COVID Testing

[Gregory Matthews]

COVID Testing:   In the current COVID climate, many people do not understand some of the issues related to medical testing for disease and the probability of actually becoming ill from the tested disease.  I will attempt to clarify some of the issues in the following hypothetical illustration.  In this illustration, the population of the United States will be 300,000,000 (Actually it is more than that.).  I will test for a mythical Smith’s disease with a test that will identify 95% of the 500,000 who actually have the disease.  In addition my test will deliver a false positive result for 1 % of the people who do not have the disease.  So, in my US population of 300,000,000 people 500,000 will have Smith’s disease and my test will identify 475,000 as actually having the disease.  In addition, my test will state that of the 299,500,000 people who do not have Smith’s disease my test will falsely state that 2,995,000 of them do have the disease. The mathematical result of this is that if my test identifies you as being positive for Smith’s disease, you are about 15% likely to actually have Smith’s disease.  Folks, this is medical science properly understood. As interpreted by the mathematics of probability.  NOTE:  My statement above is basically the work of Dr. (PhD.) Michael Starbird, in “What Are the Chances? Probability Made Clear,” The Great Courses.

NOTE #2:  Medical tests are not perfect.  They may have both false positives and false negatives.  If so, those numbers will differ from the numbers that I gave in my mythical illustration.