Sensitivity vs Specificity
- Test sensitivity indicates the ability of the test to correctly identify patients that have the disease. A test’s sensitivity is also known as the true positive rate. If a diagnostic test correctly identified 100% of all positive results, it would be as sensitive as possible.
- Test specificity indicates the ability of the test to correctly identify patients that do not have the disease. If a test correctly identifies all people without the disease as negative, it would be as specific as possible.
Specificity in COVID-19 testing
For SARS-CoV-2 antibody testing, the CDC suggests use of tests with a specificity ≥99.5% to minimize the potential for false-positive results.1
There are numerous tests that claim to detect antibodies to the SARS-CoV-2 virus; only a few are highly accurate:
How do highly specific antibody tests support good performance, even with low disease prevalence?
Let’s look at what happens in two cities, one with a 5% disease prevalence, another with 10% prevalence.
What happens when the population is tested with an assay that has higher specificity of 99.8%?
A highly specific test minimizes inaccurate results. With a higher disease prevalence, fewer people will experience incorrect results.
What happens when the specificity is reduced to 96%?
A 96% specificity may seem high, but a difference of as small as 3 to 4 percent can create dramatic changes in test results.
The model above assumes assay sensitivity of 100%
