In HART we recently published a fascinating article on smallpox, arguing for the possibility that humanity had not actually eradicated it, but merely rebranded it:
The fact they casually mention the 300 deaths following vaccination is shocking to me. I am sorry but I do not want my life or anyone in my family to be the one who is sacrificed in a vaccine campaign. No matter how much I try to love my neighbour giving up my life is a step too far. How accurate is the 300 count? Is it like today's standard an undercount, we will never know. The safe and effective game has been played for a long time.
1969 - when healthcare was less political and Pharma less powerful - when the only censorship was the occasional D-notice - when vaccines could be criticised in a medical journal even in the second year of a global influenza pandemic.
A friendly reminder re your usage of "which"/"that":
The headline should be: "Hart article >>>that<<< casts doubt...." Not "which" casts doubt.
I'm not sure how to "learn" you this, Dr. Engler. And I don't want to be obnoxious by launching into a lecture about usage of "which" versus "that." I'll leave it by saying that the situation here is sort of like the difference between "a" and "the."
P.S. Since I find myself here at your new Substack (I have trouble keeping track of all the Hart, Where Are The Numbers, PANDA, and etc Substacks -- but good on you, Dr. Engler, for all your contributions wherever they are), I want you to tell you that the March-25 webinar* you did with Ms. Hockett was VERY good. I couldn't "put it down" even though I was already reasonably familiar (as a layperson) with the topic going in. I highly recommend this presentation to EVERYONE.
There's too much excellence from the 2+ hours to list, but I was particularly struck by your comments at 1:34:01 min about the covid tracking dashboard from Johns Hopkins. I am REALLY looking forward to the upcoming PANDA article on this (if it's already been published, I didn't find it at pandata.org). Thank you in advance!
Here's a (lightly edited by me) transcript of what you said:
J. ENGLER SPEAKING:
Talking of processing numbers, I think we mentioned to you [the webinar host] before we came on that soon PANDA is going to be publishing, in the next week or two, an article on digging into the Johns Hopkins University dashboard. Because it looks like most of the numbers are actually modeled.
And then we wonder how many cities and states took their data from that and made it match. And the reason why we think it's – it's actually common sense that tells you that it's modeled is because basically, I mean, the U.S. government says it takes two years to compile flu stats, and that's just in its own country.
So suddenly we are meant to believe that a university can establish a dashboard, which it said it established in February before there were any deaths outside of China, actually. It's meant to have established a dashboard which can report in real time covid deaths from a hundred and whatever it was 60 countries. In real time.
I mean this is just completely nonsensical that they could even do this. So therefore there had to be modeling involved. And the question is what would the – what were the inputs onto those models? And my guess is that the inputs had something to do with a traditional SIR [Susceptible, Infective, Removed] curve, which is why the death counts look like SIR curves.
The fact they casually mention the 300 deaths following vaccination is shocking to me. I am sorry but I do not want my life or anyone in my family to be the one who is sacrificed in a vaccine campaign. No matter how much I try to love my neighbour giving up my life is a step too far. How accurate is the 300 count? Is it like today's standard an undercount, we will never know. The safe and effective game has been played for a long time.
Thanks for that. I posted that late last night and omitted to point out the casual nature of the mention of so many deaths. I have added a sentence.
1969 - when healthcare was less political and Pharma less powerful - when the only censorship was the occasional D-notice - when vaccines could be criticised in a medical journal even in the second year of a global influenza pandemic.
A friendly reminder re your usage of "which"/"that":
The headline should be: "Hart article >>>that<<< casts doubt...." Not "which" casts doubt.
I'm not sure how to "learn" you this, Dr. Engler. And I don't want to be obnoxious by launching into a lecture about usage of "which" versus "that." I'll leave it by saying that the situation here is sort of like the difference between "a" and "the."
P.S. Since I find myself here at your new Substack (I have trouble keeping track of all the Hart, Where Are The Numbers, PANDA, and etc Substacks -- but good on you, Dr. Engler, for all your contributions wherever they are), I want you to tell you that the March-25 webinar* you did with Ms. Hockett was VERY good. I couldn't "put it down" even though I was already reasonably familiar (as a layperson) with the topic going in. I highly recommend this presentation to EVERYONE.
There's too much excellence from the 2+ hours to list, but I was particularly struck by your comments at 1:34:01 min about the covid tracking dashboard from Johns Hopkins. I am REALLY looking forward to the upcoming PANDA article on this (if it's already been published, I didn't find it at pandata.org). Thank you in advance!
Here's a (lightly edited by me) transcript of what you said:
J. ENGLER SPEAKING:
Talking of processing numbers, I think we mentioned to you [the webinar host] before we came on that soon PANDA is going to be publishing, in the next week or two, an article on digging into the Johns Hopkins University dashboard. Because it looks like most of the numbers are actually modeled.
And then we wonder how many cities and states took their data from that and made it match. And the reason why we think it's – it's actually common sense that tells you that it's modeled is because basically, I mean, the U.S. government says it takes two years to compile flu stats, and that's just in its own country.
So suddenly we are meant to believe that a university can establish a dashboard, which it said it established in February before there were any deaths outside of China, actually. It's meant to have established a dashboard which can report in real time covid deaths from a hundred and whatever it was 60 countries. In real time.
I mean this is just completely nonsensical that they could even do this. So therefore there had to be modeling involved. And the question is what would the – what were the inputs onto those models? And my guess is that the inputs had something to do with a traditional SIR [Susceptible, Infective, Removed] curve, which is why the death counts look like SIR curves.
* LINK FOR THE WEBINAR:
https://vimeo.com/928895517?share=copy
Disgusted. Everytime. Makes me want to vomit from the sick evil that has been done to other human beings.