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Which test is best for COVID-19?

January 5, 2021

About the Author

photo of Robert H. Shmerling, MD

Robert H. Shmerling, MD, Senior Faculty Editor, Harvard Health Publishing

Dr. Robert H. Shmerling is the former clinical chief of the division of rheumatology at Beth Israel Deaconess Medical Center (BIDMC), and is a current member of the corresponding faculty in medicine at Harvard Medical School. … See Full Bio
View all posts by Robert H. Shmerling, MD


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August 24, 2020

Is the definition of false positives and false negatives correct? Usually false positives are defined as the possibility of a positive test result given one does not have the disease, not the possibility of one does not have the virus given a positive test result. (Sorry if this is confusing, I am looking at this from a statistics point of view and am trying to do some basic calculations, but I understand if this article is made to be understood more easily)

Robert H. Shmerling, MD
August 24, 2020

Hi, Alex – thanks for your question. Yes, the definitions of false-positives and false-negatives are correct but I agree, the language around this can be confusing. For false-positive results, it’s the situation in which someone who doesn’t have the disease but has a positive test result; this can also be stated the other way around: a positive test result for someone who doesn’t have the disease.

They are not probabilities (or “possibilities” as in your question) – they rely on knowing the test result and diagnosis and are based on sensitivity (positive test results among all who have the disease) and specificity (negative test results among all who don’t have the disease). A highly sensitive test has a low false-negative rate. A highly specific test has a low false-positive rate. As examples: For a test with 90% sensitivity, the false-negative rate is 10%. If the specificity is 98%, the false-positive rate is 2%.

You may be thinking of predictive value – these are probabilities in which you’re starting with a test result (not a diagnosis) and looking at the liklihood that the diagnosis is present. For example, how likely is it that a person with a positive test has the disease (positive predictive value)? Or, what’s the chance that a person with a negative result does not have the disease (negative predictive value)?

I hope this helps!

Mike O
August 23, 2020

Thank you! This clear and concise assessment of current testing options was very helpful as my family decides how to proceed after a possible exposure.

J. Michael Carter
August 14, 2020

Thanks for the COVID-19 testing summary. It’s becoming increasingly frustrating to remain optimistic as I seek an accurate rapid test kit for my family. Reading articles about how every Fisher Island resident in Florida has been tested (along with staff) and watching Dr. Vin Gupta praise an actual test kit (but couldn’t voice the company’s name). The punches to the gut continue in the capitalistic system that takes care of those who have the most 1st, 2nd, and 3rd! I’m married, in my late 50s, parents and in-laws living, 4 kids, and 2 grandkids; I can only hold and love on my wife and youngest child. Like many others, I can afford to purchase whichever rapid test I deem the most suitable for my family’s needs. The age old American SOP of I’m not important enough, or sick enough to qualify me to be in that exclusive circle. As an American living in the world’s largest capitalistic society, I should have access to the same products as those deemed the wealthiest and or the most important. So, is America really as capitalistic as portrayed? What a dangerous, empathy lacking, selfish, and very hypocritical time the majority of Americans find ourselves currently living.

Thanks for allowing me to vent and thanks again for explaining the various testing methods in laymen terminology.

shrabani sarkar
August 11, 2020

Thanks for the information

Commenting has been closed for this post.

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