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  1. #1376
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    Quote Originally Posted by old goat View Post
    your math is correct
    Unpossible. This is TGR.


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  2. #1377
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    Quote Originally Posted by cmsummit View Post
    Clinically speaking this is true. However, one should be more suspicious of COVID if also experiencing complete loss of taste and/or smell. That seems to be a somewhat unique symptom to COVID and was the symptom (in addition to the flu-like symptoms) that made me highly suspicious I had it. Back in March the CDC hadn't yet recognized anosmia and ageusia as a COVID symptom, but now they do.

    I'm quite certain my daughter had COVID during the same time frame that I did, but her only symptom was loss of smell for ~8 days.
    I was responding to skizix, who did not mention loss of taste or smell. I don't doubt you had it--you had a positive antibody test as well. Skizix has decided not to get one.

  3. #1378
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    From my test on Tuesday:

    Your SARS-CoV-2 (Coronavirus) antibody test returned POSITIVE -- suggesting that you have been exposed to the virus and your body made antibodies (99.6% specificity).

  4. #1379
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    Quote Originally Posted by old goat View Post
    As far as the value of the test--while your math is correct--with a 1% prevalence of Covid and a 1% false positive rate half the positives will be false--for an individual a positive is still 99% likely to be true.
    How can it possibly be, that half the positives will be false, but for an individual it's 99% not false? If half the overall positives are false, then it's 50% for an individual. Am I missing something there? Makes no sense otherwise.

    And BTW I am definitely not assuming I've had covid19, and am still taking all recommended precautions, for myself and others. Oviously yes, it could have been whatever flu, etc. It just felt different from anything else I've ever had, especially the cough (and severe cough with pain at the sternum, or "chest tightness" is often emphasized w/ covid symptoms).

  5. #1380
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    Quote Originally Posted by MakersTeleMark View Post
    From my test on Tuesday:

    Your SARS-CoV-2 (Coronavirus) antibody test returned POSITIVE -- suggesting that you have been exposed to the virus and your body made antibodies (99.6% specificity).
    2 of us from early hot spots.....SHOCKING!
    Old's Cool.

  6. #1381
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    Quote Originally Posted by cmsummit View Post
    2 of us from early hot spots.....SHOCKING!
    UNPOSSIBLE, right?

    The peak of my feel like death symptoms was February 26th.

  7. #1382
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    How bad was it?

  8. #1383
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    Quote Originally Posted by new yabyum View Post
    How bad was it?
    I wrote a pretty detailed writeup in the main thread. Search for my username.

    The test was a regular blood draw. Got pricked on Tuesday at 4, results came back at 8 am today. I was impressed.

  9. #1384
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    Silverton/SJ country Sherriff still fighting the fight!
    https://durangoherald.com/articles/324443

    Now that we see that infections were coming FROM mountains rather than from the city, we can ask:

    Why werenít mountain locals locked down and not allowed to access trailheads? Itís obvious that LOCALS are where the SAR were much more likely to catch this from, not from the front range ski tourers.




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    Quote Originally Posted by Benny Profane View Post
    Keystone is fucking lame. But, deadly.

  10. #1385
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    Quote Originally Posted by skizix View Post
    How can it possibly be, that half the positives will be false, but for an individual it's 99% not false? If half the overall positives are false, then it's 50% for an individual. Am I missing something there? Makes no sense otherwise.

    And BTW I am definitely not assuming I've had covid19, and am still taking all recommended precautions, for myself and others. Oviously yes, it could have been whatever flu, etc. It just felt different from anything else I've ever had, especially the cough (and severe cough with pain at the sternum, or "chest tightness" is often emphasized w/ covid symptoms).
    The test is 99% specific, which means the same as 1% false positive rate.. That means if you have the test and it's positive there's a 99% chance that it's a true positive. That's a completely separate issue than the number of tests in a population that are true vs false positives. With 1% infected and a 1% false positive rate half the positives will be false as we said before. If everyone is infected than all the positives will be true. If the infected rate is in between the percentage of true vs false positives will be higher the higher the infected rate is. But none of that affects the accuracy of the test for an individual--still a 1% chance the positive is true. That's because the accuracy of the result for an individual doesn't depend on how many others are infected.

  11. #1386
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    Quote Originally Posted by Kinnikinnick View Post
    Silverton/SJ country Sherriff still fighting the fight!
    https://durangoherald.com/articles/324443

    Now that we see that infections were coming FROM mountains rather than from the city, we can ask:

    Why weren’t mountain locals locked down and not allowed to access trailheads? It’s obvious that LOCALS are where the SAR were much more likely to catch this from, not from the front range ski tourers.
    sounds like you should stay the fuck out of the mountains then. No one here wants you to get sick.

    Also, do you even ski bro? cause i'm not seeing that you've ever posted stoke or any evidence that you ski.

  12. #1387
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    Quote Originally Posted by brutah View Post
    sounds like you should stay the fuck out of the mountains then. No one here wants you to get sick.

    Also, do you even ski bro? cause i'm not seeing that you've ever posted stoke or any evidence that you ski.
    If he hadn't got cheated out of his spring days, like bunny did as well, the stoke would have flowed.
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  13. #1388
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    Flowed like wine, where beautiful women instinctively flock like the†salmon of Capistrano.
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  14. #1389
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    The Ethics of Outdorr Recreation in Times of COVID-19

    My friendís employee got COVID in mid-March in NYC (she did test positive), infected a few of the other people at the firm, including my friend, who had flu symptoms but not horrible like many. He has had two recent antibody tests come back negative.

  15. #1390
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    Quote Originally Posted by skizix View Post
    How can it possibly be, that half the positives will be false, but for an individual it's 99% not false? If half the overall positives are false, then it's 50% for an individual. Am I missing something there? Makes no sense otherwise.
    oldgoat covered this, but yes, this is a well known statistical thing that people intuitively get wrong. Suppose the test is 99% accurate (1% false positive), but the condition is rare. Suppose that say 1 in 1000 people has it, like a gene that causes a rare birth defect. We test 1000 people. 1 of them really has it and their test is positive. Of the 999 people that don't have it, 1% get a false positive, meaning 10 people get a false positive. So out of the 11 positives, only one was real.

    For a disease like COVID where the true infection rate might be a few percent, the error is less severe, but it still could cause errors like a factor of 2. Thisis one reason to be cautious when you read an article that says "tests show large fraction of people in LA County [or any other place] already exposed." It is harder to interpret those without a very good knowledge of the false positive rate of the test.

  16. #1391
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    Quote Originally Posted by brutah View Post
    sounds like you should stay the fuck out of the mountains then. No one here wants you to get sick.

    Also, do you even ski bro? cause i'm not seeing that you've ever posted stoke or any evidence that you ski.
    Only 50-60 days a year.

    Ive been posting in the colorado weather and conditions threads for years. How about you?



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    Quote Originally Posted by Benny Profane View Post
    Keystone is fucking lame. But, deadly.

  17. #1392
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    Quote Originally Posted by Kinnikinnick View Post
    Only 50-60 days a year.

    Ive been posting in the colorado weather and conditions threads for years. How about you?
    sure do, and I've skied with plenty of mags. My stoke is easy to find. yours not so much,.

    All your posts look like whining when I search for your forum posts. But congrats on starting the most toxic thread on this site (ie, the Caroline Gleich Harrassment thread), but I guess toxicity is your specialty?

    So put up or shut up.

  18. #1393
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    your not sposed to virtue signal your a stoke filled outdoor rec enthusiast any mur
    it makes the participation trophy poli poster losers sad
    and while we dont always agree
    you know ill mount yur skis and share turns
    im pretty sure the reason why the bbi never went east of wasangles is in the thread
    "When the child was a child it waited patiently for the first snow and it still does"- Van "The Man" Morrison
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  19. #1394
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    Quote Originally Posted by old goat View Post
    The test is 99% specific, which means the same as 1% false positive rate.. That means if you have the test and it's positive there's a 99% chance that it's a true positive. That's a completely separate issue than the number of tests in a population that are true vs false positives. With 1% infected and a 1% false positive rate half the positives will be false as we said before. If everyone is infected than all the positives will be true. If the infected rate is in between the percentage of true vs false positives will be higher the higher the infected rate is. But none of that affects the accuracy of the test for an individual--still a 1% chance the positive is true. That's because the accuracy of the result for an individual doesn't depend on how many others are infected.
    I think you guys are confusing the conditions: prior to testing a person the odds of a false positive are much smaller than they are among a population for which positive results are a given. 98% of people having already been eliminated from the latter group (because 1% true positive and 1% false positive means 98% negative results).

    If you have 200 people with positives and 100 of them are real, at that point the odds of any given test being real are in fact 50/50. Which is different from saying you have a 99% chance of an accurate result when you walk in for a test (obviously this is all simplified--we're ignoring false negatives, which change the exact numbers).

    Don't forget that there are two explanations for a positive, both of which are only 1% probable...and yet, if you get a positive in that scenario you already know you are in one of those very uncommon groups.

  20. #1395
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    Sorry for the continued drift, but it's possible to make that stuff useful instead of hypothetical. The actual ratio of false positives to real would tell you how useful it would be to get the test and know you have a positive result. It's unlikely to be 50/50 in reality.

    To do that you just need to know the expected specificity of a test, how many have been given (preferably in your community) and how many positives have been found. From those you can calculate the likely rate of actual positives, like this:

    (1 - Specificity) ◊ total tests given = false positives

    Total positives - false positives = real positives

    Finally:
    Real positives / total positives = chance of any one positive being real

    Assuming you can find those numbers you wouldn't have to assume uselessness based on speculation (although the line of reasoning is the same). Now back you your regularly scheduled arguing.

  21. #1396
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    I was wrong about the significance of a positive in a disease with a low prevalence. Skizix and jono are right. If 1 % of the population has the disease and the false positive rate is 1% the chance that someone with a positive has the disease is 50%.

  22. #1397
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    Quote Originally Posted by old goat View Post
    I was wrong about the significance of a positive in a disease with a low prevalence. Skizix and jono are right. If 1 % of the population has the disease and the false positive rate is 1% the chance that someone with a positive has the disease is 50%.
    It's a little more complex because it matters who is getting the test and why. That's true if the test sample is randomly drawn from the population. Suppose the prevalence is 1%, and the false positive rate is 1%, and the false negative rate is very small (say 1%). Then if you randomly test 1000 people: 10 of them have the disease and 9.9 of them test positive (round to 10). 990 people don't have the disease and 9.9 of them falsely test positive (round to 10 again). So of the 20 positive tests, only 50% were real.

    BUT if a person decides to go in for the test because they had symptoms, they are no longer a random sample. Now we have to compare against the percentage of the population that had similar symptoms but did not have the disease. That is probably a lot lower fraction. So there are now fewer false positives to get confused by. Suppose out of 1000 people, 10 people had the disease and went in to get tested, and 100 people had a flu or something else and went in to get tested. We get 10 true positives, and 1 false positive. So now the probability that someone who went in with symptoms and got a positive has a true positive is 10/11. Very big difference because the tested population is not random any more.

    (I am not an epidemiologist, and I don't have any insight into any individual case. I do similar kinds of selection statistics at work.)

  23. #1398
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    Quote Originally Posted by skifishbum View Post
    your not sposed to virtue signal your a stoke filled outdoor rec enthusiast any mur
    it makes the participation trophy poli poster losers sad
    and while we dont always agree
    you know ill mount yur skis and share turns
    im pretty sure the reason why the bbi never went east of wasangles is in the thread
    Have you trained your phone spell check to ignore, or even worse, correct TO your unique typing style and lack of punctuation?

    If not I can't imagine how long it takes you to type out a reply because my entire world literally slows down when I try to read most of your posts.

    Sent from my SM-A505W using Tapatalk
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  24. #1399
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    Quote Originally Posted by coldfeet View Post
    It's a little more complex because it matters who is getting the test and why. That's true if the test sample is randomly drawn from the population. Suppose the prevalence is 1%, and the false positive rate is 1%, and the false negative rate is very small (say 1%). Then if you randomly test 1000 people: 10 of them have the disease and 9.9 of them test positive (round to 10). 990 people don't have the disease and 9.9 of them falsely test positive (round to 10 again). So of the 20 positive tests, only 50% were real.

    BUT if a person decides to go in for the test because they had symptoms, they are no longer a random sample. Now we have to compare against the percentage of the population that had similar symptoms but did not have the disease. That is probably a lot lower fraction. So there are now fewer false positives to get confused by. Suppose out of 1000 people, 10 people had the disease and went in to get tested, and 100 people had a flu or something else and went in to get tested. We get 10 true positives, and 1 false positive. So now the probability that someone who went in with symptoms and got a positive has a true positive is 10/11. Very big difference because the tested population is not random any more.

    (I am not an epidemiologist, and I don't have any insight into any individual case. I do similar kinds of selection statistics at work.)
    I was thinking selection bias would matter, too, but that's really only an issue if you were trying to extrapolate to claim you knew what the spread is in the general population (see comments about that upthread). If you're just trying to know what the positive rate is among the tested population and not trying to correlate that to society, then you don't need a truly random sample of the larger population. In which case, if the tested population has a much higher infected rate, then a positive result is more likely to be correct. So if tests are only given to people who had symptoms the usefulness of a positive result goes up (just as you would expect, since the test would have corroboration).

    I think the only real reach here is the assumption of homogeneity of selection criteria; that's going to vary a bit, but I'd be inclined to neglect that effect unless I really had no reason to be tested at all.

    (Also just a stats nerd.)

  25. #1400
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    Quote Originally Posted by coldfeet View Post
    It's a little more complex because it matters who is getting the test and why. That's true if the test sample is randomly drawn from the population. Suppose the prevalence is 1%, and the false positive rate is 1%, and the false negative rate is very small (say 1%). Then if you randomly test 1000 people: 10 of them have the disease and 9.9 of them test positive (round to 10). 990 people don't have the disease and 9.9 of them falsely test positive (round to 10 again). So of the 20 positive tests, only 50% were real.

    BUT if a person decides to go in for the test because they had symptoms, they are no longer a random sample. Now we have to compare against the percentage of the population that had similar symptoms but did not have the disease. That is probably a lot lower fraction. So there are now fewer false positives to get confused by. Suppose out of 1000 people, 10 people had the disease and went in to get tested, and 100 people had a flu or something else and went in to get tested. We get 10 true positives, and 1 false positive. So now the probability that someone who went in with symptoms and got a positive has a true positive is 10/11. Very big difference because the tested population is not random any more.

    (I am not an epidemiologist, and I don't have any insight into any individual case. I do similar kinds of selection statistics at work.)
    Good explanation. The false negatives are also worth mentioning. A negative can be "false" because the person is infected but hasn't made antibodies--either too soon or immune suppressed. That is a true result from the standpoint that the person is not immune to covid 19 at that moment, false in the sense that it gives the impression that the person isn' and has never been infected. Or the result can really be false--the person has antibodies but the test misses them. My understanding is that the sensitivity of some of the tests is extremely good. The Abbot test is one of them. There is also an Abbott test that detects the virus itself--not that sensitive but gets results in minutes. Negatives have to be confirmed by PCR.

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