Author: Mark Hauswald, MS, MD, FACEP, Emeritus Professor of Emergency Medicine, Past Associate Dean for Clinical Affairs and Patient Safety, Past Director of Global Health Projects, University of New Mexico Health Sciences Center
As of 2023, three kinds of COVID-19 tests are approved and available for clinical use:
Samples should be taken from sites approved by the test manufacturer or the FDA. Although deep sputum samples were more accurate early in the pandemic, current tests are very sensitive, so these samples may no longer be clinically relevant. Guidelines still recommend obtaining lower respiratory tract samples to establish a diagnosis of COVID-19 if an initial upper respiratory tract sample is negative (BII) and the patient is intubated. Endotracheal aspirates are recommended over bronchial wash or bronchoalveolar lavage samples.
When viral RNA is detected in other kinds of samples (such as stool), the patient from whom the specimen was obtained should not always be presumed to be actively infected or presently shedding the virus.
Antibody (or serology) tests are used to detect the presence of antibodies from previous infection or vaccination and can aid in the diagnosis of multisystem inflammatory syndrome in children (MIS-C) and adults (MIS-A). The presence of antibodies does not diagnose current infection. Antibody testing has also been used to document antibody production from vaccination or prior infection in immunosuppressed patients. This usage, however, is experimental because the level of antibodies needed for protection is unknown, and protection also depends on T-cell activation, which is not measured by testing. Antibody testing is primarily used for public health surveillance and epidemiologic purposes. Specific antibodies that target different parts (nucleocapsid or spike protein) of the virus are detected by antibody testing. Detection of antinucleocapsid antibody indicates SARS-CoV-2 infection, while anti–spike protein antibody is induced by SARS-CoV-2 infection or COVID-19 vaccination. These differences in antibody types should be considered when deciding whether to test for antibodies from past infection or vaccination.
See the FDA’s list of in vitro diagnostics emergency use authorizations for more information about the performance and interpretation of specific authorized tests.
Clinical laboratory staff and health care clinicians should be aware that false-negative results can occur with any molecular COVID-19 test, particularly if a mutation occurs in a part of the virus’ genome that is assessed by the test. The FDA recommends that clinical laboratory staff and health care clinicians who use these tests note that:
For more information, see the NIH’s “Testing for SARS-CoV-2 Infection.”
Author: Jessica Whittle, MD, PhD, FACEP, Professor and Vice Chair of Research, Department of Emergency Medicine, University of Tennessee College of Medicine
Most physicians understand the value of sensitivity and specificity when considering a diagnostic test. These characteristics are inherent to the test itself and independent of the prevalence of the disease for which the test looks. However, sensitivity and specificity are less helpful when determining how likely an individual test result is a true or false positive.
Sensitivity (also called the true-positive rate, epidemiologic or clinical sensitivity, recall, or probability of detection in some fields) measures the proportion of actual positive test results that are correctly identified as such (eg, the percentage of sick people who are correctly identified as having a condition). Specificity (also called the true-negative rate) measures the proportion of actual negative test results that are correctly identified as such (eg, the percentage of healthy people who are correctly identified as not having a condition).
A test that is 95% sensitive and 95% specific is considered a good test by most physicians. A test that is 95% sensitive will accurately detect a disease in 95 out of 100 samples taken from people who have the disease. By contrast, a test that is 95% specific will accurately read as negative in 95 out of 100 samples taken from people who do not have the disease.
The challenge with a test’s diagnostic accuracy comes into play when only one patient is tested. To know if a positive test result is a true or false positive, the disease’s prevalence must be taken into account by looking at the test’s positive predictive value.
Using the above test as an example, in an area where 2% of the population is infected, the test’s positive predictive value is 28%. If you tell a patient their positive test result is a true positive, you could be wrong as many as 72 out of 100 times. However, when the disease’s prevalence is 25% in the population, the positive predictive value increases to 87%. In this instance, if you tell a patient that their positive test result is a true positive, you will be correct 87 out of 100 times and wrong as many as 13 out of 100 times.
The following resources can provide more information on how to interpret test results and relay them to patients: