --> 01:34:29.220
Um and giving excess deaths and lots more younger people dying because of it

01:34:30.100 --> 01:34:36.180
You can then say and I have snapshots of uh, you know the pbs news hour in new york times saying

01:34:37.140 --> 01:34:39.300
coronavirus is so bad

01:34:40.420 --> 01:34:42.980
That in this era life expectancy is going down

01:34:44.660 --> 01:34:53.220
Now you can make that that statement is true and it gives the impression that coronavirus is impacting all age groups and also impacting young people

01:34:53.460 --> 01:34:55.700
That is a very very simple way

01:34:56.340 --> 01:35:01.940
No death certificate fraud whatsoever. No delayed death certificates to create an illusion

01:35:02.900 --> 01:35:06.740
Of coronavirus impacting all these age groups and in effectively

01:35:07.780 --> 01:35:10.420
Taking the the deaths that did happen

01:35:11.140 --> 01:35:12.500
and

01:35:12.500 --> 01:35:15.220
Uh hiding them and repurposing them

01:35:15.780 --> 01:35:20.500
Um, and also again along with all of your other great research jessica

01:35:20.900 --> 01:35:22.740
it creates the

01:35:22.740 --> 01:35:30.660
The baseline perception and the fear necessary to have provided the emergency use authorizations of the vaccines which are now

01:35:31.620 --> 01:35:38.900
Allow to debate you can get out you can have you can be on twitter 24 hours a day and in a vaccine safety group

01:35:39.540 --> 01:35:42.340
For some reason other you'll still be calling conspiracy theorist

01:35:43.220 --> 01:35:47.940
That's okay. However, it is not okay to question

01:35:48.900 --> 01:35:51.540
the underlying data which led to the

01:35:53.380 --> 01:35:55.380
Uh the emergency use

01:35:55.780 --> 01:35:58.820
authorizations to be approved in the first place. That's just

01:35:59.780 --> 01:36:00.980
not allowed

01:36:00.980 --> 01:36:04.900
No, I I agree and I might I might have asked somebody or I might ask jj this on

01:36:04.900 --> 01:36:11.700
On twitter you're pointed it out to him, but like with all this discussion about the covid shot on on twitter

01:36:12.020 --> 01:36:18.420
So that that's really the only platform. I'm on besides sub stack. I have questions about why that discussion is allowed

01:36:19.380 --> 01:36:26.420
Right. And so I have to constantly be asking myself. Unfortunately, who how does this how does this discussion?

01:36:27.220 --> 01:36:28.420
serve

01:36:28.420 --> 01:36:29.460
the overall

01:36:29.460 --> 01:36:31.060
official narrative

01:36:31.060 --> 01:36:34.740
And I think that the government would rather people be talking about

01:36:35.380 --> 01:36:36.820
covid shot

01:36:36.820 --> 01:36:37.780
harms

01:36:37.780 --> 01:36:39.780
Then a lot of other things

01:36:39.780 --> 01:36:46.260
Including but not limited to the opioid epidemic and what happened in 2020 not just in new york

01:36:46.260 --> 01:36:47.860
But but everywhere

01:36:47.860 --> 01:36:54.740
So we're in this constant like limited hangout like hamster wheel of things that they're okay with us

01:36:55.300 --> 01:36:56.740
Disgusting

01:36:56.740 --> 01:37:01.780
But they're not okay with us discussing these other things. So at some point you have to ask yourself why that is

01:37:02.500 --> 01:37:06.500
So something else that you might not I want to point this out to you as long as we're talking about it

01:37:07.220 --> 01:37:10.420
Um, this is the kind of thing you can't really teach as well on twitter

01:37:10.420 --> 01:37:14.020
But when you're talking to somebody face-to-face, you can't and i'll have to wrap up in

01:37:14.740 --> 01:37:16.740
10 minutes or so

01:37:19.380 --> 01:37:22.260
We'll get to the new york times uh we'll get to the new york times

01:37:22.420 --> 01:37:26.900
100 000 death thing in a different segment that'll be that'd be fun to look at but

01:37:27.620 --> 01:37:30.660
I just want to go into cdc wonder is the federal

01:37:31.780 --> 01:37:34.180
Database the death certificate warehouse

01:37:34.740 --> 01:37:40.980
You can't look at individual death certificates, but you can put queries in for any number of of things

01:37:41.060 --> 01:37:46.580
So whenever I cite cdc wonder this is where the data is coming wonder.cdc.gov

01:37:47.380 --> 01:37:51.940
Yes, and so when you go that it's a little clunky to use actually but once you figure it out

01:37:51.940 --> 01:37:55.620
It's it's easy, but if you go down to the causes, right?

01:37:55.700 --> 01:38:01.140
So here's these chapters and then you can open them up and you see all these specific causes of death

01:38:02.660 --> 01:38:06.180
Respiratory disease deaths are under the jay codes

01:38:07.540 --> 01:38:09.540
covid is not under there

01:38:09.780 --> 01:38:11.140
covid

01:38:11.140 --> 01:38:16.580
uo 7.1 is under codes for special purposes. So i'm going to open it up

01:38:17.460 --> 01:38:18.740
and

01:38:18.740 --> 01:38:21.140
Really these are all okay

01:38:21.140 --> 01:38:27.460
So it's codes for special purposes then they're under provisional assignment of new diseases of uncertain etiology

01:38:28.500 --> 01:38:30.500
So then I open that up

01:38:31.060 --> 01:38:33.060
This is where

01:38:33.060 --> 01:38:35.060
terrorism deaths are

01:38:37.140 --> 01:38:39.140
Okay

01:38:39.300 --> 01:38:42.020
This is where sars one is

01:38:42.660 --> 01:38:44.660
and

01:38:44.660 --> 01:38:46.660
This is where

01:38:46.900 --> 01:38:50.100
covid is under codes for emergency use

01:38:51.540 --> 01:38:53.540
Let me zoom in on that

01:38:53.700 --> 01:38:55.700
actually i'm

01:38:56.260 --> 01:38:58.260
I'm surprised that they

01:38:58.580 --> 01:39:00.580
Have a vaping one

01:39:00.580 --> 01:39:06.020
You know what it debuted on april first 2020 the same day

01:39:06.740 --> 01:39:08.740
as uo 7.1

01:39:08.740 --> 01:39:10.740
And you mentioned that earlier

01:39:10.740 --> 01:39:11.780
And there's

01:39:11.780 --> 01:39:12.340
Same day

01:39:12.340 --> 01:39:15.460
There were you know boston globe and other newspapers had covered

01:39:16.420 --> 01:39:16.980
um

01:39:16.980 --> 01:39:18.020
the

01:39:18.020 --> 01:39:19.220
vaping illnesses

01:39:19.220 --> 01:39:20.820
uh increasing starting in

01:39:21.700 --> 01:39:23.700
late 2019

01:39:23.940 --> 01:39:29.700
Uh, no actually it was more I know because a bunch of them were in uh, wisconsin in illinois

01:39:30.260 --> 01:39:32.260
so it was actually

01:39:33.300 --> 01:39:38.660
I think the first news reports here the first health department reports here were may or june

01:39:39.300 --> 01:39:43.140
2019 I can check my eyes threads on that. I can I can check that

01:39:43.700 --> 01:39:44.740
but

01:39:44.740 --> 01:39:46.980
But here's here's the point. So here's covid

01:39:47.780 --> 01:39:54.260
All capitals. I think that's important. I don't think it only means what ted rose said it means

01:39:54.980 --> 01:40:00.340
I think it has an alternate meaning. I've gone through some possibilities some plausible deniability

01:40:01.540 --> 01:40:07.540
Because these codes for emergency use this will not stay here forever that that's what i'm trying to point out

01:40:08.180 --> 01:40:10.180
This is a temporary coding

01:40:10.820 --> 01:40:12.820
so someday

01:40:13.060 --> 01:40:15.060
covid 19

01:40:15.540 --> 01:40:18.660
Is going to have to go under a different chapter

01:40:19.380 --> 01:40:22.740
Or a different disease chapter is going to have to be created or

01:40:23.540 --> 01:40:28.820
There will be a reclassification project of all deaths that attributed covid 19

01:40:29.860 --> 01:40:32.340
I'm the death certificate. This is not a permanent

01:40:33.140 --> 01:40:34.660
coding

01:40:34.660 --> 01:40:37.060
I think I think that's important to note to note

01:40:37.700 --> 01:40:41.460
Will it will it remain one coding though, or will it then get broken out?

01:40:42.500 --> 01:40:45.300
I don't I don't I don't well. I mean we'll see that that's anybody's guess

01:40:46.020 --> 01:40:49.380
But just if it covid means something else

01:40:50.260 --> 01:40:52.260
covert operation

01:40:52.980 --> 01:40:55.380
for viral infectious disease

01:40:57.700 --> 01:41:00.420
coronavirus opioid or

01:41:00.820 --> 01:41:02.340
uh

01:41:02.340 --> 01:41:03.620
vaccine

01:41:03.620 --> 01:41:05.620
injury death

01:41:06.020 --> 01:41:08.020
I'm speculating here

01:41:08.020 --> 01:41:15.300
Right, but I used to decapitalize that because I don't like the shouting of of things that the government wants us to

01:41:15.940 --> 01:41:17.860
seem are more urgent than they are

01:41:17.860 --> 01:41:22.580
But i've actually gone back to keeping it all capital because it's all capital in the icd

01:41:22.900 --> 01:41:25.780
And I I think there's there are reasons for for that

01:41:26.580 --> 01:41:29.620
Um, I yeah people all conspiracy theory

01:41:29.620 --> 01:41:33.060
I mean if if you don't believe that the government has conspired at this point

01:41:33.060 --> 01:41:35.460
I don't know who you are if you think they're banning a thousand

01:41:35.860 --> 01:41:36.980
on

01:41:36.980 --> 01:41:43.060
covid I don't know what I don't know what world people are living in if they think that so I think that that is

01:41:43.780 --> 01:41:45.780
very very

01:41:45.780 --> 01:41:50.340
Possible that there's a front-facing meaning and there are other meanings

01:41:52.180 --> 01:41:54.180
like there's a like for

01:41:54.660 --> 01:41:56.660
Zaire Ebola virus tears

01:41:57.460 --> 01:41:59.700
when it comes to the names of specific

01:42:00.580 --> 01:42:02.420
pathogens and

01:42:02.420 --> 01:42:04.420
I have some questions about those as well

01:42:05.060 --> 01:42:07.060
um, but at least

01:42:07.140 --> 01:42:09.300
um that when they are being discussed

01:42:10.180 --> 01:42:13.780
They uh can use all caps even though they're not really

01:42:14.900 --> 01:42:16.900
a um

01:42:17.860 --> 01:42:22.820
It's not even initialism. Okay. It's not even an acronym that but they'll use all caps

01:42:23.620 --> 01:42:25.620
um

01:42:26.980 --> 01:42:32.100
So the COVID-19 is not a virus. It's a disease

01:42:32.900 --> 01:42:37.220
Um, so so this isn't like saying, you know, SARS-CoV

01:42:37.780 --> 01:42:41.380
Which is SARS coronavirus being all caps. This is this is a disease

01:42:42.020 --> 01:42:46.580
Uh, so and as such, I would have expected there to be you know, uh

01:42:47.940 --> 01:42:48.980
Um

01:42:49.380 --> 01:42:52.020
You know capital C and then O V I D

01:42:52.660 --> 01:42:59.780
Or, uh, or if it's all caps that would mean that it's initialism for something or that or an acronym in this case

01:43:00.420 --> 01:43:03.780
You know, you know what I think is interesting in the ICD 10

01:43:04.260 --> 01:43:09.540
And in the who guidance the CDC is different the country specific guidance is different

01:43:09.940 --> 01:43:11.940
But in the who's guidance

01:43:11.940 --> 01:43:17.620
At least in initially in 2020 and in the official kind of version of the ICD

01:43:18.180 --> 01:43:20.660
They actually don't mention SARS-CoV-2

01:43:22.180 --> 01:43:25.940
UO 7.1 COVID-19 virus identified

01:43:27.140 --> 01:43:29.140
Which one?

01:43:29.300 --> 01:43:31.300
Which any virus?

01:43:31.860 --> 01:43:32.900
Right?

01:43:32.900 --> 01:43:34.900
Isn't that weird?

01:43:36.100 --> 01:43:41.140
And then UO 7.2 which CDC wonder does not use

01:43:42.500 --> 01:43:44.980
COVID-19 virus not identified

01:43:45.220 --> 01:43:46.740
Wow

01:43:46.740 --> 01:43:48.740
Isn't that weird?

01:43:48.980 --> 01:43:50.980
That is shocking

01:43:52.100 --> 01:43:54.100
I think so too

01:43:54.340 --> 01:43:58.660
I want to talk with people about it. It's kind of it's just hard to explain all of this in like an article to people

01:43:58.660 --> 01:44:00.660
You know what I'm saying or in a tweet?

01:44:01.300 --> 01:44:03.300
And here's vaping

01:44:04.740 --> 01:44:05.860
I don't know

01:44:05.860 --> 01:44:08.260
I I I have some questions about that

01:44:08.580 --> 01:44:14.260
But but I guess my overall theory regardless of if this has the acronym has a different meaning or whatever

01:44:14.660 --> 01:44:17.140
Is these are emergency codes

01:44:17.780 --> 01:44:23.860
They're temporary codes and the way that they are crafted provides plausible deniability

01:44:24.820 --> 01:44:29.700
And an avenue for the inevitable reclassification of these deaths

01:44:30.100 --> 01:44:34.660
Whether that's five years from now 10 years from now or 50 years from now

01:44:35.540 --> 01:44:39.140
I think that this this coding is very intentional

01:44:39.460 --> 01:44:41.220
Are you saying all countries did it?

01:44:41.300 --> 01:44:44.580
Yes, I am because most countries use this

01:44:45.300 --> 01:44:48.340
So so yes, that's exactly what I'm saying

01:44:49.220 --> 01:44:55.300
You know everybody changed it at once. Yes, they did but yes country did also come up with specific

01:44:56.420 --> 01:44:58.340
guidelines here

01:44:58.340 --> 01:45:03.700
But in related to that in New York City and this is right in their 2020 mortality report

01:45:04.100 --> 01:45:08.660
They they counted a COVID death as a death that had a positive

01:45:09.540 --> 01:45:11.780
SARS-CoV-2 test

01:45:11.780 --> 01:45:13.780
anytime within 60 days

01:45:14.900 --> 01:45:16.900
So now you know what I'm wondering

01:45:17.540 --> 01:45:22.660
I'm wondering if doing that allowed them to count deaths from January

01:45:24.500 --> 01:45:26.500
As probable and push them forward

01:45:27.460 --> 01:45:29.460
Do you see what I'm saying?

01:45:29.780 --> 01:45:32.740
Any death within 60 days. Oh wait shoot

01:45:33.620 --> 01:45:36.260
Well, let's go back and test that test that death

01:45:37.060 --> 01:45:39.060
Test the specimen or whatever

01:45:40.820 --> 01:45:43.220
That that's that's very easy to do

01:45:44.100 --> 01:45:45.620
Very easy to do

01:45:45.620 --> 01:45:47.780
Got it. I hate to be thinking like a criminal here

01:45:47.780 --> 01:45:54.020
But it's the more I've studied about this and about how you know the the fungibility of cause of death

01:45:54.580 --> 01:45:57.780
Right, which I think people think is super objective, but that's not the case

01:45:58.340 --> 01:46:03.060
That's never been the case. Right. There's always influences the zeitgeist of the time

01:46:03.700 --> 01:46:05.700
And what would be the motivations

01:46:06.340 --> 01:46:08.340
If you allow me I uh

01:46:08.340 --> 01:46:11.860
There has been so much invested into gene therapy

01:46:12.340 --> 01:46:14.340
Uh, and the HIV vaccine

01:46:15.140 --> 01:46:18.900
More has been invested into that than our much of our space program

01:46:20.020 --> 01:46:26.500
It is one of the largest us investments arguably the largest us investment between that and cancer research

01:46:27.140 --> 01:46:31.620
Much of the manhattan project was really studying the cancers, which would have been caused by

01:46:32.340 --> 01:46:34.340
Weapons of mass destruction

01:46:34.580 --> 01:46:36.580
So to think that it is

01:46:37.620 --> 01:46:39.300
It's it's crazy

01:46:39.300 --> 01:46:45.700
That this would all be done simply to have a justification to finally roll out gene therapy on the population

01:46:47.220 --> 01:46:54.180
Well, no, it is not it is not a crazy thought because if if you look at how the money has been spent

01:46:55.060 --> 01:47:01.300
Gene therapy cancer research is the top priority of the united states government for

01:47:01.860 --> 01:47:03.860
At least 50 years and it's funny

01:47:04.740 --> 01:47:06.260
or uh, it's it's it is

01:47:07.140 --> 01:47:10.260
Crazy timing that it was just yesterday that henry kissinger died and

01:47:11.060 --> 01:47:16.500
much of his activities were really related to national cancers institute biological weapons

01:47:16.980 --> 01:47:20.340
And when you really want to get down to it funding for

01:47:21.060 --> 01:47:21.940
uh

01:47:21.940 --> 01:47:23.460
genetic research

01:47:23.460 --> 01:47:30.260
Uh, so this is it is not crazy to think that something like this would have been done allowed coordinated

01:47:30.900 --> 01:47:34.180
supported to usher in gene therapy, which

01:47:35.140 --> 01:47:37.140
If you look at the roadmaps

01:47:37.140 --> 01:47:40.900
Everything in the future is going to be using platforms, which are

01:47:41.380 --> 01:47:44.900
Uh have been rolled out similar platforms to coronavirus. So

01:47:45.860 --> 01:47:49.620
The other layer to that i'll strengthen your theory. I'll raise your theory

01:47:50.740 --> 01:47:52.260
And

01:47:52.260 --> 01:47:54.260
So if you look at the flu shot

01:47:54.740 --> 01:47:58.260
The flu shots the biggest racket out there in in my opinion

01:47:58.900 --> 01:48:02.340
People don't question it. They're like a they guessed wrong

01:48:03.220 --> 01:48:09.620
Right. I got flu. Anyway, they don't see that as an adverse effect. Nobody nobody asked questions about it

01:48:10.180 --> 01:48:11.140
Right

01:48:11.140 --> 01:48:15.620
Even if uptake is relatively low each year they get to change the formulation each year

01:48:15.700 --> 01:48:18.420
They say that they're circulating strains all all of that

01:48:19.220 --> 01:48:23.780
I've seen evidence that especially since 2009 they were doing a lot of messing around

01:48:24.500 --> 01:48:26.820
A lot of messing around and it wasn't really working

01:48:27.460 --> 01:48:31.140
And it was causing problems, especially among flu shots stuff with kids

01:48:32.580 --> 01:48:36.980
So in my opinion, and I've laid this out in a couple of threads into whatever

01:48:37.540 --> 01:48:44.500
I think part of what they were hiding that the flu shot the flu season mortality was starting to get out of control

01:48:45.140 --> 01:48:47.860
And starting to they couldn't hide it

01:48:48.580 --> 01:48:52.820
Any any more especially after 2014 when the quadrivalent shot

01:48:53.380 --> 01:48:59.860
You know, anything about all the nursing home residents that gets these shots health care workers all these captive populations that get this shot

01:49:01.060 --> 01:49:06.260
And after I think 2017 2018 might have been a wake-up call. They were like, oh, shoot

01:49:07.140 --> 01:49:12.420
Right, that's when you start to see we need a universal they've always been talking about this, right?

01:49:12.420 --> 01:49:18.420
But you got got leave February 2018. We need a universal flu shot

01:49:19.060 --> 01:49:25.220
Right you and you start seeing this sequence of there's a flu pandemic coming. There's a flu pandemic coming

01:49:25.780 --> 01:49:29.780
So I have wondered if in part, I'm not saying this is the whole thing

01:49:30.340 --> 01:49:32.260
but what we saw is

01:49:32.260 --> 01:49:40.020
an emergency and a decoy and a decoy shot in in effect to off ramp egg based

01:49:40.820 --> 01:49:42.340
flu shot

01:49:42.340 --> 01:49:44.340
on ramp and bar and a

01:49:45.060 --> 01:49:47.780
And they knew they couldn't create fear around flu

01:49:48.740 --> 01:49:52.020
As I think Rick right who was it that said flu is not sexy enough

01:49:52.580 --> 01:49:59.780
Right in that perfunctory milican institute conversation in october 2019 or whatever that that was

01:50:00.580 --> 01:50:04.500
That was right. They knew they couldn't scare people of flu and I think the other thing that they knew it

01:50:04.660 --> 01:50:08.260
They couldn't risk people questioning the flu shot

01:50:09.300 --> 01:50:11.300
So they needed something else

01:50:11.300 --> 01:50:14.740
And so that's another reason I think maybe just maybe

01:50:15.380 --> 01:50:21.380
There is more excess there is higher mortality potentially in 2018 2019

01:50:22.260 --> 01:50:24.260
And in 2019 2020

01:50:25.380 --> 01:50:27.140
Then it appears

01:50:27.140 --> 01:50:28.980
and maybe

01:50:28.980 --> 01:50:33.300
That's where we classified that maybe should be blamed on the flu shot

01:50:34.100 --> 01:50:38.900
And then when you told me about Robert Malone's involvement in flu shot studies

01:50:39.860 --> 01:50:48.900
That's interesting to me. That's all I'm going to say that that is interesting. Yeah, he was managing the the data for the

01:50:50.500 --> 01:50:57.940
WCCT west coast clinical trials. He was managing the flu shot data for for Walter Reed

01:50:59.140 --> 01:51:03.860
Well, so the reason that the government is okay with everybody talking about covid shot

01:51:04.420 --> 01:51:06.660
Is because at least they're not talking about the flu shot

01:51:07.460 --> 01:51:13.780
And now they're going to launch and you keep seeing it. There's they're they're going to try to push this one shot to rule them all

01:51:14.820 --> 01:51:16.820
It's coming. I've already seen it

01:51:17.140 --> 01:51:21.460
Yep, it's been it's they don't hide this stuff. They've always wanted this stuff

01:51:21.780 --> 01:51:26.900
Right. And so now link it up to bio surveillance and and all of that

01:51:27.460 --> 01:51:30.980
So for me the flu surveillance in shot program

01:51:31.460 --> 01:51:34.580
It kept growing and growing. I think it got out of hand

01:51:34.660 --> 01:51:39.460
But I also think it gave them the pandemic that they had invested in for decades

01:51:39.940 --> 01:51:46.340
And preparing for so sooner or later if you prepare for the to battle the forest fire of the century

01:51:46.900 --> 01:51:48.900
You're going to light the matches

01:51:49.300 --> 01:51:51.300
If you never get the lightning strike you want

01:51:51.860 --> 01:51:53.700
Do you see what i'm saying?

01:51:53.700 --> 01:52:00.020
This is not hard to imagine and it's all it's all spelled out right there in there in their documents

01:52:00.660 --> 01:52:05.220
Well for people to find out more about what you're saying because I think we're all totally in agreement

01:52:05.700 --> 01:52:07.460
How do people follow you?

01:52:07.460 --> 01:52:10.500
People yes at at would underscore house

01:52:10.820 --> 01:52:12.580
76 on

01:52:12.580 --> 01:52:17.620
Twitter I refuse to call it x twitter and uh sub stack is uh,

01:52:17.700 --> 01:52:22.660
Woodhouse76.com you may get a warning that my website is dangerous

01:52:23.300 --> 01:52:25.300
ooh

01:52:26.020 --> 01:52:31.780
Work around it. I put in a complaint to norovirus or nor listen to me norovirus that

01:52:32.500 --> 01:52:38.660
I'm obviously focusing too much on this stuff norton antivirus, which is not to be confused with norovirus

01:52:38.740 --> 01:52:42.340
Which is a serious thing by the way nor virus is that'll make you sick yikes

01:52:43.780 --> 01:52:48.900
Well, thank you so much. Jessica. It's been an honor. Obviously. We got a lot more to talk about and to share

01:52:49.540 --> 01:52:52.980
Um, and i'm looking forward to that program. Thank you so much for your time

01:52:52.980 --> 01:52:55.940
Take your mark. Bye.
