[joshuamorton]

> The lifetime risk of death being involved in a car accident is 1%.

You're off by a factor of 100. It's .01%.

> The lifetime risk of dying of an opioid overdose is 2%.

For who? Someone who uses opioids? Maybe, on average, again you're off by a factor of 100 or more.

> We do not know how deadly it is, all we know is that of people who go to the hospital

No, of people who test positive, which includes people with relatively mild symptoms that don't go to the hospital, but had reason or ability to get tested.

South Korea is probably the best current testbed here, they had very widespread testing and they've had very, very slow growth recently so the CFR numbers are probably relatively accurate. They see a 3% CFR.

> Which is why Sweden remains open for business. And you know what? They're doing just fine [1].

Normalized by population, Sweden has seen more deaths and more infections than California, by about 50%, and it will likely continue to grow at a similar rate. The problem with exponential growth is that things look like they're doing just fine until suddenly they aren't and there's no way to fix things.

[arcticbull]

> You're off by a factor of 100. It's .01%.

> For who? Someone who uses opioids? Maybe, on average, again you're off by a factor of 100 or more.

No, lol, it's not. Those are averages across the US population. Your lifetime odds in the US of dying in an automotive accident is 1:103 [1].

I should have said accidental poisoning which is 1:64 [2] but half of that is actually opioids (1:96) so you're still more likely to die of an opioid overdose than being a party to a car accident. Most people don't set out to get hooked on Oxy, they get hurt or undergo surgery, are prescribed them, and that's that.

There's 40,000 deaths per year related to car accidents, which if you multiply out by the average lifetime (78.69 years) is right around 3.2 million, or 1%.

This is fair to compare against COVID because due to its extremely limited propensity for mutation, the COVID mortality rate does represent what approximates lifetime risk. (i.e. unlike the flu, you won't get it again).

> South Korea is probably the best current testbed here...

I argue the best testbed is the German study I cited where they actually tested... everyone. CFR is not mortality rate, its about an order of magnitude higher, again, I cited my data. And in my intuitive explanation that you're not factoring out adverse selection risk of only very sick people going to the hospital in the first place.

> Normalized by population, Sweden has seen more deaths and more infections than California.

Because everyone in California is inside. I'm sure they've seen an order of magnitude more flu deaths too because nothing spreads when you're inside. They're probably seeing infinitely more car accident deaths, too. Life's risky, and you're not comparing honestly.

[1] https://www.iii.org/fact-statistic/facts-statistics-mortalit...

[joshuamorton]

> Your lifetime odds in the US of dying in an automotive accident is 1:103 [1].

No they're not. The lifetime odds for the average American are. For opioids as an example, as someone who doesn't use opioids, my lifetime odds of dying from an overdose are essentially nil. The distribution is bimodal.

> This is fair to compare against COVID because due to its extremely limited propensity for mutation, the COVID mortality rate does represent what approximates lifetime risk. (i.e. unlike the flu, you won't get it again).

You claim this with great certainty, but it hasn't been around long enough to know that it won't mutate in annoying ways.

Further, it's still not fair to compare that way. In the past 2 decades, we've had 4 or more dangerous flus that aren't seasonal (SARS, MERS, H1N1, H5N1, COVID-19). Of these, most weren't infectious enough to be super dangerous, but two were (H1N1, COVID-19), each of which killed at least 100K people worldwide, and COVID-19 is on the path to claim a million lives worldwide this year.

That's not a once-in-a-lifetime event, it's once a decade or even once every few years.

> I argue the best testbed is the German study I cited where they actually tested... everyone.

And the flaws in that study have been noted elsewhere. SK is a better testbed since they also tested huge swaths of people, even those not showing symptoms, and

> CFR is not mortality rate

The CFR of the flu is .1%, which would make COVID more contagious, and 30x more deadly. I'm not sure why the mortality rate matters since given the higher infection rate, COVID would have an even higher mortality rate.

> Life's risky, and you're not comparing honestly.

And the risk from COVID goes up if everyone catches it simultaneously. The CFR goes up even further if hospitals are overwhelmed.

[arcticbull]

> No they're not. The lifetime odds for the average American are. For opioids as an example, as someone who doesn't use opioids, my lifetime odds of dying from an overdose are essentially nil. The distribution is bimodal.

So now you accept that I wasn't off by 2 orders of magnitude, but are pedantically calling out that I wrote "your" even though I specifically wrote "Your lifetime odds in the US" -- which, if we're going to be entirely pedantic, applies to everyone on earth. Maybe look up your numbers and share them?

You're ignoring how people end up addicted to opioids. The shape of the distribution is both entirely irrelevant and you haven't cited your source.

This makes me think your goal is to win an argument instead of having a genuine discussion.

> You claim this with great certainty, but it hasn't been around long enough to know that it won't mutate in annoying ways.

I'm citing data from experts [1].

> ...we've had 4 or more dangerous flus that aren't seasonal (SARS, MERS, H1N1, H5N1, COVID-19).

SARS, MERS and COVID are not flu viruses, they're coronaviridae. H1N1 and H5N1 are mutations/subtypes of the Influenza A virus. The coronaviridae are different.

> And the flaws in that study have been noted elsewhere. SK is a better testbed since they also tested huge swaths of people, even those not showing symptoms...

SK has not tested huge swaths of the population, they've tested around 1%. [2] They may have tested more than most people, but that's not what you claimed. They've tested some not showing symptoms. Huge difference as compared to testing 100% of the population.

> The CFR of the flu is .1%, which would make COVID more contagious, and 30x more deadly.

The study I referenced mentioned 0.1% for the flu vs 0.37% for COVID. Feel free to read it. That would make it 3.7X not 30X. Because the flu has been around so long the fatality rates are largely determined by mathematical modeling, and are very close to the actual fatality rate. On the other hand, we're still figuring it out for COVID.

Yes, its is more contagious. Nobody's argued that.

> And the risk from COVID goes up if everyone catches it simultaneously. The CFR goes up even further if hospitals are overwhelmed.

Which is why, scroll back up, we isolate the vulnerable.

[1] https://www.washingtonpost.com/health/the-coronavirus-isnt-m...

[2] https://www.barrons.com/articles/south-korea-coronavirus-cov...

[joshuamorton]

> So now you accept that I wasn't off by 2 orders of magnitude.

You're right, but it doesn't make the numbers you're citing any more relevant.

> SARS, MERS and COVID are not flu viruses, they're coronaviridae. H1N1 and H5N1 are mutations/subtypes of the Influenza A virus. The coronaviridae are different.

Who is being pedantic now? The point is that novel viruses are not a once in a lifetime occurrence, so you can't compare the risk of "COVID-19" to "lifetime death rate", since a new novel virus will come along in a few years. The danger is not covid-19 in particular, but novel viruses in general, and doing nothing would lead to a 1-year fatality rate for a novel virus on par with the lifetime danger of driving. Which means the lifetime danger of the virus is 20x or more the danger of driving. That's

> The study I referenced mentioned 0.1% for the flu vs 0.37% for COVID. Feel free to read it. That would make it 3.7X not 30X. Because the flu has been around so long the fatality rates are largely determined by mathematical modeling, and are very close to the actual fatality rate. On the other hand, we're still figuring it out for COVID.

Yes, but the CFR of the flu is well understood. The CFR of COVID-19 is not, and your entire argument is based on one study which is not conclusive, has had some flaws pointed out elsewhere in this thread, and generally doesn't match observed CFR elsewhere.

> Which is why, scroll back up, we isolate the vulnerable.

Which, ask any epidemiologist, doesn't work, since hospitals get overwhelmed anyway. The hospitalization rate of young people is still pretty high (maybe not quite 20% as it is for the overall population, but still more than 10%), they just don't die with reasonable care. There's a fair number of cases of healthy 20-something year olds who end up hospitalized for a week due or more due to COVID and need ventilators. Not to mention healthy something 40 year olds.

Even if you manage to perfectly isolate every at risk person, there's still a nontrivial risk of overwhelming ICUs anyway. And then the fatality rate among young people would go up as they couldn't get good care. And you're not going to perfectly isolate every at risk person. So the you have more young people hospitalized, more old people hospitalized, and well you're in a bad spot.

Or you end up expanding the definition of "at risk" to include "obese, heart disease, diabetes, or high blood pressure", and you've ended up essentially where we are now, with the majority of the US population in an "at risk" group.

> SK has not tested huge swaths of the population, they've tested around 1%

You realize that for population level statistics, that's fine. That means that 490000 tests have returned negative. If, as the Italians think, 10x as many people are infected, somehow there would need to exist 100K+ infected people, showing no symptoms, basically none of whom appeared in the 490000 negative samples. Such a probability is negligible. The sample sizes are large enough to remove the possibility.