[cameldrv]

What do you need a randomized double blind study for? You're not sure the people on the ship died of COVID?

As for adjustment factors, if you just adjusted for age, you'd get about 50% less mortality if the ship had the same age distribution as the country. So that's 5 million dead. However there are over a million people in the U.S. that are medically compromised and would have a very high fatality rate with COVID.

I also don't see what the problem with a linear extrapolation is.

Finally, I only accounted for deaths due to lack of ventilators. There also wouldn't be enough hospital beds, and that would lead to millions more deaths.

There is simply no reasonable alternative to suppressing the disease. We're talking more deaths than the Holocaust here.

[guscost]

> What do you need a randomized double blind study for? You're not sure the people on the ship died of COVID?

Er, you're not trying to figure out how the ship victims already died, you're trying to predict how many other people might die of the same cause. To do that kind of thing well, you need a hypothesis, and then you need to test it properly.

> As for adjustment factors, if you just adjusted for age, you'd get about 50% less mortality if the ship had the same age distribution as the country.

You can't "just adjust for age" or "just adjust for" anything, you're going to miss something! That's why people do clinical trials.

> I also don't see what the problem with a linear extrapolation is.

Basically, an epidemic is not a linear system, so you can't model it with linear functions. Look into the "SIR model" for a standard way to do that kind of thing. I'm not trained in this field so I'd look for a medical/science forum if you have questions.

https://mathworld.wolfram.com/SIRModel.html

[cameldrv]

> Er, you're not trying to figure out how the ship victims already died, you're trying to predict how many other people might die of the same cause. To do that kind of thing well, you need a hypothesis, and then you need to test it properly.

What would be the randomized double blind trial that you would run, and what information would it give us?

> Basically, an epidemic is not a linear system, so you can't model it with linear functions. Look into the "SIR model" for a standard way to do that kind of thing. I'm not trained in this field so I'd look for a medical/science forum if you have questions.

I'm familiar with the SIR model. What you'll find is that if R0>1, the SIR model converges to a state where S=1/R0, I=0, and R=1-1/R0. In this epidemic, R0 is approximately 2.5, of course depending on conditions. That means in the U.S. population, 60% will end in state R, which means 60% of people will get the virus. That's the 198 million number from above. It's actually a little worse than that because the SIR model doesn't have a "Dead" state, so more than 60% of the population has to get the virus in order for 60% of the end state population to have recovered.

[guscost]

> What would be the randomized double blind trial that you would run, and what information would it give us?

I have absolutely no idea how to design or run a clinical study.

> 60% of people will get the virus.

All at the same time?? Your extrapolation comparing total critical cases with the number of ICU beds seemed to assume that. Try this interactive model, which plots infections over time and takes into account how long each patient will occupy a bed: https://neherlab.org/covid19/

[cameldrv]

> All at the same time??

No, but it doesn't matter. If 10,000,000 people need to use 60,000 beds, and they each use one for three weeks, that's 500 weeks, almost ten years. Even if you could get a ventilator for all of them, Chinese experience is that about half of the vented patients die.

Hopefully in a year and a half or so we'll have a vaccine. Until then we need to keep the case counts low, first by sequestering ourselves to get the numbers down, and then by other, less draconian means once the case counts are in single/double digits.