IMPORTANT: USA downgrades COVID-19 deaths massively – Did Jews trick the US & UK Govts to get lockdown?


[Notice how the CDC is massively downgrading the deaths and panic of COVID-19. I'm wondering if we're seeing whites, and reason rising after MASSIVE INITIAL JEWISH TRICKERY? 

There is a particular report and charts I was looking at, which I'll make a video about shortly, because it shows there's some very, very, very f*cked up “predictions” going on regarding COVID and lockdown. 
When you study this closely, it seems very clear to me that Jews tried a scam. In fact, they seem to be using NON-PEER-REVIEWED science papers to fool both Governments and the public. I've come across this weird MASS PUBLICATION of science papers that are NOT peer reviewed. I'm sure that any peer review would tear these things apart, and so Jews rush to the press BEFORE the “scientific paper” gets to scientists who will rip it to shit. And this is exactly what happened in the UK and the  USA. Both Govts were NOT going to do a lockdown. 
But guess what, according to these papers, we need lockdown literally FOR THE REST OF 2020. This smells extremely Jewey, and wait until you see the data and calculations. I reckon Jews could pull this off with a classic case of “JEWISH SCIENCE” at its finest, which Hitler would have mocked outright!!! 


div>BTW I like the social distancing thing. I wish we could keep it in SA. The blacks love to queue up closely behind you and finally we have a reason to get some distance Jan]

Appearing Monday on AM 1030 KVOI Radio, Dr. Robert Redfield, the Director of the Centers for Disease Control (CDC), predicted that the death toll from the Chinese coronavirus will be “much, much, much lower” than the models have projected due to Americans following social distancing recommendations.

A transcript is as follows:

HOST: We were talking about some of the models, whether it’s from the imperial college guy in England or the University of Washington. Thank god some of these numbers are falling short of some of these catastrophic numbers. Tell me about the dynamic of the modeling and how it helps and influences decision making and then, when the reality comes in, how does the decision making transform?

DR. ROBERT REDFIELD: I think it’s really important. First, models are only as good as their assumptions. Obviously, there was a lot unknown about this virus. The ability to actively make a lot of assumptions was much wider than if this was an Influenza B outbreak. Second thing, I will say from a public health perspective, to me, the real value of models is to have a model and then try to understand — if I invest resources here, what does that do to the model? If I invest in intervention strategies here, what does that do to the model? It’s a way of beta testing how you’re going to respond and what it does to the different models. And models should never be used to assume that we have a number. You saw those numbers are quite staggering. You’ve got 200,000 to 2 million Americans are losing their lives before the fall. That’s a pretty staggering number.

HOST: Are throwing those kind of numbers out actually helpful because what they do is scare the hell out of everyone to social distance? Is that the purpose?

DR. REDFIELD: I think different people may look at it in different ways in terms of transparency. CDC had models early on. We didn’t really publicize the models. We used them internally to understand deviation strategies. I think part of the importance of getting the American public’s attention that these models did, we really need the American public to be fully engaged now with great rigor and vigilance on the social distancing. As you pointed out, those models that were done, they assume only about 50 percent of the American public would pay attention to the recommendations. In fact, what we’re seeing is a large majority of the American public are taking the social distancing recommendations to heart. And I think that’s the direct consequence of why you’re seeing the numbers are going to be much, much, much lower than would have been predicted by the models.


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