There seems to be no analysis of whether these are neutralizing antibodies. The idea of using serology for immunity certificates or "golden tickets" is never going to go well. Even with 99.9% specificity, if the population prevalence is 1%, 10% of positives will be false positives. If in real world testing, specificity is 99% and population prevalence is 1%, then 50% of positives are false positives.
If we want to ensure that the active population is always above herd immunity threshold, 10% or 20% false positives would be acceptable, since the population in contact would still be 80 or 90% immune.
If the reported immune rate is 80%, with 10-20% false positives, wouldn't the real immunity rate be 64-72%?
There seems to be no analysis of whether these are neutralizing antibodies. The idea of using serology for immunity certificates or "golden tickets" is never going to go well. Even with 99.9% specificity, if the population prevalence is 1%, 10% of positives will be false positives. If in real world testing, specificity is 99% and population prevalence is 1%, then 50% of positives are false positives.
If we want to ensure that the active population is always above herd immunity threshold, 10% or 20% false positives would be acceptable, since the population in contact would still be 80 or 90% immune.
I think this is more about finding hotspots. Where could a seeding event lead to a large outbreak. Clearly 1 person entering into NYC with COVID today would not have the same effects as 4 months ago because supposedly 20% are immune. At least for the time being at least the assumption is. So there is that effect, but also how big could the next wave be based on that. Of course that all has to be proven that detectable immunity or levels above a certain threshold will prevent you from getting infected again or at least reduce the severity over some period of time. So how many antibodies, which type, how long they last, and how much do they have an effect on reducing reinfection or severity of the next infection - all yet to be determined.
Cool, it's nice to see progress on antibody tests - the early Chinese ones in use here in Czech Republic are reportedly (accordingly to local news articles) rather noisy. Still preaty nice when they work, as you only need a drop of blood & get results in 10 minutes vs sample swabbing & complicated PCR sample processing taking up to a day.
In the US, they're $119 through Quest Diagnostics. In some areas and with some insurance companies, that cost is fully covered.
Do you know that all the Quest tests are mfg. by Abbott? I didn't see that anywhere, they didn't seem to show which test manufacturer you got when you receive results either.
If we want to ensure that the active population is always above herd immunity threshold, 10% or 20% false positives would be acceptable, since the population in contact would still be 80 or 90% immune.
I think this is more about finding hotspots. Where could a seeding event lead to a large outbreak. Clearly 1 person entering into NYC with COVID today would not have the same effects as 4 months ago because supposedly 20% are immune. At least for the time being at least the assumption is. So there is that effect, but also how big could the next wave be based on that. Of course that all has to be proven that detectabl…
> Of course that all has to be proven that detectable immunity or levels above a certain threshold will prevent you from getting infected again.
South Korea is reporting that as of last week, and say their earlier "reinfection" results and subsequent scare were flawed.
There seems to be no analysis of whether these are neutralizing antibodies. The idea of using serology for immunity certificates or "golden tickets" is never going to go well. Even with 99.9% specificity, if the population prevalence is 1%, 10% of positives will be false positives. If in real world testing, specificity is 99% and population prevalence is 1%, then 50% of positives are false positives.
If you want neutralizing antibodies you can do serum virus neutralization assay. It's more complicated and takes longer.
Testing doesn't need to be 100% to be effective, but it does need to be better than random chance. A mixture of contact tracing, PCR testing, antibody testing and effective quarantines could be used to make the virus go away, but would require a coordinated strategy that the US has not attempted to implement, much to my dismay.
In the US, they're $119 through Quest Diagnostics. In some areas and with some insurance companies, that cost is fully covered.
Do you know that all the Quest tests are mfg. by Abbott? I didn't see that anywhere, they didn't seem to show which test manufacturer you got when you receive results either.
The Abbott test may not be used everywhere. I've called them to confirm their labs local to me use the Abbott test and that's probably what you should do if you're looking to get this test. While it does not guarantee that they use the Abbott test in every region, you can see that they reference Abbott in the footnotes for question #3 in their FAQ on COVID-19 testing here: https://education.questdiagnostics.com/faq/FAQ219
There seems to be no analysis of whether these are neutralizing antibodies. The idea of using serology for immunity certificates or "golden tickets" is never going to go well. Even with 99.9% specificity, if the population prevalence is 1%, 10% of positives will be false positives. If in real world testing, specificity is 99% and population prevalence is 1%, then 50% of positives are false positives.
Would you or someone else mind expanding on this thought a little? Why does 99.9% specificity mean that 10% will be false positives? {added: great answers below} well worth understanding this point. In short specificity measures the % of the population tested which had false positives, but doesn't give you the ratio of false positives to positives or the probability that a positive test means you actually have the an…
Bayes theorem assuming 1% actual positive rate. If you test 1000 people, you will get roughly 10 positives and 1 false positive for a false positive rate of 10%.
There seems to be no analysis of whether these are neutralizing antibodies. The idea of using serology for immunity certificates or "golden tickets" is never going to go well. Even with 99.9% specificity, if the population prevalence is 1%, 10% of positives will be false positives. If in real world testing, specificity is 99% and population prevalence is 1%, then 50% of positives are false positives.
What if prevalence is 5% or 10%? Your alarming false positive rates vanish. No measure is ever going to work perfectly.
There seems to be no analysis of whether these are neutralizing antibodies. The idea of using serology for immunity certificates or "golden tickets" is never going to go well. Even with 99.9% specificity, if the population prevalence is 1%, 10% of positives will be false positives. If in real world testing, specificity is 99% and population prevalence is 1%, then 50% of positives are false positives.
Would you or someone else mind expanding on this thought a little? Why does 99.9% specificity mean that 10% will be false positives? {added: great answers below} well worth understanding this point. In short specificity measures the % of the population tested which had false positives, but doesn't give you the ratio of false positives to positives or the probability that a positive test means you actually have the an…
If the number of true positives is 10/1000, and the test gives you 11/1000 positive results, then 1/11 of your tested positive results are false positives. (Actually closer to 9% than 10%).