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This is exactly what happened. Now the UW model has been readjusted to predict 134k deaths total. The new model still suffers from the same flaw: it assumes something will change in May/June to cause the epidemic's trajectory to suddenly change direction and get under control.https://twitter.com/fchollet/status/1256297472407662593 …
Perhaps it will, perhaps it won't. But it's an odd thing for a model to assume, since our future response cannot be inferred from past data. You might as well make the reverse assumption: "gradual reopenings will cause the trajectory to change course, in the wrong direction"
That's what throws me off with these models: they don't appear to acknowledge that how the future turns out is a consequence of our actions. They start from the assumption that the curve will go flat, and then they fit a curve that fits past data plus this unjustified assumption.
A better model would be presented as a set of possible actions taken by the fed govt / state govts / the public, and outcomes conditioned on these actions. This would involve actually modeling transmission and economic/social activity, rather than fitting a curve.
And don't get me started on the "cubic model" from the WH (cubic fit in Excel?) predicting 0 deaths in two weeks
I don't think it's odd for a non-physics model to assume improved effectiveness over time when people are involved. It seems like the changes address some issues of decreasing effectiveness. How would u evaluate the drop over time in comparison to previous epidemics/other models?
The model methodology attempts to use a gaussian distribution based on Wuhan. Unfortunately, we in the us are not locking down like Wuhan, and mutations may be making it more contagious.
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