5 ms·

I think antibody tests will soon become more useful for tracking disease progression in a population than the viral tests. The collection methods may skew thing

by bb2018 6y ago

I think antibody tests will soon become more useful for tracking disease progression in a population than the viral tests. The collection methods may skew things but they still are much more close to a random sample than the viral tests which have lots of issues with test shortages and people unable to get tested (or not wanting to go to the hospital with mild symptoms).

garmaine 6y ago
They have huge false positive rates though.
- taeric 6y ago
  Do we know the rates already?
  - amluto 6y ago
    There’s preliminary data: https://covidtestingproject.org/ https://covidtestingproject.org/
- deleted 6y ago
  [deleted]
- danielfoster 6y ago
  And false negatives.
  - pedrosorio 6y 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 6y ago
  Only until the point that they don't. Unfortunately that requires a lot more people to have had covid...
- ptrincr 6y 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 6y 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 6y 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 6y ago
  [deleted]
- timr 6y 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.

by bb2018 6y ago

garmaine 6y ago

They have huge false positive rates though.

taeric 6y ago
Do we know the rates already?
- amluto 6y ago
  There’s preliminary data: https://covidtestingproject.org/ https://covidtestingproject.org/
deleted 6y ago
[deleted]
danielfoster 6y ago
And false negatives.
- pedrosorio 6y 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 6y ago
Only until the point that they don't. Unfortunately that requires a lot more people to have had covid...
ptrincr 6y 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 6y 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 6y 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 6y ago
[deleted]
timr 6y 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.