Now this can be a bit complex. But let's try. The PCR test, stands for Polymerase Chain Reaction. Now what this is is a multiplication of DNA by a heat, reverse transcriptase, double, and repeat type process. A simple but brilliant idea. When we do this test for COVID we take a sample, if the RNA is present we turn it back into DNA, then PCR it multiple times, or cycles. Ct is the number of cycles needed to get a positive reading.
Thus it would seem logical if we need say a Ct or 15 as compared to say Ct of 30 we have a lot more virus at the Ct of 15 since to get to the same threshold we had to double the multiplications. Remember each time we double and so ten times is about a 1,000 and 15 times is about 250,000. Thus Ct 15 is 250,000 more infected than Ct of 30. I know it may be a bit complex but follow me here. There was a piece in Science describing this.
Now here is where the fun begins. In the Journal of Clinical Infectious Diseases the authors have the following Figure.
This is a very complex and possibly confusing chart. Now let me try to deconvolve.
They did tests on a batch of patients.
1. Test 1 was at one week
2. Test 3 at 2 weeks
3. Test 3 at 3 weeks
4. Cell culture test (a Gold Standard, namely "truth")
Now the results are shown where we have number of samples testing positive by Ct. Remember that Ct was the number of doublings needed to get a reading of positive. By the way, if it was still not positive at 35 they said you were negative.
Now the paper shows however that the negatives grew exponentially and that the correlation between "truth" and PCR tests was weak at best! What does this mean? Simple, PCR can be problematic with extremely high false positives.
Science is a b...h is it not!
I have then taken the data and plotted the percent positive at a specific Ct value by time of test. The top blue line is first encounter. This is the ratio of those tested positive at Ct level specified to all tested at that level. The same for the other examples. Now what this shows is that at the beginning the very sick are very sick, Less so as the Ct increases. By week 1 we have a small drop. By week 2 and 3 we see few still being infected. This is an interesting chart.
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