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So a lot of you are sharing the projections from IHME ( https://covid19.healthdata.org/united-states-of-america).">https://covid19.healthdata.org/united-st... I want to draw your attention to a very optimistic assumption in their modeling.
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Let& #39;s look at this graph of their Apr 10 projection of Italy& #39;s daily death rate. It drops by 45% on the day their current projection begins?! WTF. In reality, there were MORE deaths today than on Apr 9. 2/
In fact, all their charts show a very steep drop off in deaths after peak in a way that doesn& #39;t seem to match what we know from Italy, China, or South Korea even by eyeball. What gives? 3/
Well, if you look at their methods from their preprint ( https://www.medrxiv.org/content/10.1101/2020.03.27.20043752v1.full.pdf),">https://www.medrxiv.org/content/1... you can read (pg4) that they& #39;re fitting the cumulative death curve to _a simple gaussian error function_. 4/
You might be more familiar with the derivative of that, which is best known as "the normal distribution". In other words, they& #39;ve assumed daily death rates are symmetrical around the peak! 5/
For that to be true, the post-quarantine R-factor would need to be the exact reciprocal of the pre-quarantine R-factor (generally thought to
be about 3). That means the epidemic shrinking exactly as fast as it grew! 6/
be about 3). That means the epidemic shrinking exactly as fast as it grew! 6/
There& #39;s no biological/epidemiological reason for that. And just looking at Italy, it& #39;s almost certainly much higher than 1/3. Which means these
IHME projections are probably optimistic about when the peak will arrive here and how many people will die. 7/
IHME projections are probably optimistic about when the peak will arrive here and how many people will die. 7/
The cumulative fit will start to correct itself as we get weeks past the peak, but from where we are sitting in the US pre-peak, the built-in symmetry assumption of their model is painting too rosy a picture of the future. 8/
