No I have never been to LA.

Didn't need to to find the study not very compelling but a 'common sense' counterexample doesn't change much at this stage. Far too early to say what all the factors or what the specific factors are - there's a good reason we science.

Could someone please explain that graph ^.
There are 8 entries on the x axes. What do they represent?
I’ve just today come across this nitrogen dioxide theory and would like to investigate further. Thanks.

Or why the LA and Stanford numbers are insufficient to extrapolate an IFR from. What we do know is that the 65+ demo accounts for somewhere around 75% of CV deaths. So failing to accurately represent that demo in a sample could produce huge swings when projecting an IFR in terms of a homogeneous spread of the virus throughout the population. Iirc, the Stanford study didn’t balance for age at all so we really can’t project an IFR from it. With the LA study of 863 participants, since 14% of LA County is 65+, that would work out to ~120 participants in the 65+ demo, if their study followed suit. So what’s the chance those 120 accurately represent the 1.4M 65+ LA population both in terms of age and comorbidities?

He was going for parody wrt posting style, just missed the mark.

There are so many reasons the study is only a weak data point:

- There exists a complete lack of reliable false negative data from this test, a test which does have false positives. The only thing we have is manufacturer reported data (who wants to sell their new product they just spent money developing!) that comes out at >0.5% false positive (2 out of 387). Totally inadequate sample to establish the false negative rate and a totally unreliable source. It wouldn't matter if the infection rate found was 20%, but it's 4%. Who knows what conditions cause false positives and at what rate? This isn't a mature product and all we know is that there are some. That alone almost completely invalidates the study.

- The guy who did the same study in Stanford did a clownish level population sample (a FB post!!!) and analysis imo. He claims proper randomization/sampling on this one, but:

- He got the participants from a company that provides people signed up to participate in real world surveys/tests and such. These are strongly skewed toward people who are more socially active. Who knows who opted out and who didn't and why. Are these people representative of the exposure levels of the average person?

Put it all together and it's just nonsense. False positive rate double reported and exposure bias double reported and suddenly you have an IFR of 0.7%.

It's a weak data point and people putting much faith in this are not very bright, particularly when we have strong (population-level) data points showing >1% IFR.

Idk if this has already been posted itt re: origins of the virus?:

https://project-evidence.github.io

Cliffs: lots of circumstantial evidence weighted towards the virus coming from a lab leak (but not a bio weapon).

Stanford antibody test was rejected in Denmark for being too unreliable, and seems to be produced in China.

It takes another level of hopium to think we're close to herd immunity based on that Stanford study. You could write a short book about all of the study's shortcomings.

Big problem with all of these antibody studies is the low prevalance of cases in lots of areas combined with too many false-positives. It's close to impossible to get reliable results that way.

https://www.les-crises.fr/the-tremen...vier-berruyer/

I haven't read this yet. Seems like a serious takedown of HCQ study from Raoult.

is it just me or is comparing the entire US to other countries not really very worthwhile?

i mean, wouldn't it make a lot more sense to isolate to localized regions?

That's hilarious. Is it really a Chinese test and they're relying on manufacturer reported false positive data without testing it properly?

Also, what the actual ****:
So the actual test results came in at 1.5% with antibodies (1% after taking off the manufacturer's claimed false positive rate), then they did a bunch of statistical manipulations to make that 1% into 2.8%? So actual IFR from their raw data (with cases yet to play out to death) is already 0.5% and will likely end over 1% by the end. That's some crazy ****. 1.5% could easily be entirely the false positive rate.

As I've said again and again, experts are morons and any new study that comes out is very strong odds to be wrong without even looking at it.

It's an IQ test - anyone who takes this study seriously can be completely ignored going forward as they lack the ability to analyze evidence intelligently.

For the crazy people itt still saying Sweden is doing fine, lets make a case here:

Sweden vs Finland/Norway/Denmark.

Population:
Sweden: 10,3 million // Finland/Norway/Denmark: 16,7 million.

Tests & confirmed infections:
Sweden: 75.000 / 15.000 ; 20,5% positive // Finland/Norway/Denmark: 305.000 / 18.865 ; 6,2% positive

Deaths:
Sweden: 1.765 // Finland/Norway/Denmark: 644

Deaths per million capita:
Sweden: 171 / Finland/Norway/Denmark: 39

In terms of current deaths:
Sweden: has not peaked yet. At best it wont move up further from current amount of daily deaths (>100/day). Highest number of daily deaths is today (185).

Finland: Only has 98 deaths, but peak not really visible yet. No major outbreak, peak death/day was 8 on April 15 & 18.

Denmark: Everything points to them being already past peak death. Peak death/day was 22 on April 4.

Norway: Not peaking yet though their data looks weird, maybe they reported a backlog of deaths yesterday? Can't find a good source. Anyway, peak death was on 20 april with 16 deaths.

I am still convinced Sweden will lock down at some point, too.

The other Nordic countries are starting to open up because they think the spread is too slow, how does that make you think Sweden will close down? Also, Stockholm is starting to see effects from herd immunity, there is a long way to go yet but it will only strenghten the policy makers in their current approach.

Maybe a good comparison would be Stockholm (1mil pop) vs Copenhagen+Helsinki+Oslo (2mil)?

wait what?

Belarus just keeps on rolling also. That's going to be an interesting test case.

Stockholm statistics are aggregated on the regional level (Stockholm Regional Council), quite closely approximating the metropolitan area, with 2.4 million inhabitants. For Copenhagen those numbers are 1.85M (Capital Region of Denmark), for Oslo 1.6M (Greater Oslo Region), and for Helsinki 1.3M (Greater Helsinki). Not sure how the other countries report their statistics.

Citation needed on herd immunity. Makes 0 sense even under ridiculous assumptions:

Lets just assume of the current people sick in Sweden 5k will die and that herd immunity first effects are visible at 30% herd immunity. That assumes a 0,15% mortality rate and results in >100% infected in Madrid, Lombardy and New York.

https://www.svt.se/nyheter/inrikes/1...r-mot-covid-19

It's in Swedish, maybe makes sense after google translate.

11 % of blood donors are positive for antibodies in a test catching 70-80 % of positives and 0 % false positives. Blood donors have to be healty for a minimum of two weeks before donation.

200 people who provided blood voluntarily. Come on now.

Thank you for doing the groundwork in the above post (although none of your links work ). I will address it, but first I wanted to address this post.

So, in we have 2 scenarios

1. The coronavirus that enters cells via ACE2 receptors (which humans have) escaped to Wuhan from the Wuhan coronavirus lab that is studying bat coronaviruses in live bats with at least 96% homology to SARS-COV2 that bind to ACE2 receptors.

2. A bat native to SW China somehow infected a mammal species native to SE Asia thousands of miles away. And this infected animal somehow transported live virus to a wet market thousands of miles away in NE China and infected humans. (oh yeah, wet markets trade in local flora and fauna and there is no evidence this virus infects other than through respiratory droplets, so this scenario would most likely have to involve live animals breathing on each other).

-And in your mind door #2 is the "simpler" explanation??

--As far as the Nature articles, it is all fluff. There is no data being presented at all. Even worse than that, the article states that Chinese "scientists" announced on Feb 7th that they had discovered a coronavirus in Pangolins with 99% homology to SCOV2, and yet in the 2.5 months since they have published no evidence to corroborate this.



Does this make any sense at all? What are they waiting for? At this point, the "simple" explanation was it was all bullshit misinformation.

Here is the journal paper that the live science article is referring to. Unlike the Nature articles there is actually something there, so lets dig in.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7099673/

It is technical so I could be getting something wrong, but their argument seems to be that they looked at genes associated with a specific protein in SARS-COV2 (that they argue is the most important) and determined that a partial coronavirus sample (with 1/4 of the genome missing) found in one pangolin sample (a species native to SE Asia but I guess also found in SW China?) indicated that in this one partial sample of one protein there was more homology to SARS-COV2 than in the bat coronavirus most similar genetically to SARS-COV2. And this is somehow supposed to be a smoking gun that pangolins are an intermediate host?

Nope. It is an interesting theory with some interesting data, but this is nowhere close to solid data. What they need to show to advance this theory is that a full genome from this virus is more similar to the SARS-COV2 equivalent than the bat coronavirus with 96% homology, to indicate this may be either the natural or intermediate host the virus jumped from. Ironically, this is what the Chinese "scientists" promised on Feb 7th (according to the Nature article), that they haven't delivered anything on yet.

Does this image work? Link is weird.

First results of excess death figures, apparantly published on NYT, but I got it from a local article.

Kinda unfair to list NYC but not list Madrid & Lombardy, but whatever, still very interesting.

Like I said earlier ITT, Belgium getting a lot of attention wrt our horrible death numbers, but we're actually being very accurate.

Credit where credit is due, Sweden as well. I expected Sweden to be underreporting as well since it makes sense in their position, but seems like so far they are not doing it.

I am guessing they used city data in a couple spots because they didn't have state/country data. Not because they were trying to be unfair to NYC (or Jakarta/Istanbul).

But yeah, interesting. Although even here I am not sure how you extrapolate the data to determine true IFR.

For example, some % of covid caused deaths assuredly happened to people that would have died anyways, so how do you account for this?

In my opinion during the periods of chaos where there is too much death to do post mortem tests (like pretty much everywhere in the world right now), the best proxy to actual figures is expected deaths - excess deaths.

Of course, some lives might be shortened by 3 months and some by 40 years, which is an important distinction. I guess excess death per age category would be interesting for this, but I suspect that it'll be a long time before we see those types of studies.