Chapter 18 in the R.M. Dolin book, “Truth and Trust in Crisis,” 2021
COVID is the first viral crisis of the digital age possessing unprecedented dependence on data to plan policy and manage mayhem. Before America sees its first COVID death on February 29, 2020, academics project two million Americans are about to die. With an implicit trust in their model’s assertion, we willing accept lockdowns, financial calamity, school closures, and any government mandate deemed necessary for our safety.
Against this dystopian backdrop we begin our scientific journey through COVID by determining if the deadly virus bearing down on us is human engineered and capable of existential calamity. Using high school algebra in a simple four-line spreadsheet, our analysis reveals COVID behaves like a naturally occurring virus, which does not necessarily negate it being manmade. Our model predicts significantly lower COVID deaths than either the UK or UW models accepted as canonical by government and media.
In late March, the White House Coronavirus Task Force, led by doctors Deborah Brix and Anthony Fauci, assert 250,000 Americans will die by April 14th. Shocked by their assertion, we develop two models to independently assess its validity. Our statistical model assumes COVID behaves the same in every country and utilize data from Italy’s crisis to predict 30,500 Americans are likely to die by April 14th. We use our exponential model to project future COVID deaths assuming CDC data is truthful and trustworthy. This model confirms the Brix/Fauci assertion the crisis will reach its apex on April 14th.
When Armageddon day arrives, CDC reports 23,650 Americans have thus far died from COVID, making our off 29% while the Brix/Fauci assertion is off by an astounding 967%. Dismayed they could error by a factor of ten with no one in government, media, or academia challenging the model’s validity, our COVID skepticism is set. It doesn’t seem possible experts could error so profoundly while our simple model is essentially spot-on.
While Brix/Fauci assert COVID’s rate-of-infection is a predictor of future COVID deaths we demonstrate it’s a false flag. Confidence in our model grows as we accurately predict COVID deaths each month from April to September. Meanwhile, the models used as gospel from the UW, Penn, and FEMA are consistently off by as much as 80%, and yet, no one in government, media, or academia challenges them.
Convinced academics and bureaucrats can’t be that incompetent, we suspect CDC misrepresents COVID data. Our suspicions are confirmed when it’s revealed medical professionals are falsifying COVID data. Faced with the realization CDC is not truthful or trustworthy, we seek alternate sources that can be used to ascertain COVID’s true impact. This leads us to actuarial data relied on for planning and risk assessment. Using pre-COVID actuarial projections, we develop multiple models, each providing elements of insight to estimate the likely number of COVID deaths. Our analysis reveals that fewer Americans are dying in 2020 than were expected to die before COVID started, which seems unfathomable, especially given government and media’s hyperbolic efforts to convince us we’re about to die.
On May 13th, with the COVID death count at 81,805, we combine our exponential model with our actuarial analysis to make the bold assertion that the likely number of U.S. COVID deaths is 4,354. We also predict the COVID epidemic in America ends on June 7th. Given media hysteria and government’s panicked warnings, our assertions are challenging, but we trust the math and pitch our flag while seeking validation.
If our assertions hold, it means the crisis is substantially less than being portrayed and will be over in a month. While COVID is real, to put things in perspective, pre-COVID, nearly three million Americans were expected to die in 2020 and on average, 36,000 Americans die each year from flu, and both numbers are accepted as normal.
In July, the CDC announces that in mid-June, COVID deaths dropped below their threshold for epidemics, making our bold assertion spot-on. New York, Pennsylvania, and other states confess to over-counting COVID deaths by as much as 50% and the CDC concludes roughly 97% of all COVID deaths were likely from other causes; validating our other assertion.
As COVID continues into the late summer, we investigate the rationale behind quarantining a healthy population, something never done in the history of pandemics. We cite a Johns Hopkins study finding mitigation measures had little impact on reducing COVID transmission. We demonstrate through design-of-experiment examples, why facemasks do not stop COVID’s spread and cite a CDC study reaching the same conclusion.
While investigating the efficacy of vaccines in general, and the coronavirus vaccines being developed at warp speed in particular, we consider the risks involved in simultaneously administering a new vaccine platform to an entire population without clinical trials. We review data from U.S. Senate testimony that exposes dramatic COVID vaccine side effects the Department of Defense fraudulently tries to obfuscate.
We then address the most unsettling data misrepresentation of the entire crisis. At the end of 2020, the CDC reports that 2,901,480 Americans died during the year, then in 2021, they quietly revise that number to 3,389,094, for an increase of 487,614. Given that death data is easy to count, we seek independent sources for validation, which takes us to the most trusted source for data truth, money.
We examine financial data from death industries, and our analysis reaches two unnerving conclusions. First, funeral home and casket industry revenues are highly correlated, and both underperform their pre-COVID expectations. Second, the CDC’s initial reported number of deaths strongly correlates with death industry data, but their revised death count does not. This leads us to conclude that the CDC can’t account for their additional 487,614 deaths. While it may be due to double counting or clerical error, it conveniently provides necessary cover for politicians who need COVID data to match their panicked rhetoric.
In the digital age, policy decisions and credible crisis management depend on truthful trustworthy data. Unfortunately, Americans find themselves with nowhere to turn for truth and trust, which prompts us to address the most fundamental question of the crisis; why? Why do experts cause such initial panic with dire projections having no observational evidence to suggest COVID contains existential lethality? Why does no one in academia or government question the validity of outrageous predictions that are consistently wrong by factors of ten? Why are doctors incentivized to falsify death data? Why does the media generate mass hysteria while banning all discourse outside of prescribed narratives? For these and all other COVID whys, one simple answer explains everything; it didn’t work.
We’ll likely never learn the truth behind the COVID crisis but will find articles of evidence scattered about. For example, it’s clear the virus was manmade in China’s Wuhan laboratory. The reason for hyperbolic panic early on is government officials know the lethality COVID’s been designed to deliver. Once the virus is released, their response is akin to the reaction one would expect in the aftermath of a nuclear war, only the virus doesn’t work as designed, instead the genetically modified coronavirus winds up behaving like a normal flu virus.
The failure of COVID to perform as designed creates a political dilemma, namely, how do politicians extricate themselves from the corner they panicked everyone into. Only a vaccine can provide such a crisis-ending escape, even if it doesn’t work. As luck would have it, they just happened to have a COVID vaccine laying around built on a revolutionary new platform that massages our DNA; just the kind of antidote one might have when developing deadly viruses.
Then there’s you; I told you when historians finish and fingers are pointed, those fingers will be aimed at you. If there’s one takeaway from our journey through this crisis, it’s that ferreting through lies isn’t all that hard. In many different ways, using data from divergent sources, we never utilize math beyond the high school level. If you feel foolish for being misled; forced to wear facemasks that provide no protection, forced to take a nonvaccine vaccine, forced to keep your kids from school as business get shuttered, forced into useless quarantines, you have only yourself to blame. Imagine how different our COVID experience would have been had you done due diligence and called out the nefarious members of the media, medical profession, government, and academia early in this crisis. Imagine how many lives would have been saved if you held politicians to any modicum of integrity. You and you alone are the most culpable to every hyperbolic mandate you submitted to.
Yes, COVID was real, and yes, people died from the virus, but in the end, it was at best on par with a normal flu season. There will be other viruses and the question we must address is will we allow the government to control our fate, will we let doctors betray our trust, will we believe the media tells the truth. Who will you trust and how will you validate truth in a crisis? Answering that portends your future fate.
Note: This book is based ideas and analyzes from a series of 2020 essays submitted to the NY Times, Washington Post, Chicago Tribune, etc. The essays can be found at: https://rmdolin.com/commentary/
