v3tkf7p (2023-11-16) - Were NYC COVID 2020 Deaths False？ [DailyClout]

v3tkf7p (2023-11-16) - Were NYC COVID 2020 Deaths False？ [DailyClout].vtt

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Hey, everyone. Welcome. It's Dr. Naomi Wolf, and I'm honored to be joined today by Jessica

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Hawkett and Jonathan Angler of the Distinguished Group, Pandata. Welcome, Ms. Hawkett and

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Mr. Angler. Yeah, so excited to have you. So we've got some bios. Mr. Angler started

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life as a medical doctor. I'm sorry, I should've said Dr. Angler before moving into the clinical

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industry where he gained experience in designing, running, and reporting clinical trials to regulatory

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standards. After a few years, he set up a business using automation to streamline clinical trials,

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and this was sold to you as corporation a decade later. He retrained as a lawyer because why,

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you know, why not make your Jewish mother incredibly happy?

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Yeah. Practice for a short period before re-entering the health care business world,

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and he is the co-chair with Claire Craig, whom I adore, by the way. I've never met her, but I've

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admired her forever, of the UK-based heart group, which opposes UK government policies of the last

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few years. He is also on the executive committee of the International Research Group, Panda,

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where he works closely with Jessica. Now, Jessica Hawkett lives in the Chicago area and worked in

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the K-12 education sector for more than 20 years, versus a teacher, and then as a consultant to

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schools and agencies and policy organizations. She's published many publications, including

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numerous articles and three books. Since 2020, she has used her research skills to push against

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government mandates, censorship, and false claims of COVID-19. She publishes her investigative work

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on New York City's mass fatality event on Twitter at Wood underscore House 76, and her

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sub-stack, Woodhouse76.com, and is proud to be associated with the international group Panda,

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through which she collaborates with Jonathan, Engler, and others. And so, such distinguished

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guests for today, again, welcome, welcome. The reason that we're speaking with Dr. Engler and Ms. Hawkett

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today is that Panda, Panda, their group, reached out to let us know that they had

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reviewed the 2020 New York City fatality statistics, and they had some questions,

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serious questions. So, over to you, please tell us what you found in your own research. And again,

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I just want to underscore this is their independent research. Daily Cloud has not evaluated. Our

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group has not evaluated it. It's their finding, so over to you to tell us what you found.

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Yeah, so, I mean, my first suspicions about the story that we were being told arose in

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a few years ago, actually, 2020-2021, when it looked like, basically, the COVID deaths, which

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were claimed, shot up in a peak, as well as the whole United Kingdom at the same time,

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with a few days in between.

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Okay, we're looking in, Dr. Engler, around what month was that?

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That's March 2020, yeah. And I thought that's a slightly strange thing for a spreading pathogen

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to do. And of course, the alternative theory to that, which I developed in Panda with a very

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genius evolutionary biologist who was in Panda there, was maybe it wasn't actually a spreading

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virus. Maybe it was the response to the idea that there might be a spreading virus. In other

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words, the dystopian healthcare response and how it affected the particularly elderly people at

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the time. And sort of fast forward to 2022, when we discovered that we could download some

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information from fine-grade information from Northern Italy, basically daily death information

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for a long time. What was the source of work data?

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This was the Italian Statistics Institute. So the official government stats statistic

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institute in Italy actually publishes a very fine-grained death data for going right down into relatively

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small towns and villages in Northern Italy. And so we actually analyzed that data, trying to find

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the evidence of spread. The whole critical part of the narrative is that something spread.

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So if something spreads, you should see evidence of it mathematically, because what you get is

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you get clusterings, and then you get things taking off in a small little fire somewhere,

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imagine it's a forest fire, and then that dies out and another one starts off somewhere else.

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What you wouldn't expect to see would be the simultaneous destruction

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of the whole forest at the same time. And that's a powerful analogy.

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So can we just jump in there? I know you want to set the stage and I appreciate it, but that's

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really a thought worth processing. You're saying and do epidemiologists agree with you that the

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normal way a pathogen spreads is here, and then here, and then here, rather than everywhere all

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at once? Well, that is the narrative as claimed, that it spread. That was the whole basis upon

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lockdowns, restrictions of movement. I'm asking kind of a different question,

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and I really want to get this right, so please bear with me. And again,

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I'm not a medical doctor, so my frame of reference is 400 years of English and American

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memoirs and novels and so on. And what you're saying really resonates with like accounts of

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the bubonic plague. It wasn't everywhere all at once. It was in this town, and then it was in that

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town, and then it was coming in the harbor. Are you saying that epidemiologists agree with you

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that pathogens do not spread everywhere all at once? They spread here in a cluster and then

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to there in a cluster and to there in a cluster. Is that what you're saying? Well, they should,

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that's what they should do. But of course, what they've been trying to do with the data we've

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been presenting is remake all their assumptions so that their perception of what happened, which was

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as a novel deadly virus spread from Wuhan across the world. So that fits that. But the more

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assumptions they have to change to make that model fit, the less credible it basically looks.

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Sorry, just want to dig in here, because what you're saying is kind of incredible. So you're

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saying that epidemiologists in the past agreed that pathogens spread the way you just described

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from this place to this place to this place in clusters, but that currently

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epidemiologists, I'm assuming you mean kind of institutional epidemiologists as opposed to our

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dissident friends who are epidemiologists, are now remaking their assumptions about how

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pathogens spread in order to align the expectations with the COVID narrative that everything spread

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all at once. Is that what you're saying? Yeah, so for example, they might have thought a few years

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ago, it's a classical spread of a pathogen from person to person. If you isolate somebody,

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it will reduce its spread and we can model this using complex modeling and so on. Now,

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they're having to introduce the idea of triggers that they don't really understand to explain why

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why did it take off simultaneously in these different areas? Oh, it must be a trigger that

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we don't understand. Now, we would say that is not a virus. The trigger is the spread of

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fear, panic and dystopia. But I should point out that there is a somewhat of an omerta

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over the whole story about what happened in 2020 is even people who have worked out

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that the whole vaccine programme is of dubious efficacy of safety and justification are unwilling

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to look deeply into what actually happened in spring 2020. Right, we're out on a limb both within

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the skeptical and the non-skeptical community. Well, let's bracket that. Okay, and move right

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into what do you say you've found? I get your theory that the mass deaths may not have been a

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virus in this case, behaving kind of anomalously and being everywhere all at once and killing

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people everywhere all at once. And you're right, moving country by country, right? That's not,

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I mean, I've studied the history of plagues, you know, back to Justinian and it wasn't like that.

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It was this core, this town, right? It wasn't now it's the Roman Empire, right? Now it stopped at

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this border now it's left over to, you know. Well, I mean, that is really a very unusual thing

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about this virus is that it seems to know where all the national boundaries are. Right, right,

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exactly. I'm not buying that. But anyway, I'm going to hand over to Jessica in a minute,

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but just as a sort of segue into that, just to point out our Italy analysis, which is one of

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Canada's most commented papers, actually, is the paper that I wrote in I think the September

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October last year, which raised the question of whether there was actually evidence of spread,

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or rather the simultaneous imposition of a set of conditions on the population.

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There was only so far we could go in terms of the Italy analysis, mainly for language reasons.

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It's quite difficult as an outsider to dig into the what data you need, where you might get it,

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make FOI requests for you as you call them for your requests and so on. This is where

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I'm going to hand over to Jessica because what we've basically done is we've repeated that analysis

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or part of that analysis for New York City. Okay, because one thing in just wanting to

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just make sure I understand everything you're saying, your thesis is that it's not,

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it may not be COVID that killed all those people simultaneously all at once in Italy. And now

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you're about to explain in New York City, it might have been the lockdown conditions,

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meaning isolation, these horrible protocols and hospitals, fear, multi-generational households,

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but how did you get there? Do I have that correct? You do, yeah. There's an additional twist in the

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New York situation, which may also pertain to the northern Italy situation, but we don't have enough

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information to interrogate it properly. And the additional twist is that we are putting the

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authorities to prove to us that the people actually died, the numbers being claimed actually died.

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I love that and we'll get to that. I just need to ask one question. Forgive me for stopping you

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so often. It's very important and I want to make, if you're right, it's very important and I want

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to make sure everyone watching fully understands what you're saying. How could, if you're right

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hypothetically, that it was the conditions of lockdown rather than the virus that suddenly

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killed all these people in Italy and now we're going to talk about New York City in March of

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2020, how could that happen so fast because lockdowns only started in New York on March 8th

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of 2020? Well, I mean, a lot of the Jessica will expand on this, but there are various different

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mechanisms. I mean, we've got two scenarios. One is that people died quickly and that is explainable

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in some places, although maybe not to the total extent of the number of deaths claimed. That is

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explainable by some of the policies implemented. I mean, first of all, what do you mean? Like,

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how could lockdowns are not going to kill people in three weeks? Remdesivir and ventilators can kill.

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Correct. So I was going to come on to say there are a variety of things that could well have claimed

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people's lives prematurely. I mean, you've got to remember that within any system where,

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particularly when you have elderly people who are basically maintained by quite a complex social

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care and health care environment, it doesn't take much to tip those people over the edge and you

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generate a peak of deaths. I mean, we see it with heatwaves. You see it with heatwaves.

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So people are, if you view the whole social care apparatus around elderly people, including

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their relatives, if you view that as their life support system, disrupt that, who will die.

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Oh my gosh. And so immediately, what I'm thinking about being a New Yorker is that our governor,

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I believe in March and April, moved people with code infections into nursing care homes, which

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we call older care homes, which is totally unheard of. And then there was a rash of deaths in nursing

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care homes. So your hypothesis is that, and this makes human sense, it makes intuitive sense,

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that very elderly people are kept alive by networks of people that making sure they're being looked

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after, making sure they're getting their medication, keeping their spirits up. And if you look,

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hydrating them, if you look very elderly people away in isolation, you don't even need to ventilate

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or remdesivir them necessarily for a lot of them to simply give up. And I will just chime in

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with a data point that I'm sure you've taken into account. But one of our colleagues

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analyzed the death state of four Massachusetts and found that the average COVID death was two

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years older than the average death. So they're counting people who are already dying from COVID,

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who are already at the end of their life spans, whereas I take your point, they may be hanging on

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by a thread, the thread will be extended if people love them and take care of them and come see them

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and keep them going. And it may be cut together if you remove their support system.

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Yeah, I mean, as I say, have a saying that everything was COVID and COVID was everything

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in the sense that, you know, it's the every man's virus COVID. So it's both sneaky and stealthy,

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but then it explodes like a bomb. It apparently is completely unique, but then it causes every

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single symptom anybody can ever think of. Brilliant. Sorry. It's completely mad.

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That is okay. I'm getting a clearer picture now. Thank you so much.

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Ms. Hawkett, please pick up and tell us what you found specifically about when you looked at the

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shirt. So the New York City's spring 2020 mass casualty event, even though I live in Chicago,

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I don't live in New York, has troubled me deeply since 2021, for sure. The data from New York and

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the casualty sustained in New York in 11 weeks, 27,000 extra people died. The equivalent mortality

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wise of about 10, 911 events is many, many magnitudes higher. According to whom,

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what were these? According to data, the federal mortality database, CDC wonder,

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and according to data that I obtained directly from the New York City Department of Health and

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Mental Hygiene, their 2020 vital statistics report. I've obtained a lot of data from them

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and other New York City agencies, especially on a daily basis. But yeah, about 26, 27,000

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extra deaths in 11 weeks. Huge mortality event. We do not have the names of the dead. In fact,

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journalistic efforts have only uncovered about 2,500 or so names from that event. There are no

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death certificates. There's no way in New York state to get death certificates so that we can

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simply verify that this event occurred. And I want to be clear about that too. My contention

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or my suspicion is that we have a major fraud event at work with New York City. And not just

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in terms of cause of death with noise, it's a COVID death, which is not a COVID death, but in

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so far as what the city and the federal government are claiming about the number of people who actually

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died each day on the ground in real time, in the settings that they are claimed to have occurred.

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All right. Wow. Strong words. So let me again try to understand exactly what you're saying.

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You looked at data for New York City from two government sources. One was federal, a CDC managed

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database, and one was municipal, a New York City health and mental health data. So that's

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where the all cause mortality. But then we have multiple, what I've been doing, especially over

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the past year and a half or so in earnest, is gathering multiple and different kinds of data,

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not just death data, but ambulance dispatch data, hospital occupancy data, emergency room data, 911

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call data, to really try to understand what the heck happened here. Why doesn't anybody want to

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talk about it and do all these data points fit together. Right. We have this massive spike that

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happened nowhere else in magnitude or speed. When you say this massive spike, you're talking about

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the 27,000 extra deaths higher than expected in what time period in the time period of mid-March

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2020 to the end of May 2020. Most of that, most of that mortality occurred within about four to five

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weeks, though, use that last week period as the spring 2020 event. Okay. So jumping in, do the

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municipal data about these 27,000 purported extra deaths match the CDC data about the

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purported extra deaths? No, not exactly. It's a little complicated to explain, but there are

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discrepancies. I've written about them on my on my sub stack on the order of maybe 1000 or so deaths.

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So it's not, it's a significant number, but it's not an explanation for the 27,000.

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That important. All right. Moving on, you're saying that you're trying to identify these

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individuals by death certificate. Is that correct? Well, no, I'm saying these individuals have not

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been identified. Who hasn't identified them? Nobody has identified them. We don't have to do

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isn't that due to medical privacy laws? No, not necessarily. A vital record is different from

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a medical record. In many states, you can obtain that certificates via FOIA, even with names on

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them. That's not the case with the names in every state, but with some people like Minnesota,

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I think somebody obtained every death certificate, just the basics, right? Someone so died on this

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day. These really attributed causes. And this is where they die. You can't even get that in New

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York City. And when it comes to jumping in, what is this an anomaly? Would you have been in the past

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able to make? Let me make a connection with you. This is the largest mass casualty event in New York

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City ever. And I would say almost in any in any city in US history ever. And there is no

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proof of these deaths. We have to jump in. I've got to jump in. I'm sorry. I have to ask.

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I'm asking if that's an anomaly, meaning if you were to FOIA, the 3000 people who were said to

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have died in the Twin Towers on 9-11, would Jessica Pocket have been able to FOIA proof of

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all those individual's deaths? So for 9-11, 9-11, they released the names.

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But no one verified them to my knowledge the way you are wanting. I'm asking if

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we need either names of all these people who are alleged to have died during this event,

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and or death certificates, preferably both. So I've looked at the databases for these

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purported deaths for my book, The Bodies of Others. I saw what you saw, which is totally

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unverifiable because they are strings of numbers rather than any individual names. What I'm saying

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is, is that a departure? Isn't that standard practice? And I run a tech company. So I'm asking

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this from a nerdy point of view, for data stats, where you have to conceal people's identity for

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privacy reasons, you would as a coder assign them a number. So I'm asking you... In Illinois,

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I could get every death certificate if I submitted a FOIA. So I'm saying it varies from state to

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state. And in New York state, current law does not permit me to get death certificates

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in the same way that John Bodwin did for Massachusetts. But I think more broadly,

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and this is really important, is that the government should not be able to claim that an event occurred

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without especially one of this magnitude, especially one that was used to scare the world,

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lock up children, and hurt people, force them to take a vaccine, and not have to prove the event.

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It's true as 11 that the death certificates to my knowledge have not been attempted to be

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obtained. But we have a list of names at the very least. All right. So now I understand.

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So you are balked by the fact that these data sets, which is indeed frustrating,

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are strings of numbers rather than names. And you don't know if these are real people.

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You're saying that this death pattern departs from what you'd expect to see.

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I understand that due to privacy laws in New York state, they don't have to release the names of

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these individuals to you, right? Even with, even with a FOIA. So I guess what I'm trying to understand

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is, therefore, this is the point you've reached where you're saying this is an anomaly. We can't

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confirm these people. Now we're asking New York City authorities to verify that these people are

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real people who actually die. Is that correct? Sure. Yeah. That's a big piece of it. And the

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different data sets and data points don't fit together. One example is that New York City hospitals

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claimed and the media claimed that New York City hospitals were overrun with patients.

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Data are clear. They were not overrun with patients. ED visits, visits to the emergency department,

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plummeted 60% and at the same time, we have an extra 20,000 or we had not extra 20,000, excuse me,

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extra maybe 16 or 17,000. I'm pulling the number from my head of people who died during that period

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in New York City hospitals to put it differently. New York City senior shows an occupancy,

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so that means, you know, how many patients were in beds. They show a peak occupancy in that period

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of 20,000 in patients. Their data shows about 20,000 inpatient died. It would be the biggest mass

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casualty event by far in a hospital system anywhere. Imagine you can just picture that.

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Yeah. No, I am scared to tingle bed. By the way, just to correct something that you said,

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if you don't mind, Naomi, you gave the impression that we had access to kind of anonymized roles,

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role calls of the people who died. We don't even have that. It's not like you said strings of

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numbers, replacing names. We don't have even that. All we have are totals on spreadsheet.

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Yeah. That's not okay. No, it's not okay. The New York Times has more than that, right? I mean,

25:19.120 --> 25:28.240
at a state level, they have data sets where each individual purportedly has a line. So you really,

25:28.240 --> 25:33.520
so that that's really a smoking gun there because you really can't check line by line, right? You

25:33.520 --> 25:41.840
can't check that this individual who was said to have died in Queens on March 22nd

25:42.480 --> 25:48.720
matches an individual, matches a death in Queens, right? So interesting. So is that the case for

25:48.720 --> 25:54.880
both sources of data that that both the CDC and the municipal authorities are just giving totals

25:54.880 --> 26:02.400
and not individualized spreadsheets? Is that correct? Yeah. By individualized spreadsheets,

26:02.400 --> 26:09.360
you mean like line by line death? Right. I mean, CDC wonder you cannot search individual. CDC

26:09.360 --> 26:14.400
wonders the federal databases like where all the death certificates go or the data from them,

26:14.400 --> 26:21.680
and you can't search necessarily individual deaths, right? To see what a death certificate

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says. And to be clear, we're not talking about releasing autopsies for everybody who had an

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autopsy. That's not what I'm asking. Just ask if every individual death has a line on a spreadsheet

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and what you're getting at. We do not have that for New York State or New York City,

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and it's not obtainable under state law. All right. So let thank you for explaining. So

26:44.560 --> 26:53.520
devil's advocate, people I knew who worked in pharmacies in high-death areas said that

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a lot of people were being found dead at home and never meet at the hospital. Could that help

27:00.320 --> 27:05.200
explain the anomalies that you're seeing? Yep. And I'm going to be writing about that further in

27:05.200 --> 27:11.360
the coming weeks, but really high percentage or really high increase in deaths occurring at home

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very quickly in New York City. And what I've what I found is that people did call 911. 911 calls

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were they spiked crazy and immediately with the 15 days to slow the spread. Ambulance

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dispatch data, we have some anomalies in that data that another associate and I are exploring.

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We're getting a lot of run around from the fire department of New York on the anomalies that we see,

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but ambulances were dispatched, but dispatches transporting patients from the point of pickup

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to somewhere else, like to the hospital. We're down. Whoa. Down. Ambulances per not dispatches

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per now patient dead. Yeah. Holy cow. So I mean, arguably people would choose not to go into a

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hospital in New York at that time. Trust me, I lived in New York. Yeah. Well, and they were told

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to stay home. They were told to stay home. But that doesn't explain. Would that explain

28:20.000 --> 28:25.200
deaths at home? Would those be people who would have died anyway, but chose not to go to the hospital?

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Yeah. And I think there's some of that. And I used to think that that was almost entirely

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the next explanation. I mean, you think about a guy, even who lives in a rent control department

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on the upper east side, you know, and you tell him to stay home and suddenly he's not going out,

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he's petrified, right? Like, could he have a health event? Yes, absolutely. But through our

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research, we found that ambulances and EMS was given, they were given orders that directed them

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away from bringing people to the hospital. No. Under two auspices, one under the, and we have

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the orders themselves. Two auspices were hospitals are overrun and we don't want the

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hospitals to be overrun. We want to control and we want to control spread. So the specific

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directive that was given about a cardiac arrest, patients in cardiac arrest, was basically, and

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I'm summarizing here, don't administer whole life saving measures. It was basically what

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EMS were told. And the orders that were given, you have to administer them even in the person's

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home. Right. So not, not don't administer it all. That's not quite what the orders say. But there's,

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the directives are written in such a way where there's discouragement on administering full life

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saving procedures to cardiac arrest patients, almost a kind of DNR really. In the home or in

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or say, in the home and at the point of pickup, correct. So arguably, EMT workers are being

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instructed not to do everything possible to help save someone dying of a heart, very sick with

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heart attack in your home. The person dies, then is that classified as a COVID death? Like,

30:24.400 --> 30:29.920
how does this relate to COVID? Well, yeah, we have, we have that data to suggest that

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that some people who made who died of cardiac arrest or heart deaths in their home,

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if they were tested, if they tested positive, if the body tested positive,

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then it was counted as a COVID death. And if not, it wasn't. But the biggest increase in those

30:48.160 --> 30:53.200
weeks in home death is, is heart deaths. Oh my gosh. Heart deaths.

30:53.200 --> 30:59.040
Right. So this is so scary. So you're, this, now you've really got another smoking guy.

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He's explaining and no wonder you're getting the run around from a department,

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pardon me, people were given who, who ordinarily would have saved people's lives who are having

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cardiac symptoms and or brought them to the hospital, were being told essentially not to do

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everything possible to save their lives and not to bring them to the hospital. Then these people

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died and that's part of the 27,000 spike anomaly of spike in death. By the way, it's worth pointing

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out that there are studies that show that during periods of high stress and war. So for example,

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post 9 11, there are some, as there are some studies showing that there were spike, there are

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definite spikes in acute cardiac episodes, myocardial interactions. And that's just for a,

31:48.880 --> 31:55.840
you know, a relatively short sort of period of fear and dystopia. This went on for weeks

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and was relentless, the stress on people, absolutely relentless.

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Yeah, for sure. Okay. Well, that's a huge chunk, a huge question that needs to be answered.

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And one more piece to that that I did not know and discovered only within the past six weeks or

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so, there were, I'll call them reimbursements that the federal government gave to ambulances

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for not, I'll say for not coming to the hospital. So normally an ambulance company would get certain

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reimbursements or payments when you transport a patient to the hospital, right? But these ambulances

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were being directed or encouraged to not bring people to the hospital, but they were still

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reimbursed as though they did. Right. So that incentivizes them not really to make that's exactly

32:47.280 --> 32:54.960
right. If you subsidize something, you get more of it. Right, of course. So, so hospitals, I mean,

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an interesting question is were hospitals making more visits than usual, because they would have

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had the chance to go here, this person dead, go here, this person's dead, go here, rather than

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spending two or three hours getting someone to the hospital and going back out.

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Can you read, can you say that again? It's another question. It's just if hospital,

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I'm wondering if EMT visits in a given day and up because they did not have to

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bring the patient to the hospital in order to make the same amount of money.

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You mean the dispatches? The dispatches, yeah. In other words, you can see 15 people in

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their homes in a day, if you're not bringing them to the hospital, maybe seven in a day,

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if you're going back and forth to the hospital. Sure. I mean, and from the hospital end,

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like we know that the ER visits were down. Well, ambulance dispatches transporting patients

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will give you a certain percentage. I think in New York, we figured out it was like at least

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25%, if you just do the ratios, you know, would be people brought by an ambulance.

34:04.000 --> 34:09.120
Well, I understand. I have no doubt that people were staying away from the hospital,

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but again, when you look at the 911 call data, it goes way up. So people were calling for help,

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it was coming, but help was not helping. That's what I said.

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And help was incentivized not to help. That's really scary and disturbing.

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All right. Do you have anything else that suggests that this anomalous spike has something fishy

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about it? You know, I think one thing, and this is feedback that Jonathan and I get a lot,

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I think one thing that sort of wakes people up when they finally realize it, when I'm showing

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them different things on Twitter or wherever, is the number of young adult deaths during this time.

34:49.760 --> 34:56.000
Very quickly, and the number of young adult or younger, I should say, adult by 50 ages, what,

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25 to 54, the number of younger adult deaths in hospitals, nearly all of which were attributed

35:05.280 --> 35:13.840
to COVID, which doesn't make sense because this is not even a generous definition or thought about

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how deadly COVID was or wasn't in this time period, you would not have seen a very high

35:19.680 --> 35:26.720
proportion of young deaths. I mean, just go ahead. You know, as you say, a quick stat on that,

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which I find extraordinary, is that 25% of all the COVID attributed deaths in the USA

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occurred in New York City when, in fact, only 3% of the people in that age group, we're talking

35:46.800 --> 35:56.960
about 25 to 45 years old, something 25 to 45, I think, 25% happened in New York City, only 3%

35:56.960 --> 36:04.720
of the age group of Americans live in New York. So something is either false in the data or there

36:04.800 --> 36:10.880
is some big problem with treatment. Okay, so you're saying a disproportionate number of younger

36:10.880 --> 36:20.320
adults died in New York than you'd expect to see given that only 3% of the US population

36:20.320 --> 36:25.440
of that age group lives in New York. Okay, theory there, or what evidence do you have

36:26.080 --> 36:32.240
supporting, is it just an anomaly in the data? It's an anomaly, which is just yet another data

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point which we're putting the authorities to prove. How does that happen? I mean, it can't be

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explained by social factors because New York is not a poor city. It can't be explained by

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obesity. New York is not particularly obese compared to some other places. You know, there's no

36:52.240 --> 36:58.720
rational explanation for it. Was it claimed that these were COVID deaths, like it was?

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Well, I know that the media was desperate to produce young healthy COVID. So let's go now,

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unless there's anything else you want to make sure to bring forward. We're running long time

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in the last couple of minutes. Let's highlight how you're putting the authorities on notice because

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given HIPAA protections, it's going to be hard to drag them into the light of day to account for

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these anomalies. What are your plans or what's underway? I think the first thing that we're

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trying to do is to continue. I have a lot of data. I have a lot of correspondence with different

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New York City agencies that I'm trying to put out a little bit at a time. I'm fighting a New York

37:40.080 --> 37:46.880
Health and hospital on data that they refused to release, but should. So, you know, I'm sort of

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simultaneously keep investigating and trying to get exposure through the channels that I can.

37:54.240 --> 38:00.240
It can be difficult when, you know, even fellow anti-mandate people don't seem to want to talk

38:00.240 --> 38:06.720
about New York City 2020 or early 2020 at all and say, what the heck happened? You brought up

38:06.720 --> 38:14.320
Remdesivir and ventilators, and I don't dispute that, but we don't even have data on how many

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New York City hospital patients were given Remdesivir. I've done several articles on the ventilators.

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I'm sorry to say, we don't have the data that we need to say even how many people were put on

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ventilators. I guess I certainly understand and empathize with the hurdles facing you, and I

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admire your persistence. I'm asking, you know, a practical question, right? Given HIPAA law,

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which they're going to say keeps them from telling you exactly who died, and the mechanism

38:47.600 --> 38:54.960
of FOIA, which I'm not sure you're using, right? What mechanism are you, like, apart from badgering

38:54.960 --> 38:59.680
people and trying to get exposure for this anomaly, which I applaud, and that'll move

38:59.680 --> 39:03.520
dial a little bit, but you really need more data, right? They're keeping.

39:03.520 --> 39:07.120
Well, we need more data, and we need more people who care about this. This shouldn't be just a

39:07.440 --> 39:11.280
hockey Jonathan angler thing. This should enrage, really.

39:15.280 --> 39:20.720
Well, we're on your show. You know, I'll go on and talk to anybody. I'll debate anyone. I'll

39:20.720 --> 39:27.360
talk to anybody. I'll put a graph to anyone. You know, I'm not a media strategist. You tell me,

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I really don't know how to get people to care about this. If there's a mass casual, the biggest

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mass casualty event in New York City history, and we don't have proof of it, that's unfortunate.

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But I think all the questions you're asking are legitimate for what it's worth in the body's

39:43.920 --> 39:49.120
others. I found that the New York Times was able falsely to claim that there were so many dead

39:49.120 --> 39:53.680
people that we needed refrigerated morgue trucks by not reporting the fact that there had been

39:53.680 --> 40:01.840
a stoppage from the governor on barriers, right? So I'm entirely rolling. I think these are very

40:01.840 --> 40:07.600
important questions. You know, I want to see you succeed in getting answers because they

40:07.600 --> 40:12.160
affect all of us. They were critical to the whole narrative. And, you know, again, I'm in

40:12.160 --> 40:17.520
New York or this was a very painful, awful time. And if people were doing bad things like not

40:17.520 --> 40:22.960
resuscitating people having heart attacks in their homes, that is, you know, really, really, really

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important. I guess what I'm saying is we can certainly spread the word. You're missing

40:31.360 --> 40:35.440
some critical piece of information that the authorities are not going to give you, right,

40:35.440 --> 40:42.960
voluntarily. So I think Panta needs to sue for the rest of the information, right? We can certainly

40:42.960 --> 40:48.000
put you in touch with lawyers who will do that if you don't have your lawyers in house. But

40:49.440 --> 40:53.600
apart from that, I can't really think of what else you can do except exhaust yourselves,

40:54.400 --> 40:59.280
asking these people who may have committed a giant fraud to produce more information. Am I

40:59.360 --> 41:06.400
missing something? No, you're not saying I just I wish I wish more people cared about what happened

41:06.400 --> 41:10.960
in 2020 since it was used to coerce, you know, forced medical treatments on, you know, millions

41:10.960 --> 41:18.960
of people. What the heck happened? I totally agree with you. I guess what what I'm trying to

41:19.840 --> 41:26.880
try to share with love, you know, as someone who's who's been in the trenches a long exhausting

41:26.960 --> 41:34.000
time, you know, as you have no doubt as Panta has is everyone listening, especially New Yorkers,

41:34.000 --> 41:40.640
cares about what you just said. But there are missing pieces before it can be news, right,

41:40.640 --> 41:48.480
before it can enter the new stream. And before there can be hearings, for instance, or lawsuits,

41:48.480 --> 41:55.360
right? And so to get those missing pieces, right, we need to find out if you're asking a provocative

41:55.360 --> 41:59.680
question, did 27,000 people really die? And COVID, and the answer is yes.

42:01.200 --> 42:04.640
I'm asking if 27,000 people extra people actually die.

42:05.200 --> 42:13.280
Right. Okay. Totally provocative question. From what I understand, you've battled your way

42:13.280 --> 42:19.200
to the end of that question, right? You're expecting more FOIA results. But I don't know that you have

42:19.760 --> 42:27.120
answered it with yes, for sure, it's fraud, or yes, for sure, they died, or yes, it was

42:27.120 --> 42:33.920
fraud and murder. We don't have those answers yet, right? So that's where the next step in my view

42:33.920 --> 42:40.640
needs to come in, which is, you know, legal, right, so that you said people are forced to

42:40.640 --> 42:45.520
hand over those records. At least that's what I'm hearing. I mean, I'm not sure. I can promote

42:45.520 --> 42:52.480
this and everyone will say what an interesting question, how alarming. But I, as a, as a, you know,

42:52.480 --> 42:59.280
someone who cares about this issue and wants to get to the heart of it, as a reporter,

42:59.280 --> 43:05.200
I'm in a standstill because I can't now go to the rest of the world and say, I know what happened.

43:05.200 --> 43:10.320
There was malfeasance here. I know there was fraud. What we've got are some very big important

43:10.320 --> 43:17.200
questions, right? If I can summarize what you're basically saying, I think, is that we're in a

43:17.200 --> 43:23.600
position where we've thrown the story out there and we're expecting the baton to be picked up by

43:23.600 --> 43:32.320
people who are enraged and who then apply political pressure to political people to pass executive

43:32.320 --> 43:38.320
orders or whatever, so that this is thoroughly investigated. And I think what you're saying is,

43:38.320 --> 43:41.920
no, that's not going to happen. You have to go more onto the front foot. That's what I'm saying.

43:41.920 --> 43:49.680
Basically, in terms of, and yeah, I mean, just to, Panda is not a big organization with huge

43:49.680 --> 43:56.800
resources. So we would struggle to sort of prosecute a legal case, but we possibly could do so with

43:56.800 --> 44:02.720
the assistance of, you know, some public funding for it from, you know, all right, well, let's end

44:02.800 --> 44:09.520
it there. That's a great action step. That's a great call to action. Everyone, Dr. Engler and

44:09.520 --> 44:15.600
Ms. Hockett have battled valiantly. And I hope you understand when I was pushing you, it's just like

44:16.560 --> 44:20.880
to drag this corpse into the light of day so people can see exactly what you've got.

44:22.240 --> 44:30.960
You know, they didn't work in raising really important questions and finding what I think are

44:30.960 --> 44:38.480
several smoking guns, right, that require investigation, certainly the directives to EMTs.

44:38.480 --> 44:42.800
That's like terrifying. I mean, I say this as someone who nearly died in a New York State

44:42.800 --> 44:47.440
Hospital recently. We don't know if those directives have been rescinded, right? We don't know if it's

44:47.440 --> 44:51.920
safe to put your left one in a New York State Hospital at all, right? This is the state that wants

44:52.560 --> 44:58.080
quarantine camps. They still want quarantine camps. So I think what you've done to date is

44:58.080 --> 45:03.680
incredibly important. I would like to think that people, especially New Yorkers listening,

45:03.680 --> 45:10.800
will hear you and go, this is madness. We need to oblige these agencies to turn over what they're

45:10.800 --> 45:16.320
withholding. As you know, I don't think that will happen even because, you know, Mayor Adams,

45:16.320 --> 45:22.080
who's himself under investigation, doesn't have the power probably to compel some of these agencies,

45:22.080 --> 45:28.880
certainly not at the federal level, but even, you know, even different fiefdoms in New York State

45:29.840 --> 45:35.600
have their own lawyers, right, and can resist even Mayor Adams' call. I mean, I don't know all the

45:35.600 --> 45:43.680
mechanisms of municipal secrecy in New York City, but it's a very not transparent city in a not

45:43.680 --> 45:49.040
transparent state run by, like, I guess what I'm trying to say is the agencies who have the data

45:49.040 --> 45:55.200
you're asking for were directed by the chief murderers or fraudsters, right, whether it's

45:55.200 --> 46:01.040
Andrew Cuomo or, you know, now Governor Hochl, and so they have an incentive to not turn it over

46:01.040 --> 46:07.680
and to wait out the furor. So now I'll stop there. I don't mean to be a downer, but I think that this

46:07.680 --> 46:15.920
absolutely requires more investigation. And I would say a lawsuit is critical, you know, so that you

46:15.920 --> 46:22.560
can have discovery. And so I would say if people want to send you money to fund a lawsuit, should

46:22.560 --> 46:28.320
they send it to Panda, does Panda want to think about it? What's, do you want to come back to me

46:28.320 --> 46:36.720
later and tell me what come back to you, back to you later on that? Yeah, there's a fund for that,

46:36.720 --> 46:45.760
I think. Yeah, right. So let's stop there. You've shaken me to the core. I think this is definitely

46:46.080 --> 46:50.480
an important thing to investigate further. I want to thank you both for the tireless work you've done

46:50.480 --> 46:56.640
to this point. We're proud to bring your work to the forefront. We also are going to bring this

46:56.640 --> 47:02.160
to our data scientists who may have some ideas about how to mine the data you have in order to

47:02.160 --> 47:09.760
see if there's any more that can be served as to. And, you know, we love Panda, we love, you know,

47:09.760 --> 47:14.400
your leadership on this issue, where can people find you otherwise? And then we should probably sign

47:15.200 --> 47:20.720
up. So they can find me. I mean, I write for both Panda's substack and heart substack,

47:20.720 --> 47:25.520
and also where are the numbers, which is Professor Norman Fenton and Martin Neil's substack. On

47:25.520 --> 47:34.000
Twitter, they can find me at, my Twitter handle is at Jay Engler UK. One word. Fantastic. Thank

47:34.000 --> 47:40.880
you, Dr. Engler. And how about you, Ms. Hockett? I'm at Woodhouse76.com and at Wood Underscore

47:40.880 --> 47:46.720
House76. My former Twitter name was Emma Woodhouse, which, you know, back back in the day,

47:46.720 --> 47:52.640
people might remember me when I was under that eponym fighting command date. So yeah, delighted

47:52.640 --> 47:59.040
to be on your program. Thank you so much for having us. Thank you both. And if there's a wealthy

47:59.040 --> 48:04.880
patron or two out there listening who wants to get to the heart of whether 27 extra people died

48:04.880 --> 48:14.800
in New York in spring, 20,000 extra died in the spring of 2020, thus allowing the whole narrative

48:14.800 --> 48:21.200
to unfold, please contact them or us. And if they contact us, we'll send them to help you with this

48:21.200 --> 48:25.440
critical, in my view, important lawsuit and further investigation. And let's also throw it out to

48:25.440 --> 48:30.160
all the independent media to look into it further as well. Thank you so much for all you're doing.

48:30.960 --> 48:38.400
Hey, everyone, it's Naomi Wolf of Daily Cloud. And I just want to give a thank you to our sponsor,

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of big pharma. Please use the code dailycloud for 10% off. Thank you again to the Wellness Company,

49:29.680 --> 49:31.200
our sponsor. Bye bye.