Failure to recognize when an aerosol isn't a droplet, but without the stubborn dissagreements. 7

[moon161]

For discussion of the primary matter of this thread, but the stubborn dissagreements can remain there.

https://www.eng-tips.com/viewthread.cfm?qid=483537

 

[Alistair_Heaton]

they are basically checking every blood sample in the UK now when it hits the labs for antibody's and also gene sequencing every covid test. But its months after the sample is taken before they have the full picture.

But they are not making a lot of noise about it I presume because they don't want someone taking them to court and stopping them and/or putting a load of data restrictions on them. They are not per say recording who has what immunity just if a person has it to see what the community values are.

They are also testing most sewage systems for viral load as apparently they can see what the viral load is of the covered area is. Again the data and fact they are doing it is not broadcast.

It will be 2-3 years though before the big picture is documented and published.

As for the contact stuff I lived in a social bubble of 2 family's which everyone tested positive apart from me. I wasn't wearing a mask and was cuddling a sick 5 year old for 18 hours straight because only daddy would do....

from reading about it my blood Group O neg might have been a factor.

Plus I had something strange in Jan when it all started. The female colleague that I have blamed for catching it off objects quiet strongly to being called a super spreader.

 

[RedSnake]

BMI-years new unit?

/A

“Logic will get you from A to Z; imagination will get you everywhere.“
Albert Einstein

 

[IRstuff]

Body mass index, pretty old and controversial as a single-valued gauge of obesity

https://en.wikipedia.org/wiki/Body_mass_index

BMI-years, not new, a measure of excess weight and years carried

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3524333/

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[Alistair_Heaton]

Its like dog years

If your a fat chuffer like me, then you get some years added so you can work out how near you are to the average death age.

COVID though has been hitting diabetics quite hard and as fat chuffers are more likely to be class 2 diabetic even if they don't know they are class 2 yet or are in the pre stage some have been using this BMI age as an adjustment for working out what mortality group they are in.

Due to me getting medicals every year my blood sugar increasing was spotted years ago and I have been able to adjust things to not get labelled as class 2 and be subjected to that hellish drug metformin.

Most people because they don't get tested every year end up only finding out when there blood sugar is through the roof and they have a lot less options and their body's have been going through hell for years trying to deal with it.

I write this post as a self confessed fat chuffer so don't anyone be getting upset about body shaming comments all comments in relation to being fat are about myself.

 

[FacEngrPE]

BMI has the advantage of being a simple number - easy to determine, and statistically correlates with some health situations that are deemed important. On an individual basis it is imprecise, and therefor useful mostly as a screening tool, but often provides incomplete or impossible to follow recommendations.
For BMI labeled obese (almost everyone over 40 fits this category), dieting is not necessary helpful for some of the health items that correlate. Aiming for a stable weight is likely helpful for most of us.

 

[RedSnake]

Okey I knew about BMI it was a bit of a hype here 7-8 years ago.
There was also a lot of blood testing "health control" at work checking, blood pressure good and bad cholesterol and things, it was voluntary.
We even had this 10 year checkouts 30, 40, 59, 60 by the healthcare system I think it was a project not shore they still do it though, I was never called last time.

But I never heard the expression BMI-years.
Seems to me as a difficult unit, to relate to if you don't keep track of your BMI and good/bad cholesterol ratio level every year.

Not even sure I understand why BMI-years would have anything to do with who is a super spreaders.
Do they have better lung capacity then children or atlets and can produce air born droplets that is spread further then others?
Or do they produce more saliva?
Or less saliva?
Do they bread more often?
That small kids is less infections at distance is clear since they are shorter have smaller lungs less airspeed when breathing out.

Might add I have just half read electricpetes artikel, but making a study about super spreaders with that as a starting point / base line feels odd and it was only done with 194 individuals so I am not sure how accurate it is.



/A



“Logic will get you from A to Z; imagination will get you everywhere.“
Albert Einstein

 

[electricpete]

BMI-years, not new, a measure of excess weight and years carried

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3524333/

Just as a point of clarification, that is excess BMI years.

The article I referenced in PNAS (an initialism, not an acronym!) defined their usage of BMI-years in their opening as just a simple multiplication (nothing to do with excess)

Our findings indicate that the capacity of airway lining mucus to resist breakup on breathing varies significantly between individuals, with a trend to increasing with the advance of COVID-19 infection and body mass index multiplied by age (i.e., BMI-years)

BMI at/below 18.5 is underweight, so if you're 35 years old you'd need to be underweight to be below this 650 BMI-years.
At my age 60, I'd need a BMI around 11... not much more than a skeleton.

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(2B)+(2B)' ?

 

[IRstuff]

The correlation in the article, while significant, is pretty iffy to me; there appears to be lots of caveats buried in the reasoning. They had a lot of people with BMI*yeara above 1600 that were low spreaders.

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[electricpete]

Yes I agree the correlation in figure 2 is not overwhelming. Although it seems to show that superspreaders are rarer and not as super among those with less than 850 bmi-years.

The reason I cited the article was in response to question whether individuals (vs events) can be superspreaders. That is shown somewhat in figure 1A (A is the upper left graph) where you see a very few on the far left emit waay more particles than most people. I think this particular study only looked at respiratory droplets (not viral content) so there may be other viral shedding factors that vary among individuals.



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(2B)+(2B)' ?

 

[IRstuff]

Sure, probably not that different than people who spit more than others when talking; that was one reason one dim sum restaurant finally got their servers to wear spit shields

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[RedSnake]

More then iffy.

They say

We qualified as “low spreaders” those 159 individuals who exhaled below 156 particles per liter.
We evaluated relationships between exhaled aerosol particle number and sex, age, and body mass index (BMI). No correlation was found with sex, while significant correlations were observed between exhaled aerosol, age, and BMI—and particularly BMI-years.

They do not show any graf for only age or only BMI.
This BMI-Year graf only contains 146 test persons since the rest haven't left data to be in it.
And if you draw a line at 156 particles per liter.
And then take away every super spreader that has one or more low spreader in the same BMI-year.
There is only one super spreader left at 2300 BMI-year!
Hardly a statistical proven result with 146 test persons.
I would say this is total nonsens.
Or am I missing something?

Best Regards A



“Logic will get you from A to Z; imagination will get you everywhere.“
Albert Einstein

 

[IRstuff]

I don't think that's the way they did the partitioning. The BMI correlation only applies to a small group of people designated as "superspreaders."

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[RedSnake]

There was 159 persons that exhaled bellow 156 p/l and 35 super spreaders over, a total of 194 test persons in this study.
The graf contains 146 test persons since they hadn't the right data to make the BMI-year calculation for the rest.
Red triangle = super spreaders = 25 counted
Black dots = low spreaders = 121
There is more people in the graf then 35.

There is no natural correlation between years an BMI to begin with so why make a Unit BMI*years, it does not make sense.


/A


“Logic will get you from A to Z; imagination will get you everywhere.“
Albert Einstein

 

[electricpete]

Rather than significant linear correlation, I think what the data shows more clearly is a significant threshhold effect.

If you raise the horizontal red line (minimum threshhold for superspreaders) to about 250 particles/liter, then you can count 12 superspreaders above an 850 bmi-years cutoff and 0 superspreaders below. This is in spite of the fact that about (almost) half the sampled population is below 850 bmi-years. If it were random (probability of superspreader independent of BMI-years), then the probability of a superspreader falling above 850 would be the same as the probability of falling below (0.5). So the probability that 12 just happened to all fall on the right side (similar to flipping heads 12 times in a row) is 1/2^12 ~ 0.00024 or double that for two-tailed distribution 0.0005. So I think there is something there. My analysis would not pass the world of hypothesis testing (even if there were half below 850, which there aren't quite) where you have to define the criteria before you look at the data (I picked the horizontal and vertical threshholds only after looking at the data) so if I were to claim p=0.0005 for the hypothesis that that superspreaders (defined by a 250 threshhold) are more likely above 850 than below, that would not be a legitimate claim (maybe they'd call me a "p-hacker", or worse). Nevertheless it seems a very noticeable threshhold pattern to me.

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(2B)+(2B)' ?

 

[RedSnake]

Does not help every super spreader above the line can be taken out with one or more below in the same BMI-year.

/A


“Logic will get you from A to Z; imagination will get you everywhere.“
Albert Einstein

 

[electricpete]

Yes, that's the horizontal line I wanted (thanks).

What they're trying to show are the characteristics of superspreaders. They are not particularly trying to characterize the entire population.

If I draw a random person from the general population, what is the probability that he is a respiratory-particle superspreader? We can answer that question better if we know the BMI-YRS. In particular the aspect I mentioned was:

P(Superspreader | BMI-YRS > 850) >> P(Superspreader | BMI-YRS < 850)

I agree with you the original wording in the article seems off especially talking about (linear) correlation

=====================================
(2B)+(2B)' ?

 

[IRstuff]

There are two regression lines one for superspreaders and one for lowspreaders. What can be said is that if the two top superspreaders weren't there, there wouldn't be much of a correlation for them


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[RedSnake]

What they sade was that

We note that all volunteers of <26 y of age and all subjects under 22 BMI were low spreaders of exhaled bioaerosol.

But you can't really se that from the graf, maybe that is whas annoys me.

They could as easily had sad that everybody with a 26 years x 22 BMI = 572 BMI-Year can be a super spreader.
They obviously have one at 475 that person does not fit any of the above.
And 850 can be a 34 year old with BMI 25.

So I am not shore what conclusions that can be made.
There is a lot factors left out.
Have they even written what the youngest and the oldest was?

Or maybe it is that this Unit isn't used in Sweden, can't find it if I am looking for it in Swedish.

BR A





“Logic will get you from A to Z; imagination will get you everywhere.“
Albert Einstein

 

[electricpete]

I can’t say I ever ran across the unit BMI-yr before either.

Why they chose to emphasize BMI-yrs over separately examining BMI and years, beats me. I would assume that maybe the correlation and/or threshold behavior was no more evident in the individual BMI and years data than in the combined BMI-years data (if not there would be merit to splitting it).

I will mention, the only reason I cited the article was to defend the idea of superspreader person (see figure 1A).

But another interesting thing is these authors POSTULATE that the higher respiratory droplets from old and obese people might be part of the explanation for their worse outcomes when infected (the “promiscuous” droplets are supposedly more likely to find their way into the lungs). And perhaps it’s another factor making nursing home outbreaks worse.

The strong correlation observed here between advanced BMI-years and greater propensity to generate respiratory droplets (Fig. 2) may be significant in the light of the recognized risk of those with high BMI (18, 19), advanced age (20), or both (21) (the elderly, the obese, and the obese elderly) developing severe symptoms upon COVID-19 infection. Promiscuity of respiratory droplets in the airways heightens the probability that upper airway infection transports deeper into the lungs, promoting severe symptoms, as is observed, with remarkable speed, following intranasal and intratracheal instillation of SARS = CoV-2 in NHPs (22). It also heightens the probability of expelling the aerosol into the environment and transmission of the disease, underlining the transmission risk of living circumstances that bring high-risk (high BMI-year) populations into close proximity for extended periods of time, such as nursing homes.

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(2B)+(2B)' ?

 

[Fischstabchen]

Fat cell have ACE2 receptors for COVID-19. I suspect the hypothesis of the author is that the weak immune systems of old people and people with a lot of ace2 receptor location ,fat people, are more likely to spread the virus due to more likely reaching a higher viral load due to a quicker replication of the virus and/or a weak immune response. Early in the pandemic, there was talk of using staton drugs to latch onto the ace2 receptors and slow viral replication.