A new report in the Journal of the American Medical Association finds more good news for unvaccinated people who have already had and recovered from Covid.

Anti-spike protein antibodies following Covid infection and recovery seem to persist indefinitely in unvaccinated people, researchers found. People tested 20 months after coronavirus infection had slightly higher levels of antibodies on average than those just after infection.

The key chart: the flat yellow line shows that people with natural immunity seem to have the same level of antibodies no matter when they were infected.

I want to let this go. I really do. But I can't.

You realize that flat yellow line isn't really a flat line right? The random data is plotted on a semi-log scale.

NicosMachine

The key chart: the flat yellow line shows that people with natural immunity seem to have the same level of antibodies no matter when they were infected.

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Tell me you don't understand the chart without telling me you don't understand the chart.

Inca said:

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NicosMachine

The key chart: the flat yellow line shows that people with natural immunity seem to have the same level of antibodies no matter when they were infected.

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Tell me you don't understand the chart without telling me you don't understand the chart.

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Tell me you don't understand natural immunity without saying you don't understand natural immunity.

Don't be bringing that logic that a full natural response could be superior to a vaccine specifically designed for a spike protein which has changed significantly in here

DannyDuberstein said:

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Don't be bringing that logic that a full natural response could be superior to a vaccine specifically designed for a spike protein which has changed significantly in here

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Wanna see a magic trick? You're about to disappear. Take a snapshot of this page and watch.

Mathguy64 said:

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I want to let this go. I really do. But I can't.

You realize that flat yellow line isn't really a flat line right? The random data is plotted on a semi-log scale.

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So it's increasing exponentially as opposed to linearly? Seems like a stronger argument for the benefits of natural immunity. I'm confused how the scale of the plot changes the argument.

Mathguy64 said:

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I want to let this go. I really do. But I can't.

You realize that flat yellow line isn't really a flat line right? The random data is plotted on a semi-log scale.

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You do realize that doesn't diminish the finding that natural immunity is lasting don't you?

NicosMachine said:

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Mathguy64 said:

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I want to let this go. I really do. But I can't.

You realize that flat yellow line isn't really a flat line right? The random data is plotted on a semi-log scale.

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You do realize that doesn't diminish the finding that natural immunity is lasting don't you?

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You realize that data is random and someone put a line in it like a log regression line. But the SSEs are off the chart. It's meaningless.

Where is the comparison between vaccinated and unvaccinated in that link?

Mathguy64 said:

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NicosMachine said:

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Mathguy64 said:

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I want to let this go. I really do. But I can't.

You realize that flat yellow line isn't really a flat line right? The random data is plotted on a semi-log scale.

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You do realize that doesn't diminish the finding that natural immunity is lasting don't you?

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You realize that data is random and someone put a line in it like a log regression line. But the SSEs are off the chart. It's meaningless.

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You are embarrassing yourself. Read the study. "Antireceptor-binding domain (RBD) levels did not differ by months since COVID-19 diagnosis (0.8% increase [95% CI, 2.4% to 4.2%] per month, P = .62). Data markers indicate individual anti-RBD titers; solid orange curve with shaded area, linear regression with 95% confidence range."

PerpetualLurker said:

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Where is the comparison between vaccinated and unvaccinated in that link?

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Google "vaccine waning efficacy" if you haven't heard the news that vaccine efficacy wanes after 2-3 months.

NicosMachine said:

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Mathguy64 said:

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NicosMachine said:

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Mathguy64 said:

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I want to let this go. I really do. But I can't.

You realize that flat yellow line isn't really a flat line right? The random data is plotted on a semi-log scale.

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You do realize that doesn't diminish the finding that natural immunity is lasting don't you?

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You realize that data is random and someone put a line in it like a log regression line. But the SSEs are off the chart. It's meaningless.

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You are embarrassing yourself. Read the study. "Antireceptor-binding domain (RBD) levels did not differ by months since COVID-19 diagnosis (0.8% increase [95% CI, 2.4% to 4.2%] per month, P = .62). Data markers indicate individual anti-RBD titers; solid orange curve with shaded area, linear regression with 95% confidence range."

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Stop. Just stop. They are plotting time series data on a scale from 0.1 to 2500. That data can only generously be called random. It's consistently in that banding. On that scale it's just random. I don't need to read some nonsense that someone who failed a stat class wrote to look at that data and see the correlation to a line is essentially 0. If they want to claim otherwise whatever.

The only thing that line represents is the law of large numbers.

Natural immunity is definitely a valid thing. I never said it wasn't. But at least understand how to interpret the chart before you use it to make your argument.

Mathguy64 said:

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NicosMachine said:

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Mathguy64 said:

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NicosMachine said:

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Mathguy64 said:

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I want to let this go. I really do. But I can't.

You realize that flat yellow line isn't really a flat line right? The random data is plotted on a semi-log scale.

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You do realize that doesn't diminish the finding that natural immunity is lasting don't you?

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You realize that data is random and someone put a line in it like a log regression line. But the SSEs are off the chart. It's meaningless.

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You are embarrassing yourself. Read the study. "Antireceptor-binding domain (RBD) levels did not differ by months since COVID-19 diagnosis (0.8% increase [95% CI, 2.4% to 4.2%] per month, P = .62). Data markers indicate individual anti-RBD titers; solid orange curve with shaded area, linear regression with 95% confidence range."

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Stop. Just stop. They are plotting time series data on a scale from 0.1 to 2500. That data can only generously be called random. It's consistently in that banding. On that scale it's just random. I don't need to read some nonsense that someone who failed a stat class wrote to look at that data and see the correlation to a line is essentially 0. If they want to claim otherwise whatever.

The only thing that line represents is the law of large numbers.

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So you dispute the finding that natural immunity to Sars-CoV-2 does not diminish over 20 months? While everyone had varying levels of anti-spike RBD levels (any amount above zero is indicative of some "immunity") the overall levels did not diminish over time. I'm sorry the findings aren't consistent with your wishes, but facts are facts.

I think at this point finding a different study to support natural immunity would be best, OP. There are many out there.

Um that is still a "flat" line even though they drew it on a semi log scale. It is around 180 at the left and 180 at the right. But it is just randomly drawn there in the data. They just tried.to pick a line that had half the data on both sides and it stays straight.

NicosMachine said:

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Mathguy64 said:

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NicosMachine said:

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Mathguy64 said:

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NicosMachine said:

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Mathguy64 said:

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I want to let this go. I really do. But I can't.

You realize that flat yellow line isn't really a flat line right? The random data is plotted on a semi-log scale.

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You do realize that doesn't diminish the finding that natural immunity is lasting don't you?

---

You realize that data is random and someone put a line in it like a log regression line. But the SSEs are off the chart. It's meaningless.

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You are embarrassing yourself. Read the study. "Antireceptor-binding domain (RBD) levels did not differ by months since COVID-19 diagnosis (0.8% increase [95% CI, 2.4% to 4.2%] per month, P = .62). Data markers indicate individual anti-RBD titers; solid orange curve with shaded area, linear regression with 95% confidence range."

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Stop. Just stop. They are plotting time series data on a scale from 0.1 to 2500. That data can only generously be called random. It's consistently in that banding. On that scale it's just random. I don't need to read some nonsense that someone who failed a stat class wrote to look at that data and see the correlation to a line is essentially 0. If they want to claim otherwise whatever.

The only thing that line represents is the law of large numbers.

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So you dispute the finding that natural immunity to Sars-CoV-2 does not diminish over 20 months? While everyone had varying levels of anti-spike RBD levels (any amount above zero is indicative of some "immunity") the overall levels did not diminish over time. I'm sorry the findings aren't consistent with your wishes, but facts are facts.

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You really need to read what they said. That chart you posted shows a regression line with a 95% confidence interval. That's the highlighted area outside the actual line. The paper admits the data falls outside the CI. Which as you can see it does. They admit the regression is worthless. Which it is. The paper admits they didn't track individuals over time to study whether or not their individual antibody levels increased, decreased or stayed constant. They asked people to fill out a questionnaire on if they think they had or didn't have COVID and get a single antibody test. The sample of people was admitted to be largely white and healthy based on a survey. Not anything the authors confirmed just what people wrote on a Facebook form. A highly effective way to collect a random sample I am sure. They aren't tracking anything over time. They literally wrote "there is no evidence of association between time after infection and antibody titer".

88planoAg said:

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I think at this point finding a different study to support natural immunity would be best, OP. There are many out there.

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Why? This study quite clearly shows that naturally produced antibodies do not diminish over time (20 months). "There was no evidence of association between time after infection and antibody titer (0.8% increase [95% CI, 2.4% to 4.2%] per month, P = .62) "

NicosMachine said:

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88planoAg said:

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I think at this point finding a different study to support natural immunity would be best, OP. There are many out there.

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Why? This study quite clearly shows that naturally produced antibodies do not diminish over time (20 months). "There was no evidence of association between time after infection and antibody titer (0.8% increase [95% CI, 2.4% to 4.2%] per month, P = .62) "

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Quote:

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They aren't tracking anything over time. They literally wrote "there is no evidence of association between time after infection and antibody titer".

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The last 2 replies will be nuked.

But for the record, I am a true believer of natural immunity, having been tested 4x for antibodies after symptomatic covid (mild) Dec 2020. My current antibody level is 900 and I've been directly exposed to Omicron with no symptoms. No vaccine.

That doesn't mean the OP's example isn't a bad one.

NicosMachine said:

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88planoAg said:

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I think at this point finding a different study to support natural immunity would be best, OP. There are many out there.

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Why? This study quite clearly shows that naturally produced antibodies do not diminish over time (20 months). "There was no evidence of association between time after infection and antibody titer (0.8% increase [95% CI, 2.4% to 4.2%] per month, P = .62) "

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Wait, the P value is .62? Seriously? Why did they even bother to publish this?

NicosMachine said:

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A new report in the Journal of the American Medical Association finds more good news for unvaccinated people who have already had and recovered from Covid.

Anti-spike protein antibodies following Covid infection and recovery seem to persist indefinitely in unvaccinated people, researchers found. People tested 20 months after coronavirus infection had slightly higher levels of antibodies on average than those just after infection.

The key chart: the flat yellow line shows that people with natural immunity seem to have the same level of antibodies no matter when they were infected.

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When you quote medical literature, it is not enough to cut and paste figures, you need to include the entire reference.

NicosMachine said:

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Mathguy64 said:

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NicosMachine said:

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Mathguy64 said:

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NicosMachine said:

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Mathguy64 said:

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I want to let this go. I really do. But I can't.

You realize that flat yellow line isn't really a flat line right? The random data is plotted on a semi-log scale.

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You do realize that doesn't diminish the finding that natural immunity is lasting don't you?

---

You realize that data is random and someone put a line in it like a log regression line. But the SSEs are off the chart. It's meaningless.

---

You are embarrassing yourself. Read the study. "Antireceptor-binding domain (RBD) levels did not differ by months since COVID-19 diagnosis (0.8% increase [95% CI, 2.4% to 4.2%] per month, P = .62). Data markers indicate individual anti-RBD titers; solid orange curve with shaded area, linear regression with 95% confidence range."

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Stop. Just stop. They are plotting time series data on a scale from 0.1 to 2500. That data can only generously be called random. It's consistently in that banding. On that scale it's just random. I don't need to read some nonsense that someone who failed a stat class wrote to look at that data and see the correlation to a line is essentially 0. If they want to claim otherwise whatever.

The only thing that line represents is the law of large numbers.

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So you dispute the finding that natural immunity to Sars-CoV-2 does not diminish over 20 months? While everyone had varying levels of anti-spike RBD levels (any amount above zero is indicative of some "immunity") the overall levels did not diminish over time. I'm sorry the findings aren't consistent with your wishes, but facts are facts.

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Yes, the conclusion that natural immunity to SARS COV2 does not diminish over 20 months is not proven by these data. The individual responding with statistical arguments makes valid points. However, IMO, the major problem with this conclusion is that individual patients had their antibody levels tested only at one time point. A properly conducted trial to evaluate antibody durability would be to evaluate each patient at multiple time points over a 20 month period. Anything short of that cannot support the conclusion of antibody durability.

THIS ILLUSTRATES THE MAJOR PROBLEM ON THIS BOARD AND IS PERVASIVE ON THE INTERNET.

UNQUALIFIED LAY PEOPLE READ THE 1 PARAGRAPH SUMMARY OF A STUDY AND ACCEPT IT AS FACT WITHOUT BEING ABLE TO SCIENTIFICALLY EVALUATE THE DATA!!!!

TO ALL OF YOU NOT TRAINED IN STATISTICS, SCIENCE OR MEDICINE, DEFER TO YOUR MEDICAL EXPERTS TO HELP YOU INTERPRET ANY STUDY YOU SEE ON THE INTERNET. REMEMBER, NEWSPAPER REPORTERS ARE GENERALLY LAY PEOPLE ALSO AND INCAPABLE OF ASSESSING SCIENTIFIC EVIDENCE.

WHEN I READ A LAY DISCUSSION OF EVIDENCE I CRINGE AT THE LACK OF UNDERSTANDING AND ABILITY TO COMPREHEND AND UNDERSTAND THE SCIENCE BEING QUOTED

woodlees said:

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REMEMBER, NEWSPAPER REPORTERS ARE GENERALLY LAY PEOPLE ALSO AND INCAPABLE OF ASSESSING SCIENTIFIC EVIDENCE.

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Worse, they generally are dumber than most lay people which is why they can't get a better job than newspaper reporter.

wbt5845 said:

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woodlees said:

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REMEMBER, NEWSPAPER REPORTERS ARE GENERALLY LAY PEOPLE ALSO AND INCAPABLE OF ASSESSING SCIENTIFIC EVIDENCE.

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Worse, they generally are dumber than most lay people which is why they can't get a better job than newspaper reporter.

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Double worse, they generally have a conclusion made up before they start, which leads to things like the OP happening.

cisgenderedAggie said:

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wbt5845 said:

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woodlees said:

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REMEMBER, NEWSPAPER REPORTERS ARE GENERALLY LAY PEOPLE ALSO AND INCAPABLE OF ASSESSING SCIENTIFIC EVIDENCE.

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Worse, they generally are dumber than most lay people which is why they can't get a better job than newspaper reporter.

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Double worse, they generally have a conclusion made up before they start, which leads to things like the OP happening.

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This is on the OP not understanding what data is saying. It has nothing to do with journalism.

cisgenderedAggie said:

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Sapper Redux said:

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cisgenderedAggie said:

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wbt5845 said:

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woodlees said:

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REMEMBER, NEWSPAPER REPORTERS ARE GENERALLY LAY PEOPLE ALSO AND INCAPABLE OF ASSESSING SCIENTIFIC EVIDENCE.

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Worse, they generally are dumber than most lay people which is why they can't get a better job than newspaper reporter.

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Double worse, they generally have a conclusion made up before they start, which leads to things like the OP happening.

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This is on the OP not understanding what data is saying. It has nothing to do with journalism.

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Journalists do it all the time. It didn't start with Covid, but it's gotten much worse.

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Journalists absolutely make mistakes. The breathless reporting of the garbage report by some Johns Hopkins economists is proof of that. But in this case, you're moving the goalposts.

cisgenderedAggie said:

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Sapper Redux said:

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cisgenderedAggie said:

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Sapper Redux said:

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cisgenderedAggie said:

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wbt5845 said:

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woodlees said:

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REMEMBER, NEWSPAPER REPORTERS ARE GENERALLY LAY PEOPLE ALSO AND INCAPABLE OF ASSESSING SCIENTIFIC EVIDENCE.

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Worse, they generally are dumber than most lay people which is why they can't get a better job than newspaper reporter.

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Double worse, they generally have a conclusion made up before they start, which leads to things like the OP happening.

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This is on the OP not understanding what data is saying. It has nothing to do with journalism.

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Journalists do it all the time. It didn't start with Covid, but it's gotten much worse.

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Journalists absolutely make mistakes. The breathless reporting of the garbage report by some Johns Hopkins economists is proof of that. But in this case, you're moving the goalposts.

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What goalposts did I move?

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You blamed the OP's error on journalists. This wasn't a piece of journalism. It was a research piece that couldn't support the claims it was making and the OP didn't understand the problems with the data.