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CDC Director: COVID-19 Death Toll Will Be 'Much Lower' Than Previously Predicted

Says number of deaths will be fewer than predicted by models to justify shutdown policies

 on 8th April 2020 @ 1.00am
dr  robert redfield says fewer people will die that models are predicting © press
Dr. Robert Redfield says fewer people will die that models are predicting

The director of the Centers for Disease Control (CDC) has claimed that the coronavirus death toll will be "much, much, much lower" than previously predicted.

Dr. Robert Redfield made the comments while appearing Monday on AM 1030 KVOI Radio.

Redfield predicts that far fewer Americans will die from the Chinese virus than the models have projected due to people following social distancing recommendations.


The projection models being used by the Trump administration to guide policy predict a six-figure death toll for the COVID-19 pandemic.

The best-case result, should current measures be kept in place, was between 100,000 and 240,000 people dying of the disease caused by the novel coronavirus from China.

the trump administration believes the death toll can be kept below 200k with social distancing measures © press
The Trump Administration believes the death toll can be kept below 200k with social distancing measures

"If we just social distance, we will see this virus and this outbreak basically decline, decline, decline," Redfield said.

"And I think that's what you're seeing.

"I think you're going to see the numbers are, in fact, going to be much less than what would have been predicted by the models."

The Trump administration has used a worst-case scenario projection from the Imperial College model to manage expectations for the death toll.

That model predicted 2.2 million Americans could die of the virus if no mitigation efforts occurred, according to The Blaze.

In contrast, Trump said, with social distancing and stay-at-home orders across the country, we can get that death toll down to potentially fewer than 200,000.

Another well-known model, the University of Washington's Institute for Health Metrics and Evaluation model, recently revised its death projection down to 81,766 from 93,531 the week before.

Dr. Anthony Fauci, director of the National Institute of Allergy and Infectious Diseases, has repeatedly said models are only as good as the assumptions they're built on — that includes assumptions about when COVID-19 first got to the U.S. (it could be earlier than we know) and how deadly the disease is (it's hard to tell with so little reliable data on the number of infections).

The numbers coming out of New York City over the last week show flattening of the curve in terms of the number of deaths, the number of new cases, and a decrease in the number of new hospitalizations, as well as an increase in the number of discharges of COVID-19 patients.

New York City is the epicenter of the coronavirus outbreak in the U.S., and there have been fears that it would take much longer to slow the escalation of cases and deaths, but that might be happening more quickly than expected.

over the last week  new york city is showing a flattening of the curve in terms of the number of deaths © press
Over the last week, New York City is showing a flattening of the curve in terms of the number of deaths

A transcript of Dr. Robert Redfield's comments 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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