I have not seen a single useful model from professional epidemiologists so far -- at least nothing that would guide me better than "look at China and Italy and consider that it might also happen here."
The IHME model - one of the most cited models - explicitly factored this into their model.
Here, for reference is the IHME model preprint: https://www.medrxiv.org/content/10.1101/2020.03.27.20043752v...
The parameterization of social distancing is on pages 3-4. They considered four coarse categories of interventions, with the total effect given by a ad hoc score of 1, 0.67, 0.334, or 0.
It should be blindingly obvious that can be improved upon with more data and work. Moreover, the effects of social distancing aren't even constant--compliance certainly varies from place to place and over time (enforcement changes, people get restless).
This suggests that social distancing happened 1-2 weeks sooner than their model anticipated. This will give you a much smaller number.
What is the policy you believe should have been followed instead? Are you saying that social distancing should have been abandoned? Why do you believe that this would result in fewer deaths?
People were voluntarily taking precaution well before our government bureaucracies enforced it, and it was available in public datasets. IHME just didn't look hard enough, apparently. Despite what the media keeps pushing by finding pockets of idiots, people aren't stupid. The most at-risk populations realize this and tend to shelter in place on their own and take precautions.
de Blasio on March 11th telling people to go out: https://ny.eater.com/2020/3/11/21175497/coronavirus-nyc-rest...
OpenTable data showing a voluntary reduction of restaurant activity despite de Blasio's encouragements: https://ibb.co/r2R9xnT
How does one evaluate the OpenTable data and feed it into the model they were using to estimate the amount of social distancing?
https://twitter.com/boriquagato/status/1251943418860728320
I'm saying that lengthy lockdowns, shelter-in-place, and shutting down non-storefront businesses did not provide much value, if any, and possibly had a negative effect.
The IHME trended into 95%+ CI territory over half the time. So when posters here say "well the variance was high," that's accounted for in the confidence intervals, which they also missed on wildly.
The models justified harsh authoritarian action, and the actual data way, way undershot it. Popular sentiment is "oh well, it saved lives at least" but few, if any, are looking at the acute - and more importantly, chronic - economic costs of these policies that may or may not have even helped beyond just telling people what the risks were.
>> How does one evaluate the OpenTable data and feed it into the model they were using to estimate the amount of social distancing?
Pretty simple; it was clear that news of COVID-19 alone was enough to cause people to stop going to restaurants and start basic social distancing protocols on their own without government mandating it.
EDIT: Shockingly, a bunch of downvotes without explanation are forthcoming.
The chronic effects of shutting down the economy are vast. People think money can be regenerated; it can. But what Americans have seemingly forgotten is the past where American autoworkers feared Japanese efficiency and where the Japanese economy looked to crush ours. Today, the Japanese salaryman works at least 50% more hours and his purchasing power is less than his counterpart in the United States (just look at patio11's posts on it).
https://www.kalzumeus.com/2014/11/07/doing-business-in-japan...
It's not a popular take because of recency bias (the same thing happened on 9/11 with the PATRIOT Act and always doe when outliers happen), but the data will be pretty clear in the end.
I'm interested in them.