How accurate are the covid tests?

One of the most frequent questions I’ve been getting recently is how accurate I think the covid tests are, and in particular the PCR tests. As it happens, a systematic review has recently been published in Evidence Based Medicine that looks at the covid tests (both PCR and antibody), so I thought it would be interesting to look in to the evidence together. This article gets a bit technical and math-heavy in places, so please bear with me. I think the payoff is worth it.

First, let’s make sense of what the two types of test are and how they work. The PCR (Polymerase Chain Reaction) test is designed to detect a specific sequence of nucleotides, and when it comes to detecting SARS-CoV-2, the sample is usually taken from the back of the throat. Nucleotides are the building blocks of genomes, and the idea is that if you can detect a string of nucleotides that is specific for a certain organism, then that proves the organism is present at the sample site. Since PCR is designed to detect bits of viral genome that are currently present in your respiratory tract, its purpose is to detect a currently active infection (as opposed to a past infection).

PCR works by repeating a series of chemical reactions over and over. If the sequence of nucleotides that is sought is present in the sample, then each time the reaction is repeated, the number of copies of the sequence will double, so that more and more copies accrue.

So, if you start of with one copy of the nucleotide sequence you are looking for, then after one cycle you will have two copies. After two cycles you will have four copies. After three cycles, you will have eight copies. After four cycles, you will have 16 copies. And so on. As you can see, the fact that each cycle doubles the number of copies means that the numbers quickly build to massive levels. The covid PCR tests frequently keep going up to 40 (or sometimes even 45) times.

If you start off with just one copy of the viral nucleotide sequence in the sample, then after 40 doublings, you will have over 1,000,000,000,000 copies (that’s one thousand billion copies). The reason you do this repeated cycle of doubling, is that once you get enough copies of the sequence you’re looking for, then you can use other technologies to detect it. For example, you can add molecules to the sample that visibly light up if enough copies of the sequence are present. So after enough copies are present in the sample, then they can be detected, and you get a positive result.

The number of times you choose to cycle through the steps of PCR before you decide that there was no virus in the sample after all is known as the cycle threshold. The number of cycles used to get a positve result is actually a pretty important number, because it tells you how much virus is in the sample. The lower the number of cycles required, the more virus is in the sample. The higher the number of cycles, the more likely that the result is a false positive, caused perhaps by having a tiny amount of inactive virus in the respiratory tract, or by contamination of the sample in the lab. Like I said, after 40 cycles, even a single copy of the viral sequence has become over one thousand billion copies.

One thing that’s important to understand at this point is that PCR is only detecting sequences of the viral genome, it is not able to detect whole viral particles, so it is not able to tell you whether what you are finding is live virus, or just non-infectious fragments of viral genome. If you get a positive PCR test and you want to be sure that what you’re finding is a true positive, then you have to perform a viral culture. What this means is that you take the sample, add it to respiratory cells in a petri dish, and see if you can get those cells to start producing new virus particles. If they do, then you know you have a true positive result. For this reason, viral culture is considered the “gold standard” method for diagnosis of viral infections. However, this method is rarely used in clinical practice, which means that in reality, a diagnosis is often made based entirely on the PCR test. A systematic review looking at the ability to culture live virus after a positive PCR test found that the probability of a false positive result increased hugely with each additional cycle after 24 cycles. After 35 cycles, none of the studies included in that review was able to culture any live virus.

In most clinical settings (including the one I work in), all the doctor is provided with is a positive or negative result. No mention is made of the number of cycles used to produce the positive result. This is a problem, since it’s clear that a positive result after 40 cycles is almost certainly a false positive, while a positive result after 20 cycles is most likely a true positive. Without information about the number of cycles, you have to assume that the patient sitting in front of you has covid and is infectious, with all the downstream consequences that entails.

Anyway, enough about the PCR test for now. The other main type of test is the antibody test. Here, the sample is usually taken from the blood stream. There are five different types of antibodies, but most antibody tests only look for one type of antibody, IgG, which is the most common type. Generally it takes a week or two after a person has been infected before they start to produce IgG, and with covid, you’re generally only infectious for about a week after you start to have symptoms, so antibody tests are not designed to find active infections. Instead the purpose is to see if you have had an infection in the past.

One common method that is used for antibody tests is ELISA (enzyme linked immunosorbent assay). In this method, you have a plate on which you’ve fixed antigen that the antibody you are looking for can bind to (antibodies bind to antigens – antigen is short for “antibody generator”, and it’s basically the molecular structure that a certain antibody is specifically designed to bind to).

You then add the blood sample that you want to study to the plate, at which point the antibodies in the sample will bind to the antigens (assuming the antibodies you want to find are actually present in the sample). After that you wash the plate, so that any other antibodies in the sample that you’re not actively looking for are washed off (since there’s no antigen for them to bind to).

Next you add a signaling molecule that can bind to antibodies, and which has the ability to change color when exposed to a certain enzyme. You then wash the plate again. If there are no antibodies stuck to the plate for this molecule to bind to, it will wash off. If the antibodies you are looking for were present in the blood sample, they will have stuck to the antigen on the plate, and this new molecule will in turn have stuck to them.

Finally you add an enzyme that changes the color of the signaling molecule. If the signaling molecule hasn’t been washed off in the previous step, then you will see the plate change color, and the antibody test is positive.

Apart from understanding how the tests work, we also need to understand two important terms before we get in to the details of the recent systematic review. Those terms are sensitivity and specificity, and they are critical for all diagnostic tests used in medicine, because they tell you how good a test is.

Sensitivity is the probability that a disease will be detected if the person actually has the disease. So, for example, a test for breast cancer with a sensitivity of 90% will detect breast cancer 90% of the time. Nine out of ten patients with breast cancer will correctly be told that they have the disease. One out of ten will incorrectly be told that they don’t have the disease, even though they do.

Specificity is the opposite of sensitivity. It is the probability that a person who doesn’t have the disease will be told that they don’t have the disease. So, a specificity of 90% for our imaginary breast cancer test means that nine out of ten people who don’t have breast cancer will be correctly told that they don’t have it. One out of ten people who don’t have breast cancer will incorrectly be told that they do have it.

To put it another way, sensitivity is the ability of a test to detect true positives. Specificity is the ability of a test to avoid producing false positives. A perfect test will have a sensitivity and specificity of 100%, which would mean that it catches everyone who has the disease, and doesn’t tell anyone they have the disease if they don’t. No such test exists. In general, sensitivity and specificity are in conflict with each other – if you push one up, the other will go down.

If I just told everyone I meet that they have breast cancer, my sensitivity for detecting breast cancer would be 100%, because I wouldn’t miss a single case, but my specificity would be 0%, because every single person who doesn’t have breast cancer would be told that they do. So, when designing a test, you have to decide if you’re going to maximize sensitivity or specificity. If you design a covid PCR test with a cycle threshold of 40, then you are going for maximal sensitivity – the probability of missing a case is minimized, but you’re going to get a lot more false positives than if you set the threshold at 30.

Ok, now that we know what a PCR test is and what an antibody test is, and understand sensitivity and specificity, we can move on to the recent systematic review. The review included 38 studies of PCR tests (and LAMP tests, an alternative technique that is similar to PCR). The overall sensitivity for PCR/LAMP was between 75% and 100% in the different studies, while the overall specificity was between 88% and 100% . 16 studies, with a total of 3,818 patients, were able to be pooled together to get a more accurate estimate of sensitivity. In the pooled analysis, sensitivity was determined to be 88% . It wasn’t possible to determine a pooled specificity value, since the studies included in the pooled analysis were all of people who were already known with complete certainty to be infected with covid.

The review included 25 studies of antibody tests, but only ten of these (with a total of 757 patients) provided enough data to allow sensitivity to be calculated. The sensitivity of the antibody tests varied from 18% to 96%. 12 studies provided enough information for specificity to be determined, and in these it varied from 89% to 96% .

Ok, it might be hard to understand what these numbers mean in practical terms, so we’re going to play around with them a bit in order to clarify this, and I’m going to focus on the PCR test in this final discussion, since that is what’s generating much of the hysteria around covid. As mentioned, the sensitivity of the PCR test seems to be around 88% . A good value for the specificity is harder to determine, but it’s somewhere between 88% and 100%, so if we assume a specificity of 94% (halfway between the two values) we’re probably not far off.

Let’s say the disease is spreading rampantly through the population, and one in ten people are infected at the same time. If we test 1,000 people at random, that will mean 100 of those people actually have covid, while 900 don’t. Of the 100 who have covid, the test will successfully pick up 88. Of the 900 who don’t have covid, the test will correctly tell 846 that they don’t have it, but it will also tell 54 healthy people that they do have covid. So, in total 142 people out of 1,000 are told that they have covid. Of those 142 people, 62% actually have the disease, and 38% don’t.

That’s not great. Four in ten people getting a positive test result don’t actually have covid, even in a situation where the disease is so common that 10% of people being tested really do have the disease.

Unfortunately, it gets worse. let’s assume the disease is starting to wane, and now only one in a hundred people being tested actually has covid. If we test 1,000 people, that will mean ten will really have covid, while 990 won’t. Of the ten who have covid, nine will be correctly told that they have it. Of the 990 who don’t have it, 931 will be correctly told that they don’t have it, while 59 will be incorrectly told that they do have the disease. So, in total, 68 people will be told that they have covid. But only 9 out of 68 will actually have the disease. To put it another way, in a situation where only 1% of the population being tested has the disease, 87% of positive results will be false positives.

There is another thing about this that I think is worth paying attention to. When one in ten people being tested has the disease, you get 142 positive results per 1000 people tested. But when one in a hundred has the disease, you get 68 positive results. So, even though the actual prevalence of the disease has decreased by a factor of ten, the prevalence of PCR positive results has only decreased by half. So if you’re only looking at PCR results, and consider that to be an accurate reflection of how prevalent the disease is in the population, then you will be fooled, because the disease will seem to be much more prevalent than it is.

Let’s do one final thought experiment to illustrate this. Say the disease is now very rare, and only one in a thousand tested people actually has covid. If you test 1,000 people, you will get back 61 positive results. Of those, one will be a true positive, and 60 will be false positives. So, even though the prevalence of true disease has again decreased by a factor of ten, the number of positive results has only decreased slightly, from 68 to 61 (of which 60 are false positives!). So by looking just at positive PCR tests, you can easily be convinced that the disease is continuing to be roughly as prevalent in the population, even as it goes from being present in one in a hundred people to only being present in one in a thousand. The rarer the disease becomes in reality, the less likely you are to notice any difference in the number of tests returning positive results.

I want to restate this again, in a slightly different way, to make sure the message sinks in. As the disease drops enormously, by a factor of 100, from affecting one in ten to one in a thousand tested people, there is little more than a halving in PCR positive results, from 142 to 61. So a huge reduction in real infections only causes a small reduction in PCR confirmed “cases”. In fact, the disease could vanish from the face of the Earth, and you would still be getting 60 positive results for every 1,000 tests carried out!

The same trend is seen even if the PCR test were to have a much better specificity than we are estimating here, of say 99% . Here’s a quick illustration, since I don’t want to tire you with too many more numbers. If one in ten has the disease and you test 1,000 people, you will get back 97 positive results, of which 88 will be true positives and 9 will be false positives. If one in 100 has the disease, you will get back 19 positive results, of which 9 will be true positives and ten will be false positives. If one in 1,000 has the disease, you will get back 12 positive results, of which 11 will be false positives.

So, even if the test has a very high specificity of 99%, when the virus stops being present at pandemic levels in the population and starts to decrease to more endemic levels, you quickly get to a point where most positive results are false positives, and where the disease seems to be much more prevalent than it really is.

As you can see, the less prevalent the disease is in reality, the more likely the test is to generate a false positive result, and the less useful the test is as a method for figuring out who actually has covid. And the less prevalent the disease is, the more prevalent it will seem to be in relation to reality. If decisions about covid continue to be made largely based on what PCR tests show, we might never be able to call off the pandemic!

And that, ladies and gentlemen, is why PCR positive cases are a very poor indicator of how prevalent covid is in the population, and why we should instead be basing decisions on the rates of hospitalization, ICU admission, and death. If we just look at the PCR tests, we will continue to believe that the disease is widespread in the population indefinitely, even as it becomes less and less common in reality. And that is assuming the rate of testing doesn’t increase. If we combine this built-in problem with accuracy, with a massive increase in testing (as has happened in most countries over the course of the pandemic), then we can create the impression of a disease that is continuing to spread wildly through a population, even when it isn’t.

You might also be interested in my article about how deadly covid actually is, or, if you want to dig further in to the problems created by testing, you might be interested in my article about breast cancer screening.

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Author: Sebastian Rushworth, M.D.

I am a practicing physician in Stockholm, Sweden. My main interests are evidence based medicine, medical ethics, and medical history. I frequently get asked questions by my patients about health, diet, exercise, supplements, and medications. The purpose of this blog is to try to understand what the science says and to translate it in to a format that non-scientists can understand.

83 thoughts on “How accurate are the covid tests?”

  1. Thank you Sebastian , this is invaluable and the best article on PCR for covid that has been written.
    Hopefully it will help more people understand the reality.
    Do you have any idea of the cycle threshold of PCR testing in various countries?
    I can’t find such information, even though it is crucial .

    1. Thanks Samuel,
      I’m not sure, but my guess would be that most countries do 40+ cycles. I know that’s the cases here in Sweden, and at present I only know of one hospital (Sahlgrenska in Gothenburg) where doctors are provided with the CT value along with the result.

  2. Shouldn’t the false positive rate be a function of the amount of virus in each of the swabs – the more there is, the more the chance of cross contamination and vice versa?

  3. Thank you for your explanation -the first time I’ve managed to grasp what a ‘false positive’ is and how it can corrupt the statistical evaluation of the real state of a population’s infection.

  4. These numbers ensure that we will always have enough ‘cases’ above the, then maybe not so arbitrarily chosen, threshold of 50/100.000 even if the disease was eradicated.
    Although the fact that we were often below that number during the summer suggests a better specificity- or how would you explain that?

    I just want to add that Germany’s Drosten test is based upon a ridiculously high 45 cycles, whilst Fauci himself has stated that anything beyond a 35ct is meaningless, see link, and that the more or less case-free NFL is using tests with a number of 30ct (link at jordan schachtel).

    In addition, I have read that instead of properly searching for 3 DNA snippets of the virus (whether the snippets are chosen properly in light of the virus seemingly not yet done proper isolation is a whole different story and can of worms) and adding a confirmation phase on top of the initial search phase, many if not most tests and labs these days search for only one, the E snippet, and omit that confirmation phase, leading to further inflated and completely false positive results.
    (I have also read that the choice of the primer can make a huge difference, but cannot evaluate that.)

    Prof. Hockertz has stated that in every other medical area but Covid, people who sell or performed such uncertified and non-standardized tests would immediately be jailed.

    That lack of standardization and certification alone renders the tests, testing and all comparisons and decisions based upon them and it completely obsolete and fraudulent, which is why Dr. Fuellmich is going to sue Drosten&co.

    I suppose, that standardization and certification will eventually come, at a low rate of say a 25ct, as this would be the best and easiest, if not even only, way to end the casedemic, and also, the best, if not even only, way to wrongly credit the vaccines for that eradication and termination and thereby make them, and the strategies chosen sofar, seem a success.

  5. In the UK its standard practice to test up to 40 or 45 cycles depending on your assay – we take anything at 37+ with a pinch of salt and usually repeat it on another assay with different target or methodology. In my lab we use a two target LDT PCR and we usually use a TMA assay or vice versa for any confirmation tests required.

  6. Thank you for walking the reader through the mathematics of testing. Astonishing how doctors are not being informed on the specific testing procedure (PCR CT value) although it makes such a big difference in the test’s validity to find active infections!
    The reporting of Covid “cases” all over the world, seen in the light of science, is pure scaremongering without further verification of actual infections. Even in “science-based Sweden”… I find this very irritating indeed, and hope that doctors like you will be listened to by the health authority!
    Thank you also for your article on how deadly Covid really is!

  7. this is absolutely excellent. It amazes me that when I first mentioned you to my Swedish wife she told me a few minutes later that you didn’t exist according to her internet sources!. Anyway my question is to do with Koch’s postulate and whether the virus has been isolated and whether it is now mutating and vulnerable to vaccines. Or should we abandon vaccination as an unnecessary goal in favour of therapeutics like HCQ, zinc and Azithromycin? thanks so much for all your hard work informing us of the science in this complex area.

    1. Haha, thanks Peter. It’s been at least a few months now since I received an e-mail from someone asking if I’m a real person and a real doctor, so I think a general acceptance that I am real has now been reached!

      Well, that’s a difficult question. We’ve known about the four ”common cold” coronaviruses for decades now, but no vaccine has yet been developed. At the same time, I doubt anyone has really tried.
      Coronaviruses don’t mutate very rapidly, so it should be possible to create a vaccine that is at least moderately effective.

  8. I agree with pcr not being reliable for an ongoing infection and that it is better to look at ICU admission etc but I think your exercise here is primarily a theoretical one. Meaning there is nothing that says the sensitivity or specificity scales equally at any given number of tests done. Testing is done at different places which cannot all scale up equally, contamination depends on the location where the sample is taken and studied and the infectivity of people in the surrounding. These all vary with time to make it more complex.

  9. Thanks for very clear explanations and great analysis. However, the positivity rates being reported (the faction of tests that come back positive) show that the estimate you are using for the specificity of PCR is much too low. Here in Massachusetts, the positivity rate for the two weeks Oct.11-24 was 1.55%. That means 98.45% of the people tested got a negative result. Even if all of those were false positives, that would imply a specificity of 98.45%. Since some of those tested were true positives, the actual specificity is higher than that. Furthermore, in the particular Massachusetts city I live in, the positivity rate was 0.36%, which implies a specificity of more than 99.64%. I have not looked at the particular studies you mentioned that claimed a lower specificity than that, but the tests here in Massachusetts have a much higher specificity. In those states that have a higher positivity rate than Massachusetts (which is most of them), we can be sure that most of the PCR positives are true positives.

    1. Thanks Irwin,
      That’s why I also included calculations based on a specificity of 99% .
      In that scenario, the numbers aren’t quite so bad, but you still quickly get to a point where most positives are false positives and where the disease seems more prevalent than it is. Do you know what cycle threshold is used in the city where you live?

  10. Once again, from the popular press- tabloid, broadsheet and news ‘magazines’, – not a column-centimetre of explanation / investigation into the Foundational Stone of the Narrative. Just regurgitation of fear, lies and manipulation.
    Thank you again for the clear simple & succinct illumination of dark deeds !!!

  11. More like the Pure Gold value of PCR. – It can make ‘something’ out of ‘nothing’ so no further lies required 😉

  12. That’s a very good explanation. Thanks!

    I want to add that on the ground at least here in Malaysia, multiple PCR tests are conducted over an extended period of time to rule out false results.
    A person is not considered Covid19 positive until all tests are out to rule out false positive or negative results.

    I expect similar practice in most other places

  13. Australia now has very low positive test numbers following a much smaller “wave” than affected US and Europe – suggests our specificity is within a bees whisker of 100% rather 94%. (my lab quotes 100% fwiw) Good explanation of the complexities of medical test interpretation though – Thankyou.

  14. Thank you. Since asking the question, I have found an official Australian government document that states that over a CT of 24 the virus is not recoverable. That indicates that Australian testing is very highly specific, which explains our very low case numbers.
    Those countries doing a CT of 40 really need to get properly educated !

  15. Sebastian on Thursday Friday in Australia, the state of NSW conducted a total of about 35,000 tests.
    Results were about eight new infections. Our figures don’t seem to match your predictions. Care to comment?

  16. Agree. But most patients do get tested within a week of having symptoms and so epidemiologically it gives some idea of prevalence of infection. I think everyone is looking at all parameters and the social behaviour dynamics of each society and their vulnerability to serious covid is worth looking at too

  17. Hi Sebastian,

    nice work. It is always a pleasure to read your blog.

    Regarding PCR tests and specificity: Does this systematic review show sth. like the difference between theory and practice?

    Following the evidence distributed by the RKI in the media (at least in germany) anyone who doubts that the specificity is below 99,X % is “naive” (twitter speak: “stupid as hell”).
    The claim is that the current PCR tests are testing for at least two primers and therefore one single pcr test has (nearly) the accuary of two independent PCR tests. This mostly ends up in a specificity of about 99,X %.

    Any thoughts on this?

    Best Regards

  18. “…why we should instead be basing decisions on the rates of hospitalization, ICU admission, and death….”
    That would be a good idea, but how do we know if they dont use the same PCR tests and get the same results ? As far as i know the people in icu in the hospital near where i live are tested with the PCR test no matter if they have symptoms or not.

    Thanks for your great article and explanations.

  19. Yet another excellent article. Thank you so much for your good and valuable work.

    I wanted to share this information from Iceland, that people might be interested in. You can see the number of tests done per day at the border, as well as the number of positive test results. It’s interesting to see that they were often running over 1000 tests with zero positive test results, suggesting that the specificity is very high (possibly 99.9% if you look at a few days of border screening). The data has been reported daily since August. There were also tests done domestically, but these tests were mostly on symptomatic people or those who had been exposed to positively diagnosed individuals, which I imagine would reduce the false positives / (true positives + false positives) ratio.

    From what I can gather, here in Iceland we use so-called RT-PCR tests that use RNA as template rather than double-stranded DNA used by PCR. I haven’t studied the differences in detail, but I will also link to a study that compares them. I think that most countries are not using RT-PCR.

    PCR vs RT-PCR:,as%20enzymes%20in%20RT%2DPCR.&text=PCR%3A%20Forward%20and%20reverse%20primers%20are%20used%20in%20the%20PCR.

    1. Hi Erling,
      When I write PCR, I mean RT-PCR. All PCR tests for covid use RT-PCR, because covid is an RNA virus. It’s genome is coded in RNA, not DNA, so regular PCR isn’t possible. Do you know what CT they were using for border screening?

  20. Wow. Thank you for methodically walking the reader through this. The PCR information is especially helpful. I have a much better understanding now.
    Question: Given that the European Union (and many other nations) showed test positivity rates at or below 2% or 3% for much of last spring (May-July, for instance) would it be fair to assume the the actual PCR specificity is perhaps just a bit higher than your (suggested) 94%? If your assumption of 94% was correct, then we would never see positivity rates below 6%. Is my thinking on this correct? Thank you again.

    1. Hi John,
      Yes, that is correct. The real world testing in parts of the world suggests a better specificity than has been found in the studies. It is strange, and I don’t know why that appears to be the case. That’s why I also included calculations based on 99% specificity.

  21. Dear Dr Samuel Zagarella
    ” I have found an official Australian government document that states that over a CT of 24 the virus is not recoverable.” Would you be able to share the reference please? That is very valuable.

  22. Thanks, Sebastian. It is very simple to understand because of your effort to explain something complex in a simple way. It amazes me that the test result is so confused with the diagnosis of the disease. The bottom line is that we are experiencing a CRP pandemic.

  23. Sebastian
    Going of what you have written it seems reasonable to think that many are using a lower CT cycle number , Yes? Also my understanding is that in New Zealand anybody who tests positive is tested again and if that second test is negative a third test is done , which would tend to reduce false alarms.

  24. I’m wondering if the extremely sharp rise in infections across Europe is brought about by the onset of the fall/winter rise seasonal viruses and everyone with any symptoms is rushing to get tested – this may mean that many more folks with nearly asymptomatic infections are being tested. This may mean our testing is more efficient and closer to seeing the true prevalence as well as being buoyed by the seasonality of corona viruses. One thing that is interesting is the rise of deaths from the virus at rates that seem steeper than cases and with much shorter delays between cases and deaths – a new strain circulating or lack of care in overwhelmed health systems or poor statistics?

  25. It’s the link I shared above, and specifically the reference I was referring to from that article was this one:
    Bullard J, Dust K, Funk D, Strong J, Alexander D et al. Predicting infectious SARS-CoV-2 from diagnostic samples,
    Clinical Infectious Diseases, ciaa638, (accessed 18 June 2020

  26. Thanks Sebastian for another brilliant article.

    ”For SARS-COV-2 there is no technical specification developed” (for the PCR-test), that is a direct quote from FHM’s home page. FHM go on to state that this is according to the policy of EU Kommissions, and thus the same in all EU countries. Further down in the text it says that instead of a technical specification for SARS-COV-2, one can use samples from other deseases and modify them (whatever that means).

    That sounds a lot like what I heard from other sources, that there is still no Koch’s Postulates for Covid-19. So the question becomes, how do we then know that this present increase in the ”Cases”, are not the ordinary Cold and Flu virus, which always increases in the Autumn? Especially since all the usual statistics from the Cold and Flu has disappeared, it’s gone, now everything is ”Covid Cases”, or more accurate ”Covid-19 m.m”.

  27. If I understand it correctly, a prevalence of a RNA fragment which then is used and enhanced in a PCR test, does NOT mean that you’re sick or even infected, it only means that you had a RNA virus (dead or alive) in your throat. So, if your immune system works perfectly well and kill, or going to kill the virus, it might still show up as positive in the PCR test, depending upon how many cykles has been used, which then makes the question about how many cycles are really used, very interesting and very important.

    A research study made in England May 2020 shows in ”Table 2” a graph, where on the Y-axis you have ”Culture-Positive” (gold standard from the lab), and on the X-axis you have Ct-value (or cycles). If you then look at 35 cycles on the X-axis, then go to the PCR reference line, proceed to the left and you get about 10% Culture-Positive on the Y-axis, which gives about 90% false positives. I understand that there is more things considered in real life, but it’s strange that in Sweden we use 45 cycles as standard, why?
    If 24 cycles should be the top for accurate tests, why use anything above?

  28. Madrid sees a relaxation at the moment – is it to do with changed testing strategy?–miracle–was-created-in-madrid–antigen-testing–restrictions-and-%22individual-responsibility%22.ByGEh7yHYv.html
    I wonder if antigen testing used perhaps in conjuncture with PCR, to establish whether an active infection is going on AND whether it’s due to SARS-CoV-2, would lead to more reliable results?

  29. I see. Thank you for explaining that to me.
    Sadly, no, I don’t know what CT they were using. If I ever find out, I’ll be sure to let you know.
    Unrelated, but not complete. I know they were taking samples from both the throat and nose. I hear that can lead to more accurate results than taking only one of those. Not sure if they then mix the samples or run two tests, one for each.

  30. Hi,
    can you find out when the infection was based on the results?
    How many cycles do you need to say 1, 3 or 5 months ago the person was infected?

    1. Hi Holger,
      The answer is both yes and no. If you have 20 cycles or less, you most likely have a currently active infection. If you have 35 cycles or more, you could either have an infection that is ramping up or an infection that is in the past. Some people continue to be PCR positive for weeks or even months after infection, but in these situations the number of cycles is invariably high.

  31. Reporting of deaths is based on ‘deaths within 28 days of a positive COVID test’, so if the test results are inflated, won’t the death stats be inflated as well? So how can we find out what is really happening?

    1. I’d like to know that too. I haven’t seen the Swedish data, but I have seen the UK data, and they are in line with how they normally are this time of year. Covid is not currently putting any extra stress on the system in the UK beyond what would normally be seen in the autumn respiratory virus season.

  32. Multiple people have argued that specificity is a lot higher than your article assumes, and I can add another data point: in Italy this summer the number of positive results went below 0.5%, indicating that specificity was higher than 99.5%. You article spends a lot of time on a hypothetical case of 94%, and then a brief paragraph with a “very high specificity of 99%”, which is instead too low. As a consequence, it gives the reader a really misleading impression of what’s going on.

    Maybe you could post an update using a lower bound of 99.5%? Numbers will come out quite differently.

    1. The 94% is based on the average from the study discussed. A separate review found an average specificity of 96% . I can’t explain why the real world numbers don’t match the studies, normally real world results are worse than studies, not better. Even with a specificity of 99,5% you will quickly get a high proportion of false positives as the disease becomes rarer or you test people in which the probability of having covid is low.

  33. Hey, very cool article! I was also trying to take a closer look to the PCR technique, but I stumbled across one thing I still wasn’t able to figure out myself. Perhaps I can find an answer to my question here.

    The traditional PCR technique (as far as I understand) is based on a fixed number of cycles before an analysis is performed with so-called gel electrophoresis. To my understanding in addition to a fluorescent signal also the _weight/length_ of the amplificates is an observable to check whether the correct sequence was amplified. This was done by comparing the way length in the gel to some reference ladder, where the travelled distance is somewhat anti-proportional to the weight.

    Taking a comparative look to the real-time qPCR I didn’t find the information yet whether or not (besides the, again, fluorescent signal) this weight/length is also measured there. If not, then the specificity should even be worse in the qPCR. Does anybody know this?

    Thanks for any reply! 🙂

  34. As far as I know, in Italy a standard of 20-24 test cycles was used in Summer, it was later switched to 45 in late September. These numbers are not official. Some say the standard is now 34, others that it is 50. Unfortunately, nobody seems to know what is being done in the labs. In any case, the difference in the number of cycles may explain why some testing campaigns in Italy reported zero positives this summer. But things seem to have changed in a way that makes Sebastian’s calculations close to reality

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