> robust contact tracing works
Doesn't that rely on the individual opting in/using it? I have a feeling most people don't want the government tracing their every move (even though it already is geographically).
No, I don't. I think it's implausible. But this is what those in local public health are calling for. Granted, there's the IMHE model, which somehow fantastically thinks the virus will mostly be gone in Santa Clara County in mid-May, but it's shown very little agreement with the actual data and is nearly as bad as saying the Easter Bunny will take the virus away.
> Doesn't that rely on the individual opting in/using it? I have a feeling most people don't want the government tracing their every move (even though it already is geographically).
No, if you get the infection count low enough, you can investigate each individual case to death like Singapore has been doing it (though cases are growing beyond Singapore's ability to maintain this).
Yeah, that IHME model.. It's unfortunate that it's become the model most people have become acquainted with. It has its uses, but the down-slope has previously generated critiques.
Good Carl Bergstrom thread: https://twitter.com/CT_Bergstrom/status/1250304069119275009
A few select quotes from that thread:
> 6. But this is a mix of two different processes, an acceleration phase prior to control, and a deceleration phase once controls are in place. Given that, why does the model predict symmetric death curves?
> 7. The answer is that this is a modeling assumption that the research team has made. They have chosen to fit a particular sigmoidal curve called the Gaussian Error Function (erf function, for short) to the data representing the cumulative number of deaths that have occurred.
> 13. The actual trajectory tracks the forecast pretty closely, but then starts to turn around. Once that happens, the back side of the curve is constrained to mirror the front side; the epidemic is predicted to wane quickly. By May 17, the uncertainty range collapses to 0 deaths.
> 14. This strikes me as unrealistic. Even ignoring the real-world coupling between states (this is not included in the model), I am not persuaded that the epidemic will necessarily be entirely finished in just over a month.
And a very important point he brings up:
> 16. In defense of the model, every model is a tool with a purpose. The primary purpose of their model is to predict peak health care need, not the endpoint of the outbreak. That said, people need to be aware of a model's purpose and be cautious when using it for anything else.
In other words, it's actually a pretty bad model* for predicting the down-slope. I fully expect that we'll hit 100k deaths for this first wave.
*unless the US were to have done a Wuhan-style lockdown.
Decay seems to be very slow even in the jurisdictions with the strictest controls. (I do think the hardest hit jurisdictions may show something close to symmetry).
The disease is probably circulating in some subpopulations with Rt near or even above 1.0. Even if overall we're showing decay, those groups can continue to grow...
I also really, really, really don't like that if the peak is in the past, the model webpages claim that it predicted it perfectly; when really the webpage is just looking at the history.
