You are viewing a single comment's thread from:

RE: FRAUD: CDC showing again they are a political/propaganda arm and not practicing science...

in Proof of Brain2 years ago

This is definitely a point of concern. Consistent testing methodology is necessary if you are going to compare results. However, I still have questions...

You say 28 is fewer cycles than most places use today. How do you know this?

How many more positive test results do you get if, for example, using 30 cycles instead of 28? How many more false positives? Are the differences really large or insignificant? What does the curve look like?

Intuition tells me that there is some number of cycles that gets you a desired high level of accuracy and going beyond that doesn't do much except perhaps to make recovered cases somewhat more detectable. After all, no number of cycles should tell you that you have are or have been infected with something you haven't. However, I don't confuse my intuition with actual science.


After all, no number of cycles should tell you that you have are or have been infected with something you haven't.

It can show the presence of just about any virus with enough cycles. It doesn't mean you are infected. That is part of the problem. It can amplify just environmentally present miniscule items and thus provide a "this is present" result.

As the CT cycles are increased this becomes more and more likely.

The idea of using this to test for the presence of something is useful. If it is consistent. When it is not consistent and the results are being compared as some form of equivalence that is a fallacy.

Yes, comparing them as absolutely equivalent is misleading but again how misleading depends on the actual difference it makes in results. Ideally tests should be done as consistently as possible but we don't have the luxury of the perfect test. Everybody rubs that swab up their nose or down their throat a little differently. I'm just saying that it doesn't mean that comparisons are meaningless. You just have to take into account what a different cycle count means to your results and I think that would be fairly well understood by now. Accurate conclusions can still be inferred by applying the appropriate mathematical transformation. Doesn't mean results will be presented in an accurate way with all of that taken into consideration of course but assuming it is then it is still science.

Show me something that takes that into consideration and codifies it then we can have a talk...

I haven't been able to find it.

I've only been able to find PDFs without such specific guidelines...

Still the document I linked to the original document shows a specific methodology that using this technique would absolutely result in lower cases and that methodology is ONLY being applied to the vaccinated people.

28 is also a lower CT than all other cases I have found so far. The most common appear to be either 35 or 40. I've seen as high as 45 before but that was a few months ago and I no longer remember where it was to search and find it.

Well, that's exactly my point. I stipulate that a 35-45 cycle count will result in more positive test results than 28. But if it is 1% higher it is irrelevant because that would be within the margin of error. If it is 50% then that's another story. Without knowing how MUCH higher, it's not very meaningful and may or may not affect the test results enough to matter. Also, what that PDF says may or may not be what labs actually do. The fact of the matter is that this cycle count value has shifted around some as more has been learned. For instance, it was reported at one point that a value above 34 leads to too many false positives, specifically it detects the (dead) virus in those who have already recovered and are no longer contagious (but not just trace environmental amounts). Obviously, the goal should be to detect, as much as possible, only live active virus but 100% accuracy will not be achieved ever. It seems to be that if the value is lowered to 28 it would be lowered to 28 for every test, not just for those who have received the vaccine. When my son was tested they did not ask about vaccination so I'm not sure how they would know that anyway.

You did read that it was essentially rules for how the labs were to submit to the CDC. So if they use CT at all then it won't be accepted by the CDC if a person was vaccinated unless the CT is 28 or less. So sure labs could do higher. Yet it won't be within the guidelines so CDC is not likely to use any of that data.

They did say you could submit samples using other testing methods besides PCR. Though as far as I know there is actually very little of that type of testing occurring.

Even 1% is significant if it is only being applied to vaccinated people. Then those results being compared to the unvaccinated as some kind of equivalency and to show effectiveness.

I suspect you didn't read the documents I provided. They go more over the difference in results but it largely depends upon the sample size.(though perhaps not in enough detail in those I supplied. The one from the inventor of the PCR test though is enough) Since the sample size in this case will likely be very large this could be a huge deal.

You do realize that less than 1% of people die from COVID that get it. Yet they still have us locked down, and in a state of fear. Yet 1% is insignificant?

Yet... there is no getting around the fact it is not scientific.

You don't measure your control group with one setting on a device, while measuring the other groups on different settings.

These days that is not uncommon but it definitely is not scientific. It is useful for politics and agendas, but that's about it.

"You did read that it was essentially rules for how the labs were to submit to the CDC. So if they use CT at all then it won't be accepted by the CDC if a person was vaccinated unless the CT is 28 or less. So sure labs could do higher. Yet it won't be within the guidelines so CDC is not likely to use any of that data.

They did say you could submit samples using other testing methods besides PCR. Though as far as I know there is actually very little of that type of testing occurring."

The testing locations in my area ask you what kind of test you want. The choices are PCR or the rapid antigen test. In fact, the rapid antigen test seems to be the default however PCR is required for certain things (e.g. return to school earlier if you have a known exposure).

What are you basing your statement that "1% is significant"? The false positive rate is 2.3% (mean). Not sure what the false negative rate is. 1% can be significant for some things and not for others. Death is pretty significant. But a vaccine that made a 1% difference would be laughed at. The biggest worry early on was that a relatively modest increase in the average number of hospitalizations would overwhelm hospitals because they typically operate pretty close to capacity. As it has become better understood how to best treat those with COVID-19 this has become somewhat less of a concern.

Even if the results varied by 50%, as long as that was understood and factored into the results then there is not a problem. Any published scientific results should and almost certainly will include that information. And I go back to my previous point that i don't think they are currently distinguishing between tests for those who have been vaccinated and those who have not. At least they weren't asking that question when I was at a testing location a week ago. If they aren't asking then the methodology is the same whether you are vaccinated or not. Of course, that doesn't mean they won't change what they are doing.

As far as "scientific", of course it can still be scientific. It depends on other factors mentioned above. I agree that it is better to measure the same way but as long as the affect that measuring differently has is well understood than you can still compare the numbers as long as you are taking that into consideration. For political purposes, it isn't so much how the data is collected as how it is presented. Who was it that said "there are lies, damned lies and statistics"? A statistic can be made to say anything via careful wording and be true.

The false positive rate is 2.3% (mean)

Nah. Show me evidence of that. That is heavily dependent on WHERE you are measuring. With there being no clear definition of the CTs to to use you immediately should understand that rate would vary from location to location depending upon what CT they use.

It is irrefutable that using different measurements and treating them as any kind of equivalence is not scientific and will produce corrupted data.

I mean you can try to refute it (you seem to be) but if you are being logical and at all trying to keep it scientific it really can't be done.

If you can show me they are using the same CT for all of the RT-PCR testing across all the regions then we can have a discussion about what % rates are. I mean I can also give you widely different % of mortality statistics depending upon where I take that sample from.

Should I cherry pick the one that fits what I want the narrative to be?

I definitely try not to and would accept being called out on it.

The truth is there is no standard. Even the document I based this post upon accepts 28 OR LESS. That or less is important because that can be anything from 1 CT to 28 CT. That is a huge variance and if you followed the links I provided on the RT-PCR and how it works it immediately becomes clear how useless that information actually would be to any scientific comparison.

It is very useful to politics, propaganda, or defending a desired narrative.

As to false positives. The fact you even bothered sharing that 2.8% in the face of knowing there is no standard CT is a bit concerning.

Some articles about the false positive rate below though I haven't found the one that had that particular mean value. Yes, it depends on where you are, and even more on how prevalent COVID-19 is where you are. A bigger problem (or at least a more significant percentage of wrong results) is false negatives. I did not grab the links but one article suggested near 100% false negative early after an infection and 20% false negative 5 days after infection. Another article suggested current COVID-19 tests result in false negatives 33% of the time on average. I suspect the false negative rate is much lower once you've reached the point of being symptomatic which typically takes 5-6 days but up to 14 days. Various studies (no doubt with various CT values) on false positives seem to suggest a false positive rate of 1 to a few percent. I don't get the impression that the CT values used thus far (up to 40) commonly give false positives so much as they are more likely to detect early infection and recent recovery. True false positives seemed to be most commonly caused by contamination at various points in the testing process (contamination of reagents, contamination during collection, etc.)

"Review of external quality assessments revealed false positive rates of 0-16.7%, with an interquartile
range of 0.8-4.0%. Such rates would have large impacts on test data when prevalence is low. Inclusion of
such rates significantly alters four published analyses of population prevalence and asymptomatic ratio. "

"Using current data providing by the Public Health England (PHE) as of the most recent complete data, a false positive rate of 1.16% (95% CI 1.09 - 1.23%) was found for the PHE PCR test for the period 1 January through 29 March 2021."

The below article explains why different CT values are useful in different scenarios and what a positive result likely means at different CT values. It seems that it actually makes sense to test an asymptomatic person who has had the vaccine at a lower CT value just as it would make sense to test a symptomatic person at much higher values. But yes, you have to be very careful how you compare the results for the purposes of counting infections.

My point is measuring with different CT values is fine as long as the effects of different CT values are understood and taken into account when publishing results. I would think that would be obvious. On the other hand, if you are using results from different CT values and just taking the raw numbers without considering the effect of the different cycle counts, then yes, of course it would be misleading. I'm just saying it isn't automatically misleading. It depends on if and how they account for the difference when reporting the results. Scientific studies (which tend to be published as something a bit longer than a paragraph and include a lot of data you don't necessarily get unless you read the study itself) will probably take these things into account. They usually do. What the media reports and politicians say in their one sentence summaries of such reports may be a completely different story. Often "science" is blamed for being political when it isn't the science so much as how the results are selectively interpreted.

You seem to be suggesting that they shouldn't use different CT values in different circumstances but the above article explains why it is useful to do so. The fact of the matter is that it can make sense to test people at different CT levels based on their circumstances and the purpose of doing so isn't to nefariously make invalid comparisons though of course someone could do that.

Oh, and thank you for the replies. I am not trying to attack you. I truly appreciate civil dialog and discussion.

I'm the same way. It's nice to discuss/debate things without the conversation devolving into personal attacks which is what seems to happen most of the time.

I agree. If I feel like I am attacking you at any point I do apologize for that. I do try not to. I am human though and I do make mistakes.

I appreciate you taking the time to reply. I kind of think you are trying too hard to defend that which appears to be indefensible at the moment. I can understand the motivations of why you might want to.

It is scary. It also sucks to think the so-called "scientific" authorities may not be being particularly scientific. It is scary to think "science" as an institution may have been co-opted an hijacked by politics, and power brokers. The Scientific Method is a tool that doesn't change. However, people are not immune from human nature.

I don't like the fact I am talking about this. I also freely admit I do not trust any particularly large organizations at this point.

They all seem to be corrupted in varying degrees by money, and special interests as far as I can tell.

Will this flavor my articles? Certainly. It is my own bias.

Though I would love to see enough evidence to make me feel more trusting and less concerned. Instead I tend to keep finding more evidence to reinforce my current concerns.

The amount of cycles used seem to vary a great deal from what I've seen. Some places report the number of cycles they used. Some do not. They do seem to be higher than 30 and I've seen as high as 45.

As to the difference. I pretty much go off of what the guy who invented the PCR test stated.

Whether it is insignificant or not would also depend on the sample size.

Regardless it is relevant to the scientific method to be consistent. Opinion on insignificance is not part of the scientific method. It is something that corrupts it.

I did a quick search...

Here is one article.

They recommend up to 40 there... Though there is no STANDARD which is a big part of the problem.

CT is the number of cycles.

This PDF might be useful...


It is a rabbit hole. If you search on your own you'll likely find some useful info I don't know about.

Here is an interesting article:
Coronavirus: The Truth about PCR Test Kit from the Inventor and Other Experts – Video

I found another article that explains it pretty well:
Explained: What is the ‘Ct value’ in a Covid-19 test?

"What is the significance of the ICMR threshold of 35?

Globally, the accepted cut-off for Ct value for Covid-19 ranges between 35 and 40, depending on instructions from the respective manufacturers of testing equipment. The ICMR has arrived at the Ct value of 35 based on laboratory experiences and inputs taken from several virology labs."