• Corona Update 24, Mathematical proof self-tests are only 3% correct, 97

    From skybuck2000@21:1/5 to All on Thu Feb 17 11:39:47 2022
    Corona Update 24, Mathematical proof self-tests are only 3% correct, 97% false positives !

    3% of the corona/covid 19 self-tests are correct, 97% are false positives !

    The mathematical proof has been delivered (using Bayes' theorem):

    Roche's corona self-test has a sensitivity of 96.52% and a specificity of 99.68%.

    If "C19" stands for the presence of the disease COVID-19 ("corona") and
    + and − respectively for a positive and negative result of the test, this means:

    sensitivity: P( + | C19 ): 0.9652

    specificity: P( - | not C19): 0.9968

    That seems very high. But if the prevalence is only 1 in 10,000, i.e

    prevalence: P( C19 ): 0.0001

    This implies:

    P( + ) = P( + | C19 ) P( C19 ) + P( + | not C19 ) P ( not C19 ) =

    = 0.9652 x 0.0001 + 0.0032 x 0.9999 = 0.0033

    and

    P( C19 | + ) = ( P( + | C19 ) P( C19 ) ) / P( + ) =

    = ( 0.9652 x 0.0001 ) / 0.0033 = 0.03


    If 10,000 people are tested with this test, including probably 1 infected person,
    then the infected person will almost certainly get a positive result.
    But of the 9,999 uninfected people, 32 will get a false positive result.
    The 9967 people with a negative result are almost certain that they are not infected.
    But of the 33 with a positive result, only 1 is infected,
    only it is unknown who that is.
    So the chance that an individual is actually infected after a positive result is only slightly more than 3% in this scenario.
    This self-test is therefore of little use to determine whether you are infected with corona,
    unless the prevalence is around 1% or higher.

    (This information has been known and published since 20 june 2021 !)

    Bye,
    Skybuck ! =D

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  • From Martin Brown@21:1/5 to All on Thu Feb 17 22:39:07 2022
    On 17/02/2022 19:39, skybuck2000 wrote:
    Corona Update 24, Mathematical proof self-tests are only 3% correct, 97% false positives !

    Deliberately misleading tosh based on a false assumption.

    3% of the corona/covid 19 self-tests are correct, 97% are false positives !

    The mathematical proof has been delivered (using Bayes' theorem):

    Roche's corona self-test has a sensitivity of 96.52% and a specificity of 99.68%.

    If "C19" stands for the presence of the disease COVID-19 ("corona") and
    + and − respectively for a positive and negative result of the test, this means:

    sensitivity: P( + | C19 ): 0.9652

    specificity: P( - | not C19): 0.9968

    That seems very high. But if the prevalence is only 1 in 10,000, i.e

    prevalence: P( C19 ): 0.0001

    That is a *VERY* big if though.

    Right now in the UK Covid prevalence is 0.05, 5% or 1 in 20.

    https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/conditionsanddiseases/bulletins/coronaviruscovid19infectionsurveypilot/16february2022

    It will be a very long while before the Covid prevalence here is
    anything like 1:10000. It would be nice just to get it under 1%.

    IOW in a room with 14 people in it there is a 50:50 chance that at least
    one of them has Covid-19. False positives are irrelevant at the moment.
    It is an even worse 1 in 13 in Northern Ireland for some reason.

    False negatives are far more dangerous when they are being misused as a permission to do something. Testing misses about 20% of real positives.

    --
    Regards,
    Martin Brown

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  • From Rick C@21:1/5 to All on Thu Feb 17 15:21:54 2022
    On Thursday, February 17, 2022 at 2:39:59 PM UTC-5, skybuck2000 wrote:
    Corona Update 24, Mathematical proof self-tests are only 3% correct, 97% false positives !

    3% of the corona/covid 19 self-tests are correct, 97% are false positives !

    The mathematical proof has been delivered (using Bayes' theorem):

    Roche's corona self-test has a sensitivity of 96.52% and a specificity of 99.68%.

    If "C19" stands for the presence of the disease COVID-19 ("corona") and
    + and − respectively for a positive and negative result of the test, this means:

    sensitivity: P( + | C19 ): 0.9652

    specificity: P( - | not C19): 0.9968

    That seems very high. But if the prevalence is only 1 in 10,000, i.e

    prevalence: P( C19 ): 0.0001

    This implies:

    P( + ) = P( + | C19 ) P( C19 ) + P( + | not C19 ) P ( not C19 ) =

    = 0.9652 x 0.0001 + 0.0032 x 0.9999 = 0.0033

    and

    P( C19 | + ) = ( P( + | C19 ) P( C19 ) ) / P( + ) =

    = ( 0.9652 x 0.0001 ) / 0.0033 = 0.03


    If 10,000 people are tested with this test, including probably 1 infected person,
    then the infected person will almost certainly get a positive result.
    But of the 9,999 uninfected people, 32 will get a false positive result.
    The 9967 people with a negative result are almost certain that they are not infected.
    But of the 33 with a positive result, only 1 is infected,
    only it is unknown who that is.
    So the chance that an individual is actually infected after a positive result
    is only slightly more than 3% in this scenario.
    This self-test is therefore of little use to determine whether you are infected with corona,
    unless the prevalence is around 1% or higher.

    (This information has been known and published since 20 june 2021 !)


    This sounds serious. Maybe you should tell someone about it?

    --

    Rick C.

    + Get 1,000 miles of free Supercharging
    + Tesla referral code - https://ts.la/richard11209

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  • From Robert Latest@21:1/5 to Rick C on Fri Feb 18 07:26:54 2022
    Rick C wrote:
    (This information has been known and published since 20 june 2021 !)


    This sounds serious. Maybe you should tell someone about it?

    It is serious. Looks like the whole Covid scare was started by experts who didn't do their homework on test sensitivity and specificity. This is amazing! A major scientific breakthrough coming from no less than sci.electronics.design! Sometimes it takes a view from the outside to see what's really going on. Maybe moden consumer electronics wouldn't be so crappy if we had more epidemeologists in its design.

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  • From David Brown@21:1/5 to Martin Brown on Fri Feb 18 09:40:42 2022
    On 17/02/2022 23:39, Martin Brown wrote:
    On 17/02/2022 19:39, skybuck2000 wrote:
    Corona Update 24, Mathematical proof self-tests are only 3% correct,
    97% false positives !

    Deliberately misleading tosh based on a false assumption.

    3% of the corona/covid 19 self-tests are correct, 97% are false
    positives !

    The mathematical proof has been delivered (using Bayes' theorem):

    Roche's corona self-test has a sensitivity of 96.52% and a specificity
    of 99.68%.

    If "C19" stands for the presence of the disease COVID-19 ("corona") and
    + and − respectively for a positive and negative result of the test,
    this means:

    sensitivity: P( + | C19 ): 0.9652

    specificity: P( - | not C19): 0.9968

    That seems very high. But if the prevalence is only 1 in 10,000, i.e

    prevalence: P( C19 ): 0.0001

    That is a *VERY* big if though.

    Right now in the UK Covid prevalence is 0.05, 5% or 1 in 20.

    https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/conditionsanddiseases/bulletins/coronaviruscovid19infectionsurveypilot/16february2022


    It will be a very long while before the Covid prevalence here is
    anything like 1:10000. It would be nice just to get it under 1%.

    IOW in a room with 14 people in it there is a 50:50 chance that at least
    one of them has Covid-19. False positives are irrelevant at the moment.
    It is an even worse 1 in 13 in Northern Ireland for some reason.

    False negatives are far more dangerous when they are being misused as a permission to do something. Testing misses about 20% of real positives.


    The relevant number is not the prevalence of Covid in the population at
    large, but the prevalence of Covid amongst people taking a self-test.
    Since self-tests are usually taken by people with symptoms, or people
    with very close contact to people who have Covid, the number is not
    going to be 1 in 20 but more like 1 in 3 or 4.

    --- SoupGate-Win32 v1.05
    * Origin: fsxNet Usenet Gateway (21:1/5)
  • From Martin Brown@21:1/5 to David Brown on Fri Feb 18 09:42:55 2022
    On 18/02/2022 08:40, David Brown wrote:
    On 17/02/2022 23:39, Martin Brown wrote:
    On 17/02/2022 19:39, skybuck2000 wrote:
    Corona Update 24, Mathematical proof self-tests are only 3% correct,
    97% false positives !

    Deliberately misleading tosh based on a false assumption.

    3% of the corona/covid 19 self-tests are correct, 97% are false
    positives !

    The mathematical proof has been delivered (using Bayes' theorem):

    Roche's corona self-test has a sensitivity of 96.52% and a specificity
    of 99.68%.

    If "C19" stands for the presence of the disease COVID-19 ("corona") and
    + and − respectively for a positive and negative result of the test,
    this means:

    sensitivity: P( + | C19 ): 0.9652

    specificity: P( - | not C19): 0.9968

    That seems very high. But if the prevalence is only 1 in 10,000, i.e

    prevalence: P( C19 ): 0.0001

    That is a *VERY* big if though.

    Right now in the UK Covid prevalence is 0.05, 5% or 1 in 20.

    https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/conditionsanddiseases/bulletins/coronaviruscovid19infectionsurveypilot/16february2022


    It will be a very long while before the Covid prevalence here is
    anything like 1:10000. It would be nice just to get it under 1%.

    IOW in a room with 14 people in it there is a 50:50 chance that at least
    one of them has Covid-19. False positives are irrelevant at the moment.
    It is an even worse 1 in 13 in Northern Ireland for some reason.

    False negatives are far more dangerous when they are being misused as a
    permission to do something. Testing misses about 20% of real positives.


    The relevant number is not the prevalence of Covid in the population at large, but the prevalence of Covid amongst people taking a self-test.
    Since self-tests are usually taken by people with symptoms, or people
    with very close contact to people who have Covid, the number is not
    going to be 1 in 20 but more like 1 in 3 or 4.

    The UK publishes those figures too and they are very age dependent.

    Quoting a paragraph from the source I referenced above:

    "In England, the percentage of people testing positive for COVID-19
    varied substantially across age groups, with the highest for those aged
    2 years to school Year 6 at 7.60% (95% confidence interval: 6.89% to
    8.35%) and lowest for those aged 70 years and over at 2.23% (95%
    confidence interval: 2.03% to 2.45%), in the week ending 12 February 2022."

    School age children it is 7+/-2%.
    Over 70's it is 2.2 +/- 0.2%

    UK is doing quite a lot of population testing. There are quite a few
    other infections that give Covid like symptoms this time of year!

    The numbers I quoted are from the population survey which does a 100k
    samples from apparently healthy people chosen at random. It does have a
    couple of notable biasses - downwards in that someone with Covid who
    doesn't want the hassle of self isolating will not bother to return it
    and upwards in that it detects shedding viral DNA which continues for a
    while afterwards. Week on week it is a clear comparable measure though.

    Worried well hypochondriacs seem to be burning up LF tests on a near
    daily basis and they have a roughly 0.1% chance of a false positive. I
    have been randomly sampled by REACT a couple of times and taken a test
    in anger once, my wife twice after being pinged by the tracing app. They
    go short supply from time to time especially when Covid levels are so
    high. Many people have switched off their tracing app and UK so-called
    Test and Trace has been a complete disaster from the very beginning.

    Apply them to a few million people when the Covid rate is actually low
    and you do get a serious fraction of false positive with nuisance value.
    In the past the rule was LF positive then do a "definitive" PCR test but
    that has been scrapped. Give it a week now and you won't even be legally obliged to self isolate after a positive Covid test(madness).

    Part of the save The Boris distraction scam.

    --
    Regards,
    Martin Brown

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  • From David Brown@21:1/5 to Martin Brown on Fri Feb 18 14:06:36 2022
    On 18/02/2022 10:42, Martin Brown wrote:
    On 18/02/2022 08:40, David Brown wrote:
    On 17/02/2022 23:39, Martin Brown wrote:
    On 17/02/2022 19:39, skybuck2000 wrote:
    Corona Update 24, Mathematical proof self-tests are only 3% correct,
    97% false positives !

    Deliberately misleading tosh based on a false assumption.

    3% of the corona/covid 19 self-tests are correct, 97% are false
    positives !

    The mathematical proof has been delivered (using Bayes' theorem):

    Roche's corona self-test has a sensitivity of 96.52% and a specificity >>>> of 99.68%.

    If "C19" stands for the presence of the disease COVID-19 ("corona") and >>>> + and − respectively for a positive and negative result of the test, >>>> this means:

    sensitivity: P( + | C19 ): 0.9652

    specificity: P( - | not C19): 0.9968

    That seems very high. But if the prevalence is only 1 in 10,000, i.e

    prevalence: P( C19 ): 0.0001

    That is a *VERY* big if though.

    Right now in the UK Covid prevalence is 0.05, 5% or 1 in 20.

    https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/conditionsanddiseases/bulletins/coronaviruscovid19infectionsurveypilot/16february2022



    It will be a very long while before the Covid prevalence here is
    anything like 1:10000. It would be nice just to get it under 1%.

    IOW in a room with 14 people in it there is a 50:50 chance that at least >>> one of them has Covid-19. False positives are irrelevant at the moment.
    It is an even worse 1 in 13 in Northern Ireland for some reason.

    False negatives are far more dangerous when they are being misused as a
    permission to do something. Testing misses about 20% of real positives.


    The relevant number is not the prevalence of Covid in the population at
    large, but the prevalence of Covid amongst people taking a self-test.
    Since self-tests are usually taken by people with symptoms, or people
    with very close contact to people who have Covid, the number is not
    going to be 1 in 20 but more like 1 in 3 or 4.

    The UK publishes those figures too and they are very age dependent.

    Quoting a paragraph from the source I referenced above:

    "In England, the percentage of people testing positive for COVID-19
    varied substantially across age groups, with the highest for those aged
    2 years to school Year 6 at 7.60% (95% confidence interval: 6.89% to
    8.35%) and lowest for those aged 70 years and over at 2.23% (95%
    confidence interval: 2.03% to 2.45%), in the week ending 12 February 2022."

    School age children it is 7+/-2%.
    Over 70's it is 2.2 +/- 0.2%

    UK is doing quite a lot of population testing. There are quite a few
    other infections that give Covid like symptoms this time of year!


    Fair enough. Here in Norway we've moved away from mass self-testing.
    People are mostly testing to confirm suspected Covid.

    The numbers I quoted are from the population survey which does a 100k
    samples from apparently healthy people chosen at random. It does have a couple of notable biasses - downwards in that someone with Covid who
    doesn't want the hassle of self isolating will not bother to return it
    and upwards in that it detects shedding viral DNA which continues for a
    while afterwards. Week on week it is a clear comparable measure though.

    Worried well hypochondriacs seem to be burning up LF tests on a near
    daily basis and they have a roughly 0.1% chance of a false positive. I
    have been randomly sampled by REACT a couple of times and taken a test
    in anger once, my wife twice after being pinged by the tracing app. They
    go short supply from time to time especially when Covid levels are so
    high. Many people have switched off their tracing app and UK so-called
    Test and Trace has been a complete disaster from the very beginning.

    I wonder whether the false positive risk is per person, or per test? By
    that I mean, are the false positives caused by long-term effects so that
    0.1% of people will usually test false positive, or are they short-term
    so that for any given person, 0.1% of their tests will be false positive?


    Apply them to a few million people when the Covid rate is actually low
    and you do get a serious fraction of false positive with nuisance value.
    In the past the rule was LF positive then do a "definitive" PCR test but
    that has been scrapped. Give it a week now and you won't even be legally obliged to self isolate after a positive Covid test(madness).


    We no longer have to confirm with a PCR test if you have had three
    vaccines and test positive on a self-test. Maybe the false-positive
    rate is lower amongst the fully vaccinated (I haven't seen statistics on
    that or thought much about how it could apply).

    I got Covid a couple of weeks ago. There was not much doubt - I had
    symptoms (mild, but definite), a very clear self-test, and someone I'd
    been training judo with a few days earlier had got it.

    A lot of people are finding it odd that we are opening up and isolating
    less despite rising case numbers. But I think we are at the stage where there's little that can be done to limit the spread.

    Part of the save The Boris distraction scam.


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