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3656 lines
121 KiB
3656 lines
121 KiB
WEBVTT
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Hell's thing 1, 2, tells 2, 1, 2...
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BEEP BEEP!
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LAUGHTER
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Ahem...
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That should be okay...
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Yes...
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That should be just best...
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Ahem...
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00:30.000 --> 00:42.000
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I should also point out that our viewers will have noticed that we are sitting here unmasked,
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00:42.000 --> 00:45.000
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and I should point out that actually we are, in an interesting sense,
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a model of something that I believe is not on the public radar.
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00:50.000 --> 00:54.000
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So, if I'm correct, you, Robert, have had COVID.
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I've had COVID.
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Technically speaking in the chat, I am Katniss.
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00:58.000 --> 01:00.000
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It's first, Kristi...
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01:00.000 --> 01:01.000
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I've been vaccinated.
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01:01.000 --> 01:03.000
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You missed it by a hair, I'm afraid.
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01:03.000 --> 01:07.000
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Alright, I am unvaccinated, but I am on prophylactic ivermectin,
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01:07.000 --> 01:10.000
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and the data actually, shocking as this will be to some people,
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the data suggests that prophylactic ivermectin is something like 100% effective
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at preventing people from contracting COVID when taken properly.
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01:19.000 --> 01:24.000
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So, aside from the risk that possibly the ivermectin I got wasn't real,
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01:24.000 --> 01:30.000
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and I have every reason to think it was, it certainly appears to be the genuine article.
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01:30.000 --> 01:35.000
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I believe that what we have here is a demonstration of a kind of composite herd immunity,
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where through three different routes, COVID, vaccine, and ivermectin, we are protected,
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01:41.000 --> 01:43.000
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and you are doubly protected.
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01:43.000 --> 01:47.000
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So, I would just say that for anybody who's enthusiastic about the vaccines,
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if you're unconvinced by what we have to say about the hazard of them,
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01:50.000 --> 01:54.000
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one thing to consider is that the way to get society to herd immunity,
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01:54.000 --> 01:58.000
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and therefore drive COVID-19 to extinction, which ought to be our goal,
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the way to do it is to get people into this category one way or the other.
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02:02.000 --> 02:05.000
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Whether that's through prophylaxis, whether it's through a vaccine,
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02:05.000 --> 02:08.000
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or whether it's because they've had COVID already.
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02:08.000 --> 02:14.000
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One could argue that if everybody just took ivermectin for a month,
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worldwide, really independent.
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02:17.000 --> 02:21.000
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And someone will find the title that I have given in this episode.
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02:21.000 --> 02:25.000
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I would ask them to stick with the episode.
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02:25.000 --> 02:28.000
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I'm telling you why I titled this idea.
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02:28.000 --> 02:34.000
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I really believe that actually we have the capacity at any moment we decide to utilize it
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to end the pandemic and that it is well within reach
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should we choose to see what is in front of us.
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02:41.000 --> 02:44.000
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What I want is high morbidity.
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02:44.000 --> 02:46.000
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I want people to complain.
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02:46.000 --> 02:48.000
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What I do, I go to Des Moines.
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02:48.000 --> 02:51.000
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Ladies and gentlemen of people on the screen, I have nothing against Des Moines.
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02:51.000 --> 02:53.000
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I live there for four years. I go to Des Moines.
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02:53.000 --> 02:56.000
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I infect a couple of Sentinel cases in Des Moines.
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02:56.000 --> 02:59.000
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I go to Seattle. I infect a couple of cases there.
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02:59.000 --> 03:06.000
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Annie Wershing was my friend in Chicago in the time before I moved to the Netherlands.
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03:06.000 --> 03:11.000
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And we worked at the same bar called Shuba's.
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03:11.000 --> 03:19.000
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We spent about two years together as friends, whatever.
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03:19.000 --> 03:23.000
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We had a lot of good times with a lot of different people.
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03:23.000 --> 03:30.000
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It was a really interesting time in my life as a bartender and a high school teacher
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03:30.000 --> 03:33.000
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and not really knowing what I wanted to be yet.
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03:33.000 --> 03:39.000
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And she moved to LA, met Steve in Chicago before she moved to LA.
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03:39.000 --> 03:41.000
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He's a voice actor.
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She had to take the shot to be on that set upstairs up there.
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03:46.000 --> 03:52.000
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And she got a pretty advanced brain cancer and died on January 29th, 2023.
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03:52.000 --> 04:00.000
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I'm 100% sure it's because she was forced to be transfected and boosted in order to be on set in Hollywood.
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04:00.000 --> 04:05.000
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And they did it to a lot of people and they did it with a worst-case scenario narrative.
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04:05.000 --> 04:07.000
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They're all guilty.
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04:08.000 --> 04:14.000
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And as a consequence of doing that, what I do is I create a schism between the polis and the public health system.
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I fracture the integrity of trust and reliance upon the population and its government.
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I'm not going to do that.
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04:39.000 --> 04:40.000
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I'm not going to do that.
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04:40.000 --> 04:41.000
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I'm not going to do that.
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04:41.000 --> 04:42.000
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I'm not going to do that.
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04:42.000 --> 04:43.000
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I'm not going to do that.
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04:43.000 --> 04:44.000
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I'm not going to do that.
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04:44.000 --> 04:45.000
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I'm not going to do that.
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04:45.000 --> 04:46.000
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I'm not going to do that.
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04:46.000 --> 04:47.000
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I'm not going to do that.
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04:47.000 --> 04:48.000
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I'm not going to do that.
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04:48.000 --> 04:49.000
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I'm not going to do that.
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04:49.000 --> 04:50.000
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I'm not going to do that.
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04:50.000 --> 04:51.000
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I'm not going to do that.
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04:51.000 --> 04:52.000
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I'm not going to do that.
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04:52.000 --> 04:53.000
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I'm not going to do that.
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04:53.000 --> 04:54.000
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I'm not going to do that.
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04:54.000 --> 04:55.000
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I'm not going to do that.
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04:55.000 --> 04:56.000
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I'm not going to do that.
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04:56.000 --> 04:57.000
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I'm not going to do that.
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04:57.000 --> 04:58.000
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I'm not going to do that.
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04:58.000 --> 04:59.000
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I'm not going to do that.
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04:59.000 --> 05:00.000
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I'm not going to do that.
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05:00.000 --> 05:01.000
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I'm not going to do that.
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05:01.000 --> 05:02.000
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I'm not going to do that.
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05:02.000 --> 05:03.000
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I'm not going to do that.
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05:03.000 --> 05:04.000
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I'm not going to do that.
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05:04.000 --> 05:05.000
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I'm not going to do that.
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05:05.000 --> 05:06.000
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I'm not going to do that.
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05:06.000 --> 05:07.000
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I'm not going to do that.
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05:07.000 --> 05:08.000
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I'm not going to do that.
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05:08.000 --> 05:09.000
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I'm not going to do that.
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05:09.000 --> 05:10.000
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I'm not going to do that.
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05:10.000 --> 05:11.000
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I'm not going to do that.
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05:11.000 --> 05:12.000
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I'm not doing that.
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05:12.000 --> 05:13.000
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I'm not doing that.
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05:13.000 --> 05:14.000
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I'm not doing that.
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05:14.000 --> 05:15.000
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I'm not doing that.
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05:15.000 --> 05:16.000
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I am not going to do that.
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05:16.000 --> 05:17.000
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I've not done that.
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05:17.000 --> 05:18.000
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I think I've never done it.
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05:18.000 --> 05:19.000
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I think I've never done that.
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05:20.000 --> 05:21.000
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I think I've never gone.
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05:21.000 --> 05:22.000
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I've never gone.
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05:22.000 --> 05:23.000
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I think I've never gone.
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05:23.000 --> 05:24.000
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I think I've never gone.
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I think I've never gotten.
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This schedule for 60 minutes next is going on French, British, Italian, Japanese television.
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People everywhere are starting to listen to him. It's embarrassing.
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I feel so nervous. Like what in the world, man?
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Ooh, we had a little glitch there. We got to catch up on that one.
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06:47.000 --> 06:50.000
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There we go. I think that's good.
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07:17.000 --> 07:46.000
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So a little bit rusty here, a little bit rocky road here.
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Sorry about that. We are getting another show in tonight.
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I thought I would do a little relaxing one instead of always trying to be so on point.
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07:59.000 --> 08:07.000
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Mark Housatonic did a wonderful short video today on his third channel on YouTube.
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If you haven't checked it out, I would highly recommend it.
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08:12.000 --> 08:16.000
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He may have cleaned it up and put it on some of his other channels.
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08:16.000 --> 08:24.000
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And if that's the case, then also make sure to check those out as well.
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That's a little loud to me, but we'll see here.
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08:31.000 --> 08:37.000
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I can definitely see the brick wall at the back of the theater. I hope you can see it too.
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08:37.000 --> 08:43.000
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We are becoming more and more the biology that is much easier for them to ignore.
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08:43.000 --> 08:48.000
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The new pivot is to ignore us.
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08:48.000 --> 08:52.000
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So we're just going to keep doing the work that we're doing.
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We're just going to keep talking to the talk and walking the walk.
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08:56.000 --> 09:05.000
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If they can't keep up, they're not going to get rained on them because they're all stuck in the cave.
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09:05.000 --> 09:14.000
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So if we make our way out, and other people don't follow, I don't think we really have to worry about it too much yet.
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09:14.000 --> 09:19.000
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After we've mapped this all the way out, we can help the rest of the people get out of there.
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09:19.000 --> 09:24.000
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This stream is brought to you by a patch clamp physiologist, retired.
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A patch clamp physiologist is an expert of making giga-ohm seals with...
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Borosilic and glass pipettes and making very high-resistance low-noise recordings from neurons.
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09:39.000 --> 09:46.000
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Sometimes the live brain slices are even live animals, and so that's why we decided to call this the giga-ohm biological,
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high-resistance low-noise information brief.
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You can find me located at giga-ohmbiological.com and you can communicate with me at gigaohm.bio.
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09:55.000 --> 10:00.000
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At the website, you can find my confession at that link called Scooby,
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10:00.000 --> 10:04.000
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and you can find a way of supporting me in a number of different ways.
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10:04.000 --> 10:11.000
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A single link, a schedule, and then at the bottom there are ways to subscribe, either monthly, quarterly, or annually,
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10:11.000 --> 10:17.000
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and it would just be wonderful if we could get enough people to do that,
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10:17.000 --> 10:22.000
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so we could just keep this going two or three times a day.
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10:23.000 --> 10:30.000
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Right now, I think I can swing one, and soon we're going to have one plus a PDF once a week.
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10:30.000 --> 10:36.000
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I think sooner or later, every one of these is going to be up on sub-stack.
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10:36.000 --> 10:39.000
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I did take the weekend off because we had a lot of basketball games,
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but we're going to get back in the groove again here.
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These are the supporters of giga-ohmbiological that make it possible.
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10:45.000 --> 10:48.000
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This list has not been updated in the last couple days,
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10:48.000 --> 10:53.000
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so don't be too ashamed or rather too upset if your name wasn't there yet,
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10:53.000 --> 10:57.000
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because that's just a matter of having too many things.
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11:00.000 --> 11:03.000
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I just converted my garage for a new cat.
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A new cat, what does that mean?
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A new cat is a little nicer than my new cat.
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You're going to tell me what a new what would you convert your garage for a new cat is.
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11:17.000 --> 11:19.000
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We're going to break this illusion of consensus.
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We're in the fifth year. Don't forget to point that out to people.
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Oh, a new car, okay, yeah, yeah.
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And I don't even know who can afford a new car nowadays.
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That's pretty impressive.
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This was probably a conflated background signal.
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Just remember that intramuscular injection of any combination of substances
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with the incentive augmenting the immune system.
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Transmission in healthy humans is permanently negligent,
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and it is the 29th of January, 2024.
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This is the going biologically high-resistance low-noise information
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we brought to you by a biologist.
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We're fighting against this faith in a novel virus that supposedly killed millions,
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but millions more were saved from.
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11:58.000 --> 12:01.000
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It likely came from gain of function, and therefore we'll come again.
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We can't tell this story to our kids, even if the TV wants us to,
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and the way to break this cycle is to teach them the biology that includes
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there's no evidence for spreading New York City infectious clones are the only real threat.
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placebo batches were likely distributed in transmission and healthy mammals is dumb.
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You can remind them that the protocols were mostly murdered,
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gain of function is mostly mythology,
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and the scooby-doo that is being fooled into solving a mystery is real
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because these people are spectacularly committed to lies.
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12:30.000 --> 12:37.000
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Well, this is actually a separate room in the back of my garage.
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It used to be, I guess, a wood shop or something like that.
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It's got a lot of outlets.
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12:43.000 --> 12:47.000
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It's got its own separate heater and air conditioner,
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12:47.000 --> 12:51.000
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and it's kind of got a separate entry door with locks on both sides.
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12:51.000 --> 12:53.000
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It's really like an add-on.
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12:53.000 --> 12:58.000
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It's a really weird, lucky thing to be in the back of my garage.
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12:58.000 --> 13:04.000
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I have a renting house in Pittsburgh that I had to take because I had to give up the house
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13:04.000 --> 13:09.000
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that I was renting to own because I lost my position at the University of Pittsburgh.
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13:09.000 --> 13:14.000
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I've heard other stories of people losing their homes,
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13:14.000 --> 13:18.000
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but I think I've got the one real legitimate.
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13:18.000 --> 13:24.000
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Anyways, let me switch out of this one.
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13:24.000 --> 13:27.000
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I'm just going to switch out of this one,
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13:27.000 --> 13:31.000
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and I will drop in the other one.
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13:38.000 --> 13:42.000
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So that's probably a copyrighted song, and something's going to get screwed up there.
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13:42.000 --> 13:44.000
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I had that mixed in, correct.
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13:44.000 --> 13:46.000
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And then, good evening, ladies and gentlemen.
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13:46.000 --> 13:51.000
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This is Giga Own Biological, a high-resistance low-noise information brief brought to you by a biologist.
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My name is Jonathan Cooley.
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I am the biologist bringing you that show from the back of his garage in Pittsburgh, Pennsylvania.
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13:57.000 --> 14:02.000
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I am fighting against a few things.
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14:02.000 --> 14:05.000
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I'm fighting against tyranny of the mind.
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14:05.000 --> 14:07.000
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I'm fighting against misleading the young.
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14:07.000 --> 14:14.000
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I'm fighting against this manipulation of our organized habits and opinions.
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14:15.000 --> 14:23.000
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And I believe that for quite some time, our society has been manipulated and led to believe in a mythology about public health
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under the pretense that eventually they were going to shake up our world and start governing us by this mythology.
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14:29.000 --> 14:32.000
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I believe we are at that pivot point right now.
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14:32.000 --> 14:38.000
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I believe we should have woken up much sooner that we were in this pivot point, but we did not.
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14:38.000 --> 14:41.000
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And that is kind of a pity, but you know what can you do about it?
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We're here now, and we've got to make the best of it.
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14:44.000 --> 14:52.000
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The principle of informed consent has been ignored for the duration of the pandemic, and that can be one place to start with our young people.
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14:52.000 --> 15:01.000
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We can also start with just kind of analogy to try and convince them that this elaborate act that they saw in 2020 at the beginning of the pandemic
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15:01.000 --> 15:09.000
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that was kind of like an emergency, kind of like a tornado drill, kind of like a weird, I don't know.
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15:09.000 --> 15:18.000
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Well, it seemed a little forced. And then also the drama between the public health officials and Donald Trump and them laughing behind him and stuff like this.
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15:18.000 --> 15:24.000
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This was all about creating this mystery that you were supposed to solve to try and figure out what were these people up to.
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15:24.000 --> 15:33.000
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Were they trying to hide anything and then getting into arguments in front of people that was all about this.
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15:33.000 --> 15:52.000
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So we know that this pandemic was created by a series of orchestrated plans over a long and a short time scale from seating scientific programs and peer reviewed publications to, to, to form the foundation of pandemic potential
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15:52.000 --> 15:56.000
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to running government level exercises to respond to pandemic potential.
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15:56.000 --> 16:16.000
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And then to have this team of worst case scenario actors on TV and on social media from 2019 ready to go so that when the media and the narrative needed controlling that these people were already there as trusted voices in these alternative spaces.
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16:17.000 --> 16:26.000
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And I believe these are one of the reasons these people are a very important reason why a number of people were taken behind the scenes early on.
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16:26.000 --> 16:38.000
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You may not be aware of the fact that they rolled out the shots in Hollywood on Hollywood sets earlier than they rolled it out in other places.
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16:38.000 --> 16:45.000
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It's similar to how it has been reported by certain people from behind the scenes that it was rolled out on movies.
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16:45.000 --> 16:49.000
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I mean, TV news sets.
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16:49.000 --> 16:59.000
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In other words, TV news programs and the people that participated and worked on staff were kind of more or less coerced into taking the shot.
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16:59.000 --> 17:04.000
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And they were coerced by two things. One, that they were essential workers.
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And number two, that they were being given very special batches of the countermeasure.
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Most or all of them got Moderna. They did this on Hollywood sets.
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And in fact, I know from firsthand accounts that they did it at Hollywood parties over the Christmas season during 2020.
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17:25.000 --> 17:30.000
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I want you to think about that very carefully because not very many people know that.
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It's even possible that Annie took one of those shots because she was offered one of them in a situation like that.
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17:38.000 --> 17:47.000
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But for sure, all of the lowest level people on Hollywood sets were required to take the shot in order to even be on set.
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17:47.000 --> 17:49.000
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Never mind masking.
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17:50.000 --> 17:57.000
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And so this enforced a narrative among people. It enforced a narrative among an entire culture.
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17:57.000 --> 18:04.000
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And that it shouldn't be underestimated how difficult it is to get past that.
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And that's why I do this thing with Star Trek because I really, I had always had the idea that I was going to do some kind of Star Trek episode
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18:16.000 --> 18:23.000
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and make it about immunology. And then I was going to send it to Annie and it was going to stop this whole thing.
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And she was going to help and it was going to get on Instagram and it was going to be all this big deal.
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18:29.000 --> 18:34.000
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Total plan. It was all laid out. I knew what I was going to do.
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18:34.000 --> 18:40.000
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And it was too late but wasn't going to save her family. But, you know, I didn't know.
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18:41.000 --> 18:45.000
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And then it just got on the back burner and on the back burner and it never happened and never happened.
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18:45.000 --> 18:54.000
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And then suddenly I was reminded of the fact that I had this idea to do a Star Trek episode episode from the future.
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18:54.000 --> 18:57.000
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Like a message from the future.
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18:57.000 --> 19:08.000
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And I got the recall because I found out that she was on this this Picard show where she was a Borg Queen who helped them travel back in time
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19:08.000 --> 19:15.000
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to like reset the past so that the bad future didn't happen where Picard was like a bad guy.
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19:15.000 --> 19:20.000
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It was such a weird thing because then I was like, oh my gosh, that's kind of my idea.
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19:20.000 --> 19:31.000
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It was to call back from the future and say that somebody had taught the wrong immunology to the human race in order to ruin the Federation of Planets
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19:31.000 --> 19:34.000
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before it could ever form.
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19:34.000 --> 19:37.000
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So bizarre.
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19:37.000 --> 19:39.000
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And now she's gone.
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19:39.000 --> 19:46.000
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All gone. Like just vanished. Just like Nathan. A whole beautiful family without a parent. Forever.
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19:46.000 --> 19:53.000
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Because of this. Because of bad ideas. Not because of the spread of an RNA.
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19:54.000 --> 20:17.000
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I am absolutely, absolutely serious when I say that I'm probably going to die crazy or angry or jaded unless something absolutely amazing happens in my lifetime.
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20:18.000 --> 20:24.000
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And I'm fine. I am totally fine with it taking the rest of my lifetime, me being 52 yesterday.
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20:24.000 --> 20:31.000
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I am totally fine with it taking the most of the rest of my lifetime in order for this to reset itself.
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20:31.000 --> 20:38.000
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For us to go back to a time when our children could be innocent and biology was sacred.
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20:38.000 --> 20:45.000
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I am totally fine with that.
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20:45.000 --> 20:48.000
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But I'm not fine with this not ever going back.
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20:48.000 --> 20:56.000
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I'm not fine with my kids growing up in a world with this kind of duality.
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20:56.000 --> 21:12.000
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This kind of lack of respect. Lack of reverence. I'm not going to allow it to happen and I hope you won't either.
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21:12.000 --> 21:23.000
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Lots of interesting things. Lots of interesting things happening. Some good, some bad, some questionable, some weird.
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21:23.000 --> 21:28.000
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We've talked about a lot of it and this is the most important part of it.
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21:28.000 --> 21:35.000
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They ignore this. All of them ignore this. You can call me a lot of different names.
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21:35.000 --> 21:39.000
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But in reality, this is the message that I care about.
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21:39.000 --> 21:54.000
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This is the message I want to give to our kids. This is the message that I'd love if we could get to college age kids before they take their HPV shot to stay on campus or something like that.
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21:54.000 --> 22:01.000
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Or actually there are quite a few universities that might make them take a COVID booster in order to be on campus.
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22:01.000 --> 22:07.000
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So I wanted to do a little recap here just to make sure to remind you number one.
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22:07.000 --> 22:21.000
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The last couple of days we did a couple Ralph Barrick videos where we showed that in 2007 it still seemed like he was trying to use coronavirus to kind of harness it as a biotechnology.
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22:21.000 --> 22:41.000
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And he saw it as a resource. He saw it as something that he could manipulate genetically so that he could control it.
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22:41.000 --> 22:59.000
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He could attenuate it and keep it attenuated. It could be a universal vaccine. He was looking at combinations of antibodies that could be universally prophylactic or universally neutralizing against these pathogens across lots of different subtypes.
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23:00.000 --> 23:14.000
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And he wasn't talking about it as a doomsday kind of problem. He was talking about it by a very tractable set of biological questions and a couple really firm ideas about how to tackle the problem.
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23:14.000 --> 23:26.000
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We could make fast, live attenuated vaccines using recombinant viruses that have their translation regulatory sequences altered.
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23:26.000 --> 23:40.000
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And we can also generate monoclonal antibodies from these recombinant viruses in vitro and then make those monoclonal antibodies and use them as prophylactic or as countermeasures.
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23:41.000 --> 23:53.000
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And so in 2007, all the way up to like 2016, he's pretty much talking about it as though it's not a big deal. And then around 2016, it starts to become this potential for pandemics.
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23:54.000 --> 24:16.000
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It starts to become this potential for catastrophe. And they start to have these discussions about the regulation of their work and almost protest too much about the regulation of their work and come up with pretty extreme examples of how in the worst case scenario,
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24:17.000 --> 24:24.000
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regulation of our work could end up making a catastrophe much worse than it should have been if you wouldn't regulate our work.
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24:24.000 --> 24:30.000
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And this went on through 2018 and right up into the start of the pandemic. So what I wanted to-
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24:30.000 --> 24:32.000
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What I want is high morbidity.
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24:32.000 --> 24:45.000
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As I point this out, one of the things that I wanted to remind you is that the second line here, the pre-narrative pre-coopted or pre-selected group of narrative controllers,
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24:45.000 --> 24:52.000
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I wanted you to do a thought experiment with me. And I found a TV show that I think will help us. Actually, I shouldn't say I found it.
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24:52.000 --> 25:03.000
|
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One of your fellow viewers and GigaOM fans found this TV show and thought it would be a very relevant thought experiment for us to do in order to think about how,
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25:03.000 --> 25:13.000
|
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with a pre-selected group of narrative controllers, you could make a bunch of people believe something very, very wrong for a very, very long time.
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25:13.000 --> 25:21.000
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So let's check this out. I think this is going to be a really instructive little thing. I'm probably not going to have to talk very much, so I'm going to enjoy my tea.
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25:21.000 --> 25:32.000
|
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I'm going to take some notes and every once in a while I might stop to say something. So if you have a particular question that you want answered and you don't mind typing it into the chat,
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25:32.000 --> 25:36.000
|
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maybe every once in a while I can stop and answer something if it's a good question.
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25:36.000 --> 25:44.000
|
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Then it becomes a round saying there's probably good questions I'll ignore, but we can do a little Q&A too as we watch this video.
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25:46.000 --> 25:49.000
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I think you're really going to enjoy it.
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26:06.000 --> 26:09.000
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There we go.
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26:36.000 --> 26:47.000
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Public health officials must race to solve the mystery to track the source of this deadly infection before it can kill again.
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26:48.000 --> 26:56.000
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All right, you see what I mean? This can be good. We're going to learn how public health was done before the pandemic.
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27:07.000 --> 27:12.000
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Some of the names in this program have been changed.
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27:12.000 --> 27:16.000
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December, 1979.
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27:16.000 --> 27:20.000
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A cross town bus in Madison, Wisconsin.
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27:20.000 --> 27:27.000
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A young woman by all appearances in perfect health. Until.
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27:27.000 --> 27:31.000
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Her collapse was sudden and terrifying.
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27:31.000 --> 27:34.000
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Unconscious, barely breathing.
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27:34.000 --> 27:38.000
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The young woman lay sprawled out in the aisle.
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27:49.000 --> 27:54.000
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Responding within minutes, paramedics rush to the scene.
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28:05.000 --> 28:14.000
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And what they found concerned them.
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28:17.000 --> 28:25.000
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The young woman had a high fever. Her pulse was weak and her blood pressure was dropping rapidly.
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28:26.000 --> 28:33.000
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Fortunately, the University of Wisconsin Medical Center was only moments away.
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28:35.000 --> 28:40.000
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By the time they reached the emergency room, she was going into shock.
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28:44.000 --> 28:48.000
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The ER staff would have to work fast.
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28:48.000 --> 29:07.000
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They had no clues to work with.
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29:07.000 --> 29:14.000
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Only a driver's license with her name, Emily Murray, and her age, just 18 years old.
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29:14.000 --> 29:17.000
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Because clues to her disease will be in her wallet.
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29:19.000 --> 29:23.000
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Meanwhile, her blood pressure was continuing to plummet.
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29:23.000 --> 29:28.000
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And an odd pink rash had appeared on her face and hands.
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29:31.000 --> 29:39.000
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As the ER team fought to stabilize her, throat and blood cultures as well as blood samples were sent off to the lab.
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29:39.000 --> 29:43.000
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The cultures would take 24 hours to grow.
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29:43.000 --> 29:59.000
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Emily was moved to the Intensive Care Unit, where she was placed on kidney dialysis and her vital signs could be closely monitored.
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29:59.000 --> 30:07.000
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She seemed to stabilize, and then her case took a strange turn.
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30:08.000 --> 30:15.000
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The mysterious rash became more pronounced. It now covered her entire body.
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30:15.000 --> 30:19.000
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Urologist Dr. Russell Chesney was called in.
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30:19.000 --> 30:26.000
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His first priority to bring her out of shock, to figure out what was going on.
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30:26.000 --> 30:30.000
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I knew that I had never seen anybody look quite like this.
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30:30.000 --> 30:35.000
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She had this rash, this sunburn rash, and it was spreading.
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30:35.000 --> 30:48.000
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It was something that was affecting all of her organs. She had bad lungs, she had shock, she had profound diarrhea, she had kidney failure.
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30:48.000 --> 30:58.000
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The sudden onset of Emily's symptoms and the bizarre red rash made Dr. Chesney suspect she had contracted a severe infection.
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30:58.000 --> 31:04.000
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There was no time to wait for lab results. He had to act immediately and aggressively.
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31:04.000 --> 31:07.000
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Do you know where you are?
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31:07.000 --> 31:15.000
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So we treated her with a very broad spectrum of antibiotics, kind of a shotgun approach, if you will.
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31:15.000 --> 31:28.000
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And we wanted to make sure that if this were an infection, that we were preventing it from spreading and that we were preventing the organisms from persisting.
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31:28.000 --> 31:34.000
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He's not thinking about transmission and thinking about her being sick from something that is interesting.
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31:34.000 --> 31:39.000
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Trying to find any possible clue to what had made her so sick.
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31:42.000 --> 31:48.000
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The parents really indicated that she hadn't been exposed to anything. There was nobody else in the family sick.
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31:48.000 --> 31:57.000
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She had some siblings and they were perfectly well. And the parents were perfectly well. Nobody was sick at school.
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31:57.000 --> 32:00.000
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And that's really intriguing.
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32:00.000 --> 32:05.000
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Examining Emily's chest x-rays, Dr. Chesney tried to understand what had happened.
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32:05.000 --> 32:16.000
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Her cardiac silhouette is not that full, it's narrow like we would see with shock. And she certainly doesn't have congestive heart failure or anything. There are no curly B lines.
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32:16.000 --> 32:21.000
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What he saw was perplexing. It didn't make any sense.
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32:21.000 --> 32:27.000
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The thing that was confusing to us and looking at her chest, it was clear she didn't have pneumonia.
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32:27.000 --> 32:36.000
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And she also didn't have a collapse of her lungs or anything like that. What she actually had was, she had hemorrhage from the lung.
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32:36.000 --> 32:41.000
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Emily's lungs were bleeding. It was hard for her to breathe.
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32:41.000 --> 32:47.000
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Dr. Chesney recognized this was a dangerous and potentially deadly complication.
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32:47.000 --> 32:57.000
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But Chesney had no idea what the cause was. The more he learned about her case, the more baffled he became.
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32:57.000 --> 33:02.000
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Her symptoms seemed random, disconnected.
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It was the nightmare of any parent. That morning their daughter had left the house a healthy teenager.
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33:11.000 --> 33:14.000
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Now she was hooked up to IV lines and monitors.
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33:14.000 --> 33:17.000
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Put her on a vent. Holy shit, yeah.
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33:17.000 --> 33:21.000
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Luckily, IV fluids and dialysis eventually began to help.
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33:21.000 --> 33:24.000
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I don't know why they're letting the parents see her and they're going to get sick.
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33:24.000 --> 33:28.000
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And their blood pressure started to rise to a safer level.
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33:28.000 --> 33:37.000
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And it stayed there for an hour or two and I felt comfortable in going home and trying to find out more about this.
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33:38.000 --> 33:43.000
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With the patient finally stable, Chesney could concentrate on the diagnosis.
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33:43.000 --> 33:47.000
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He sought a second opinion from his wife.
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33:47.000 --> 33:55.000
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Dr. Joan Chesney is the head of the infectious disease division at the University of Wisconsin School of Medicine.
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33:55.000 --> 34:02.000
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It would have been funny if they had went like, his wife is a competitive baker.
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34:03.000 --> 34:13.000
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The patient's high fever, diarrhea and dehydration were all classic symptoms of an infection.
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34:13.000 --> 34:18.000
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But she has a lot of other extra features that just don't make sense.
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34:18.000 --> 34:23.000
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Well, one of the things she has is a rash that is spreading like crazy.
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34:23.000 --> 34:28.000
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Total body rash, angry looking. I really can't figure what's going on.
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34:29.000 --> 34:33.000
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To Dr. Joan Chesney, the symptoms sounded familiar.
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34:33.000 --> 34:35.000
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I recommend cooking.
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34:35.000 --> 34:38.000
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Does she have bright red eyes?
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34:38.000 --> 34:41.000
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A red rash and red eyes.
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34:41.000 --> 34:47.000
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It reminded Joan of a journal article she had recently seen by a doctor in Colorado.
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34:47.000 --> 34:57.000
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The article outlined a new syndrome called toxic shock, characterized by shock, a rash and multi-organ disease.
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34:57.000 --> 35:03.000
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The illness was linked to a toxin produced by the bacteria staphylococcus aureus.
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35:03.000 --> 35:07.000
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The disease was named toxic shock syndrome.
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35:07.000 --> 35:11.000
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In extreme cases, it could be fatal.
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35:11.000 --> 35:17.000
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The next morning, Joan Chesney came in to examine Emily Murray.
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35:17.000 --> 35:24.000
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In her 11-year studying infectious diseases, she had never seen anything like it.
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35:24.000 --> 35:31.000
|
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Blood vessels became inflamed when the bacteria released its toxins, causing a rash that covered Emily's entire body.
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35:31.000 --> 35:42.000
|
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In the journal article, the staph aureus bacteria was described as infecting the patient's bodies through an open wound.
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35:42.000 --> 35:49.000
|
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But Emily did not have any cuts or wounds for the bacteria to infect, so where had it come from?
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35:49.000 --> 36:00.000
|
|
My biggest question was, is this toxic shock syndrome, as he described it, but I was very skeptical about the staph aureus, particularly because she didn't have any infection site.
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36:00.000 --> 36:08.000
|
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Emily did have many of the same symptoms. She even developed small hemorrhages in her eyes.
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36:08.000 --> 36:12.000
|
|
Chesney was determined to unravel this medical mystery.
|
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36:12.000 --> 36:21.000
|
|
The other bacterial infections that can cause shock and multi-system disease, but they don't generally cause the rash or the red eyes.
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36:21.000 --> 36:26.000
|
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So it was one of those things that you just had a sixth sense that there was something not right about this.
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36:26.000 --> 36:29.000
|
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Yeah, it is a staphylococcus infection, but they don't know where it comes from.
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36:29.000 --> 36:32.000
|
|
The description of toxic shock syndrome.
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36:32.000 --> 36:34.000
|
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But not completely.
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36:34.000 --> 36:35.000
|
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Oh.
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36:36.000 --> 36:41.000
|
|
Joan Chesney wondered if they were seeing the birth of a new and terrifying disease.
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36:41.000 --> 36:43.000
|
|
Oh, a new disease.
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36:43.000 --> 36:50.000
|
|
You have to make yourself keep an open mind to the fact that it might be a new virus, it might be a new bacteria.
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36:50.000 --> 36:58.000
|
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We were wondering if it could have been some kind of chemical reaction that she maybe absorbed a chemical through her skin or take.
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36:58.000 --> 37:06.000
|
|
Think about how different it is if they think she absorbed a chemical through her skin or it's the development of a new disease.
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37:06.000 --> 37:11.000
|
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One is potentially a Kim dot com billions of dead.
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37:11.000 --> 37:21.000
|
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And you should have been having PPE on and now you're an asymptomatic carrier that's going to kill everybody you come in contact with in the next two weeks or.
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37:22.000 --> 37:35.000
|
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Nobody's in danger and you're treating her completely incorrectly with a broad spectrum antibiotics that could actually make it worse.
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37:35.000 --> 37:44.000
|
|
You see how weird that is that there's a those are very different things in a drug that nobody knew about.
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37:45.000 --> 37:49.000
|
|
Then just hours later, a second case appeared.
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37:49.000 --> 37:54.000
|
|
19 year old Kaylee Wilson was rushed to the University of Wisconsin Medical Center.
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37:54.000 --> 37:57.000
|
|
Like Emily, she arrived in the ER.
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37:57.000 --> 38:02.000
|
|
So now a second case will not be evidence for chemical exposure.
|
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38:02.000 --> 38:07.000
|
|
Now a second case will be evidence for spreading pathogen, you see.
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38:07.000 --> 38:12.000
|
|
And now what I want you to pay attention to it is the spread of bad ideas.
|
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38:12.000 --> 38:17.000
|
|
It's not the spread of RNA that's happening here in this video.
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38:17.000 --> 38:24.000
|
|
Are with a raging fever, extremely low blood pressure and a bizarre red rash.
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38:24.000 --> 38:31.000
|
|
The ER staff pumped her with fluids desperately trying to raise her blood pressure.
|
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38:32.000 --> 38:35.000
|
|
Something's going on at the University of Wisconsin doors.
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38:35.000 --> 38:39.000
|
|
I want to tell a very bad joke about it but I can't.
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38:39.000 --> 38:42.000
|
|
Joan Chesney was immediately notified.
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38:42.000 --> 38:48.000
|
|
We see patients all the time who have very unusual presentations of some disease.
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38:48.000 --> 38:54.000
|
|
But there's only one of them and we don't we often don't figure out what it is no matter how hard we try.
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38:54.000 --> 38:59.000
|
|
But here we had two right, less than 24 hours apart.
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38:59.000 --> 39:02.000
|
|
Those of whom were very sick.
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39:02.000 --> 39:06.000
|
|
The similarity between the two cases still can't be.
|
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39:06.000 --> 39:12.000
|
|
Joan's experience with infectious diseases told her this couldn't be a coincidence.
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39:12.000 --> 39:19.000
|
|
She recommended supportive treatment, massive amounts of oxygen, and a broad spectrum of antibiotics.
|
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39:19.000 --> 39:22.000
|
|
Ooh, cheese had poisoning as really dangerous in Wisconsin.
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39:22.000 --> 39:25.000
|
|
Soon after Kaylee was admitted, Joan learned that a third-
|
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39:25.000 --> 39:27.000
|
|
That only really happens in bald people.
|
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39:27.000 --> 39:31.000
|
|
...was being treated at a hospital just across town.
|
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39:31.000 --> 39:34.000
|
|
This was no random event.
|
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39:34.000 --> 39:39.000
|
|
1977 is widespread.
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39:39.000 --> 39:41.000
|
|
Well, this happened in 1977.
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39:41.000 --> 39:44.000
|
|
I think the video started on the 9th.
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39:44.000 --> 39:48.000
|
|
To say my heart rate doubled would be an understatement.
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39:48.000 --> 39:51.000
|
|
It was scary.
|
|
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|
39:51.000 --> 39:57.000
|
|
Joan knew it was time to bring in the director of the Wisconsin Department of Health, Dr. Jeff Davis.
|
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|
39:57.000 --> 39:58.000
|
|
Here we go.
|
|
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|
39:58.000 --> 40:05.000
|
|
The fact that three cases were occurring in one community simultaneously certainly was of impact.
|
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40:05.000 --> 40:09.000
|
|
We felt it was certainly unusual needed to be investigated right away.
|
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40:09.000 --> 40:13.000
|
|
Boy, he sure looks like a public health official, doesn't he? Just my goodness.
|
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40:13.000 --> 40:21.000
|
|
And he's going to call up the oaster home in the Gopher State next door within a few hours, I'm sure.
|
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40:21.000 --> 40:30.000
|
|
As chief epidemiologist for the state of Wisconsin, it was Dr. Davis's job to make sense of this outbreak.
|
|
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40:30.000 --> 40:34.000
|
|
To figure out how these three cases were related.
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40:34.000 --> 40:42.000
|
|
Had the young women all been exposed to something in common, what was the source of the illness?
|
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40:43.000 --> 40:50.000
|
|
Dr. Davis interviewed the three patients, asking about pets, allergies, dietary habits.
|
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40:50.000 --> 40:57.000
|
|
Anything that might provide a link, a clue to the origin of this mysterious infection.
|
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40:57.000 --> 40:59.000
|
|
We asked about a lot of activities.
|
|
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40:59.000 --> 41:06.000
|
|
These were fairly far reaching, you know, where people shopped, you know, where they went, what their usual activities were.
|
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41:07.000 --> 41:14.000
|
|
Davis then compared the interviews, looking for overlapping data, the one key point where the patient's lives intersected.
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41:14.000 --> 41:18.000
|
|
What he found was absolutely nothing.
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41:18.000 --> 41:20.000
|
|
Was absolutely nothing.
|
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41:20.000 --> 41:27.000
|
|
And they were from basically the greater Madison area. They didn't have anything in common.
|
|
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41:27.000 --> 41:35.000
|
|
The mystery was growing, and unless doctors and public health officials could identify the source of the toxic infection.
|
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|
41:35.000 --> 41:40.000
|
|
More young women could be in danger.
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41:40.000 --> 41:44.000
|
|
A strange outbreak, a mysterious infection.
|
|
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41:44.000 --> 41:47.000
|
|
This is a commercial break returning from commercial break.
|
|
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|
41:47.000 --> 41:52.000
|
|
In Madison, Wisconsin, young women were being rushed to the hospital.
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|
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41:52.000 --> 41:56.000
|
|
In each case, the symptoms were the same.
|
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41:56.000 --> 42:04.000
|
|
High fever, dangerously low blood pressure, signs of shock, and a bizarre sunburn like rash.
|
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42:05.000 --> 42:18.000
|
|
As doctors struggled to keep the women alive, health officials worked round the clock to find the cause.
|
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|
42:18.000 --> 42:26.000
|
|
Wisconsin state epidemiologist Dr. Jeff Davis combed through the women's medical records, searching for clues.
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|
42:26.000 --> 42:29.000
|
|
What did these patients have in common?
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42:30.000 --> 42:35.000
|
|
The only thing they shared was that they were all young, and they were all women.
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42:35.000 --> 42:42.000
|
|
It seemed like nothing. In fact, it was the beginning of an answer.
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42:42.000 --> 42:47.000
|
|
So that's when I thought what differentiates women from men.
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42:47.000 --> 42:52.000
|
|
And given their age, I thought that menstruation may be a factor.
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42:52.000 --> 42:57.000
|
|
Unfortunately, the medical files had no record of menstrual cycles.
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42:57.000 --> 43:01.000
|
|
Dr. Davis would have to revisit the patients.
|
|
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|
43:01.000 --> 43:05.000
|
|
Emily Murray, the first, was in the best shape of the three.
|
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43:05.000 --> 43:09.000
|
|
Her kidneys were failing, and she'd been put on dialysis.
|
|
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43:09.000 --> 43:12.000
|
|
But she was at least lucid enough to talk.
|
|
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|
43:12.000 --> 43:17.000
|
|
Yes.
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43:17.000 --> 43:23.000
|
|
Regular, since that time. Normal, monthly periods.
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43:23.000 --> 43:28.000
|
|
Over the next day, the other patients told him the same thing.
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43:28.000 --> 43:33.000
|
|
They had both been menstruating when they got sick.
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43:33.000 --> 43:38.000
|
|
At last, Davis had found something all the patients had in common.
|
|
|
|
43:38.000 --> 43:42.000
|
|
But what did it mean? Was it even significant?
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|
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|
43:42.000 --> 43:47.000
|
|
He shared his findings with infectious disease expert Dr. Joan Chesney.
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43:47.000 --> 43:48.000
|
|
She was skeptical.
|
|
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43:48.000 --> 43:53.000
|
|
My reaction was, well, Jeff, if you take any group of young women at one point in time,
|
|
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|
43:53.000 --> 43:56.000
|
|
you know, significant number are going to be having their period.
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43:56.000 --> 44:00.000
|
|
And he said, well, I know, but I just can't find anything else.
|
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|
|
44:00.000 --> 44:06.000
|
|
But Davis's interviews uncovered another clue supporting his suspicions.
|
|
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|
44:07.000 --> 44:14.000
|
|
One of the women had suffered similar but less severe symptoms a month before.
|
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44:14.000 --> 44:20.000
|
|
The implications were frightening.
|
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|
44:20.000 --> 44:24.000
|
|
Had the young women taken a pain reliever that was contaminated,
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44:24.000 --> 44:29.000
|
|
a tainted batch of oral contraceptives.
|
|
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44:29.000 --> 44:35.000
|
|
Davis and Chesney wondered if other doctors in the area were seeing the same strange illness.
|
|
|
|
44:35.000 --> 44:41.000
|
|
It was time to get the word out, to get as many brains working on the mystery as possible.
|
|
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|
44:41.000 --> 44:46.000
|
|
We found a real sense of urgency to let other people know as quickly as possible
|
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|
44:46.000 --> 44:54.000
|
|
and to see if people had seen it, not recognized it, to be sure we picked up any additional cases.
|
|
|
|
44:54.000 --> 44:59.000
|
|
Dr. Chesney presented her cases at a hospital conference on infectious disease.
|
|
|
|
44:59.000 --> 45:01.000
|
|
Thank you all for coming.
|
|
|
|
45:01.000 --> 45:07.000
|
|
We wanted to tell you about three patients that we've seen in the last two days.
|
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|
|
45:07.000 --> 45:13.000
|
|
And we wanted to bring it to your attention so that if any of you saw a patient with this in the next few months
|
|
|
|
45:13.000 --> 45:18.000
|
|
or if you've seen a patient with this over the last six months, please let us know.
|
|
|
|
45:18.000 --> 45:22.000
|
|
I'm sure it's not just going on here in Madison, but it's probably-
|
|
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|
45:22.000 --> 45:28.000
|
|
When she asked if anyone had seen patients with similar symptoms, a medical resident spoke up.
|
|
|
|
45:28.000 --> 45:31.000
|
|
Chesney, I saw a similar patient six months ago.
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|
45:31.000 --> 45:35.000
|
|
He had treated a young woman in her teens a few months earlier.
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45:35.000 --> 45:39.000
|
|
Dr. Chesney asked to look at the patient's records.
|
|
|
|
45:39.000 --> 45:41.000
|
|
We're all quite concerned about it right now.
|
|
|
|
45:41.000 --> 45:44.000
|
|
Thank you again for letting us come today.
|
|
|
|
45:44.000 --> 45:46.000
|
|
The bowl's just beginning.
|
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|
45:46.000 --> 45:50.000
|
|
As she reviewed the file, Dr. Chesney saw all the telltale signs.
|
|
|
|
45:50.000 --> 45:55.000
|
|
Look, she was in shock at the time and she had a rash just like I told you earlier.
|
|
|
|
45:55.000 --> 45:57.000
|
|
In the red eyes you had mentioned to me.
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|
|
|
45:57.000 --> 46:03.000
|
|
Um, evening is whether anybody recorded that she was having her period when all of this started.
|
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|
46:03.000 --> 46:04.000
|
|
You find it?
|
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|
46:04.000 --> 46:05.000
|
|
Here it is.
|
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|
46:05.000 --> 46:09.000
|
|
They did document that she was having her period at the time of her symptoms.
|
|
|
|
46:09.000 --> 46:14.000
|
|
This was yet another documented case of the mysterious illness.
|
|
|
|
46:14.000 --> 46:19.000
|
|
Wisconsin was firmly in the grip of an outbreak.
|
|
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|
46:19.000 --> 46:21.000
|
|
An outbreak.
|
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|
46:21.000 --> 46:23.000
|
|
Wisconsin's having an outbreak.
|
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|
|
46:23.000 --> 46:26.000
|
|
The teenager was being admitted to the Wisconsin medical center.
|
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46:26.000 --> 46:27.000
|
|
All these teen girls.
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46:27.000 --> 46:29.000
|
|
Like the other women when she arrived at the ER.
|
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|
46:29.000 --> 46:31.000
|
|
She was disoriented and covered.
|
|
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|
46:31.000 --> 46:36.000
|
|
How come these women aren't afraid of getting what these other women have?
|
|
|
|
46:36.000 --> 46:43.000
|
|
What if their menstruation cycles all sequence up and that is sync up and then they all get sick together?
|
|
|
|
46:43.000 --> 46:48.000
|
|
Have you heard there's another teenager in the emergency room with a few scratch and shock
|
|
|
|
46:48.000 --> 46:50.000
|
|
and they'd like you to come now please.
|
|
|
|
46:50.000 --> 46:51.000
|
|
Wow.
|
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|
46:52.000 --> 46:53.000
|
|
Hi Allison.
|
|
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|
46:53.000 --> 46:55.000
|
|
My name is Dr. Chesney.
|
|
|
|
46:55.000 --> 46:58.000
|
|
This new patient was also menstruating.
|
|
|
|
46:58.000 --> 47:00.000
|
|
They all wear new balance shoes.
|
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|
|
47:00.000 --> 47:01.000
|
|
That's what it is.
|
|
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|
47:01.000 --> 47:02.000
|
|
Oh my gosh.
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|
47:02.000 --> 47:04.000
|
|
Those will kill you for sure.
|
|
|
|
47:04.000 --> 47:06.000
|
|
Dr. Chesney had been developing a theory about this.
|
|
|
|
47:06.000 --> 47:08.000
|
|
You want to see what I got for my birthday?
|
|
|
|
47:08.000 --> 47:12.000
|
|
Since the patients were all menstruating at the onset of illness,
|
|
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|
47:12.000 --> 47:15.000
|
|
Chesney ordered a vaginal culture to test for bacteria.
|
|
|
|
47:15.000 --> 47:17.000
|
|
You know I like green.
|
|
|
|
47:17.000 --> 47:19.000
|
|
Check those bad boys out.
|
|
|
|
47:19.000 --> 47:20.000
|
|
Can you see them?
|
|
|
|
47:20.000 --> 47:21.000
|
|
Those are those green.
|
|
|
|
47:21.000 --> 47:24.000
|
|
The culture was incubated on a growth medium.
|
|
|
|
47:24.000 --> 47:25.000
|
|
Green Jordan 4s.
|
|
|
|
47:25.000 --> 47:26.000
|
|
They're pretty cool.
|
|
|
|
47:26.000 --> 47:27.000
|
|
24 hours later.
|
|
|
|
47:27.000 --> 47:31.000
|
|
It was placed in a reagent solution and identified as staphylococcus.
|
|
|
|
47:31.000 --> 47:32.000
|
|
You can't really see them.
|
|
|
|
47:32.000 --> 47:33.000
|
|
Sorry.
|
|
|
|
47:33.000 --> 47:35.000
|
|
The bacteria associated with toxic shocks.
|
|
|
|
47:35.000 --> 47:36.000
|
|
There we go.
|
|
|
|
47:36.000 --> 47:37.000
|
|
Staphylococcus.
|
|
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|
47:37.000 --> 47:38.000
|
|
We got it.
|
|
|
|
47:38.000 --> 47:42.000
|
|
Joan Chesney's initial diagnosis had proven correct.
|
|
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|
47:42.000 --> 47:43.000
|
|
Exactly.
|
|
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|
47:43.000 --> 47:46.000
|
|
And sure enough it was what we call a pure culture.
|
|
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|
47:46.000 --> 47:49.000
|
|
That was the only bacteria that grew and it was a heavy growth.
|
|
|
|
47:49.000 --> 47:56.000
|
|
So that was our first clue, hard clue that maybe our thoughts were going in the right direction.
|
|
|
|
47:56.000 --> 48:02.000
|
|
For Dr. Jeff Davis, the epidemiologist, it was time to place the entire state.
|
|
|
|
48:02.000 --> 48:04.000
|
|
Man I had Jordan 4s in high school.
|
|
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|
48:04.000 --> 48:07.000
|
|
I actually had a 35.
|
|
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|
48:07.000 --> 48:11.000
|
|
I actually had a friend in high school and we had black and white ones.
|
|
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|
48:11.000 --> 48:12.000
|
|
Was it black?
|
|
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|
48:12.000 --> 48:17.000
|
|
He had black and gray and I had the red and white and then we like each traded a shoe.
|
|
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|
48:17.000 --> 48:18.000
|
|
It was dope.
|
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|
48:19.000 --> 48:26.000
|
|
A hundred physicians that Wisconsin was facing an outbreak of the deadly toxic shock syndrome.
|
|
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|
48:26.000 --> 48:31.000
|
|
He requested information and sample cultures from any patients who displayed symptoms.
|
|
|
|
48:31.000 --> 48:35.000
|
|
It was important to get this letter out because they needed to learn about the illness.
|
|
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|
48:35.000 --> 48:38.000
|
|
They needed to learn what was occurring.
|
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|
48:38.000 --> 48:42.000
|
|
We made recommendations for laboratory tests to obtain them so that expanded their ability
|
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|
48:42.000 --> 48:45.000
|
|
to get the appropriate test.
|
|
|
|
48:45.000 --> 48:53.000
|
|
In a time before email, Davis's letter on toxic shock was distributed the old fashioned way by U.S. mail.
|
|
|
|
48:53.000 --> 48:57.000
|
|
But all across the state, physicians got the message.
|
|
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|
48:57.000 --> 48:59.000
|
|
Watch out for unusual cases.
|
|
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|
48:59.000 --> 49:08.000
|
|
It was really that very, very unique combination of symptoms and signs that we tried to let people know about
|
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|
49:08.000 --> 49:13.000
|
|
and don't give them some penicillin and send them home because they won't be better in the morning.
|
|
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|
49:13.000 --> 49:17.000
|
|
You need to get them to the hospital right away.
|
|
|
|
49:17.000 --> 49:20.000
|
|
The response was overwhelming.
|
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|
49:20.000 --> 49:24.000
|
|
Hospital statewide reported cases of the deadly illness.
|
|
|
|
49:24.000 --> 49:27.000
|
|
Not just one or two, but hundreds of them.
|
|
|
|
49:27.000 --> 49:32.000
|
|
Young women all over Wisconsin were infected with toxic shock syndrome.
|
|
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|
49:32.000 --> 49:36.000
|
|
And health officials had no idea why.
|
|
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|
49:37.000 --> 49:44.000
|
|
In 1980, dozens of young Wisconsin women were coming down with the disease.
|
|
|
|
49:44.000 --> 49:48.000
|
|
This is like a return from menstrual toxic shock syndrome.
|
|
|
|
49:48.000 --> 49:50.000
|
|
From commercial.
|
|
|
|
49:50.000 --> 49:54.000
|
|
So what they're calling it now is menstrual toxic shock syndrome.
|
|
|
|
49:54.000 --> 50:00.000
|
|
Now, keep in mind how important it is that there's only like two people in this story
|
|
|
|
50:00.000 --> 50:02.000
|
|
who essentially are controlling the narrative.
|
|
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|
50:02.000 --> 50:07.000
|
|
Everybody else is going to call that lady with the glasses and ask her for her advice
|
|
|
|
50:07.000 --> 50:11.000
|
|
about whether or not their case fits her description.
|
|
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|
50:11.000 --> 50:17.000
|
|
Whether her case or whether their case fits into her category and what she's doing for it.
|
|
|
|
50:17.000 --> 50:22.000
|
|
So you see this pattern that happens very quickly already in this.
|
|
|
|
50:22.000 --> 50:26.000
|
|
It's a dramatization of what's something that supposedly happened in real life.
|
|
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|
50:26.000 --> 50:37.000
|
|
What would happen if you had people in position already prepared to stay committed?
|
|
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|
50:37.000 --> 50:46.000
|
|
What if you had that guy, the health director of all the state of Wisconsin ready to stay
|
|
|
|
50:46.000 --> 50:52.000
|
|
committed to a respiratory pathogen spreading that was specific for women for some reason
|
|
|
|
50:52.000 --> 50:55.000
|
|
and had an elaborate story to go along with it?
|
|
|
|
50:55.000 --> 50:59.000
|
|
How long could he have made that go on?
|
|
|
|
50:59.000 --> 51:04.000
|
|
If he would have even gotten that one doctor with the funny glasses, the lady, the wife
|
|
|
|
51:04.000 --> 51:08.000
|
|
of the guy who originally treated the first patient to go along with it.
|
|
|
|
51:08.000 --> 51:11.000
|
|
How long then would that go on?
|
|
|
|
51:11.000 --> 51:16.000
|
|
Now, if that lady had already been put in place at that hospital by previous assignment
|
|
|
|
51:16.000 --> 51:21.000
|
|
and already knew that this was going to happen and it was designed to be this way
|
|
|
|
51:21.000 --> 51:24.000
|
|
and that the worst case scenario was necessary to be accepted.
|
|
|
|
51:24.000 --> 51:27.000
|
|
How long could they make this go on?
|
|
|
|
51:27.000 --> 51:31.000
|
|
How long could they confuse other doctors in the state?
|
|
|
|
51:31.000 --> 51:37.000
|
|
Now, how long do you think it could go on if they had a test that wasn't specific for this?
|
|
|
|
51:37.000 --> 51:41.000
|
|
But they told everybody that when it tests positive and you don't have the symptoms,
|
|
|
|
51:41.000 --> 51:44.000
|
|
you're just an asymptomatic carrier.
|
|
|
|
51:44.000 --> 51:50.000
|
|
How long do you think this could spiral out of control if you had a collaboration of TV
|
|
|
|
51:50.000 --> 51:54.000
|
|
and social media?
|
|
|
|
51:54.000 --> 51:59.000
|
|
How long would this spiral on if you had control of the highest levels of governments
|
|
|
|
51:59.000 --> 52:04.000
|
|
around the world so that even across cultures and across languages,
|
|
|
|
52:04.000 --> 52:08.000
|
|
the messaging would be very similar about toxic shock syndrome?
|
|
|
|
52:08.000 --> 52:13.000
|
|
How long could you keep it going?
|
|
|
|
52:13.000 --> 52:18.000
|
|
Now, think about how long you keep it going if it was happening to both men and women,
|
|
|
|
52:18.000 --> 52:23.000
|
|
old and young, and they said they knew nothing about it
|
|
|
|
52:23.000 --> 52:27.000
|
|
and they kept insisting that they knew nothing about it
|
|
|
|
52:27.000 --> 52:31.000
|
|
and that you created a rumor in the background that this could be even worse
|
|
|
|
52:31.000 --> 52:39.000
|
|
than the most natural virus because it could be a man-made laboratory virus.
|
|
|
|
52:39.000 --> 52:45.000
|
|
That's why I'm showing you this dramatization of a real-life mystery that needed to be solved
|
|
|
|
52:45.000 --> 52:50.000
|
|
because those people were getting sick and one of the first assumptions they jumped to
|
|
|
|
52:50.000 --> 52:58.000
|
|
was a contagious new developing disease that they didn't need any protection from either masks or even gloves.
|
|
|
|
52:58.000 --> 53:02.000
|
|
It's extraordinary!
|
|
|
|
53:06.000 --> 53:09.000
|
|
The local doctors were baffled.
|
|
|
|
53:09.000 --> 53:12.000
|
|
More cases were hearing across the state.
|
|
|
|
53:12.000 --> 53:17.000
|
|
And then, several weeks into the outbreak, the Wisconsin Department of Health learned
|
|
|
|
53:17.000 --> 53:23.000
|
|
that three women in Minnesota had also been hospitalized with unusual symptoms.
|
|
|
|
53:23.000 --> 53:27.000
|
|
Epidemiologist Jeff Davis was baffled.
|
|
|
|
53:27.000 --> 53:30.000
|
|
Toxic shock syndrome is not contagious.
|
|
|
|
53:30.000 --> 53:31.000
|
|
How would it spread?
|
|
|
|
53:31.000 --> 53:34.000
|
|
Yeah, I've seen that dog game of werewolf. I really like that.
|
|
|
|
53:34.000 --> 53:35.000
|
|
I've got to cover that at some point.
|
|
|
|
53:35.000 --> 53:37.000
|
|
I think it's important to see the event.
|
|
|
|
53:37.000 --> 53:41.000
|
|
Because clearly this was going on in a couple of states.
|
|
|
|
53:41.000 --> 53:47.000
|
|
At the Centers for Disease Control in Atlanta, Dr. Bruce Dan was part of the investigation.
|
|
|
|
53:47.000 --> 53:52.000
|
|
To suddenly hear that women in Wisconsin and Minnesota were having the same symptoms,
|
|
|
|
53:52.000 --> 53:56.000
|
|
and not just the same symptoms, very strange collection of symptoms.
|
|
|
|
53:56.000 --> 54:00.000
|
|
You don't have to be a really trained epidemiologist to realize you had a real epidemic on your hands,
|
|
|
|
54:00.000 --> 54:03.000
|
|
and something very strange was going on.
|
|
|
|
54:03.000 --> 54:06.000
|
|
Oh, the chalkboard.
|
|
|
|
54:06.000 --> 54:08.000
|
|
Now they're going to solve the problem.
|
|
|
|
54:08.000 --> 54:12.000
|
|
It's a problem with the CDC's epidemiological intelligence service.
|
|
|
|
54:12.000 --> 54:16.000
|
|
I had a network, and this would be also a shock syndrome.
|
|
|
|
54:16.000 --> 54:20.000
|
|
You can subscribe and get on biological so I can afford to chalkboard it into this.
|
|
|
|
54:20.000 --> 54:22.000
|
|
If I had a chalkboard, this would be over.
|
|
|
|
54:22.000 --> 54:27.000
|
|
The investigators, the infectious disease experts who had seen years and years of disease,
|
|
|
|
54:27.000 --> 54:32.000
|
|
especially in medical centers and universities where they get referred lots of very unusual cases,
|
|
|
|
54:32.000 --> 54:37.000
|
|
who said, you know, we have never ever seen anything like this before.
|
|
|
|
54:37.000 --> 54:38.000
|
|
You guys are handling something.
|
|
|
|
54:38.000 --> 54:40.000
|
|
Oh, I would ask for chalk.
|
|
|
|
54:40.000 --> 54:44.000
|
|
Not only that, but I would ask for the chalk that the Japanese physicists like to have.
|
|
|
|
54:44.000 --> 54:54.000
|
|
There's a special kind of hard-pressed chalk that physicists and math professors like hoard and covet.
|
|
|
|
54:54.000 --> 54:58.000
|
|
And I would only use that chalk if you got me a chalkboard.
|
|
|
|
54:58.000 --> 55:00.000
|
|
Just to let you know, I wouldn't fool around.
|
|
|
|
55:00.000 --> 55:05.000
|
|
I mean, this would be Jurassic Park level chalkboard.
|
|
|
|
55:05.000 --> 55:08.000
|
|
You know, finest chalk, finest slate, the whole thing.
|
|
|
|
55:08.000 --> 55:13.000
|
|
Totally new, totally unrecognized as far as we're concerned.
|
|
|
|
55:13.000 --> 55:16.000
|
|
The CDC's investigative team rolled into action.
|
|
|
|
55:16.000 --> 55:18.000
|
|
Yeah, then you're not using the right chalk.
|
|
|
|
55:18.000 --> 55:19.000
|
|
You've got to have this.
|
|
|
|
55:19.000 --> 55:20.000
|
|
You've got to have this.
|
|
|
|
55:20.000 --> 55:21.000
|
|
We've got to have this.
|
|
|
|
55:21.000 --> 55:22.000
|
|
We've got to have this.
|
|
|
|
55:22.000 --> 55:24.000
|
|
Just to let the white chalkboard champs.
|
|
|
|
55:24.000 --> 55:25.000
|
|
For math professors.
|
|
|
|
55:25.000 --> 55:32.000
|
|
We needed to figure out whether this was a regional outbreak or a national outbreak.
|
|
|
|
55:32.000 --> 55:34.000
|
|
Oh, my gosh, a national outbreak.
|
|
|
|
55:34.000 --> 55:41.000
|
|
I wanted to put out the word and ask people had they seen this illness in other locations
|
|
|
|
55:41.000 --> 55:45.000
|
|
than Wisconsin and Minnesota.
|
|
|
|
55:45.000 --> 55:47.000
|
|
Only two things were served.
|
|
|
|
55:47.000 --> 55:48.000
|
|
I'm not.
|
|
|
|
55:48.000 --> 55:51.000
|
|
Toxic shock syndrome was dangerous and was spreading.
|
|
|
|
55:51.000 --> 55:53.000
|
|
I definitely need a chalkboard to solve this.
|
|
|
|
55:53.000 --> 55:59.000
|
|
On Sunday, February 8, 1980, Ronald and Jeanette Dulek were on their way to church.
|
|
|
|
55:59.000 --> 56:03.000
|
|
Geraldine, their 16-year-old daughter, was running late.
|
|
|
|
56:03.000 --> 56:08.000
|
|
Oh, no, another teenager getting struck by the toxic.
|
|
|
|
56:08.000 --> 56:13.000
|
|
Oh, she's out on the floor, yo, right in the laundry.
|
|
|
|
56:22.000 --> 56:25.000
|
|
At St. Mary's Hospital in Milwaukee.
|
|
|
|
56:25.000 --> 56:27.000
|
|
Oh, now it's in Milwaukee.
|
|
|
|
56:27.000 --> 56:29.000
|
|
These people will figure it out.
|
|
|
|
56:29.000 --> 56:31.000
|
|
Has Geraldine flickered in and out of consciousness?
|
|
|
|
56:31.000 --> 56:33.000
|
|
The ER staff charted her final thoughts.
|
|
|
|
56:33.000 --> 56:34.000
|
|
He's got a mustache.
|
|
|
|
56:34.000 --> 56:38.000
|
|
He's going to solve the problem from multiple high-risk symptoms.
|
|
|
|
56:38.000 --> 56:41.000
|
|
I always trust the doctor and the pilot with the mustache.
|
|
|
|
56:41.000 --> 56:44.000
|
|
And your temperature short to 106 degrees.
|
|
|
|
56:44.000 --> 56:49.000
|
|
Doctor struggled to make a diagnosis until the attending physician received...
|
|
|
|
56:49.000 --> 56:51.000
|
|
Oh, that's Mrs. Letter.
|
|
|
|
56:51.000 --> 56:52.000
|
|
She's going.
|
|
|
|
56:52.000 --> 56:53.000
|
|
She's getting infected.
|
|
|
|
56:53.000 --> 56:58.000
|
|
He recognized his patient's symptoms as a textbook case of the brand-new epidemic.
|
|
|
|
57:03.000 --> 57:06.000
|
|
Meeting with Geraldine's family, the doctor asked if she could...
|
|
|
|
57:06.000 --> 57:08.000
|
|
Fear the wind to force me if I grow a mustache.
|
|
|
|
57:08.000 --> 57:10.000
|
|
And it would also take me about six months, but...
|
|
|
|
57:10.000 --> 57:11.000
|
|
She had.
|
|
|
|
57:11.000 --> 57:12.000
|
|
I could probably grow one, but...
|
|
|
|
57:12.000 --> 57:14.000
|
|
Their answer wouldn't have confirmed his diagnosis.
|
|
|
|
57:14.000 --> 57:15.000
|
|
That's great.
|
|
|
|
57:15.000 --> 57:17.000
|
|
Toxic shock syndrome.
|
|
|
|
57:17.000 --> 57:22.000
|
|
He's got a nice contact with students in the Department of Health to get the latest information
|
|
|
|
57:22.000 --> 57:23.000
|
|
on treatment.
|
|
|
|
57:23.000 --> 57:26.000
|
|
We were talking like two weeks now, I think.
|
|
|
|
57:26.000 --> 57:27.000
|
|
The balance.
|
|
|
|
57:27.000 --> 57:28.000
|
|
Geraldine was given fluids to...
|
|
|
|
57:28.000 --> 57:29.000
|
|
They still don't know.
|
|
|
|
57:29.000 --> 57:31.000
|
|
...and helped raise her blood pressure.
|
|
|
|
57:31.000 --> 57:33.000
|
|
She was also given...
|
|
|
|
57:33.000 --> 57:35.000
|
|
I have a 100% bare dollar.
|
|
|
|
57:35.000 --> 57:36.000
|
|
I have a 100% bare dollar.
|
|
|
|
57:36.000 --> 57:43.000
|
|
If Geraldine stood any chance of survival, treatment would have to take effect quickly.
|
|
|
|
57:43.000 --> 57:49.000
|
|
News of the 16-year-old's desperate condition reached Neil Rosenberg,
|
|
|
|
57:49.000 --> 57:50.000
|
|
a male walking...
|
|
|
|
57:50.000 --> 57:52.000
|
|
Wow, this has got a funny-shaped laptop.
|
|
|
|
57:52.000 --> 57:55.000
|
|
He was intrigued by the mysterious illness.
|
|
|
|
57:55.000 --> 58:01.000
|
|
When I first heard about Geraldine Dulac, it came not with a name, but fear in the voice
|
|
|
|
58:01.000 --> 58:02.000
|
|
of an anonymous caller.
|
|
|
|
58:02.000 --> 58:07.000
|
|
I was sitting at my desk, looking for a story as I usually do when the phone rang.
|
|
|
|
58:07.000 --> 58:09.000
|
|
And it was a caller from China.
|
|
|
|
58:09.000 --> 58:13.000
|
|
And she told me that there was a new virus breaking out in China,
|
|
|
|
58:13.000 --> 58:16.000
|
|
and the only thing that was working was Remdesivir.
|
|
|
|
58:17.000 --> 58:26.000
|
|
The person who said, the young woman, was seriously ridiculous.
|
|
|
|
58:26.000 --> 58:30.000
|
|
On the south side of Milwaukee, from a killer virus.
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58:30.000 --> 58:37.000
|
|
Tracking the story, Rosenberg contacted Dr. Jeff Davis at the Wisconsin Department of Health.
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58:37.000 --> 58:42.000
|
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He learned the mysterious illness had a surprising connection.
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58:43.000 --> 58:46.000
|
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He gave me a graphic description of the symptoms.
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58:46.000 --> 58:50.000
|
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And at one point, I said, is there any common leak?
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58:50.000 --> 58:52.000
|
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He said, they were all menstruating.
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58:52.000 --> 58:54.000
|
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And that really threw me for a loop.
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58:54.000 --> 58:56.000
|
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And I said, well, what do you think that means?
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58:56.000 --> 58:59.000
|
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And he says, we really don't know, Neil.
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58:59.000 --> 59:04.000
|
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There's an airplane response there, right?
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59:04.000 --> 59:10.000
|
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It means that their uterine wall was shedding.
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59:11.000 --> 59:13.000
|
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There should be some biological death.
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59:13.000 --> 59:16.000
|
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What do you think that means?
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59:16.000 --> 59:20.000
|
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It's a big building with patients, but that's not important right now.
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59:20.000 --> 59:21.000
|
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I'm sorry.
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59:21.000 --> 59:24.000
|
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I love that movie.
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59:24.000 --> 59:28.000
|
|
Rosenberg's story made front page news.
|
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59:28.000 --> 59:34.000
|
|
For Jeff Davis and the Department of Health, it also opened a floodgate.
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59:34.000 --> 59:38.000
|
|
That article had a lot of information about toxic shocks in Rome.
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59:39.000 --> 59:42.000
|
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And I started getting a lot of phone calls.
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59:42.000 --> 59:43.000
|
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He needs a mustache.
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59:43.000 --> 59:45.000
|
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He's sweating where he shouldn't be sweating.
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59:45.000 --> 59:49.000
|
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I think he's not happy about being on camera that funny guy.
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59:49.000 --> 59:52.000
|
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A huge number of phone calls.
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59:52.000 --> 59:56.000
|
|
And so that article had an extraordinary impact.
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59:56.000 --> 01:00:01.000
|
|
Hundreds of calls began pouring in.
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01:00:01.000 --> 01:00:04.000
|
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Physicians called to report suspected cases.
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01:00:04.000 --> 01:00:07.000
|
|
What are you talking about six months previously?
|
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|
01:00:07.000 --> 01:00:10.000
|
|
There was a U.N. war game covering weaponized tampons.
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01:00:10.000 --> 01:00:12.000
|
|
What the hell are you talking about?
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|
01:00:12.000 --> 01:00:14.000
|
|
That can't be possible.
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01:00:14.000 --> 01:00:15.000
|
|
I think that must be a joke.
|
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|
01:00:15.000 --> 01:00:17.000
|
|
He's a funny guy.
|
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|
01:00:17.000 --> 01:00:25.000
|
|
Women call to share their stories of surviving about with the deadly syndrome.
|
|
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|
01:00:25.000 --> 01:00:29.000
|
|
Astonished by the response, Davis launched a case deck today.
|
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|
01:00:29.000 --> 01:00:32.000
|
|
Wow, those are complicated phones.
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|
01:00:32.000 --> 01:00:36.000
|
|
Health officials work non-stop gathering information.
|
|
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|
01:00:36.000 --> 01:00:41.000
|
|
They had to find the link between toxic shock syndrome and menstruation.
|
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|
01:00:41.000 --> 01:00:47.000
|
|
Through scores of interviews, the team compared 35 confirmed cases of toxic shock
|
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|
01:00:47.000 --> 01:00:50.000
|
|
to a larger control group of healthy women.
|
|
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|
01:00:50.000 --> 01:00:54.000
|
|
All the women, healthy or infected, lived in the same area.
|
|
|
|
01:00:54.000 --> 01:00:59.000
|
|
They were all about the same age and shared similar lifestyles.
|
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|
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01:01:00.000 --> 01:01:08.000
|
|
I can confirm that looks like a Wisconsin girl to health.
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|
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|
01:01:08.000 --> 01:01:10.000
|
|
That looks like a Wisconsin host to me.
|
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|
01:01:10.000 --> 01:01:11.000
|
|
With the participants.
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|
01:01:11.000 --> 01:01:12.000
|
|
Wow.
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|
01:01:12.000 --> 01:01:15.000
|
|
That's impressive.
|
|
|
|
01:01:15.000 --> 01:01:19.000
|
|
Some of the women described feeling unusually sick.
|
|
|
|
01:01:19.000 --> 01:01:22.000
|
|
I think I went to like high school with like 10 girls that looked like her.
|
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|
01:01:22.000 --> 01:01:23.000
|
|
That's great.
|
|
|
|
01:01:23.000 --> 01:01:25.000
|
|
Every time they got their periods.
|
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|
01:01:26.000 --> 01:01:33.000
|
|
But their symptoms had not escalated.
|
|
|
|
01:01:33.000 --> 01:01:36.000
|
|
Unlike Geraldine Dulek.
|
|
|
|
01:01:36.000 --> 01:01:43.000
|
|
Subdramal, predrome, syndromes, signs and symptoms that are, I can't do it,
|
|
|
|
01:01:43.000 --> 01:01:46.000
|
|
but that's what James Giordano would call that, right?
|
|
|
|
01:01:46.000 --> 01:01:51.000
|
|
Predrome, signs and symptoms before the main.
|
|
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|
01:01:51.000 --> 01:01:55.000
|
|
At St. Mary's hospital, the teenager was getting worse.
|
|
|
|
01:01:55.000 --> 01:02:01.000
|
|
Her condition had been steadily deteriorating.
|
|
|
|
01:02:01.000 --> 01:02:07.000
|
|
Finally, after 20 days in the hospital, she slipped into an irreversible coma.
|
|
|
|
01:02:07.000 --> 01:02:08.000
|
|
Holy shit!
|
|
|
|
01:02:08.000 --> 01:02:14.000
|
|
And on February 28th, Geraldine Dulek died from catastrophic organ failure.
|
|
|
|
01:02:14.000 --> 01:02:17.000
|
|
I thought she was in good hands with the mustache
|
|
|
|
01:02:17.000 --> 01:02:22.000
|
|
and the holy catastrophic organ failure Batman.
|
|
|
|
01:02:22.000 --> 01:02:25.000
|
|
How is that happening?
|
|
|
|
01:02:25.000 --> 01:02:30.000
|
|
How is it possible that that's happening?
|
|
|
|
01:02:30.000 --> 01:02:39.000
|
|
It's happening because there is a consensus about an unknown.
|
|
|
|
01:02:39.000 --> 01:02:45.000
|
|
Please understand that these people are, well, what we're being shown is a
|
|
|
|
01:02:45.000 --> 01:02:51.000
|
|
reenactment of people making bad decisions based on bad assumptions.
|
|
|
|
01:02:51.000 --> 01:02:56.000
|
|
Not intentionally, just because that can happen.
|
|
|
|
01:02:56.000 --> 01:03:01.000
|
|
But now imagine, imagine if you orchestrated it.
|
|
|
|
01:03:01.000 --> 01:03:07.000
|
|
Just please try to imagine how powerful it would be if you orchestrated it with a few
|
|
|
|
01:03:07.000 --> 01:03:13.000
|
|
well-rehearsed, very authoritative leaders
|
|
|
|
01:03:13.000 --> 01:03:17.000
|
|
in very influential positions.
|
|
|
|
01:03:17.000 --> 01:03:22.000
|
|
Wisconsin had lost its first victim to toxic shock syndrome.
|
|
|
|
01:03:22.000 --> 01:03:25.000
|
|
She would not be the last.
|
|
|
|
01:03:25.000 --> 01:03:26.000
|
|
Wow.
|
|
|
|
01:03:26.000 --> 01:03:32.000
|
|
Until 1980, the American public had never heard of toxic shock syndrome.
|
|
|
|
01:03:32.000 --> 01:03:38.000
|
|
But now the rare bacterial infection was erupting in the Midwest.
|
|
|
|
01:03:38.000 --> 01:03:42.000
|
|
One teenager had already died in Wisconsin.
|
|
|
|
01:03:42.000 --> 01:03:46.000
|
|
Now, the disease showed up in Iowa.
|
|
|
|
01:03:46.000 --> 01:03:52.000
|
|
On May 16th, 36-year-old Chris Lekock was rushed to the hospital.
|
|
|
|
01:03:52.000 --> 01:03:57.000
|
|
Her liver and kidneys were failing.
|
|
|
|
01:03:57.000 --> 01:04:03.000
|
|
The emergency room team worked hard to stabilize their patient.
|
|
|
|
01:04:03.000 --> 01:04:07.000
|
|
Hard lungs and arm muscles.
|
|
|
|
01:04:07.000 --> 01:04:11.000
|
|
They call you in the hospital's infectious disease.
|
|
|
|
01:04:11.000 --> 01:04:15.000
|
|
That's an ER doctor with a prosthetic arm.
|
|
|
|
01:04:15.000 --> 01:04:16.000
|
|
That's dope.
|
|
|
|
01:04:16.000 --> 01:04:18.000
|
|
Expert. Dr. Charles Helms.
|
|
|
|
01:04:18.000 --> 01:04:20.000
|
|
Could also be an android, I guess.
|
|
|
|
01:04:20.000 --> 01:04:25.000
|
|
But I think it's probably a doctor with a prosthetic arm.
|
|
|
|
01:04:25.000 --> 01:04:31.000
|
|
I get a call from Dr. Hingway, who was the resident on call in the intensive care unit,
|
|
|
|
01:04:31.000 --> 01:04:36.000
|
|
the medical intensive care unit, about a case that was really had him worried and concerned
|
|
|
|
01:04:36.000 --> 01:04:40.000
|
|
and wondered that infectious disease consults.
|
|
|
|
01:04:40.000 --> 01:04:43.000
|
|
Dr. Helms had never seen anything like it.
|
|
|
|
01:04:43.000 --> 01:04:49.000
|
|
It was as if the patient's entire body was shutting down, one organ after another.
|
|
|
|
01:04:49.000 --> 01:04:56.000
|
|
It's unusual to see a young, healthy person as she was.
|
|
|
|
01:04:56.000 --> 01:05:03.000
|
|
Come in so desperately ill, particularly with so many systems of her body involved.
|
|
|
|
01:05:03.000 --> 01:05:08.000
|
|
As her condition got worse, Chris was moved to the intensive care unit,
|
|
|
|
01:05:08.000 --> 01:05:10.000
|
|
where she could be monitored.
|
|
|
|
01:05:10.000 --> 01:05:14.000
|
|
In addition to her liver and kidneys, her lungs were failing.
|
|
|
|
01:05:14.000 --> 01:05:22.000
|
|
Perhaps of most concern to us here, her respiratory status, her ability to breathe and oxygenate her blood was...
|
|
|
|
01:05:22.000 --> 01:05:31.000
|
|
Now it's interesting, I think to note that a lot of these, the toxic shock syndrome is basically like a cytokine storm.
|
|
|
|
01:05:31.000 --> 01:05:38.000
|
|
I think that in current immunological lingo, this would be called a cytokine storm,
|
|
|
|
01:05:38.000 --> 01:05:42.000
|
|
and this multiple organ failure would be a result of a cytokine storm.
|
|
|
|
01:05:42.000 --> 01:05:44.000
|
|
That's my guess.
|
|
|
|
01:05:44.000 --> 01:05:47.000
|
|
Do you even argue with me in the chat if you want?
|
|
|
|
01:05:47.000 --> 01:05:50.000
|
|
In dire straits.
|
|
|
|
01:05:50.000 --> 01:05:53.000
|
|
Doctors rushed to intubate the patient.
|
|
|
|
01:05:56.000 --> 01:05:58.000
|
|
They put her on a respirator.
|
|
|
|
01:06:02.000 --> 01:06:04.000
|
|
Her blood pressure was crashing.
|
|
|
|
01:06:07.000 --> 01:06:09.000
|
|
Her organs weren't functioning.
|
|
|
|
01:06:09.000 --> 01:06:11.000
|
|
They were losing her.
|
|
|
|
01:06:13.000 --> 01:06:21.000
|
|
Their only hope of keeping Chris alive was to raise her blood pressure, to get blood to her vital organs.
|
|
|
|
01:06:23.000 --> 01:06:30.000
|
|
Despite the CDC's efforts, not all doctors were aware that a strange infection was on the move.
|
|
|
|
01:06:31.000 --> 01:06:41.000
|
|
If it was a bacterial infection, that she was on a sufficiently broad range of antibiotics to protect her while we figured out what was going on with her.
|
|
|
|
01:06:41.000 --> 01:06:46.000
|
|
Chris Lekock was placed on life support in the ICU.
|
|
|
|
01:06:46.000 --> 01:06:50.000
|
|
Her family sat by her side as she slipped into a coma.
|
|
|
|
01:06:50.000 --> 01:06:58.000
|
|
So one of the things you should realize that happened during the pandemic is that people were told that antibiotics don't work on viruses.
|
|
|
|
01:06:58.000 --> 01:07:03.000
|
|
And in this case, even though they're not absolutely sure what's going on,
|
|
|
|
01:07:03.000 --> 01:07:07.000
|
|
I think they generally speaking because of the presence of this one protein,
|
|
|
|
01:07:07.000 --> 01:07:10.000
|
|
I've decided that it's an indication of bacterial infection.
|
|
|
|
01:07:10.000 --> 01:07:15.000
|
|
So they're putting these people on a broad spectrum antibiotic set.
|
|
|
|
01:07:15.000 --> 01:07:24.000
|
|
But a broad spectrum antibiotic set for the unknown disease COVID was absolutely positively off the table.
|
|
|
|
01:07:25.000 --> 01:07:34.000
|
|
And you have to see how devastating that was for outcomes and especially because it was a controlled narrative.
|
|
|
|
01:07:34.000 --> 01:07:39.000
|
|
People were there and they said it over and over again.
|
|
|
|
01:07:39.000 --> 01:07:46.000
|
|
They went on social media and said people shouldn't be overusing antibiotics on a viral syndrome.
|
|
|
|
01:07:46.000 --> 01:07:51.000
|
|
Remember that because that was 2020 and 2021.
|
|
|
|
01:07:52.000 --> 01:07:54.000
|
|
But Chris was not alone.
|
|
|
|
01:07:54.000 --> 01:07:59.000
|
|
Toxic shock was now a national problem.
|
|
|
|
01:07:59.000 --> 01:08:02.000
|
|
At the CDC, the calls were streaming in.
|
|
|
|
01:08:02.000 --> 01:08:06.000
|
|
Hundreds of girls were sick and some were dying.
|
|
|
|
01:08:06.000 --> 01:08:11.000
|
|
Epidemiologist Bruce Dan tracked the outbreak.
|
|
|
|
01:08:11.000 --> 01:08:15.000
|
|
It was happening nationally and it doesn't state all over the country.
|
|
|
|
01:08:15.000 --> 01:08:19.000
|
|
Suddenly, young, previously healthy women who were going about their life,
|
|
|
|
01:08:19.000 --> 01:08:25.000
|
|
in high school, going to college, going to work, raising kids, selling, get ill, as if they had the flu.
|
|
|
|
01:08:25.000 --> 01:08:30.000
|
|
And some of them would be dead in the next 12 or 24 hours from a totally unknown cause.
|
|
|
|
01:08:30.000 --> 01:08:32.000
|
|
That's frightening.
|
|
|
|
01:08:32.000 --> 01:08:38.000
|
|
The CDC task force kept running totals of confirmed toxic shock cases.
|
|
|
|
01:08:38.000 --> 01:08:41.000
|
|
Reports were coming in from all over the country.
|
|
|
|
01:08:41.000 --> 01:08:45.000
|
|
Nationwide, the death toll had risen to seven.
|
|
|
|
01:08:45.000 --> 01:08:51.000
|
|
As the numbers kept pouring in, we got more and more calls saying we've seen another case and another case and another case.
|
|
|
|
01:08:51.000 --> 01:08:54.000
|
|
There's a lot of pressure to say we have to solve this very quickly.
|
|
|
|
01:08:54.000 --> 01:08:59.000
|
|
Find the answer to stop this epidemic and save a lot of lives.
|
|
|
|
01:08:59.000 --> 01:09:09.000
|
|
The CDC put together an MMWR, a mortality and morbidity weekly report on toxic shock syndrome.
|
|
|
|
01:09:09.000 --> 01:09:14.000
|
|
It wasn't alert to physicians at hospitals all across the country.
|
|
|
|
01:09:14.000 --> 01:09:23.000
|
|
The MMWR would help doctors make an early diagnosis of toxic shock patients.
|
|
|
|
01:09:23.000 --> 01:09:29.000
|
|
It's basically the CDC's mechanism for getting information out to doctors, nurses, health officials across the country.
|
|
|
|
01:09:29.000 --> 01:09:34.000
|
|
It's also mechanism for getting information back in.
|
|
|
|
01:09:34.000 --> 01:09:39.000
|
|
The CDC's report arrived at the Iowa hospital just in time.
|
|
|
|
01:09:43.000 --> 01:09:48.000
|
|
Dr. Helms recognized Chris Lekock's symptoms immediately.
|
|
|
|
01:09:51.000 --> 01:09:54.000
|
|
It was textbook toxic shock syndrome.
|
|
|
|
01:09:54.000 --> 01:09:58.000
|
|
Dr. Helms followed the CDC's recommendations.
|
|
|
|
01:09:58.000 --> 01:10:02.000
|
|
Massive amounts of fluids and antibiotics to fight infection.
|
|
|
|
01:10:02.000 --> 01:10:05.000
|
|
Massive amounts of fluids and antibiotics.
|
|
|
|
01:10:05.000 --> 01:10:08.000
|
|
The CDC could only watch and wait.
|
|
|
|
01:10:11.000 --> 01:10:15.000
|
|
Back at the CDC, the numbers continue to rise.
|
|
|
|
01:10:17.000 --> 01:10:22.000
|
|
107 cases had now surfaced in 33 separate states.
|
|
|
|
01:10:22.000 --> 01:10:26.000
|
|
Clearly, this was the beginning of a nationwide epidemic.
|
|
|
|
01:10:26.000 --> 01:10:28.000
|
|
But what was causing it?
|
|
|
|
01:10:28.000 --> 01:10:39.000
|
|
Your first hunch, if you want to play hunches, is probably maybe these are women who got a bad batch of some medication that women commonly take during their menstrual period for aches and pains and so forth.
|
|
|
|
01:10:39.000 --> 01:10:43.000
|
|
But you can't play your hunches when you're dealing with something like this. You have to do a real study.
|
|
|
|
01:10:43.000 --> 01:10:50.000
|
|
And so the CDC launched a nationwide hunt to discover the cause of toxic shock.
|
|
|
|
01:10:50.000 --> 01:10:55.000
|
|
You've got the names of 50 women from their medical records in hospitals across the United States.
|
|
|
|
01:10:55.000 --> 01:10:59.000
|
|
How do you find them? How do you call them? Where are they now?
|
|
|
|
01:10:59.000 --> 01:11:03.000
|
|
For each patient, they needed to interview three control subjects.
|
|
|
|
01:11:03.000 --> 01:11:13.000
|
|
They had to develop a way of tracking and tracing 50 women across the United States to track down what was happening with toxic shock syndrome.
|
|
|
|
01:11:13.000 --> 01:11:17.000
|
|
They needed phone books and piles of phone records.
|
|
|
|
01:11:17.000 --> 01:11:21.000
|
|
They asked each of the patients for the names of three friends.
|
|
|
|
01:11:21.000 --> 01:11:25.000
|
|
They asked the patients for the names of three friends.
|
|
|
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01:11:25.000 --> 01:11:32.000
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So it's not just a matter of making 200 phone calls, but maybe 400, 800,000 phone calls to get hold of all these people.
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01:11:32.000 --> 01:11:36.000
|
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It took a huge amount of work and I'm very short time to do it.
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01:11:36.000 --> 01:11:42.000
|
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With the days passing and more women falling ill, health officials raised to get to the bottom of the mystery.
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01:11:42.000 --> 01:11:52.000
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So we devised a questionnaire about 125, 150 questions asking everything we can think about about their current health status, medications they may be taking.
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01:11:52.000 --> 01:11:56.000
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Certainly everything we can think about their menstrual period, do you wear pads or tampons?
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01:11:56.000 --> 01:12:00.000
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Do you exercise during your period? Do you jog? Do you take showers? Do you take baths?
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01:12:00.000 --> 01:12:04.000
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What do you do unusual or not do unusual during your period?
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01:12:04.000 --> 01:12:08.000
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To get an idea of what would make the cases different than the controls?
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01:12:08.000 --> 01:12:14.000
|
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Why did the one group of young women get toxic shock syndrome and get violently ill and other women were totally healthy?
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01:12:14.000 --> 01:12:24.000
|
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It was clear to us that if you asked enough questions you would probably find out why women with toxic shock syndrome were different than other women.
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01:12:24.000 --> 01:12:28.000
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Turns out the answer surprised us.
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01:12:28.000 --> 01:12:36.000
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After weeks of medical detective work, the CDC investigators had found the common link.
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01:12:36.000 --> 01:12:41.000
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There was one thing that set the women with toxic shock apart.
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01:12:41.000 --> 01:12:44.000
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100% of them used tampons.
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01:12:44.000 --> 01:12:49.000
|
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What could it be about tampons that would cause this severe disease and cause women to die?
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01:12:49.000 --> 01:12:51.000
|
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Somebody had it right in the chat in the beginning.
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01:12:51.000 --> 01:12:56.000
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The solution to one mystery was the beginning of the next.
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01:12:56.000 --> 01:13:20.000
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CDC investigators presented their startling findings to every tampon manufacturer in the country.
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01:13:20.000 --> 01:13:25.000
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We invited the tampon manufacturers to come to Atlanta to CDC to discuss with us.
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01:13:25.000 --> 01:13:28.000
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They called the tampon manufacturer.
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01:13:28.000 --> 01:13:34.000
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Come and tell us what you guys know about this possibility and I'm sure you guys will be honest with us.
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01:13:34.000 --> 01:13:38.000
|
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First of all, to tell them what the results are or study with so they would be aware.
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01:13:38.000 --> 01:13:41.000
|
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And secondly, to find out from them, tell us about tampons.
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01:13:41.000 --> 01:13:44.000
|
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How are they made? Where are they made? What are they made of?
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01:13:44.000 --> 01:13:49.000
|
|
The executives agreed to provide the CDC with the information.
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01:13:49.000 --> 01:13:52.000
|
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But on one point, they were unequivocal.
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01:13:52.000 --> 01:13:57.000
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They had no intention of taking their products off the market.
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01:13:57.000 --> 01:14:01.000
|
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They believed the scientific proof was lacking.
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01:14:01.000 --> 01:14:10.000
|
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Still, CDC investigator Katherine Shans felt the evidence linking tampons to toxic shock was clear enough.
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01:14:10.000 --> 01:14:15.000
|
|
The disease needed two things to occur.
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01:14:15.000 --> 01:14:22.000
|
|
One was the presence of staph aureus and actually an infection with staph aureus.
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01:14:22.000 --> 01:14:26.000
|
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The other was the use of tampons.
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01:14:26.000 --> 01:14:30.000
|
|
And so the CDC went public with their findings.
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01:14:30.000 --> 01:14:34.000
|
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They needed to warn women about the potential threat.
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01:14:35.000 --> 01:14:38.000
|
|
But the mystery was far from solved.
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01:14:38.000 --> 01:14:42.000
|
|
Dozens of questions still lingered.
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|
01:14:42.000 --> 01:14:49.000
|
|
Investigators needed to conduct a second study to determine why tampons were making women sick.
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01:14:49.000 --> 01:14:52.000
|
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What caused the infection?
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01:14:52.000 --> 01:14:55.000
|
|
Had specific brands become contaminated.
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01:14:55.000 --> 01:15:01.000
|
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So we collected tampons to test them in the laboratory to see if any particular tampon, any brand, any style
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01:15:01.000 --> 01:15:05.000
|
|
from any kind of manufacturing location might be contaminated.
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01:15:05.000 --> 01:15:11.000
|
|
And though we looked at hundreds and thousands of tampons, you know, hundreds and thousands of hours of laboratory town to look for that,
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01:15:11.000 --> 01:15:18.000
|
|
we couldn't find any particular tampon that were contaminated with anything that would cause a disease.
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01:15:18.000 --> 01:15:22.000
|
|
The story of the outbreak made national headlines.
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01:15:22.000 --> 01:15:28.000
|
|
All over America, women were confused and terrified.
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01:15:28.000 --> 01:15:31.000
|
|
This was also under sort of a national spotlight.
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|
01:15:31.000 --> 01:15:38.000
|
|
And suddenly, not only do you have the spotlight on you from just your local colleagues, but the Director of CDC, the Surgeon General,
|
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|
01:15:38.000 --> 01:15:44.000
|
|
the Department of Health and Human Services Secretary, and even the Presidential Office is looking very quickly at you to say,
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01:15:44.000 --> 01:15:47.000
|
|
hey, this is a real problem. Are you guys going to solve it?
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|
01:15:47.000 --> 01:15:52.000
|
|
Throughout the summer and fall, the epidemic raged on.
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01:15:52.000 --> 01:15:55.000
|
|
And panic began to set in.
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01:15:55.000 --> 01:16:03.000
|
|
As more and more women found themselves in a battle with a mysterious disease, fighting for their lives.
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01:16:03.000 --> 01:16:09.000
|
|
All across America, women were dying and helped.
|
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|
01:16:09.000 --> 01:16:11.000
|
|
Return from commercial break.
|
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|
01:16:11.000 --> 01:16:17.000
|
|
As scientists raced to find answers, more patients were being rushed to the hospital.
|
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|
01:16:17.000 --> 01:16:27.000
|
|
Patients like 25-year-old Pat Kemp, the mother of two small children, she had early flu-like symptoms.
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|
01:16:27.000 --> 01:16:34.000
|
|
Now, she was in the ER, and her husband was worried.
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|
01:16:34.000 --> 01:16:40.000
|
|
Every 15 or 20 minutes I was allowed to enter into the emergency room.
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|
01:16:40.000 --> 01:16:43.000
|
|
Sorry for the recaps after commercials.
|
|
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|
01:16:43.000 --> 01:16:48.000
|
|
You're supposed to be asking questions and not making funny comments, and then I could have something to talk about,
|
|
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|
01:16:48.000 --> 01:16:51.000
|
|
but the funny comments are just making me laugh.
|
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|
01:16:51.000 --> 01:16:52.000
|
|
But I can squeeze it back.
|
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|
01:16:52.000 --> 01:16:57.000
|
|
As Pat's condition deteriorated, Mike grew more concerned.
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|
01:16:57.000 --> 01:17:04.000
|
|
To think that just a few days prior, she was the young, healthy mother of my children, and we were enjoying life
|
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|
01:17:04.000 --> 01:17:17.000
|
|
and making plans for our future to see her in a hospital setting, looking totally unlike her normal self and fighting to take every breath.
|
|
|
|
01:17:17.000 --> 01:17:25.000
|
|
The medical community was now on high alert for patients who showed signs of toxic shock syndrome.
|
|
|
|
01:17:25.000 --> 01:17:30.000
|
|
And Pat Kemp was a classic case.
|
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|
01:17:30.000 --> 01:17:38.000
|
|
Admitted to the ICU, Pat was treated with antibiotics to fight the infection, but her situation was grave,
|
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|
|
01:17:38.000 --> 01:17:43.000
|
|
and Mike could see she had taken a turn for the worse.
|
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|
01:17:43.000 --> 01:17:51.000
|
|
It was so alarmed at how her coloring had changed, and later I understood that that was because her blood vessels were bursting under her skin,
|
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|
01:17:51.000 --> 01:17:55.000
|
|
due to the toxins and the poison in her body.
|
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|
01:17:55.000 --> 01:17:59.000
|
|
And I said, well, doctor, what's the worst thing I can expect?
|
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|
01:17:59.000 --> 01:18:03.000
|
|
And he said, Mike, that's a good question to ask.
|
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|
01:18:03.000 --> 01:18:10.000
|
|
You know, my fear was, would she have lung damage or brain damage or some other organ that could be damaged by all this?
|
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|
01:18:10.000 --> 01:18:16.000
|
|
And he said, you know, that's a fair question, but our fight right now is just to try to keep her alive.
|
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|
01:18:16.000 --> 01:18:21.000
|
|
And at that point, it dawned on me just how critical she was.
|
|
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|
01:18:22.000 --> 01:18:30.000
|
|
Even as Pat Kemp lay on that hospital bed, the CDC was working around the clock to pinpoint the source of her infection.
|
|
|
|
01:18:30.000 --> 01:18:34.000
|
|
Was it a style of tampon, one specific brand?
|
|
|
|
01:18:34.000 --> 01:18:38.000
|
|
That's when investigators had a breakthrough.
|
|
|
|
01:18:38.000 --> 01:18:45.000
|
|
In this particular study, one particular brand of tampon accounted for about two-thirds of all the cases.
|
|
|
|
01:18:45.000 --> 01:18:50.000
|
|
And it was a brand of tampons and only about a fifth of women in the United States were using.
|
|
|
|
01:18:50.000 --> 01:18:54.000
|
|
So something was hardly risky about this tampon.
|
|
|
|
01:18:54.000 --> 01:19:00.000
|
|
The brand was a relatively new product that had been aggressively marketed as a super-absorbent tampon.
|
|
|
|
01:19:00.000 --> 01:19:02.000
|
|
Hey, somebody got that one.
|
|
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|
01:19:02.000 --> 01:19:06.000
|
|
Millions of dollars per month. Nice! Well done, guys.
|
|
|
|
01:19:06.000 --> 01:19:14.000
|
|
They told us that they had made changes in the composition of tampons over the last several years.
|
|
|
|
01:19:14.000 --> 01:19:21.000
|
|
Prior to 1975, all tampons had been made of cotton and rayon.
|
|
|
|
01:19:21.000 --> 01:19:32.000
|
|
And they had begun introducing high absorbency chemical materials into tampons to, obviously, to increase the absorbency.
|
|
|
|
01:19:32.000 --> 01:19:38.000
|
|
The FDA acted swiftly and pulled the brand from the shelves.
|
|
|
|
01:19:38.000 --> 01:19:43.000
|
|
When they did that, the number of cases of toxic shock syndrome dropped off dramatically.
|
|
|
|
01:19:43.000 --> 01:19:53.000
|
|
And not surprisingly, if tampon is responsible for two-thirds of the cases, removing that tampon from the market, as quickly as you can, reduce the number of cases.
|
|
|
|
01:19:53.000 --> 01:19:55.000
|
|
The CDC got the word out.
|
|
|
|
01:19:55.000 --> 01:19:58.000
|
|
Tampons were directly linked to toxic shock syndrome.
|
|
|
|
01:19:58.000 --> 01:20:09.000
|
|
Man, I flew from the Philippines and back when I was a kid, and I can still remember clear as day that that entire frickin' airplane was full of smoking.
|
|
|
|
01:20:09.000 --> 01:20:15.000
|
|
And there were still, you know, ashtrays, and my mom smoked. I can remember it, wow.
|
|
|
|
01:20:15.000 --> 01:20:19.000
|
|
But for Pat Kemp, it was already too late.
|
|
|
|
01:20:19.000 --> 01:20:26.000
|
|
Despite the doctor's rapid diagnosis, she lay in a coma, unable to breathe on her own.
|
|
|
|
01:20:26.000 --> 01:20:29.000
|
|
And I would spend the evening with her at the hospital.
|
|
|
|
01:20:29.000 --> 01:20:31.000
|
|
She squeezed my hand.
|
|
|
|
01:20:31.000 --> 01:20:37.000
|
|
My one question is, once they develop this toxic shock syndrome, are they just kind of lost?
|
|
|
|
01:20:37.000 --> 01:20:43.000
|
|
Are these people also still menstruating and using a tampon incorrectly?
|
|
|
|
01:20:43.000 --> 01:20:45.000
|
|
And that's why they cascade out of control.
|
|
|
|
01:20:45.000 --> 01:20:53.000
|
|
Or once they get into this scenario, are they, they kind of, it's a crapshoot, whether they can be pulled out of the nose dive?
|
|
|
|
01:20:53.000 --> 01:20:55.000
|
|
That's the only part I don't understand here.
|
|
|
|
01:20:55.000 --> 01:20:57.000
|
|
Tears are rolling out.
|
|
|
|
01:20:57.000 --> 01:21:01.000
|
|
This can be rough, I see it in those tears where we're at.
|
|
|
|
01:21:01.000 --> 01:21:05.000
|
|
Because of the blood vessels bursting in her eyes and so on.
|
|
|
|
01:21:09.000 --> 01:21:13.000
|
|
On September 6th, 1980, Pat Kemp lost her bat.
|
|
|
|
01:21:13.000 --> 01:21:15.000
|
|
No randomized control.
|
|
|
|
01:21:15.000 --> 01:21:17.000
|
|
No trials, no none.
|
|
|
|
01:21:17.000 --> 01:21:19.000
|
|
Another victim of this terrible shock.
|
|
|
|
01:21:19.000 --> 01:21:21.000
|
|
Oh wow, she died too, crazy.
|
|
|
|
01:21:21.000 --> 01:21:25.000
|
|
But the story wasn't over.
|
|
|
|
01:21:25.000 --> 01:21:29.000
|
|
Although one brand of tampons had been pulled from the shelves.
|
|
|
|
01:21:29.000 --> 01:21:33.000
|
|
More cases of the infection turned out really still around the country.
|
|
|
|
01:21:33.000 --> 01:21:37.000
|
|
Women were getting sick while using other brands.
|
|
|
|
01:21:37.000 --> 01:21:39.000
|
|
And no one knew exactly why.
|
|
|
|
01:21:39.000 --> 01:21:43.000
|
|
Absorbency levels seemed to be a factor.
|
|
|
|
01:21:43.000 --> 01:21:47.000
|
|
As well as how long they remained inside the body.
|
|
|
|
01:21:48.000 --> 01:21:57.000
|
|
To alert the public, the FDA required tampon manufacturers to include information in their packaging about toxic shock syndrome.
|
|
|
|
01:21:57.000 --> 01:21:59.000
|
|
And how to avoid it.
|
|
|
|
01:21:59.000 --> 01:22:04.000
|
|
In Iowa, Chris Lekock spent weeks lying near death.
|
|
|
|
01:22:04.000 --> 01:22:08.000
|
|
Finally, the aggressive antibiotic therapy kicked in.
|
|
|
|
01:22:08.000 --> 01:22:12.000
|
|
Her body fought off the staph aureus bacteria.
|
|
|
|
01:22:13.000 --> 01:22:20.000
|
|
Chris's doctor, Richard Helms, credits the research of the CDC for saving her life.
|
|
|
|
01:22:20.000 --> 01:22:31.000
|
|
Chris was fortunate that she came in to a hospital in this country at that particular point in the evolution of American medicine.
|
|
|
|
01:22:31.000 --> 01:22:33.000
|
|
Where we had a syndrome.
|
|
|
|
01:22:33.000 --> 01:22:35.000
|
|
Where we had an approach to that syndrome.
|
|
|
|
01:22:35.000 --> 01:22:40.000
|
|
And that syndrome included treatment of staphylococcus aureus.
|
|
|
|
01:22:40.000 --> 01:22:48.000
|
|
Nearly a month after she was admitted, Chris Lekock was released from the hospital.
|
|
|
|
01:22:48.000 --> 01:22:55.000
|
|
Today, she's still thankful for Dr. Helms' quick thinking.
|
|
|
|
01:22:55.000 --> 01:22:57.000
|
|
They saved my life.
|
|
|
|
01:22:57.000 --> 01:22:58.000
|
|
There's no doubt about it.
|
|
|
|
01:22:58.000 --> 01:23:00.000
|
|
They saved my life.
|
|
|
|
01:23:00.000 --> 01:23:02.000
|
|
They were on top of it.
|
|
|
|
01:23:02.000 --> 01:23:05.000
|
|
They had to try a lot of different things.
|
|
|
|
01:23:05.000 --> 01:23:10.000
|
|
You have to realize that my kidneys failed.
|
|
|
|
01:23:10.000 --> 01:23:13.000
|
|
I went into congestive heart failure.
|
|
|
|
01:23:13.000 --> 01:23:20.000
|
|
I was being kept alive by life support.
|
|
|
|
01:23:20.000 --> 01:23:25.000
|
|
And they kept me alive.
|
|
|
|
01:23:25.000 --> 01:23:30.000
|
|
And I'm very, very grateful to them.
|
|
|
|
01:23:30.000 --> 01:23:34.000
|
|
They spent the one unfortunate year, hunt evidence.
|
|
|
|
01:23:34.000 --> 01:23:41.000
|
|
But women like Chris, in the following years, simply worked too well.
|
|
|
|
01:23:41.000 --> 01:23:45.000
|
|
They became tiny incubators for disease.
|
|
|
|
01:23:45.000 --> 01:23:51.000
|
|
The perfect growth medium for the staph aureus bacteria.
|
|
|
|
01:23:51.000 --> 01:23:56.000
|
|
Manufacturers went back to old-fashioned cotton and rayon.
|
|
|
|
01:23:56.000 --> 01:23:59.000
|
|
And health officials got out the morning.
|
|
|
|
01:23:59.000 --> 01:24:02.000
|
|
The need to change tampons regularly.
|
|
|
|
01:24:02.000 --> 01:24:05.000
|
|
And watch for flu-like symptoms.
|
|
|
|
01:24:05.000 --> 01:24:11.000
|
|
The outbreak taught larger lessons as well.
|
|
|
|
01:24:11.000 --> 01:24:19.000
|
|
I think one of the lessons of toxic shock syndrome is that, just as much as we've learned about bioterrorism and anthrax lately, is that you need to have...
|
|
|
|
01:24:19.000 --> 01:24:21.000
|
|
What did he say?
|
|
|
|
01:24:21.000 --> 01:24:27.000
|
|
As much as we've learned about bioterrorism and anthrax lately?
|
|
|
|
01:24:27.000 --> 01:24:29.000
|
|
This was from the 90s, right?
|
|
|
|
01:24:29.000 --> 01:24:34.000
|
|
Remember, we could look up exactly when this show was.
|
|
|
|
01:24:34.000 --> 01:24:51.000
|
|
I think one of the lessons of toxic shock syndrome is that, just as much as we've learned about bioterrorism and anthrax lately, is that you need to have a group of highly trained professionals who at a moment's notice can look into solve and fix an epidemic.
|
|
|
|
01:24:51.000 --> 01:24:56.000
|
|
One of the things about epidemics is you never know where they're going to happen or where they're going to come from.
|
|
|
|
01:24:56.000 --> 01:25:00.000
|
|
No, the story is from the 90s.
|
|
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01:25:00.000 --> 01:25:04.000
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The TV shows from the 90s, I think, and they're talking about the 70s.
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01:25:04.000 --> 01:25:09.000
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You're right about it being later or earlier, but they're doing a reenactment of it now.
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01:25:09.000 --> 01:25:11.000
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And this, I think, this show, I can look.
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01:25:11.000 --> 01:25:12.000
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Let me see.
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01:25:12.000 --> 01:25:16.000
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Maybe it'll be on the...
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01:25:16.000 --> 01:25:25.000
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No, it doesn't say it here.
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01:25:25.000 --> 01:25:32.000
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But I don't think that I think this was really, like, you know, in the 90s and then they were reenactment.
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01:25:32.000 --> 01:25:35.000
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He is early detection and swift reaction.
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01:25:35.000 --> 01:25:37.000
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Mike Kim and his wife, Sister Carol.
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01:25:37.000 --> 01:25:39.000
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You've got to watch out for that.
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01:25:39.000 --> 01:25:40.000
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You've got to watch out for that.
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01:25:41.000 --> 01:25:44.000
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Myself and my daughters and our family.
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01:25:44.000 --> 01:26:07.000
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Our goal today is for the next generation of young women who are using feminine hygiene products today to please read the warning labels that are on the boxes of these products or inside on pamphlets and have an awareness that if you have any flu-like symptoms, you could be endangering your life and to remove the product and seek medical attention immediately.
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01:26:08.000 --> 01:26:16.000
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That simple warning came 30 or 45 days too late to save my wife's life.
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01:26:16.000 --> 01:26:27.000
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Today, nearly 20 years after the first outbreak, the numbers of syndrome cases caused by tampons have declined sharply, but they have not disappeared.
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01:26:27.000 --> 01:26:33.000
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Hundreds of incidents are still reported each year.
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01:26:33.000 --> 01:26:40.000
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Thanks to new diagnostic tools and early detection, many of those lives can now be saved.
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01:26:51.000 --> 01:26:53.000
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That was fun.
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01:26:53.000 --> 01:26:55.000
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Just for a quick close out here.
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01:26:55.000 --> 01:27:02.000
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Don't forget that we're really trying to interrogate the infectious cycle.
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01:27:02.000 --> 01:27:13.000
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And I believe that right now we are being sort of bamboozled by an illusion of consensus being created by a bunch of people that are in place.
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01:27:13.000 --> 01:27:31.000
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They're on purpose to make sure that we don't figure out the kinds of molecular biological tricks that could be used in order to seed the narrative of a pandemic to make sure that this pandemic potential is believed to have actually occurred so that they never have to say it again.
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01:27:31.000 --> 01:27:34.000
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They can just sound the alarm and then things are going to happen again.
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01:27:34.000 --> 01:27:42.000
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I want to remind you that it is actually Robert Malone himself who told us this idea that these produces viruses.
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01:27:42.000 --> 01:27:49.000
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In most cases, a large fraction, if not the majority of the virus particles that are produced are defective.
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01:27:49.000 --> 01:27:53.000
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Then I get for anything and I'm infectious. They just kind of float around.
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01:27:53.000 --> 01:27:58.000
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And among other things, they interact with the immune system as does the live virus.
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01:27:59.000 --> 01:28:10.000
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So we need to do the homework necessary to figure out why it is that the vast majority of particles in a coronavirus infection are non infectious and we are doing that work right now.
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01:28:10.000 --> 01:28:25.000
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And more importantly, we're trying to put together a history of clones so that we can see how long these people have been so happy about being able to use clones to bridge this gap between things that we don't have infectious material to study.
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01:28:25.000 --> 01:28:29.000
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Things that we can't culture and things that we can study.
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01:28:29.000 --> 01:28:48.000
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And this is a review from 1994 and here they're already seeing the possibility of obtaining infectious clones and corresponding to the genomes of RNA viruses has greatly enhanced the potential investigations and that you can substitute things.
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01:28:48.000 --> 01:28:56.000
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And they facilitate studies of viruses that are present only in low titers and infected cells or whose isolation is problematic.
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01:28:56.000 --> 01:29:09.000
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And so we can go on and look at an article by Allison Tortura and Cina Bavari Allison Tortura being the last postdoc of Ralph Barrack before the pandemic.
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01:29:09.000 --> 01:29:25.000
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And we can read all about reverse genetic systems and how handy they are for using CDNA concepts to create full length infectious clones allowing precise targeting of genetic manipulation and also the creation of near homogenous viral
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01:29:25.000 --> 01:29:32.000
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stocks that can't be that are near homogenous when compared to traditional viral stocks.
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01:29:32.000 --> 01:29:41.000
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And that near homogeneity makes a very different story for what kinds of things could be in theory seeded when using infectious clones to do so.
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01:29:41.000 --> 01:29:43.000
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The signal would be different.
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01:29:43.000 --> 01:29:56.000
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And so we're going to talk about viral packaging just very briefly just to say that the packaging and the making of new viruses for coronavirus versus flu for example is very different.
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01:29:56.000 --> 01:30:05.000
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One of the things that I'd like to point out and give you a hint about is the end proteins really a lot more important than you might think for the assembly of viruses and coronavirus in particular.
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01:30:05.000 --> 01:30:21.000
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Here's a little diagram to remind you that influenza virus is a negative RNA and that means it needs to bring its own proteins with it and that little process of copying the genome of a flu virus seems to involve transport in and out of the nucleus
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01:30:21.000 --> 01:30:31.000
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where a coronavirus actually doesn't transport in and out of the nucleus and does all of its work in double membrane vesicles that are budding off of the ER.
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01:30:31.000 --> 01:30:45.000
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I suspect that according to this diagram and this seems to be the truth that subgenomic mRNAs are also assembled into viruses and that is the preponderance of viral particles expressing subgenomic RNAs.
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01:30:45.000 --> 01:30:58.000
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And so in that case you can imagine very easily the most abundant subgenomic RNAs are the ones that are most likely to be packaged and that would be NME and S interestingly enough.
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01:30:58.000 --> 01:31:07.000
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So if we keep working on this then what is the virus actually hijacking it's hijacking the machinery that already exists for putting things into vesicles and making exosomes.
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01:31:08.000 --> 01:31:14.000
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We want to also argue about RNA copying and whether or not it can be copied with the same fidelity as DNA.
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01:31:14.000 --> 01:31:27.000
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I'm making the argument that it can't and trying to use this analogy of a audio cassette versus a CD one of which can be copied quite regularly and one of which cannot.
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01:31:28.000 --> 01:31:35.000
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That scenario that kind of explains to me in an analogous way why a coronavirus is very difficult to culture and sustain in culture.
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01:31:35.000 --> 01:31:53.000
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But if you start with a DNA molecule an equivalent of it and you grow large quantities of it in either with using PCR or if you wanted to grow industrial sized quantities you might use E. coli like like an OVO did for its vaccine.
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01:31:54.000 --> 01:32:01.000
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Then you can make lots of quantities of that DNA then you could use a commercial polymerase to change that into RNA.
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01:32:01.000 --> 01:32:18.000
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And then you would have an extremely homogenous collection of really the sky's the limit how much you want to make of this genomic RNA that you can then apply to a cell culture and get it packaged into virus that you can then use to make models in the laboratory of disease.
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01:32:18.000 --> 01:32:20.000
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You can store it, you can go back to it.
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01:32:20.000 --> 01:32:31.000
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And what I'm arguing is you can make enough quantities of it if you wanted to with enough investment with the standard techniques known to use for other biologics to make enough to distribute around the world.
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01:32:31.000 --> 01:32:39.000
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And if you did that then you would have a signal that would be very homogenous and very detectable for PCR and for sequencing.
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01:32:39.000 --> 01:32:57.000
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And so after a few times of talking this through with Kevin McKernan, Kevin McKernan has blocked me and then recently I caught this little comment where he says that he's not talking to me anymore but he's making fun of me.
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01:32:57.000 --> 01:33:08.000
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And he says that it's just bio babble that coronaviruses circulate the globe every year that they hyper optimized the receptor binding domain to make it spread farther doesn't mention the fear and cleavage site.
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01:33:08.000 --> 01:33:23.000
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He says that he assumes that the virus originated in 2019 and he's claiming that prior circulation is an idea of his rather than mine says that the cloning hypothesis is chemtrail retarded.
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01:33:23.000 --> 01:33:35.000
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He says you just have to infect a few people or transfect a few people he says which is exactly what Giordano has said and what I've been saying for three years and he writes it here as though it was his idea.
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01:33:35.000 --> 01:33:39.000
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Then he calls it a keystone cop hypothesis.
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01:33:39.000 --> 01:33:49.000
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He says leaking the virus is better for world governments and he doesn't do the math on excess deaths and he still hasn't done it and he doesn't care if it was a man.
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01:33:50.000 --> 01:33:54.000
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Or if it was an iatrogenic murder fest.
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01:33:54.000 --> 01:34:09.000
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There was also a pandemic because coronaviruses circulate the globe every year according to this grad school dropout Steve or Eric Lander protege who worked for the human genome project and now as a cannabis genetics company.
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01:34:10.000 --> 01:34:23.000
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Jessica Rose thinks it's a great idea back when I was telling this idea to the entire Steve curse steering committee they all didn't think it was a good idea but Jessica did Matt Crawford did.
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01:34:24.000 --> 01:34:41.000
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And so it's very curious that this guy wastes his time trying to come against someone who's doesn't have a job has gotten laid off from a second job for telling the truth during the course of the pandemic was actually offered a paltry eight thousand dollars and a non disclosure
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01:34:41.000 --> 01:35:00.000
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agreement from Children's Health Defense and as a as a parting gift and I decided not to say anything and not to take that and the main reason being because then people like Kevin McCurnan could go on ad infinitum as they are on Twitter right now calling me a scammer or calling
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01:35:00.000 --> 01:35:13.000
|
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me a liar or making up stories or or whatever and also then just speculate that maybe I took a hundred thousand dollars and I wouldn't be able to say anything because I would have signed an NDA.
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01:35:13.000 --> 01:35:20.000
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And so I didn't sign an NDA and I can say whatever the hell I want to and according to CHD I'm worth eight thousand.
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01:35:21.000 --> 01:35:30.000
|
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My family's worth eight thousand my sacrifice to put my name in the Wuhan cover up book is worth eight thousand plus time spent.
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01:35:32.000 --> 01:35:46.000
|
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Or at least according to some people in the management of CHD I should say because I know that I have lots of friends that I still love who work at CHD who are fighting for the same things that we are fighting for and that's why I'm not afraid.
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01:35:47.000 --> 01:35:54.000
|
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That's why I'm not worried because I know CHD will weather this storm and I know that CHD will come out on the other side of better organization.
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01:35:56.000 --> 01:35:59.000
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But something very very very wrong is a foot.
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01:36:00.000 --> 01:36:03.000
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Something very wrong is a foot and I do need your help.
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01:36:04.000 --> 01:36:15.000
|
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I do need your help fighting this because I am all alone in my garage in Pittsburgh with about forty five subscribers which turns out to be pretty close to like you know five hundred dollars a month.
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01:36:16.000 --> 01:36:18.000
|
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And total so I need help.
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01:36:18.000 --> 01:36:26.000
|
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We need to have a Brett Weinstein style support here where if I had a thousand subscribers we could make this work.
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01:36:28.000 --> 01:36:41.000
|
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But we've got to be able to do this math and nobody else is doing it but us and he's a tonic live and Jessica Hockett and Nick Hudson and Denny Denny Rancore and a few other people.
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01:36:42.000 --> 01:36:47.000
|
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Everybody else isn't doing it. Everybody else is not talking about this stuff.
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01:36:48.000 --> 01:36:50.000
|
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They're just trying to make diffuse real again.
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01:36:51.000 --> 01:37:04.000
|
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Robert Malone and Kevin McCurnan and Archmetic and Jessica Rose are all trying to make diffuse real again and I want to make RNA clones real again.
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01:37:05.000 --> 01:37:17.000
|
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I want to make RNA real again. RNA biology real again. I want to stop this this charade where everybody's pretending to make a contribution to a tug of war and they're not even pulling on the rope.
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01:37:18.000 --> 01:37:27.000
|
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They're not asking relevant questions and they're arguing about irrelevant things by taking irrelevant positions and writing irrelevant books.
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01:37:29.000 --> 01:37:33.000
|
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And it's got to be stopped. We cannot let them do this to our children.
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01:37:34.000 --> 01:37:45.000
|
|
The double stranded DNA contamination is just a dumb focus point for what should be a 40 point objection to the wholly inappropriate use of transfection on healthy humans.
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01:37:46.000 --> 01:37:49.000
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Never mind healthy young people. Never mind healthy children.
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01:37:51.000 --> 01:37:58.000
|
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And the diffuse proposal and the discussion of what it means and whether these things were done or not is all a hoax.
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01:37:58.000 --> 01:38:11.000
|
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And we're going to show it. We're going to talk about it. We're going to outline it. And then you're going to have to everyone is going to have to recalibrate what they think about the people that have been pushing this.
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01:38:12.000 --> 01:38:15.000
|
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What they think about the people that have been pushing this.
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01:38:15.000 --> 01:38:19.720
|
|
pushing this. You're going to have to start really evaluating what you think
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01:38:19.720 --> 01:38:25.000
|
|
about the people who have been pushing this. You're really going to have to
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|
01:38:25.000 --> 01:38:30.360
|
|
think about what you think about the people who have been pushing this. This
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01:38:30.360 --> 01:38:35.560
|
|
idea of a of a worst case scenario being a gain of function bio weapon, the
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|
01:38:35.560 --> 01:38:41.040
|
|
people that picked us up on this road, the people who laid down this list,
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|
01:38:41.040 --> 01:38:48.080
|
|
these these people. It produces viruses. In most cases, a large fraction, if not
|
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|
|
01:38:48.080 --> 01:38:52.800
|
|
the majority of the virus particles that are produced are defective. And I
|
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01:38:52.800 --> 01:38:57.120
|
|
good for anything. They're not infectious. They just kind of float around. And among
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01:38:57.120 --> 01:39:00.560
|
|
other things, they interact with the immune system as does the live virus.
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01:39:04.480 --> 01:39:08.720
|
|
And so this is the lie that they told us for almost two years straight from the
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|
01:39:08.720 --> 01:39:14.560
|
|
TV all through social media arguing about the relevance of antibodies, arguing
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01:39:14.560 --> 01:39:18.480
|
|
about neutralizing versus non neutralizing antibodies, arguing about
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01:39:18.480 --> 01:39:23.440
|
|
antibodies from virus versus antibodies from infection versus antibodies from
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01:39:23.440 --> 01:39:28.960
|
|
the vaccine. Ladies and gentlemen, we need to wake up and apologize to our
|
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|
01:39:28.960 --> 01:39:33.520
|
|
children. It's not our fault that this happened. But if you listen to the wrong
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01:39:33.520 --> 01:39:36.880
|
|
people, you're going to hear the wrong things. And as you start listening to the
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01:39:36.880 --> 01:39:41.440
|
|
right people, you will start to be able to see the light. The intellectual
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01:39:41.440 --> 01:39:45.280
|
|
bright web is out there somewhere. The independent bright web is out there
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01:39:45.280 --> 01:39:49.280
|
|
somewhere. And I hope Gigo and biological is part of this light that's going to
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|
01:39:49.280 --> 01:39:56.320
|
|
prevent this lie from becoming the truth. But we cannot underestimate the the
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01:39:59.360 --> 01:40:06.160
|
|
the odds against us. We can't estimate the under estimate the odds against us. We
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|
01:40:06.240 --> 01:40:09.440
|
|
can't underestimate how many of these things are close to becoming true.
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01:40:10.240 --> 01:40:13.680
|
|
How close we are to having a digital currency. How close we are to having
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01:40:13.680 --> 01:40:16.800
|
|
digital ID to be on the internet. We need to be aware of that.
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01:40:19.760 --> 01:40:23.040
|
|
If we're going to get rid of this faith in a novel virus to make sure that our kids
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01:40:23.040 --> 01:40:27.120
|
|
don't get on this train, we need to be aware and we need to start talking.
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01:40:27.840 --> 01:40:33.680
|
|
We need to start posting. We need to start blocking. We need to start muting. We need to start
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01:40:34.320 --> 01:40:39.920
|
|
coordinatedly promoting the people who have this message that we need to get to our kids.
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01:40:42.240 --> 01:40:48.800
|
|
Message about the real history of epidemics and about sanitation and water treatment.
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|
01:40:48.800 --> 01:40:54.640
|
|
The real story about novel coronaviruses and how RNA viruses are done in the laboratory.
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01:40:55.440 --> 01:41:01.520
|
|
Real story about PCR, the real story about asymptomatic spread being a narrative
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01:41:01.520 --> 01:41:05.440
|
|
and the real story of gain of function. We can't let them get on this train and ride away.
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01:41:08.560 --> 01:41:11.440
|
|
Can't let them get on this train and ride away, ladies and gentlemen.
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01:41:13.040 --> 01:41:19.440
|
|
Here's just something to remind you, for example, that it was a plan. This is the sparse pandemic
|
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01:41:19.440 --> 01:41:26.960
|
|
document behind my head here where they talk about how the Corovacs side effects and the
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01:41:26.960 --> 01:41:30.960
|
|
rumors of them travel on the internet and start to disrupt the social sphere
|
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01:41:31.840 --> 01:41:36.080
|
|
a few years after the pandemic happens. This is all part of the story.
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01:41:37.200 --> 01:41:42.240
|
|
The document you see over there, I believe, is from Alberta Health Services in Canada,
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01:41:42.240 --> 01:41:49.520
|
|
where they remind kids that their parents only have control and that is access to your health
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01:41:49.600 --> 01:41:57.120
|
|
information from ages 0 to 11. At 12 to 13, your parent or guardian can request access,
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01:41:58.000 --> 01:42:02.960
|
|
can request access, but doesn't necessarily have it. So listen very carefully.
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01:42:08.320 --> 01:42:13.600
|
|
Keep in mind, my AHS Connect is the only way to access your health information.
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01:42:15.120 --> 01:42:19.280
|
|
Until you're 12 years old, your parent or guardian will be able to access your health
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01:42:19.280 --> 01:42:25.680
|
|
information through proxy access, a special permission granted to them by your health care
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01:42:25.680 --> 01:42:32.160
|
|
team. So the health care team is actually granting you permissions to have access to your kid's
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01:42:32.160 --> 01:42:40.800
|
|
medical records. What part about inverting your sovereignty to permissions? Is this,
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01:42:42.000 --> 01:42:47.280
|
|
could this be any more spot on dead on balls accurate smack on point for what I've been saying
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01:42:47.280 --> 01:42:52.240
|
|
for the last three years that they were going to invert your freedom to permissions?
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01:42:53.520 --> 01:43:01.600
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Here is a Health Services Canada document saying that it is a special permission granted to the
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01:43:01.600 --> 01:43:08.320
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parents of kids under the age of 12 to have access to their data and that at age 14 and beyond,
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01:43:08.320 --> 01:43:09.920
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they don't have access anymore.
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01:43:09.920 --> 01:43:21.680
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I can't stress enough to you how important it is to see how far we are from winning,
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01:43:21.680 --> 01:43:32.080
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how close this is to becoming a truth, especially in places like Canada and the UK and Australia
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01:43:32.080 --> 01:43:38.480
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and New Zealand, which are going to be used as psychological bludgens to make sure that we accept
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01:43:38.480 --> 01:43:46.640
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whatever they force on them. We've got to break this illusion of consensus. We've got to break
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01:43:46.640 --> 01:43:52.880
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this faith in a novel virus. We've got to make sure our kids realize that this faith in a five-year
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01:43:52.880 --> 01:44:01.200
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continuous spread of a novel RNA pathogen is wrong. It is a lie. It is a conflated background signal.
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01:44:01.200 --> 01:44:08.240
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It is a conflated planted signal. It is a conflated noise signal. I don't know what it is.
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01:44:09.440 --> 01:44:16.560
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But there is no way in God's green earth that without the use of clones and the making of quantities
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01:44:16.560 --> 01:44:23.120
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of them that this molecular biology data is even close to true. Otherwise, it's all false.
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01:44:24.320 --> 01:44:28.480
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And if it's even remotely close to true, if any of these signals are real,
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01:44:28.480 --> 01:44:33.760
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it has to be a combination of background and planted. It has to be.
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01:44:33.760 --> 01:44:43.040
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Biology is the way out. Call for all pause on all childhood vaccinations in the United States,
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01:44:43.040 --> 01:44:47.280
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at least for the first year of life to start with. If you want to be wimpy about it,
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01:44:47.280 --> 01:44:51.920
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if you want to just get the conversation started. But I think it's very easy to say that it should
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01:44:51.920 --> 01:44:58.480
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be stopped. I think using the word strict liability puts people on their heels because they don't
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01:44:58.480 --> 01:45:03.680
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expect you to understand or use those words. But any lawyer worth their salt definitely knows
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01:45:03.840 --> 01:45:08.320
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that strict liability is two words you don't say in front of a pharmaceutical company.
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01:45:08.320 --> 01:45:12.320
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Investigate the use of deadly protocols to cause mass casualty events or
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01:45:13.040 --> 01:45:19.440
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investigate the use of a coordinated effort of messaging to lie about mass casualty events.
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01:45:19.440 --> 01:45:24.480
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As Jessica Hawket seems to have uncovered in New York and in Chicago and in
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01:45:24.480 --> 01:45:30.960
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her not in Chicago, in New York and in Italy with Jonathan Engler. And then of course,
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01:45:30.960 --> 01:45:34.480
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I want to look into transfection. I want to look into the use of clones. But I don't think
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01:45:34.480 --> 01:45:41.920
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you need to look very hard because that's the way RNA virology is done. So take back your sovereignty
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01:45:41.920 --> 01:45:47.840
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of you and your children. Get out of the who get out of the UN and the CDC of the United States.
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01:45:47.840 --> 01:45:50.880
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And if you want to know who these people are, you will see that they don't use the word
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01:45:50.880 --> 01:45:55.520
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transfection. They don't talk about clones. And if they do, they say it's dumb. They make fun of
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01:45:55.600 --> 01:46:01.040
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the Scooby-Doo. They make fun of the idea that the government might use an elaborate hoax instead
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01:46:01.040 --> 01:46:06.240
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of an actual bio weapon. And they make fun of the idea that you would object to all vaccines
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01:46:06.240 --> 01:46:10.560
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because vaccines are some of the greatest things ever invented. And they don't talk about strict
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01:46:10.560 --> 01:46:15.600
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liability at all, even when their father is a patent lawyer that used to work for the Kennedy
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01:46:15.600 --> 01:46:23.120
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administration. Ladies and gentlemen, they are doing this because they know that as the population
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01:46:23.120 --> 01:46:28.320
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decreases over the next couple generations, they will be losing the opportunity to collect this data.
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01:46:28.880 --> 01:46:33.360
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And so they want your kids and they want your kids kids. That's what this is all about.
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01:46:34.720 --> 01:46:40.160
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It's about their AI. It's about the idea that they've lied to one another and each other
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01:46:40.160 --> 01:46:45.360
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about eventually all this stuff's going to come together and it's going to be one great big singularity
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01:46:45.360 --> 01:46:51.520
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moment. It's a mythology, ladies and gentlemen. It is a mythology. They've been telling each
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01:46:51.600 --> 01:46:56.320
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other for decades and it's not getting any closer to being real. Ladies and gentlemen,
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01:46:56.320 --> 01:47:00.720
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stop all transfections in humans because they are trying to eliminate the control group by any
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01:47:00.720 --> 01:47:09.280
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means necessary. This has been giga-owned biological where intramuscular injection in any combination
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01:47:09.280 --> 01:47:14.000
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of substances with the intent of augmenting the immune system is dumb, where transfection and
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01:47:14.000 --> 01:47:18.560
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healthy humans is criminally negligent and where viruses are not patterned in tegrides.
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01:47:51.520 --> 01:48:03.040
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Hey ladies and gentlemen, thank you very much. If you can, please take the time to share my
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01:48:03.040 --> 01:48:11.600
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work on the internet anywhere where you frequent and if you can, please help me recruit people
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01:48:11.600 --> 01:48:20.800
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that have the financial wherewithal to contribute $10 a month or to contribute $290 a year or
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01:48:20.800 --> 01:48:28.640
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contribute $81 every three months to help my family keep this going. I do put a lot of work
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01:48:28.640 --> 01:48:33.680
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into these streams. I put a lot of reading into these things and a lot of thought into it and
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01:48:33.680 --> 01:48:40.880
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it's going to get a lot better if I can find the support and so without a doubt I'd like to thank
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01:48:40.880 --> 01:48:53.760
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all these people. And thank you for watching and I will see you again tomorrow.
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01:48:58.480 --> 01:49:04.400
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That was a nice one. Man, oh man, what could they do if they had a bunch of people in the right
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01:49:04.400 --> 01:49:08.080
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places, right? What could they do if they had a bunch of people in the right places
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01:49:09.040 --> 01:49:15.360
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controlling the narrative and making sure that everybody believed that there was a novel pathogen
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01:49:16.720 --> 01:49:23.280
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and that RNA was the answer. Imagine what they could have done if they had a bunch of people in
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01:49:23.840 --> 01:49:29.760
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in all the dark places in the internet pushing a worst-case scenario so that even if you tried
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01:49:29.760 --> 01:49:36.720
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to figure out what was going on you'd only find bad news. Imagine if they had intercepted some
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01:49:36.800 --> 01:49:42.960
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of the doctors that showed up in New York City very early and offered them fame and comfort to
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01:49:44.000 --> 01:49:48.240
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do the narrative for them for a little while on social media to make sure that the worst-case
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01:49:48.240 --> 01:49:55.200
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scenario was taken seriously and that the compliance numbers were as high as possible. Imagine what
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01:49:55.200 --> 01:50:00.400
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would happen if they made a bunch of really beautiful high-colored high-resolution computer
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01:50:00.480 --> 01:50:09.120
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animated videos about the illusion of consensus about the the immunology surrounding the counter
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01:50:09.120 --> 01:50:14.640
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measure and the immunology surrounding infection so that it would be very easy to spread these bad
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01:50:14.640 --> 01:50:20.880
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ideas across the internet, across languages, across cultures. Just imagine what would happen if they did
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01:50:20.880 --> 01:50:34.000
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that.
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