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A friend of mine was detected COVID-19 positive through PCR one month back. He was asymptotic as per doctors and had no symptoms. He quarantined himself and increased his intake of water. After 1 month, he got himself tested and the result was negative. His antibodies value was +7.0.

My question: Is it possible to get COVID-19 false positive ? 2) Is it possible that a person comes as COVID-19 positive due to bad sampling technique or something ? 3) Given the antibody value as 7.0. Is it possible that the same person gets COVID-19 positive again ?

(My theory is that COVID-19 will try to come to his body but his antibodies value is so high that it won't affect him.)

I likeThatMeow
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Badddy
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1 Answers1

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The rt-PCR tests for Covid-19 are not 100% specific so yes it's possible to get a false positive.

From the China PCR test

The sensitivity of the RT-PCR diagnostic test was estimated to be 0.777 (95% CI: 0.715, 0.849), while the specificity was 0.988 (95% CI: 0.933, 1.000). The confidence intervals include sampling error in addition to the error due to probabilistic knowledge of the data.

This means that out of 100 true negative patients, the test will correctly identify 98.8 as negative. Out of 100 true positive patients, the test will correctly identify 77.7 as positive. The positive predictive value (PPV, Given a positive test, what are the chances that the patient is actually positive) and negative predictive value however depend on the population sample that is being tested. This answer explains it fairly well.

We don't have enough data on antibodies yet to interpret them.

https://www.medrxiv.org/content/10.1101/2020.04.24.20078949v1

Narusan
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Graham Chiu
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    "this suggests 1:100 positives could be false positive" is not true, it depends on the ratio between true positives and true negatives. If, for example, you did 1,000,000 tests on a population with 0 true positives, you would expect to return 12,000 positives, all of which would be false. The correct interpretation is instead that "this suggests that 1/100 people who are actually negative will nonetheless test positive". – Bryan Krause May 27 '20 at 21:45
  • What's the difference? – Graham Chiu May 28 '20 at 01:42
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    You have stated it as 1/100 positives are false positive; that is not the same as 1/100 negatives will test positive. If the test population contains a lot of no-CoV subjects then the number of positives that are false positive will be much much higher than 1/100. I gave maybe an extreme example of 100% false positive, but let's say you test a population of 1000, 10% are CoV cases and 90% are virus-free. 1.2% (1-specificity) of the 900 (=11) will test positive incorrectly, as will 77.7% (sensitivity) of the 100 (=78). Total 89 positive tests, 11/89 = 12% are false positive, rather than 1.2%. – Bryan Krause May 28 '20 at 01:51
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    Exactly! Also, this is because most screening tools (and the PCR Test as well) are only used on risk groups. The sensitivity and specificity are not dependant on the population sample, but the rate of true to false positives and true to false negatives is. This is why it doesn’t make sense to do any medical test without an indication (regardless of the cost). Only very very few screening tools are used on a whole population sample. – Narusan May 28 '20 at 06:07
  • So why aren't you complaining to the OP here that their question lacks research? – Franck Dernoncourt May 31 '20 at 00:06
  • Does the OP have 8k points?? – Graham Chiu May 31 '20 at 03:48
  • @Narusan did you mean “this is why” instead of “this is because”? Otherwise I don’t understand your comment... – Jonas Heidelberg May 31 '20 at 16:53
  • @JonasHeidelberg It appears my German got the better of me... Yes of course! This is why* most screening tools are only used on risk groups* was what I meant to say. – Narusan May 31 '20 at 17:16
  • Why don't you guys suggest an edit to fix the misunderstanding?? – Graham Chiu Jun 02 '20 at 01:58
  • @GrahamChiu I can’t suggest an edit, the edit immediately becomes effective. Please edit the edit or revert it altogether, if you have any objections. – Narusan Jun 02 '20 at 10:18
  • The number of points the OP has shouldn't impact how their questions are received. – Franck Dernoncourt Jun 02 '20 at 14:31
  • @BryanKrause So, Wuhan tested 6.8M - 11M people in the last few weeks. They picked up 206 positives. Are those potentially all false positives?? – Graham Chiu Jun 03 '20 at 00:04
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    @GrahamChiu I am solely arguing from the statistical facts of the sensitivity/specificity numbers you reported in your own answer, and the correct interpretation of those numbers. Maybe data from China should be questioned or maybe the specificity is way better than .988. If the specificity is truly .988 you would expect 120,000 positive tests in a sample of 10 million if no one is infected. I believe they used a bulk screening approach which might reduce sensitivity but also improve specificity. – Bryan Krause Jun 03 '20 at 03:32
  • They did screening in batches of 10, and if a batch were positive then they tested each individual in that batch – Graham Chiu Jun 03 '20 at 04:32
  • I have no idea how that affects the specificity – Graham Chiu Jun 03 '20 at 04:34
  • Yeah, it really depends on the reasons for false positives as well as the stats on the batch screening. I assume there are numbers out there somewhere but I don't have them. – Bryan Krause Jun 03 '20 at 14:17
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    @BryanKrause (and GrahamChirlu) One possible cause of false positives is contamination of negative samples with positive samples. This particular source of false positives would lead to false positive rate (1 - specificity) to be correlated with the number of true positives... – cbeleites unhappy with SX Jun 05 '20 at 18:25