A diagnostic test should never claim 100% sensitivity or specificity.
So we are all on the same page, let's review what sensitivity and specificity actually mean. According to the US Food and Drug Administration, the organization which regulates medical diagnostic testing in the US:
In studies of diagnostic accuracy, the sensitivity of the new test is estimated as the proportion of subjects with the target condition in whom the test is positive. Similarly, the specificity of the test is estimated as the proportion of subjects without the target condition in whom the test is negative.
As an FDA guidance document notes:
These are only estimates for sensitivity and specificity because they are based on only a subset of subjects from the intended use population; if another subset of subjects were tested (or even the same subjects tested at a different time), then the estimates of sensitivity and specificity would probably be numerically different. ... This type of uncertainty decreases as the number of subjects in the study increases.
Sensitivity and specificity estimates (and other estimates of diagnostic performance) can be subject to bias. Biased estimates are systematically too high or too low. Biased sensitivity and specificity estimates will not equal the true sensitivity and specificity, on average. Often the existence, size (magnitude), and direction of the bias cannot be determined. Bias creates inaccurate estimates.
One of the key issues is that of the "reference standard", that is what actually defines that a tested condition is actually present or absent. The US Centers for Disease Control and Prevention notes:
The “gold standard” for clinical diagnostic detection of SARS-CoV-2 remains laboratory-based [nucleic acid amplification tests].
Thus, the definition of sensitivity and specificity for a new nucleic acid amplification test (NAAT) is circular, with the reference standard being another NAAT.
As FDA guidance continues:
Two sources of bias that originally motivated the development of this guidance include error in the reference standard and incorporation of results from the test under evaluation to establish the target condition.
These sources of bias and uncertainty are why reputable testing companies don't claim 100% sensitivity or specificity. The reality is that ">99% sensitivity" is also almost certainly overly optimistic and does not incorporate all of the possible sources of bias described in depth by the FDA.
One final note is that a diagnostic test can have 100% sensitivity if it reports all tests positive or 100% specificity if it reports all tests negative. Obviously, such a test has no clinical utility.
