Covid-19 Tests: Can You Trust the Results?

If your Covid-19 test was negative, can you breathe a sigh of relief? What if it’s a false negative? If it was positive, is that reliable evidence of infection or might it be a false positive result? How trustworthy are these tests? As with so much in science, the answer is complicated; it’s not a straightforward black-and-white certainty. An article by William Nettleton in the April 15, 2021 issue of American Family Physician sheds some light on the subject.

Which test? As of March 15, 2021, 256 molecular tests and 15 antigen tests for the SARS-CoV-2 virus had been given Emergency Use Authorization (EUA) by the U.S. Food and Drug Administration (FDA). Molecular tests such as reverse transcriptase polymerase chain reaction (RT-PCR) detect viral nucleic acids. Antigen tests use immunoassays to detect viral proteins. And then there are serologic tests that measure antibodies resulting from infection or vaccination; but these can’t be used to diagnose current infections.

Molecular tests are the most sensitive. Because they amplify nucleic acids, they can detect even small amounts of virus. Both kinds of test are highly specific; some tests are less sensitive than others and are more prone to false-negative results. Molecular tests cost more ($100 compared to between $5 and $50 for antigen tests). Both kinds of test can give results in 10-15 minutes, although reports may not be available for several days. Specimens are usually collected with nasopharyngeal and nasal swabs; sometimes molecular tests are done on sputum and saliva samples.

Some important terms:

            Specificity means the percentage of people without the disease who test negative.

            Sensitivity means the percentage of people with the disease who test positive.

            PPV (positive predictive value) is the percentage of positive tests that are true positives.

            NPV (negative predictive value) is the percentage of negative tests that are true negatives 

Both PPV and NPV are dependent on the prevalence of the disease in the population being tested. 

            Positive likelihood ratio (LR+) is the true positive rate divided by the false positive rate. 

            Negative likelihood ratio (LR-) is the true negative rate divided by the false negative rate.  

            LR+ and LR- are measures of how the pre-test probability of a diagnosis changes to a different post-test probability after a positive or negative test.

This table from the AFP article will help to put these terms in perspective:

Table

Description automatically generated

The FDA has published a SARS-CoV-2 Reference Panel to help determine the comparative performance among authorized tests.

Symptomatic vs. asymptomatic

Numerous studies have shown that the sensitivity of the test is greater for people with symptoms than for people who are asymptomatic.

Timing

Viral load has been shown to decrease during the week after onset of symptoms. 

The instructions of all the FDA EUAs warn that false positive results may occur if specimens are collected 5-12 days after symptom onset. 

How to interpret test results

So, it’s not a simple matter of whether a test is positive or negative. There are many 

things to consider:

  • What test was done? What is its sensitivity and specificity?
  • Was the specimen collected properly and handled correctly?
  • Is the patient symptomatic? If so, when did symptoms start?
  • Have they been exposed to someone with a confirmed or probable case of Covid-19? 
  • Is Covid-19 prevalent in the population?
  • Is there an alternative diagnosis, such as influenza?

Difficult decisions

Medicine is messy. It’s not an exact science. Doctors often have to make decisions and take actions when they don’t have all the facts. Eventually we hope to learn more about Covid-19, but meanwhile we must take chances; even our best educated guesses are still only guesses.

What if the pre-test probability of infection is high, but the test is negative? Believing a 

false negative is a true negative would risk spreading the disease; wouldn’t it be safer to recommend isolation precautions?

We don’t know for sure how long a patient can infect others. What if the symptoms are going away and the patient has had no fever for 24 hours? Is it safe to disregard a positive test at that point and let the absence of symptoms determine whether isolation precautions are still needed? 

Is there a point at which we can assume that an infected or vaccinated patient has become immune?

Conclusion: the truth is complicated

You may have thought that a simple test would reliably give you a yes-or-no answer to the question “Do I have Covid-19?” Sorry to burst your bubble. It’s not enough to know that you have tested positive or negative for Covid-19. There are many other factors to consider. It’s complicated.

This was originally published as a SkepDoc’s Corner column on the  CSI website

Dr. Hall is a contributing editor to both Skeptic magazine and the Skeptical Inquirer. She is a weekly contributor to the Science-Based Medicine Blog and is one of its editors. She has also contributed to Quackwatch and to a number of other respected journals and publications. She is the author of Women Aren’t Supposed to Fly: The Memoirs of a Female Flight Surgeon and co-author of the textbook, Consumer Health: A Guide to Intelligent Decisions.

Scroll to top