Lies, Covid Lies, and Statistics

Exaggerating the fatality risk associated with Covid-19 and portraying unscientific guesses as unqualified facts stood out as key Administrative State failures in the early days of Covid. Take the Administrative State’s early statements regarding Covid case fatality and mortality rates. A case fatality rate is a ratio of how many people infected with a particular disease die as a result; the mortality rate is the overall percentage of the population (including both healthy and infected) that dies from it.[1] So, case fatality rates can be exaggerated either when the number of infections is understated or the number of deaths overstated. America’s Administrative State managed both.

The number of infections was understated at the outset Covid due to lack of developed tests and rationing of tests for those who appeared to be the sickest. Falsely low infection numbers made the virus appear deadlier than it was, particularly to younger and healthier people. Central government control of test development, and an early CDC test-development failure, slowed development and distribution of diagnostic tests in the U.S. compared to, say, South Korea and Germany. Even when material was available from samples taken for influenza testing, the Centers for Disease Control and Prevention (CDC) and the Food and Drug Administration directed that tests not be developed to detect Covid.[2] In medical settings, state health departments sometimes denied Covid testing.

We did not, could not, know the actual Covid case fatality rate in early 2020. That did not stop agency officials from testifying before Congress suggesting high case fatality and mortality rates with great confidence and few caveats. In March 2020, a House Committee held a hearing to review Covid issues.[3] During the hearing one Congressman asked about “the number of cases and the number of fatalities,” stating he had seen reports that recovery rates were better than 50%. The Director for the CDC responded, stating that “we would say it’s probably about 85 percent.” His only hedge was to state it may be lower, at 80-85%. His testimony implied that 15% of people infected with Covid would not recover or would die.

Dr. Fauci, Director of the National Institute of Allergy and Infectious Diseases, testified that Covid was “10 times more lethal than the seasonal flu.” According to Dr. Fauci, the flu had a mortality rate of .1%. At ten times that rate, he was suggesting that 1% of the American population, or 3.3 million people would die of Covid. In 2020, there were approximately 384,536 Covid-caused deaths.[4]

Covid fatalities may also have been exaggerated. The United States counted a “Covid death” if Covid was listed as either a cause or a contributing cause. Data suggests that 90% of death certificates citing Covid recorded Covid as the underlying cause, but some research suggests that Covid was the sole cause in only 5% of those deaths.[5]

The early days of Covid were uncertain; statistics were constantly changing. Not having an accurate number or recognizing that data may be erroneous is understandable. What is less understandable and dangerous is asserting faulty data as fact and implementing national quarantine, isolation, and vaccine mandates based on it, while ridiculing and silencing people who questioned the statistics. For example, policymakers discounted a Santa Clara study performed in April, 2020, which suggested much wider community spread of Covid-19 than previously estimated (and hence a much lower fatality rate).

The recognized problems of relying on the questionable statistics provided by the Administrative State included the potential to endorse “extreme measures” without supporting evidence, economic and social disruptions, inappropriately extreme medical interventions (ventilators), and the inability of patients to provide informed consent (vaccines) when the information provided was false.[6]

Five years later, we still suffer the aftereffects of mandated shutdowns, vaccine campaigns, other extreme Administrative State measures based on inaccurate data. Not surprisingly, the government’s reliance on such data also eroded trust in public health authorities.

[1] https://newslit.org/updates/case-fatality-rate-vs-mortality-rate/

[2] https://www.npr.org/sections/health-shots/2020/03/14/815727231/opinion-early-coronavirus-testing-failures-will-cost-lives

[3] https://www.congress.gov/116/chrg/CHRG-116hhrg40428/CHRG-116hhrg40428.pdf; https://pubmed.ncbi.nlm.nih.gov/32782048/

[4] https://www.statista.com/statistics/1382342/number-covid-deaths-us-by-age/

[5] https://www.medicalnewstoday.com/articles/how-are-covid-19-deaths-counted-and-what-does-this-mean#Died-of-or-with-COVID-19

[6] https://pmc.ncbi.nlm.nih.gov/articles/PMC7163529/

April 1, 2025