> not getting access to hospital resources is much lower than expected
I don't know how you can say 'lower than expected'. Many interventions were non-medical, depending on social behaviour (e.g. adhering to social distancing), effectiveness of governance and enforcement, as well as economic and political (e.g. supply of test kits, ventilators). And even then, we were dealing with a new virus, there was limited data about all kinds of variables. For example, if people are intubated twice as long in the US due to high levels of obesity compared to China, you need twice as much ventilator capacity.
Point being, we always had to deal with a very wide confidence interval.
Now combine that with the fact we're looking to predict an exponential number, rather than something linear, and you can get wildly different outcomes. In New York the doubling time began around 2 days. That meant the difference between hospitalising 50k or 100k was a matter of starting social distancing two days later. The difference between 50k and say 1.6 million, was just 10 days. Hospital resources can't expand that fast, at best you can add 30% extra beds and shift all bed-use to dealing with corona with emergency interventions, but you can't just scale 3000%.
That's where the field hospitals came in. Not because it was guaranteed or fully expected to need them, but because there was a good chance, and there was too little information to conclude they wouldn't be necessary.
I don't know how you can say 'lower than expected'. Many interventions were non-medical, depending on social behaviour (e.g. adhering to social distancing), effectiveness of governance and enforcement, as well as economic and political (e.g. supply of test kits, ventilators). And even then, we were dealing with a new virus, there was limited data about all kinds of variables. For example, if people are intubated twice as long in the US due to high levels of obesity compared to China, you need twice as much ventilator capacity.
Point being, we always had to deal with a very wide confidence interval.
Now combine that with the fact we're looking to predict an exponential number, rather than something linear, and you can get wildly different outcomes. In New York the doubling time began around 2 days. That meant the difference between hospitalising 50k or 100k was a matter of starting social distancing two days later. The difference between 50k and say 1.6 million, was just 10 days. Hospital resources can't expand that fast, at best you can add 30% extra beds and shift all bed-use to dealing with corona with emergency interventions, but you can't just scale 3000%.
That's where the field hospitals came in. Not because it was guaranteed or fully expected to need them, but because there was a good chance, and there was too little information to conclude they wouldn't be necessary.