>is that mortality rate even among young people would become much higher as soon as hospitals become overwhelmed.

I don't see how this follows. The point the parent was making is that young people don't seem to need hospital care. Why would they suddenly start dying just because 'hospitals are overwhelmed'? They still won't need them...

> Why would they suddenly start dying just because 'hospitals are overwhelmed'? They still won't need them...

Also, when hospitals are overwhelmed they stop all treatment. That young person who gets shot; has a road traffic accident; has a drug or alcohol overdose; has a problematic pregnancy and birth; has cancer -- all of these treatments become harder to provide.

Original comment is talking about deaths, there are many, many more hospitalizations.

> The point the parent was making is that young people don't seem to need hospital care.

Low risk doesn't mean no risk, and we see plenty of younger people in hospital, and in intensive care, because of covid-19.

ICNARC has a report that they update over time using data from UK intensive care units. https://www.icnarc.org/Our-Audit/Audits/Cmp/Reports

https://www.icnarc.org/DataServices/Attachments/Download/c5a...

Age at admission (years), number of people discharged alive (%), number of people died (%)

  16-39     240 (78.4)     66 (21.6)
  40-49     350 (73.2)    128 (26.8)
  50-59     568 (57.0)    429 (43.0)
  60-69     503 (41.8)    701 (58.2)
  70-79     293 (32.2)    617 (67.8)
     80+     57 (31.3)    125 (68.7)

Once admitted to ICU people aged 16-39 have a 21.6% chance of dying vs a 78.4% chance of being discharged alive.

bad use of statistics. if gp is to be believed, once in ICU you are already in the 0.x %. the question then is, are you in the 0.1 or 99.9.

The ggp made no mention at all of hospitalization rates, only fatality rates.

Not true, the point of the parent is that young people don't seem to die. For 0.1% dying, how many are going to the hospital? Let's say it's 10% (completely random number), if you increase the population then 10% completely overcrowds the hospitals, quality of care plummets and 0.1% becomes 5% (once again, completely random number).

Not taking any position nor bringing data in this debate, just pointing out the logic

But they probably have “flatten them curve” in mind, where you maintain some social distancing to reduce the speed of spread.

But some jurisdictions are so locked down that there is virtually no spread at all, leaving the population highly vulnerable to a second wave.

You seem to be focused on a scenario where we allow the virus to spread among all groups, but that was not GP's suggestion. GP's point is that we can pinpoint who is at high risk and who is not, but that was not the case for the Spanish flu. (You talk of age as if it's the only risk factor, but it's clearly not.)

Hospitals would only become overwhelmed if the virus were to spread rapidly among high risk groups. Not many low risk individuals will wind up needing hospitalization.

Lastly, it would be more constructive to the debate to link to data instead of asserting that data exist somewhere out there which support your point.

> It's strange that engineers are giving in to this biased and non-rational mental model, treating this situation as linear and robust.

It's exactly what the model giving us 2.2M deaths in the US with strict quarantine was doing. Extrapolating the cruise ship case of 1% death to 80% of the US. Parent math is actually more reasonable.

There’s lot of data from New York and elsewhere showing young people do not have nearly the same hospitalization rates as older people. Yes, we need to manage But engineers should also not find themselves governed by panic and fear.

Where can I find these models which account for all factors? I've never seen a model including e.g. long-term economic consequences.