2020 MEDICAL YEAR IN REVIEW
Testing for Evidence of the COVID-19 Virus By Alan Preston, MHA, Sc.D.
Ever since COVID-19 was present in the USA, the challenge was to determine how fast would it spread and what harm could it cause, and to whom? In the world of epidemiology, we look at the incidence rate of a disease as the first onset of the disease. The prevalence of a disease is the number of people who have already acquired the disease. Capturing the rate of transmission of any given communicable disease requires an understanding of both. Early this year (i.e., February 2020), the news agencies reported the number of cases every day based on those tested. The problem, in the beginning, was that the correct number of cases in the general population was at least ten times more than the number of cases being reported. This created two significant problems; one underestimated the number of infected individuals and overestimated the death rate (i.e., case fatality rate CFR) since the death rate is based on the number of infected cases. And not until midMarch did the testing begin in earnest to more accurately determine how many people may be infected. The number of tests before mid-March was less than 60 per day, which increased to 127,000 per day on March 18, 2020. As of November 2020, there have been over 1,327,000 per day in the U.S., or 156,318,000 COVID-19 cumulative tests performed. The more people tested, the more people will test positive; however, as a percentage of tested individuals, it will hold steady and predictable, as it has for a while at 6 to 10% tested positive. That suggests that those who think they are infected with COVID-19 find out that 90 to 94% of that population are COVID-19 negative. Why would someone get tested, and what kind of test are they receiving? The CDC suggests that anyone with influenzalike illness (ILI) or COVID-like illness 22
(CLI) should be tested to rule in/out COVID-19. When over 90% of the tests are negative, that suggests the public has a high degree of fear and desire to understand whether they are infected. Their ILI symptoms may be related to allergies, a superficial sinus infection or a postnasal drip that causes a cough or sneezing unrelated to COVID19. The challenge for many healthcare professionals is when to perform a test and what kind of test should they perform? There are primarily two categories of COVID-19 tests; the PCR test and the Antibody test. The PCR test is appropriate for current diagnosis for the most part, which I will explain in a bit, and the Antibody test is used to determine if someone had COVID19 in the past. The challenge with the PCR test is that the results are binary; positive or negative. As most physicians understand, a laboratory test often has ranges. The ranges help physicians understand the acuity of the patient based on a lab value range. The PCR test also has a range. The range is based on a cycle threshold (CT). The current cutoff on most PCR tests is close to 40 CT. Suppose the CT is over 40, which suggests a negative test. If the CT is under 40, that means positive. However, most PCR tests for other types of viruses are closer to 30 to 35 on the high end. What are the implications of allowing a PCR CT of 30
SAN ANTONIO MEDICINE • December 2020
to 40 to indicate a positive COVID-19? The implication is many people are labeled positive for COVID-19 when they should be labeled negative. They should be labeled negative because of the viral load. The PCR test amplifies genetic matter from the virus in cycles. If you find a high amount of viral load in a person, fewer cycles are required. The greater the viral load, the more likely the patient is to be contagious. And if it takes 40 cycles to detect a small amount of viral load, then the likelihood that the "infected" person can pass the virus is significantly negligible. Unfortunately, the number of amplification cycles needed to find the virus is never included in the results sent to doctors. If it were, doctors could tell how infectious the patients are. It is difficult to estimate the number of tests suggesting a patient is positive when, in fact, they are, for all practical purposes, negative. A September 2020 NY Times article looked at three sets of testing data that include cycle thresholds. What they found was astonishing; in Massachusetts, New York and Nevada, up to 90 percent of people testing positive barely carried any virus. Tests with cycle thresholds so high detect genetic fragments that pose no particular risk to the public. Yet the public policy mandates have enormous economic consequences when data is overstated, and politicians rely on data (overstated or otherwise) for man-
