Brownstone Institute
Modeling Gone Bad
From the Brownstone Institute
A new paper documents that the pre-vaccination case fatality rate was extremely low in the non-elderly population.
Age-stratified infection fatality rate of COVID-19 in the non-elderly population
Environmental Research, Volume 216, Part 3, 1 January 2023, 114655
Abstract
The largest burden of COVID-19 is carried by the elderly, and persons living in nursing homes are particularly vulnerable. However, 94% of the global population is younger than 70 years and 86% is younger than 60 years. The objective of this study was to accurately estimate the infection fatality rate (IFR) of COVID-19 among non-elderly people in the absence of vaccination or prior infection. In systematic searches in SeroTracker and PubMed (protocol: https://osf.io/xvupr), we identified 40 eligible national seroprevalence studies covering 38 countries with pre-vaccination seroprevalence data. For 29 countries (24 high-income, 5 others), publicly available age-stratified COVID-19 death data and age-stratified seroprevalence information were available and were included in the primary analysis. The IFRs had a median of 0.034% (interquartile range (IQR) 0.013–0.056%) for the 0–59 years old population, and 0.095% (IQR 0.036–0.119%) for the 0–69 years old. The median IFR was 0.0003% at 0–19 years, 0.002% at 20–29 years, 0.011% at 30–39 years, 0.035% at 40–49 years, 0.123% at 50–59 years, and 0.506% at 60–69 years. IFR increases approximately 4 times every 10 years. Including data from another 9 countries with imputed age distribution of COVID-19 deaths yielded median IFR of 0.025–0.032% for 0–59 years and 0.063–0.082% for 0–69 years. Meta-regression analyses also suggested global IFR of 0.03% and 0.07%, respectively in these age groups.
The current analysis suggests a much lower pre-vaccination IFR in non-elderly populations than previously suggested.
Large differences did exist between countries and may reflect differences in comorbidities and other factors. These estimates provide a baseline from which to fathom further IFR declines with the widespread use of vaccination, prior infections, and evolution of new variants.
From the data above, Median infection fatality rate (IFR) during the PRE-VACCINATION ERA was:
- 0.0003% at 0–19 years
- 0.002% at 20–29 years
- 0.011% at 30–39 years
- 0.035% at 40–49 years
- 0.123% at 50–59 years
- 0.506% at 60–69 years
- 0.034% for people aged 0–59 years people
- .095% for those aged 0–69 years.
These IFR estimates in the non-elderly population are much lower than previous calculations and models had suggested.
Does anyone remember back to early 2020? The dire predictions of a global disaster – of a case fatality rate and of an infectivity rate (R0) that were unheard of in modern times for a respiratory disease? The predictions were that the “novel coronavirus,” as it was called then, was going to be the next Spanish flu. That the only solution was for entire nations to lockdown. This was the modeling that caused governments worldwide to panic. This was the modeling that caused the legacy media to melt down.
One scientist who clearly led this effort and led the world astray with his dire forecasting, was Neil Ferguson, PhD of Imperial College.
Ferguson’s team at Imperial College London has claimed credit for saving millions of lives through the lockdown policies that implemented his models. It is the Imperial College models that projected millions of deaths in the first year in the UK, if stringent lockdowns were not implemented. Once implemented, Ferguson and Imperial college quickly took credit for the “success” of lockdowns.
The estimate of 3.1 million lives saved by Dr. Ferguson was derived from a thoroughly “ludicrous unscientific exercise, whereby they purported to validate their model by using their own hypothetical projections as a counterfactual of what would happen without lockdowns.” Other models and real-world data have discredited Ferguson’s models, but the damage was done. Lockdowns, quarantines, masking, poorly-tested EUA products – such as experimental vaccines have taken their toll on all of us. In the end, what, if any of them were necessary?
Elon Musk calls Ferguson an “utter tool” who does “absurdly fake science.” Jay Schnitzer, an expert in vascular biology and a former scientific direct of the Sidney Kimmel Cancer Center in San Diego, tells me: “I’m normally reluctant to say this about a scientist, but he dances on the edge of being a publicity-seeking charlatan” (National Review).
Again and again, year and year, decade after decade, the NHS and world governments, including our own, have turned to Dr. Ferguson for infectious disease modeling. Ferguson gives them what they want. A reason for the bureaucrats, the administrative state to once more step up and be important. One of his doom-and-gloom models can increase federal disaster preparedness budgets to astronomical proportions. That is raw power for the lowly public health official. What is not to like?
Except for a singular factoid:
Ferguson’s predictions of sky-high high case fatality rates were grossly exaggerated.
The lockdowns were a complete and utter failure.
But this is not Ferguson’s first failed infectious disease modeling stumble upon the world stage. These are two examples of his earlier predictions:
- Ferguson predicted that up to 150 million people could be killed from bird flu during the 2005 outbreak. This prediction was off by an astounding amount, with a grand total of 282 people dying worldwide from the disease between 2003 and 2009.
- In 2009, one of Ferguson’s models predicted 65,000 people could die from the Swine Flu outbreak in the UK — the final figure was below 500. This modeling was what caused so many public health officials to panic, and create a worldwide panic of officials and the populace.
So, why did Boris Johnson and our government turn to his models for guidance early on in the COVID crisis? Why did they accept Ferguson’s assertions that lockdowns would work, without any evidence or public policy guidance indicating that such draconian measures would have any impact whatsoever?
Were they just that naive?
Here is where it gets even crazier. There are those who passionately argue that the modeling that Ferguson did back in early 2020 is proof that 1) the “non-pharmaceutical interventions (lockdowns and masks) worked because (circular logic here) his modeling predictions didn’t come true and 2) that the vaccines worked beyond all measure because again, his modeling predictions didn’t come true.
Yet, here we are. An important new paper (discussed above) documenting that the pre-vaccination case fatality rate was extremely low in the non-elderly population. That means more evidence the Ferguson’s models were wrong (again) and what do we hear from the state-sponsored media?
Crickets.
A colleague of mine who is in the US Senate reported back to me recently that Republican senators were high-fiving each other about the success of Warp-speed based on Ferguson’s modeling data in a recently paper.
You can’t make this stuff up.
Republished from the author’s Substack.
Author
From the Brownstone Institute
In the last weeks of the campaign, Donald Trump is slicing and dicing the Federal income tax nearly as fast as he served up fries at the McDonald’s drive-thru window last weekend. So far, he has proposed to extend the lower rates, family tax credits, and investment incentives of the 2017 Tax Act after they expire in 2025 and to also exempt tips, Social Security benefits, and overtime wages from the Federal income tax.
Those items alone would generate a revenue loss of $9 trillion over the next decade, but he has recently proposed to also exempt firefighters, police officers, military personnel, and veterans from the Federal income tax as well.
We estimate the latter would cost another $2.5 trillion in revenue loss over 10 years. As it happens, there are 370,000 firemen, 708,000 policemen, 2.86 million uniformed military personnel, and 18.0 million veterans in the US. These 22 million citizens have an estimated average income of $82,000 per year, which translates to about $60,000 each of AGI (adjusted gross income). At an average income tax rate of 14.7% these exclusions would generate $250 billion per year of reduced income tax payments.
In all, Trump has thus tossed out promises to cut income taxes by $11.5 trillion over the next 10-year budget window. In turn, these sweeping reductions would amount to upwards of 34% of CBO’s estimated baseline income tax revenue of $33.7 trillion over the period. Alas, even in the halcyon days of Reagan supply-side tax cutting no one really dreamed of eliminating fully one-third of the so-called crime of 1913 (the 16th Amendment which enabled the income tax).
10-Year Revenue Loss:
- Extend the 2017 Trump tax cuts: $5.350 trillion.
- Exempt overtime income: $2.000 trillion.
- End Taxation of Social Security benefits: $1.300 trillion.
- Exempt Tip income: $300 billion.
- Exempt Income of Firemen, Policemen, Military and Veterans: $2.500 trillion.
- Trump Total Revenue Loss: $11.500 trillion.
- CBO Income Tax Baseline Revenue: $33.700 trillion.
- Trump Revenue Loss As % of Baseline: 34%.
Then again, Trump may have something virtually epic in mind. To wit, scrapping the income tax entirely in favor of taxing consumption via levies on imported goods and merchandise.
“In the old days when we were smart, when we were a smart country, in the 1890s and all, this is when the country was relatively the richest it ever was. It had all tariffs. It didn’t have an income tax,” Trump said at a sit-down with voters in New York on Friday for Fox & Friends.
“Now we have income taxes, and we have people that are dying.”
The New York Times is deeply alarmed: “The former president has repeatedly praised a period in American history when there was no income tax, and the country relied on tariffs to fund the government.”
Actually, however, 19th-century America was even smarter than Trump realizes. In 1900 total Federal spending amounted to just 3.5% of GDP because back then America was still a peaceful republic and had no Warfare State or even significant standing army at all. And save for the most advanced precincts of Europe, the Welfare State hadn’t yet been invented, either.
So, yes, the so-called “revenue tariffs” of the 19th century did meet the income needs of the Federal government to the point of actually balancing the budget year after year between 1870 and 1900. Indeed, the actual annual surpluses were large enough to pay down most of the Civil War debt, to boot.
Today, of course, the Warfare State, Welfare State, and the Washington pork barrels account for 25% of GDP. So Trump may be directionally correct in wanting to tax consumption rather than income, but, as usual, he’s off by about seven orders of magnitude when it comes to the size of the Federal budget that needs to be financed.
Still, Trump has stepped up to the plate when it comes to a 21st-century version of the revenue tariff. He has pledged to impose a 20% universal tariff on all imports from all countries with a specific 60% rate for Chinese imports. Based on current US import levels of $3.5 trillion per year from worldwide sources and $450 billion from China, Trump’s tariffs would generate about $900 billion of receipts per annum.
To be sure, Trump’s claim that these giant tariffs would be paid for by Chinamen, Mexicans, and European socialists is just more of his standard baloney. Tariffs are paid for by consumers, but that’s actually the hidden virtue of the Tariff Man’s favorite word.
The truth is, government should be paid for via taxation on current citizens, not fobbed off in the form of giant debts on future citizens, born and unborn. So if we are going to have Big Government at 25% of GDP rather than a 19th-century government at 3.5% of GDP, and Trump is a Big Government Man if there ever was one, better that the burden be placed on consumption, not production, income, and investment.
After all, today the “makers” get hit good and hard by the current exceedingly lopsided income tax system. Thus, the top 1% pays 46% of income taxes, while the top 5% pays 66% and the top 10% pays 76% of all income taxes. On the other end, by contrast, the bottom 50% pays just 2.3% of individual income taxes, while 40% of all families pay no income tax at all.
In any event, the math works out such that the proposed Trumpian revenue tariffs would generate about $9 trillion over the next decade, or nearly 80% of the $11.5 trillion revenue loss from drastically shrinking the income tax coverage and collection rate. So that’s a big step in the direction of fiscal solvency rather than more UniParty free lunches.
To be sure, the proper redirection of Federal tax policy would be a national sales tax or VAT levy, which could be applied to both goods and services and to domestically produced output as well as to imports. Thus, a 5% VAT on the current $20 trillion per year of total PCE (personal consumption expenditures) would generate the equivalent of Trump’s revenue tariff, while a 15% levy on total PCE could replace both the Trump tariff and the remainder of the income tax entirely.
Notwithstanding its shortcomings, however, a revenue tariff is a long overdue start in the right direction. Trump’s bold stance in favor of taxing consumption rather than income and requiring all households to bear the cost of government, not just the small number of producers at the top of the economic ladder, is clearly superior to the status quo.
Still, this sweeping change in the composition and incidence of tax policy doesn’t really put the impending fiscal disaster to bed. Not by a long shot.
If you assume Trump’s big revenue tariffs and sweeping income tax cuts and that the other Federal payroll, corporate, and excise taxes remain the same, 10-year revenues compute to just $60 trillion versus built-in spending of $85 trillion per the CBO baseline. In short, even with a giant Trumpified version of the historical revenue tariff, Trump’s budget plan would still generate $25 trillion of red ink over the next decade.
10-Year Budget Outlook with Trump Tax Cuts and Tariffs, 2025 to 2034:
- Individual income taxes with Trump cuts: $22.0 trillion.
- Trump Revenue Tariffs: $9.0 trillion.
- Existing Payroll Taxes: $20.9 trillion.
- Existing Corporate Tax Ex-Trump Cut to 15% on Manufacturers: $4.6 trillion.
- Other Existing Federal Receipts: $3.5 trillion.
- Total Federal Revenue Under Trump Policy: $60.0 trillion.
- CBO Baseline Federal Outlays: $85.0 trillion.
- 10-Year Trump Deficit: $25.0 trillion.
To be sure, Trump has promised to turn Elon Musk loose on a crusade against government waste and inefficiency, and we say more power to him. If anyone has the courage and smarts to take on the Swamp, surely Elon Musk is at the top of the list.
Then again, Trump has promised to shield 82% of the budget from any cuts at all. That’s right. Elon could huff and puff and shrink the non-exempt programs and agencies by one-third and still leave deficits in excess of $20 trillion over the next decade.
10-year Cost Of Programs Trump Has Championed, Promised Not To Cut or Can’t Cut:
- Social Security: $20.0 trillion.
- Medicare: $16.0 trillion.
- Federal Military and Civilian Retirement Pensions: $2.5 trillion.
- Veterans’ programs: $3.0 trillion.
- National Security Budget: $15.5 trillion.
- Interest On the Public Debt: $13.0 trillion.
- Total Exempt Programs: $70.0 trillion.
- Exempt Programs As % of $85 trillion CBO Baseline: 82%.
In short, even with Trump’s full revenue tariffs and assuming Elon could actually slash 33% of the non-exempt budget without closing the Washington Monument, the bottom-line math leaves little to the imagination. Spending at $80 trillion would amount to 22.7% of GDP, while Trump’s tariff-heavy revenue package would generate $60 trillion of Federal receipts over the next decade, amounting to about 17.0% of GDP.
In turn, that would leave a structural deficit of nearly 6% of GDP as far as the eye can see. And that projection assumes no recession ever again and that interest on a public debt approaching $60 trillion by 2034 would average just 3.3% across the maturity spectrum.
We will take the unders on that proposition any day of the week and twice on Sunday. That is to say, CBO’s projection of $1.7 trillion of annual interest expense by 2034 is likely understated by several trillion. Per year.
In any event, the challenge of financing these giant deficits along with $900 billion per year of Trump tariffs would be considerable. The latter alone would amount to nearly 10% of annual US consumption of consumer goods and fixed investment goods.
So if the Fed were to “accommodate” these massive Trump tariffs by running the printing presses red-hot in an attempt to compensate for lost household purchasing power, it could well trigger a burst of inflation even more virulent than that of 2021-2024.
On the other hand, were it to adhere to the correct sound money solution and refuse to “accommodate” both the massive Trump deficits and the giant Trump tariffs, bond yields, and interest rates would soar, even as the Main Street economy contracted sharply in response to a one-time 10% increase in the general price level.
Financing massive budget deficits honestly in the bond pits rather than at the Fed’s printing presses would also unleash the mother of all meltdowns in today’s insanely inflated financial markets. Trump would therefore get his tariff and some substantial reshoring of industrial production, but also a hair-curling recession on Main Street and a Bronx Cheer from the canyons of Wall Street.
Unfortunately, that’s the price America would have to pay even under Trumpian economics to purge the destructive effects of decades of UniParty spend, borrow, and print policies.
Still, we can actually think of a decidedly worse scenario. To wit, perpetuation of the UniParty status quo, which is what we would get from the Washington ruling party that replaced a failing mind in the Oval Office with an empty one on the Democratic presidential ticket.
A version of this piece appeared on the author’s site.
Author
From the Brownstone Institute
I beg all of you who were or will be offered an influenza vaccination to consider the content of this post when deciding whether to accept.
We have published posts presenting evidence that the influenza threat has been inflated.
The US authorities knew that fraud was essentially taking place, and they bent over backward to defend each other and cover up the scam.
Here’s the first part of the story of why I have suspected and then known about this for at least 25 years.
In the mid-1990s, as the Cochrane Collaboration was starting, some of us in its Acute Respiratory Infection Group started writing protocols for Cochrane reviews on the topics that interested us (Cochrane being then a volunteer bottom-up organization).
In my case, it was influenza and other respiratory agents. So, we wrote protocols and published reviews on the effects (effectiveness and harms) of influenza vaccines (all types of inactivated and live attenuated) on children, adults, asthmatics, the elderly, and those who care for the elderly.
We initially looked only at randomized controlled trials and then bowed to pressure to include observational data. The latter were quickly ditched to preserve our sanity. That’s because observational data, in this case, told you everything and its opposite—not a new story.
I was eventually kicked out of the asthmatics review, but the other four were updated continually until we realised there was no point in going on, and 3 of the reviews were stabilized (no more updates). The three stabilized reviews are:
- Demicheli V, Jefferson T, et al. Vaccines for preventing influenza in healthy adults. 2018
- Jefferson T, Rivetti et al. Vaccines for preventing influenza in healthy children. 2018
- Demicheli V, Jefferson T et al. Vaccines for preventing influenza in the elderly. 2018
- Thomas RE, Jefferson T, et al. Influenza vaccination for healthcare workers who care for people aged 60 or older living in long-term care institutions.
(The fourth review is currently being updated.)
The reviews have been cited several thousand times and read many more times. They include data from 105 (real) placebo-controlled trials involving over 100,000 individuals.
So that’s the background. By this stage, you will be asking: so what?
The so what is that randomised (real) placebo-controlled trials give you a good idea of the incidence of influenza (in the older trials, by a rise in antibody titres and or a viral positive culture isolate). When you pool the data together, you are not looking at one trial or dataset; you are looking at several data sets observed and recorded at the height of the “winter crisis” season.
In the healthy adult’s review, the placebo arm picked up 465 cases out of 18,593 participants. So, of the folks with symptoms, 97.5% were not caused by influenza. No trials were able to detect deaths, and hospitalisations were relatively rare. The trials spanned 50 years of data, so we had all the highs, the lows, and the maybes and even 2 influenza pandemics.
Trials are studies where researchers can control things, verify, and follow up on cases. The placebo arm incidence is essential for an accurate view of what is happening. Models are not required. Once we started looking at the verified influenza deaths in the placebo arm, we saw that the number of cases was in the hundreds. Complications were very rare; for deaths, we found zilch—certainly not the figures put forward by the CDC, which not even Anthony Fauci believed. This fits with the data we showed here and here.
So influenza is rare, loads more agents causing the same signs, symptoms are lumped under the appalling term “flu,” and population interventions such as inactivated vaccines do not stand a chance against a relatively rare moving target like influenza. So you see my mummy was right when she used to say to me: “Tommy darling, never use the F word.”
In the next posts, TTE will explain how and why inflating the threat is essential to keeping unethical bodies like the CDC and the UKHSA going (I mention these two, but they are all at it) and analyse some misleading statements and policies based on deceptive and inflated data.
This post was written by an old geezer who’s been working on this for three decades and hopes that the content of posts like these will be his legacy.
Other Relevant Work
Jefferson T, Di Pietrantonj C, Debalini M G, Rivetti A, Demicheli V. Relation of study quality, concordance, take home message, funding, and impact in studies of influenza vaccines: systematic review BMJ 2009; 338 :b354 doi:10.1136/bmj.b354
Jefferson T. Influenza vaccination: policy versus evidence BMJ 2006; 333 :912 doi:10.1136/bmj.38995.531701.80
Jefferson T, Di Pietrantonj C, Debalini MG, Rivetti A, Demicheli V. Inactivated influenza vaccines: methods, policies, and politics. J Clin Epidemiol. 2009 Jul;62(7):677-86. doi: 10.1016/j.jclinepi.2008.07.001. Epub 2009 Jan 4. PMID: 19124222.
Doshi P. Are US flu death figures more PR than science? BMJ. 2005 Dec 10;331(7529):1412.
Doshi P. Influenza: marketing vaccine by marketing disease BMJ 2013; 346:f3037 doi:10.1136/bmj.f3037
Republished from the author’s Substack
Author
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