3 ms·

Right, so do the math. 5% of positives required intensive care. If 197 million Americans get this, That means 10 million people go to intensive care. There a

Right, so do the math. 5% of positives required intensive care. If 197 million Americans get this, That means 10 million people go to intensive care. There are 60,000 ICU beds in the U.S. If 10 million people need the ICU, effectively none get a ventilator and they all die. Now it's true that the cruise ship passengers skewed significantly older, but on the other hand, they were all ambulatory and healthy enough to be taking a cruise. There are populations that are at significantly higher risk than the cruise ship passengers. Also, Chinese experience was that about half of the people admitted to the ICU eventually died.

dvsfish 7y ago
>Now it's true that the cruise ship passengers skewed significantly older, but on the other hand, they were all ambulatory and healthy enough to be taking a cruise. While yes this is true technically, I'm not sure the bar for "healthy enough" is as high as you're making out it is. In my experience (apologies for the anecdote), significantly obese people are quite capable of going on a cruise almost always.
- cameldrv 7y ago
  I'm talking about people in nursing homes, people in hospitals, people on immunosuppressants, for example, after a transplant (who wouldn't go on a cruise because of norovirus etc), people with other immune diseases, etc. There are a lot of these people out there, and these people would be very hard hit if we just let COVID run through the population.
guscost 7y ago
But on the other other hand, they were all traveling, eating cruise ship food, and probably drinking, all of which could weaken their immune systems. We can add speculative adjustments all day long, but there's no way we're going to get a randomized double-blind study out of it. Also you can't conclude much of anything based on a linear extrapolation, even if you have good data.
- cameldrv 7y ago
  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 7y ago
    > 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 https://mathworld.wolfram.com/SIRModel.html
    - cameldrv 7y ago
      > 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.

dvsfish 7y ago

>Now it's true that the cruise ship passengers skewed significantly older, but on the other hand, they were all ambulatory and healthy enough to be taking a cruise. While yes this is true technically, I'm not sure the bar for "healthy enough" is as high as you're making out it is. In my experience (apologies for the anecdote), significantly obese people are quite capable of going on a cruise almost always.

cameldrv 7y ago
I'm talking about people in nursing homes, people in hospitals, people on immunosuppressants, for example, after a transplant (who wouldn't go on a cruise because of norovirus etc), people with other immune diseases, etc. There are a lot of these people out there, and these people would be very hard hit if we just let COVID run through the population.

guscost 7y ago

But on the other other hand, they were all traveling, eating cruise ship food, and probably drinking, all of which could weaken their immune systems. We can add speculative adjustments all day long, but there's no way we're going to get a randomized double-blind study out of it. Also you can't conclude much of anything based on a linear extrapolation, even if you have good data.

cameldrv 7y ago
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 7y ago
  > 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 https://mathworld.wolfram.com/SIRModel.html
  - cameldrv 7y ago
    > 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.