Ep 111: Mortality Realities - Professor Michael Levitt Explains Fully!
The Fat Emperor Podcast
ivor cummins
4.8 • 758 Ratings
🗓️ 9 April 2021
⏱️ 72 minutes
🧾️ Download transcript
Summary
Had an excellent and data-packed convo with Nobel Prize winner and good friend, Professor Michael Levitt of Stanford University!
It's long-ish but covers all of the crucial excess mortality data from CDC, mortality.org and/or Euromomo databases.
So ZERO reason for censoring this one - even though the actual governmental data is fascinating!
Always remember: don't ever discuss the data...without actually understanding it. Ever.
VIDEO VERSION WITH SLIDES: https://youtu.be/BrSW667soBM
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Transcript
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| 0:00.0 | Welcome to the Fat Emperor podcast. |
| 0:05.0 | I'm your host, Iber Cummins. |
| 0:07.0 | Hey guys, I'm back with Professor Michael Levitt, Nobel Prize winner, |
| 0:11.0 | who has been doing all the mathematics on our viral situation since back in February 2020, |
| 0:17.0 | before it even started. |
| 0:19.0 | And overwhelmingly, the analyses have turned out to be quite prophetic, but in some cases, not so much so. So we're going to talk about that in this revisitation. So great to see again, Michael. |
| 0:32.6 | Ivan, it's great to see you. It's really been terrific and, you know know wonderful to be back on your show oh no thank |
| 0:39.8 | you and i've had a great time in london there we met personally to record from the movie uh got a nice |
| 0:45.2 | lunch yeah it seems like the good old days because that was the summer and look the thing went away |
| 0:51.8 | like we expected in the summer. But here we are now. |
| 0:55.3 | So I guess we'll start with that maybe. |
| 0:57.9 | As one of the controversial things was you were quite bullish during the summer on Twitter |
| 1:02.9 | about predicting that the US was coming to a close. |
| 1:07.5 | Now, Europe certainly was. |
| 1:09.3 | But the US kind of went on with all kinds of seasonal patterns. |
| 1:13.0 | So maybe just a quick chat on that one. |
| 1:15.9 | So that was really me making a mistake. |
| 1:21.7 | And the mistake was, and it's a mistake which actually hurts a lot that I wasn't looking at my own data. |
| 1:29.3 | We had been putting out these plots every single day, |
| 1:34.3 | plots which basically show the number of cases or number of deaths, |
| 1:39.3 | and then superimposed on that a cloud of blue dots, |
| 1:42.3 | which are different predictions up to that day, |
... |
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