[M T]

Pregnant patients prior to delivery are being universally tested, with about 1.5% positive. This is by PCR testing. It would fit with the LA county antibody prevalence testing showing low single digit exposure.

It isn't clear to me what "universally" meant there.  Are you talking of the one study in NYC that came out in preprint recently, or perhaps you're saying that such testing is currently the standard procedure in LA county, or maybe you're saying it is all across the US?

People should be wary of using such a number as indicating 1.5% infection rate.  You need to think about when the infection happened and what are the effects of false positive & false negative on these numbers.

This study looks at the probability of a positive vs a false-negative result of a PCR test, based on sets of repeated testing of individuals.   For instance, if 100% of the pregnant patients were infected 30 days before the test, the number of positive results would be somewhere around the number reported.  (I'm NOT saying that is what happened.  I'm just trying to show one needs to be careful not to interpret the results without stopping to think.)

They also provide graphs to indicate how false positive rates (which they didn't try to measure) also affect the interpretation of prevalence, and urge better understanding of those numbers.

our results suggest that there may be some benefit to testing indiscriminately;conducting a single test on someone who had symptoms 10 days ago will have a nearly 33% false negative rate (using a nasal swab; 52.89% for a throat swab). As a means of determining population level exposure to SARS-CoV-2, serological tests are far more likely to provide an accurate profile.

(but, as we've seen, serological tests have their own set of problems, so far).

This study presents a case of a patient with clinical signs but had 9 negative PCR tests before getting the first positive tests.

[M T]

Pregnant patients prior to delivery are being universally tested, with about 1.5% positive. This is by PCR testing. It would fit with the LA county antibody prevalence testing showing low single digit exposure.

It isn't clear to me what "universally" meant there.  Are you talking of the one study in NYC that came out in preprint recently, or perhaps you're saying that such testing is currently the standard procedure in LA county, or maybe you're saying it is all across the US?

People should be wary of using such a number as indicating 1.5% infection rate.  You need to think about when the infection happened and what are the effects of false positive & false negative on these numbers.

This study looks at the probability of a positive vs a false-negative result of a PCR test, based on sets of repeated testing of individuals.   For instance, if 100% of the pregnant patients were infected 30 days before the test, the number of positive results would be somewhere around the number reported.  (I'm NOT saying that is what happened.  I'm just trying to show one needs to be careful not to interpret the results without stopping to think.)

They also provide graphs to indicate how false positive rates (which they didn't try to measure) also affect the interpretation of prevalence, and urge better understanding of those numbers.

our results suggest that there may be some benefit to testing indiscriminately;conducting a single test on someone who had symptoms 10 days ago will have a nearly 33% false negative rate (using a nasal swab; 52.89% for a throat swab). As a means of determining population level exposure to SARS-CoV-2, serological tests are far more likely to provide an accurate profile.

(but, as we've seen, serological tests have their own set of problems, so far).

This study presents a case of a patient with clinical signs but had 9 negative PCR tests before getting the first positive tests.