4 ms·

They have huge false positive rates though.

by garmaine 7y ago

taeric 7y ago
Do we know the rates already?
- amluto 7y ago
  There’s preliminary data: https://covidtestingproject.org/ https://covidtestingproject.org/
deleted 7y ago
[deleted]
danielfoster 7y ago
And false negatives.
- pedrosorio 7y ago
  If the rate of false positives and false negatives is the same but the true prevalence is << 0.5, then you will overestimate the number of positives.
brm 7y ago
Only until the point that they don't. Unfortunately that requires a lot more people to have had covid...
ptrincr 7y ago
Not sure why you are being downvoted: https://www.oxfordbiosystems.com/COVID-19-Rapid-test https://www.oxfordbiosystems.com/COVID-19-Rapid-test "In order to test the detection sensitivity and specificity of the COVID-19 IgG-IgM combined antibody test, blood samples were collected from COVID-19 patients from multiple hospitals and Chinese CDC laboratories. The tests were done separately at each site. A total of 525 cases were tested: 397 (positive) clinically confirmed (including PCR test) SARS-CoV-2-infected patients and 128 non- SARS-CoV-2-infected patients (128 negative). The testing results of vein blood without viral inactivation were summarized in the Table 1. Of the 397 blood samples from SARS-CoV-2-infected patients, 352 tested positive, resulting in a sensitivity of 88.66%. Twelve of the blood samples from the 128 non-SARS-CoV-2 infection patients tested positive, generating a specificity of 90.63%." That gives us 62% false positive ratio according to (where a study finds the prevalence to be 6% of subjects using the test): http://vassarstats.net/clin2.html http://vassarstats.net/clin2.html In some cases we have research being carried out with such low positive results that they can entirely be accounted for by the low specificity. So for example if you took samples from 100 people, based on 90% specificity, even if everyone had never had corona, 10 could be found positive. Credit to this post: https://old.reddit.com/r/COVID19/comments/g7f373/second_round_of_covid19_community_testing/foh3b3p/ https://old.reddit.com/r/COVID19/comments/g7f373/second_roun... However it should be noted the article in question for this submission does not mention the type of test used.
- raverbashing 7y ago
  I wonder what's the process through which false positives happen in this case. Previous infection by milder Coronaviruses? Edit: I'm looking at the reddit post but I have a lot of reservations with the "prevalence 0.06", unless we'll use the test to test absolutely everybody and not only people who are suspect. Has that calculator been validated as well? If the test was 12 false positives in 128 negatives, how come they can claim the false positive rate is 60%?
  - ptrincr 7y ago
    Apologies for the way this was linked to. The 6% is from this study: https://www.miamidade.gov/releases/2020-04-24-sample-testing-results.asp https://www.miamidade.gov/releases/2020-04-24-sample-testing... "Our data from this week and last tell a very similar story. In both weeks, 6% of participants tested positive for COVID-19 antibodies, which equates to 165,000 Miami-Dade County residents" That is what the commentator is referring to in the linked post. So if you plug their own figures into the calculator: Sensitivity .8866 Specificity .9063 and a Prevalence of .06 based on the study, you get the 62% false positive rate. As the prevalence increases, as with the NYC study which found the positive rate to be 21% (prevalence), the false positive rate decreases, down to 28% of the NYC study.
  - deleted 7y ago
    [deleted]
  - FrojoS 7y ago
    Yes. That’s one possible explanation. Interestingly quite a lot of people might be somewhat immune to the new Corona virus due to anti bodies from previous Corona cold infections. More than 30% showed such antibodies in a recent study. https://www.finanzen.net/nachricht/aktien/drosten-hinweis-auf-hintergrundimmunitaet-gegen-neues-coronavirus-8784418 https://www.finanzen.net/nachricht/aktien/drosten-hinweis-au... (Sorry that the only source I have ready right now)
  - nodamage 7y ago
    60% is the probability that a particular positive test result is actually a false positive. It's not the overall the false positive rate.
deleted 7y ago
[deleted]
timr 7y ago
There are many different tests, from different manufacturers. Some of the tests have higher false-positive rates than others. Some have higher false-negative rates. Even a survey with an imperfect test can be designed to yield reliable data.

They have huge false positive rates though.

taeric 7y ago

Do we know the rates already?

amluto 7y ago
There’s preliminary data: https://covidtestingproject.org/ https://covidtestingproject.org/

deleted 7y ago

[deleted]

danielfoster 7y ago

And false negatives.

pedrosorio 7y ago
If the rate of false positives and false negatives is the same but the true prevalence is << 0.5, then you will overestimate the number of positives.

brm 7y ago

Only until the point that they don't. Unfortunately that requires a lot more people to have had covid...

ptrincr 7y ago

Not sure why you are being downvoted: https://www.oxfordbiosystems.com/COVID-19-Rapid-test https://www.oxfordbiosystems.com/COVID-19-Rapid-test "In order to test the detection sensitivity and specificity of the COVID-19 IgG-IgM combined antibody test, blood samples were collected from COVID-19 patients from multiple hospitals and Chinese CDC laboratories. The tests were done separately at each site. A total of 525 cases were tested: 397 (positive) clinically confirmed (including PCR test) SARS-CoV-2-infected patients and 128 non- SARS-CoV-2-infected patients (128 negative). The testing results of vein blood without viral inactivation were summarized in the Table 1. Of the 397 blood samples from SARS-CoV-2-infected patients, 352 tested positive, resulting in a sensitivity of 88.66%. Twelve of the blood samples from the 128 non-SARS-CoV-2 infection patients tested positive, generating a specificity of 90.63%." That gives us 62% false positive ratio according to (where a study finds the prevalence to be 6% of subjects using the test): http://vassarstats.net/clin2.html http://vassarstats.net/clin2.html In some cases we have research being carried out with such low positive results that they can entirely be accounted for by the low specificity. So for example if you took samples from 100 people, based on 90% specificity, even if everyone had never had corona, 10 could be found positive. Credit to this post: https://old.reddit.com/r/COVID19/comments/g7f373/second_round_of_covid19_community_testing/foh3b3p/ https://old.reddit.com/r/COVID19/comments/g7f373/second_roun... However it should be noted the article in question for this submission does not mention the type of test used.

raverbashing 7y ago
I wonder what's the process through which false positives happen in this case. Previous infection by milder Coronaviruses? Edit: I'm looking at the reddit post but I have a lot of reservations with the "prevalence 0.06", unless we'll use the test to test absolutely everybody and not only people who are suspect. Has that calculator been validated as well? If the test was 12 false positives in 128 negatives, how come they can claim the false positive rate is 60%?
- ptrincr 7y ago
  Apologies for the way this was linked to. The 6% is from this study: https://www.miamidade.gov/releases/2020-04-24-sample-testing-results.asp https://www.miamidade.gov/releases/2020-04-24-sample-testing... "Our data from this week and last tell a very similar story. In both weeks, 6% of participants tested positive for COVID-19 antibodies, which equates to 165,000 Miami-Dade County residents" That is what the commentator is referring to in the linked post. So if you plug their own figures into the calculator: Sensitivity .8866 Specificity .9063 and a Prevalence of .06 based on the study, you get the 62% false positive rate. As the prevalence increases, as with the NYC study which found the positive rate to be 21% (prevalence), the false positive rate decreases, down to 28% of the NYC study.
- deleted 7y ago
  [deleted]
- FrojoS 7y ago
  Yes. That’s one possible explanation. Interestingly quite a lot of people might be somewhat immune to the new Corona virus due to anti bodies from previous Corona cold infections. More than 30% showed such antibodies in a recent study. https://www.finanzen.net/nachricht/aktien/drosten-hinweis-auf-hintergrundimmunitaet-gegen-neues-coronavirus-8784418 https://www.finanzen.net/nachricht/aktien/drosten-hinweis-au... (Sorry that the only source I have ready right now)
- nodamage 7y ago
  60% is the probability that a particular positive test result is actually a false positive. It's not the overall the false positive rate.

deleted 7y ago

[deleted]

timr 7y ago

There are many different tests, from different manufacturers. Some of the tests have higher false-positive rates than others. Some have higher false-negative rates. Even a survey with an imperfect test can be designed to yield reliable data.