Anti-body testing results--possible explanations

1,684 Views | 9 Replies | Last: 5 yr ago by KidDoc
Patentmike
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Thought it might be a good idea for a thread to discuss the possible reason why the antibody tests are showing so much higher rates of SARS-CoV-2 infection than predicted from the PCR testing that has been done. These points have been discussed in threads about specific studies done, such as by Stanford, USC and others, but having them in one place may be helpful.

The hope is that this thread remains about the science.

So, why do the the antibody studies suggest an 8x to 50x higher incidence of SARS-CoV-2 infection than predicted from RT-PCR and/or symptom based diagnosis of COVID-19? Possibilities:

  • Missed cases--we know the RT-PCR has a somewhat narrow time window in which it is reliable and missed cases are at least part of the difference.
  • The virus is simply far less pathogenic than we thought. Everyone getting sick has a comorbidity of some type, even if it isn't recognized. Within this we can include the virus is really bad only if you get infected with by a large initial dose--think packed NY Subway car with an infected person breathing/coughing in the middle of the crowd. This has some legs as AggieHawg will tell you.
  • There is a less virulent variant of SARS-CoV-2 that is competing with the nasty version. See https://www.biorxiv.org/content/10.1101/2020.03.31.015941v1 for ideas of what this might look like. The insertion to create furin cleavage site creates a vulnerability to ZAP protein because of three CpG dinucleotides coding the site.
  • Cross reactivity of antibodies for a different coronavirus to SARS-CoV-2. I read the blurb for the USC study on the USC website. The researchers there did controls to address this possibility. We cannot rule this out until we see their data and not just the conclusions. (BallerStaff referenced this study in a post that is worth a read).
  • Non-random study participants (the cohort). If the study participants are not selected correctly, then the cohort is not representative of the overall population (similar to doing political polls, your results are affected by the people questioned/studied).

My thoughts for the day. I have been hopeful of a less virulent variant from the beginning and I am biased towards hoping that's the right one. Anyone, add on any scientific explanations I might have missed or add sources to support what you think is happening.
PatentMike, J.D.
BS Biochem
MS Molecular Virology


Jerkin_my_durkin
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You had me at cleavage site
KidDoc
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Don't base anything on that Stanford study. It is garbage and will be tossed in the trash. This guy breaks down the TNTC issues with it.

No material on this site is intended to be a substitute for professional medical advice, diagnosis or treatment. See full Medical Disclaimer.
KidDoc
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Patentmike said:

Thought it might be a good idea for a thread to discuss the possible reason why the antibody tests are showing so much higher rates of SARS-CoV-2 infection than predicted from the PCR testing that has been done. These points have been discussed in threads about specific studies done, such as by Stanford, USC and others, but having them in one place may be helpful.

The hope is that this thread remains about the science.

So, why do the the antibody studies suggest an 8x to 50x higher incidence of SARS-CoV-2 infection than predicted from RT-PCR and/or symptom based diagnosis of COVID-19? Possibilities:

  • Missed cases--we know the RT-PCR has a somewhat narrow time window in which it is reliable and missed cases are at least part of the difference.
  • The virus is simply far less pathogenic than we thought. Everyone getting sick has a comorbidity of some type, even if it isn't recognized. Within this we can include the virus is really bad only if you get infected with by a large initial dose--think packed NY Subway car with an infected person breathing/coughing in the middle of the crowd. This has some legs as AggieHawg will tell you.
  • There is a less virulent variant of SARS-CoV-2 that is competing with the nasty version. See https://www.biorxiv.org/content/10.1101/2020.03.31.015941v1 for ideas of what this might look like. The insertion to create furin cleavage site creates a vulnerability to ZAP protein because of three CpG dinucleotides coding the site.
  • Cross reactivity of antibodies for a different coronavirus to SARS-CoV-2. I read the blurb for the USC study on the USC website. The researchers there did controls to address this possibility. We cannot rule this out until we see their data and not just the conclusions. (BallerStaff referenced this study in a post that is worth a read).
  • Non-random study participants (the cohort). If the study participants are not selected correctly, then the cohort is not representative of the overall population (similar to doing political polls, your results are affected by the people questioned/studied).

My thoughts for the day. I have been hopeful of a less virulent variant from the beginning and I am biased towards hoping that's the right one. Anyone, add on any scientific explanations I might have missed or add sources to support what you think is happening.
However I do think your point #2 will turn out to be true:

  • The virus is simply far less pathogenic than we thought. Everyone getting sick has a comorbidity of some type, even if it isn't recognized. Within this we can include the virus is really bad only if you get infected with by a large initial dose--think packed NY Subway car with an infected person breathing/coughing in the middle of the crowd. This has some legs as AggieHawg will tell you.
No material on this site is intended to be a substitute for professional medical advice, diagnosis or treatment. See full Medical Disclaimer.
Not a Bot
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I think the mathematical point is the biggest. When you are testing a population and the disease has a low prevalence, the false positives will have a magnified effect on your total result.

(Feel free to correct my math if I'm wrong here, but I know the concept is correct):
When you test 1,000 people, 30 test positive, and your test has 98% specificity...that means 2% of those 1,000 tests will be false positives. That takes away 20 people who tested positive and likely never had exposure. So 20 out of your 30 never had it.

That's why these sorts of tests are difficult when the prevalence of a disease is so low. That's alsi why in yesterday's press conference Dr Birx recommended testing healthcare workers because their rate of exposure is much higher. You would likely see a much more accurate picture of a symptomatic vs. asymptomatic cases.
Keegan99
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Quote:

That's why these sorts of tests are difficult when the prevalence of a disease is so low. That's alsi why in yesterday's press conference Dr Birx recommended testing healthcare workers because their rate of exposure is much higher. You would likely see a much more accurate picture of a symptomatic vs. asymptomatic cases.


Except healthcare workers would be ones much more likely to get infected by large doses.

So if the "infectious dose" hypothesis is true, such testing would not present an accurate picture.
Not a Bot
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I think it could give you a baseline in terms of people who stay asymptomatic against heavier viral loads.
Diyala Nick
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Moxley said:

I think the mathematical point is the biggest. When you are testing a population and the disease has a low prevalence, the false positives will have a magnified effect on your total result.

(Feel free to correct my math if I'm wrong here, but I know the concept is correct):
When you test 1,000 people, 30 test positive, and your test has 98% sensitivity...that means 2% of those 1,000 tests will be false positives. That takes away 20 people who tested positive and likely never had exposure. So 20 out of your 30 never had it.

That's why these sorts of tests are difficult when the prevalence of a disease is so low. That's alsi why in yesterday's press conference Dr Birx recommended testing healthcare workers because their rate of exposure is much higher. You would likely see a much more accurate picture of a symptomatic vs. asymptomatic cases.


Replace sensitivity with specificity and you are correct. The flip side is that is your sensitivity is 98%, you are likely to have missed 2% of cases in your sampling.
Not a Bot
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Fixed, thanks!
cone
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i hate that guy's face
KidDoc
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cone said:

i hate that guy's face
He does come off a bit ******y but I find his data interesting.
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