While public officials continue to be browbeaten by public cries to “shut everything down,” driven by a relentless media in hyperdrive to cover every step of this “COVID-19 crisis,” more and more Americans are waking up to the notion that the current “crisis” might not quite fit current facts.

Part of the skepticism derives from the fact that national policy and practice seems to have taken the Tesla Roadster approach of 0-60 in 1.9 seconds.

February 29^th: President Trump called his first press conference regarding COVID-19. Here, Anthony Fauci said, “the country as a whole still remains at a low risk but this remains an evolving situation” while saying that fewer than 20% of those infected would need hospitalization and that most severe cases would be seen in older individuals and those with underlying conditions.

March 15^th: as the CDC was issuing their guidelines including social distancing and avoiding gatherings of 50 or more, President Trump introduced his “fifteen days to flatten the curve” initiative, mirroring CDC guidelines.

March 29^th: Fauci predicts that COVID-19 could kill 100-200,000 Americans and President Trump announces that CDC’s social distancing guidelines will be kept in place until April 30^th.

March 31^st: Fauci’s death projections had increased to 240,000 and President Trump wanted “every American to be prepared for the tough days ahead.”

What happened to instigate such rapid and unprecedented government recommendations? Apparently, two disease models -- one created by the Imperial College London and another created by the University of Washington’s Institute for Health Metrics and Evaluation.

Though both models moved the media from simmering crisis to full rolling-boil calamity, both have since found major detractors (IHME, Imperial College) as the public continues to wait for their hypothesized several hundred thousand death tolls to materialize in real time.

Yet, without the media fanfare surrounding the previous models, Sunetra Gupta, a professor of Theoretical Epidemiology at Oxford, created a model which suggests that the virus was circulating in the UK by mid-January. This is important because it could mean that half of UK residents have already been exposed to the virus, increasing immunity and thereby decreasing cases.

Data provided by the CDC could suggest a similar situation here in the U.S.

According to this graph, the CDC began receiving COVID-19 testing January 18^th. Public health labs began to test for the disease February 27^th, but were required to send all tests to the CDC for confirmative testing until March 14^th. Note the spike in testing once the CDC stamp of approval was no longer needed for a confirmative test and more tests were made available to public and private health care facilities.

The page on which this graph is located does not indicate whether the numbers of COVID-19 tests submitted are positive or negative, just that they were specimens presented to the CDC for confirmation. Another page on the CDC website, provides the number of cases in the U.S. by report date with the first positive COVID case recorded by the CDC, January 22, 2020.

According to reports, COVID-19 was first identified in China November 17^th and travel between China and the U.S. wasn’t restricted until January 31^st. If COVID-19 is as infectious as the public has been warned, how in the world could it not have made its way to U.S. shores between November and the end of January?

Is it not possible to assume that the ILI seen in American hospitals since January -- illnesses that weren't positive for flu but acted like the flu -- could have been untested SARS-CoV-2 (COVID-19) and thus remained unknown? This has been recorded as one of the largest flu seasons in the U.S. since 2009 with hundreds of thousands of cases of ILI collected by CDC surveillance.

When CDC COVID-19 testing data are overlaid on a graph with reported influenza-like-illness data (because ILI numbers were at least two orders of magnitude higher, CDC COVID-19 testing numbers were multiplied by 100 to make a graphic comparison easier to see.), the data curves are strikingly similar. This could indicate that as people exhibiting flulike illnesses (110,554 in week 6) were seen by U.S. physicians unable to diagnose them with a known influenza, physicians with the ability, had ILI patients tested for COVID-19, sending those tests to the CDC for verification.

SARS Ig immunity appears (from non-peer reviewed research) to last for 12 years and continued comparison studies with SARS and SARS-CoV-2 indicates that CoV-2 response will mirror SARS. 

So, though an increase in testing will inevitably capture more cases, if SARS-CoV-2 has been circulating in the population since November and has conferred immunity on surviving patients similar to SARS, the number of cases and COVID-19 deaths should stay relatively low -- and isn’t that what’s being reported in real time? 

It’s important to analyze and remember this scenario as the U.S. emerges from its quarantine cocoon to the inevitable cries from politicians of “But we had to act to keep people safe,” and “If we hadn’t shut everything down the death rate would have been so much worse.”

It’s understandable when situations involving human life elicit emotional responses over the rational. Christian hearts especially are geared to Jesus’ new and most important of all commandments. But it appears that many more lives will be affected by hardships invoked through the current economic freefall than the virus itself. Now is the time to practice appropriate risk assessment for our nation and allow its citizens to get back to work. One day, a pandemic of real consequence will sweep across the globe. People will need to be able to listen to adept and accurate warnings without wondering if they’re hearing the Boy Who Cried Wolf.