Who cares? They are all going to say the same thing. We have MORE than enough of a sample now.

90% of LA County deaths had 1+ serious underlying condition(s). I have not seen the average age published, but the numbers I've seen indicate age 65+ is around 75-80%.

I have no benchmark to compare that to previous outbreaks (e.g. 1918, 1957, 1968), but I know it is significantly higher than 1918, which afflicted younger people out of proportion.

Yup, who cares.

Because once you get the answer you want, stop asking.

The CDC and MLB studies should be out this week. You should be eager for those results. But you are clearly just here to shout into the void, so have at it.

Just leaving this here.

Wrong, I'm not eager for the results because I already know they'll agree with the other findings. The statistical sample is large enough that the MOE is small.

YOU are "eager" for them because YOU don't understand statistics.

IF and that's a BIG IF the studies show something else, my viewpoint will adjust.

But, they won't. Because statistics 101

I think you are reading this post wrong. TS is not saying anything about what he thinks the mortality rate is in that post.

Hydroxy in proper dosages is very, very safe. It has been administered to 10s of millions of people. Prior to CV Hydroxy side affects were almost nil; the few with serious side affects (e.g. retinal disorders) had taken Hydoxy for 5+ years.

OD'ng on any safe drug can produce side affects.

ETA: In the political madness surrounding Hydroxy I have yet to see a study in the proper setting for an antiviral: administered to those very early in the infection cycle. The studies I've seen all want to measure effects well into the infection cycle when complications arise.

https://statmodeling.stat.columbia.e...sting-results/

Read the comments, please.
I'm too lazy to do the work for you guys.

iirc from physics class, the 'DOUBLE' method of accounting for errors is another error.

So you need to DOUBLE it again to take account of this error.

Dude you are so full of ****.

Every post you've posted here has been drenched in a ridiculous amount of confidence that you have figured out everything there is to know about Corona. You are very clearly dying on the hill you are standing on right now. If new data comes out, you'll find ways to say the data is bull **** or find other excuses.

At least play a consistent character and don't say stupid crap like "if there is other proof my viewpoint will adjust". It changes your perception from being an entertaining troll to debate against to being an actual zero IQ cuck pleb.

Do you think R-0 is around 2?

Basically if Stanford was flawed then this study will be too, because it used the same methodology.

I don't understand why these "experts" are not pursuing sewage analysis. It has been proven reliable for decades.

I think it varies based on several properties. From what I've read 2-2.5 seems to be fairly reasonable estimate.

Do you think R-0 is around 2?

If you want to go back to posts he made on April 5, you can see what he thinks about that. I just quoted that post because he took me to the woodshed for having an opinion that he know has adopted as his own.

I don't think this is true. From what I have read, the main concern with the Santa Clara study was how they selected the people who participated, a process that was done much differently in the LA study, and one which will be much different in the MLB study.

More importantly, there hasn't been any contradictory studies that I have been able to find. I understand that this one is being criticized, but that criticism is coming from the peanut gallery, not people who have gone out and collected their own data. It also tracks with studies from Europe, as well as the sewage stuff I have read.

But we should get CDC data pretty soon. That should be informative.

States announcing they will reopen soon. Georgia on Friday and Tennessee next week.

You said you're from a third world country...I assume English isn't your first language despite speaking it well?

First post: Taking you to the woodshed for throwing out a figure with zero reasoning (without me having an opinion on that figure)

Last post: I am not taking on 0.5% at all, how you get that out my post is beyond me. I was discussing absolute lower bounds at the population level using ridiculously generous assumption, for which I came up with 0.5% for NY as an absolute lower bound using ridiculous assumptions.

So this is a dual self-beclowning on your part. You were replying to your (comically wrong) view of what my posts said rather than they actually said from a plain reading.

I really want to believe the 0.2-0.4% mortality figures for obvious reasons. But even looking past the data, one thing I can't wrap my mind around is that China is 3 months ahead of us on this. If the disease was really that mild (and they should know by now), why are they still taking it so seriously with the lockdowns and economy shutdowns.

Would they really do that with a disease only 2x as deadly as the flu that targeted elderly? Doesn't add up. I guess you have the issue with hospitals overwhelming if you let the disease run free, so maybe that is the concern; but even then it seems like they seem to still think it is VERY serious business, with data 3 months ahead of ours.

The sewage stuff is hilariously broad, with a 40x range in estimates.

The criticism of this study stands whether or not we've "collected our own data". It hinges on 2 assumptions:

- That the false positive rate reported by the manufacturer for a small sample is correct
- That the participants aren't biased toward covid infection (social, outgoing people likely to sign up for studies and real life surveys and those who respond or don't drop out because think they might have had covid and want to know).

They're two enormous assumptions given how cuck-level the first attempt was. We have a low percentage with an admitted >0.5% false positive rate with wide error bounds and population we don't know is representative. It's a very weak data point at best, against some very strong data on the other side for >1% IFR.

https://www.theguardian.com/world/20...-in-three-days

I've seen 10x as a general range. Even so, if it estimates 10-100x under-counting, that is meaningful.

https://time.com/5824039/singapore-o...grant-workers/

I missed your response on your R-0 estimate.

So anything from 5x to 200x undercounting - 50x spread. 5% undercounting is a very high death rate (the death: detected is at 7% and by the time the detected infected die that will be >10%). You need >10x undercounting to get to a 1% death rates in non-overwhelmed areas.

You don't need to conduct a poll to call it data.

We may be a peanut gallery but it's simple math with public death counts.

TS's point about NY and other places is compelling.

14-20k dead so far in a population of 8.4m = .17-.24% mortality rate assuming 100% of the state was infected.

If you don't think 100% were infected, adjust accordingly.
That all ignores those who live with serious health issues.

Repeat in towns in Italy etc and find similar things.

What's the problem?

I hope their reports show it's really less deadly, but we'd still need an explaination for NY etc.

The MA study was 430 reported cases with estimate range [2300, 115000], so about 7x under-count assuming lowest bound. Assuming geometric mean that goes up to 16k, or about 35x under-count.