By Denis Rancourt, Joseph Hickey, and CORRELATION
Here is our latest article for CORRELATION
In it we conclude that, from a scientific perspective, the counterfactual outcomes of Fitzpatrick et al. (2022) used by Peter Hotez to repeatedly make his fantastic and unverifiable claims that millions of lives were saved by the COVID-19 vaccines in the USA have the same value as propaganda.
Original post: https://correlation-canada.org/did-covid-vaccines-save-millions-of-lives-in-usa/
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Did the COVID-19 vaccines save millions of lives in the USA? Quantitative assessment of published claims
Denis G. Rancourt,* PhD , and Joseph Hickey, PhD
Abstract
Many media and public-record statements, including Congressional statements and testimony, since 2022, have often asserted that COVID‑19 vaccination in the USA prevented some 100 million infections, saved some millions of lives, saved some tens of millions of hospitalizations, and saved some 1 trillion dollars in associated medical costs. These fantastic and unverifiable claims are based on theoretical models of so‑called counterfactual scenarios, which are back predictions under hypothetical absence of COVID‑19 vaccination. The said claims are reported in several scientific articles, often in leading scientific journals, however their authors sparingly show and essentially never examine the time evolution of the back predictions for plausibility. We calculate time evolutions corresponding to the back predictions. We show that if one accepts the counterfactual models and their inputs to then calculate the corresponding excess all-cause mortality that would have occurred, then one graphically obtains excess all-cause mortality by time (by week) that is contrary to realistic behaviours. By accepting the counterfactual models, we must believe that the two main COVID-19 vaccination campaigns (doses 1+2 and first-booster dose rollouts, in early and late 2021, respectively) coincidentally were each applied just in time prior to two staggering spontaneous many-fold increases in viral virulence. In other words, we must believe that the massive and repeated COVID-19 vaccine rollouts did not significantly reduce mortality in 2021 and in 2022 compared to 2020 (they actually did not) because the virus became more virulent than ever in those years, twice, in early 2021 and in late 2021―early 2022, producing 5‑fold hypothetical increases in excess all-cause mortality by year. The counterfactual scenarios are so improbable that they can, on the sole basis of the predictions themselves, be qualified as impossible.
Table of contents
1 Context and purpose
On 10 October 2024, Dr. Peter Hotez testified to Congress under legal obligation to tell the truth as follows (transcript, at pages 42-43):
Table 1. Extract of Congressional interview of Peter Hotez, 10 October 2024.
COMMITTEE ON OVERSIGHT AND ACCOUNTABILITY, SELECT SUBCOMMITTEE ON THE CORONAVIRUS PANDEMIC, U.S. HOUSE OF REPRESENTATIVES,
WASHINGTON, D.C.
INTERVIEW OF: PETER HOTEZ
Thursday, October 10, 2024
https://oversight.house.gov/wp-content/uploads/2024/12/Hotez-Final_Redacted.pdf
(accessed 2025-09-16)
(bold highlights added)
2 Staff. … Dr. Hotez …
3 … I want to echo our majority colleagues’ thanks and
4 appreciation for you being here.
5 It goes without saying, but you are one of the Nation’s preeminent experts in
6 vaccines, and so I’d like to take a few minutes to collect your perspectives on some topics
7 in this area, and I’d like to begin with the COVID-19 vaccine specifically.
8 Dr Hotez. Yeah.
9 EXAMINATION
10 BY MR. LICHTMAN:
11 Q Just as a starting point, can you explain the role that the COVID-19 vaccine
12 had in saving lives and reducing suffering from the COVID-19 pandemic?
13 A Yes, I’d be happy to do that.
14 The studies by my colleague and friend Alison Galvani at Yale find that in the
15 United States COVID vaccines probably saved 3.1 or 3.2 million lives and averted 18
16 million hospitalizations.
17 So no question this has had a huge impact on the health of the American people.
18 I mean, if it wasn’t for those vaccines, instead of 1-plus million deaths, it would be 4
19 million deaths. I mean, it just would have been absolutely catastrophic.
20 And, in addition, now we know COVID vaccinations also have other benefits. So
21 this virus is a thromboembolic virus, so it’s not only causing respiratory illness. Now we
22 know it’s causing heart attacks, it’s causing strokes. So the prevention of heart attacks
23 and strokes from vaccination, huge, and also the prevention of long COVID.
24 So absolutely game-changing in terms of its impact in the United States, and the
25 same globally in places where the vaccines were made available. And that’s where we
1 came in, to make the vaccines that the Pharma companies wouldn’t make.
2 Q Of course. And I believe either similar or perhaps the same research out of
3 the Commonwealth Fund also showed that the COVID-19 vaccines significantly reduced
4 medical expenditures here in the United States and helped contain some of those costs.
5 Do you agree with that?
6 A Absolutely. I can’t remember the exact figure but it was really high.
7 Q But despite its historic contributions to moving society past the darkest days
8 of the COVID-19 pandemic, there have been suggestions that COVID-19 vaccines are
9 unsafe.
10 …
Here, “[t]he studies by my colleague and friend Alison Galvani at Yale” and all of this refer to a blogpost by Fitzpatrick et al. (2022) dated 13 December 2022 on the website of The Commonwealth Fund.
The said blogpost (Fitzpatrick et al., 2022) gives results entirely based on counterfactual modelling (that is, back predictions under hypothetical absence of COVID-19 vaccination), without giving sufficient detail to allow scientific verification of either the calculation itself or its inputs, whereas related methods have apparently been used by the authors elsewhere (Pandey et al., 2022; Sah et al., 2022; Vilches et al., 2022a). The claims and the explicit inputs and methods, to our knowledge, have not been explained in a follow-up publication.
The said claims (Fitzpatrick et al., 2022) have been uncritically and disproportionately covered in mainstream media, since its posting and recently, for example, as follows.
New York Times
“How many lives have been saved by Covid vaccines?
Scientists believe that the vaccines have prevented millions of deaths. A study in the journal Lancet Infectious Diseases estimated that the shots saved 14.4 million lives worldwide in the first year alone.
In the United States, they are thought to have prevented more than 18.5 million hospitalizations and 3.2 million deaths by the end of 2022.” (2025-09-02)
https://www.nytimes.com/2025/09/02/health/trump-covid-vaccines.html
CBC
“ “The mRNA technology has been proven to be highly effective,” Hotez said. “By some estimates, 3.2 million American lives were saved by COVID mRNA vaccines during the pandemic.” ” (2025-08-25)
https://www.cbc.ca/news/health/mrna-vaccine-barda-explainer-1.7602830
ABC News
“ “Here’s the bottom line: mRNA vaccines for COVID, according to estimates from Yale School of Public Health, saved 3.2 million lives,” Dr. Peter Hotez, a professor of pediatrics and molecular virology at Baylor College of Medicine in Houston, told ABC News.” (2025-05-23)
https://abcnews.go.com/Health/safety-efficacy-mrna-vaccines-amid-recent-scrutiny/story?id=122068940
CNN
“The Covid-19 vaccines have kept more than 18.5 million people in the US out of the hospital and saved more than 3.2 million lives, a new study says – and that estimate is most likely a conservative one, the researchers say.” (2022-12-13)
https://www.cnn.com/2022/12/13/health/covid-19-vaccines-study
The Hill
“The Commonwealth Fund estimated the vaccines prevented more than 18.5 million hospitalizations and 3.2 million deaths from December 2020 to last month.
Researchers added the vaccines also prevented 120 million more COVID-19 infections and saved the U.S. more than $1 trillion.” (2022-12-13)
Yale School of Public Health (Facebook account)
VIDEO: “A sampling of media coverage of the new Yale School of Public Health and The Commonwealth Fund analysis that found U.S. COVID vaccinations have saved 3 million lives.” (2022-12-19; accessed 2025-09-27)
It is important to rigorously assess influential claims ― both in the context of the body of relevant science and for logic and validity of the underlying assumptions ― because the said claims may be demonstrably incorrect. False claims accepted by government officials and their advisors can have a disastrous effect on public health policy and society. The analysis below shows that Dr. Peter Hotez, in particular, appears not to have critically ascertained the value of the claims in the blogpost of Fitzpatrick et al. (2022) but instead relied on the status of its senior author (his friend; and collaborator, as per Bartsch et al., 2021) and her institution.
2 Nature of the counterfactual exercise
The blogpost results of Fitzpatrick et al. (2022) were obtained by a counterfactual theoretical calculation. In counterfactual analysis (BGI Consulting, 2007) “the outcomes of the intervention are compared with the outcomes that would have been achieved if the intervention had not been implemented.” Here, the intervention is COVID-19 vaccination in the USA. Therefore, the counterfactual theoretical calculations involve back predictions of mortality and other outcomes under hypothetical absence of vaccination. It is impossible to actually know how many people would have died (or been saved) from not being vaccinated. Instead, the number of lives saved is calculated using elaborate theoretical hypotheses and inputs (such as disease characteristics and vaccine efficacy) presumed to be valid.
In order to estimate the number of lives saved, counterfactual modellers need to estimate how many SARS-CoV-2 infections would have occurred through time without vaccination, and how many of these infections would have caused death. Simply put, the vaccine cannot save you if you would not have been infected. This brings us to arguably the most tenuous part of the counterfactual calculation used by Fitzpatrick et al. (2022): The hypothetical prevalence (infections) by time is calculated by contagion dynamics modelling, which has its own assumptions, complexities and uncertainties; not to mention that it may not be applicable whatsoever (Hickey et al., 2025).
The other main difficulty is that the modellers assume in all current vaccine counterfactual calculations that the vaccine efficacy inputs are reliable, despite being produced via contrived, questionable and non-transparent clinical trials (Gøtzsche, 2013; Rancourt, 2025a; Siri, 2025).
Fitzpatrick et al. (2022) concluded that in the USA:
· 3.2 million deaths
· 18.5 million hospitalizations
· 120 million infections
· $1.15 trillion in medical costs
were averted up to 2022-11-30 (two year period) by COVID-19 vaccination.
Using the same kind of counterfactual approach (contagion dynamics modelling + presumed-valid vaccine efficacy estimates), Watson et al. (2022) obtained a similarly fantastic result for the USA (taking the average of their two similar scenarios):
· 1.83 million deaths
averted up to 2021-12-08 (one year period) by COVID-19 vaccination.
The Watson et al. (2022) study has been fundamentally criticized (Rancourt and Hickey, 2023; Ophir et al., 2025; Sorli, 2025).
The counterfactual analysis of Ioannidis et al. (2024, 2025) gives a number of lives saved by COVID-19 vaccination in the USA through 2024 (four year period) that is an order of magnitude (10 times) less than the numbers obtained by Fitzpatrick et al. (2022) and by Watson et al. (2022).
Ioannidis et al. (2024, 2025) obtain 2.5 million lives saved globally through 2024. Using the fractions USA / World of lives saved obtained by Watson et al. (scenario 1: 1.76/14.4 and scenario 2: 1.90/19.8; from their supplementary material), the Ioannidis et al. global value (2.5 million) corresponds for the USA to:
· 270 thousand deaths
averted through 2024 (four year period) by COVID-19 vaccination.
The results of Fitzpatrick et al. (2022) and Watson et al. (2022) on the one hand are irreconcilable on their face with the results of Ioannidis et al. (2024, 2025) on the other hand. Both Fitzpatrick et al. (2022) and Watson et al. (2022) used “contagion dynamics modelling + presumed-valid vaccine efficacy estimates” whereas Ioannidis et al. (2024, 2025) used “seroprevalence data and reported COVID-19 deaths + presumed-valid vaccine efficacy estimates” in the counterfactual method, thus avoiding contagion dynamics modelling.
Rancourt (2025b) critically assessed the papers of Ioannidis et al. (2024, 2025), and finds no reliable reason to belief that the COVID-19 vaccines saved any lives. Nonetheless, it appears that authors can misguide themselves far more with contagion dynamic modelling than with seroprevalence data, as most epidemiologists would expect.
A better way is to devise a method that avoids counterfactual models altogether, and relies solely on measured data, especially higher reliability data such as mortality. This was done by McNamara et al. (2022). They performed an ecological study in which they exploited the established fact that assigned COVID-19 mortality, like all-cause mortality, is highly dependent on age, in fact exponential with age. They cleverly used death in lower age groups to normalize death in the elderly age groups, prior to and during vaccination, in the USA in the period 2020-11-01 to 2021-04-10. In their extensive analysis of the data, McNamara et al. (2022) found a null result: “the magnitude of the impact of vaccination roll-out on deaths was unclear.”
Therefore, in this case the sequence of reliability is:
3.2 million lives saved in two years
LOW reliability
(using contagion dynamics modelling + presumed-correct vaccine efficacy)
▼
270 thousand lives saved in four years
MEDIUM reliability
(using seroprevalence data + presumed-correct vaccine efficacy)
▼
vaccination impact on death not detected
HIGH reliability
(ecological study of age-stratified mortality)
It is not surprising that using contagion dynamics modelling is unreliable for hindcasting anything about the declared COVID-19 pandemic in that Hickey et al. (2025) have demonstrated that high-resolution and global geotemporal variations in excess all-cause mortality are incompatible with viral spread of a respiratory disease.
However, the purpose of the present article is not merely to point out the unreliability of the Fitzpatrick et al. (2022) blogpost, and published articles using the same counterfactual approach (Ogden et al., 2022; Shoukat et al., 2022; Steele et al., 2022; Vilches et al., 2022a, 2022b; Watson et al., 2022; Yamada et al., 2023).
Rather, we provide a proof that the Fitzpatrick et al. (2022) method implies impossible consequences when their counterfactual mortality is plotted by time (deaths per week) over the period of application, irrespective of any criticism of the validity of their method and inputs.
We have previously applied our demonstration of implausibility to 95 countries studied by Watson et al. (2022) (Rancourt and Hickey, 2023). Here, we apply the said demonstration of implausibility in more detail to the USA for the blogpost results of Fitzpatrick et al. (2022). The same holds for all the studies using essentially the same counterfactual approach with comparable presumed COVID-19 vaccine efficacies, such as: Ogden et al. (2022), Sah et al. (2022), Shoukat et al. (2022), Steele et al. (2022), Vilches et al. (2022a, 2022b), Watson et al. (2022), and Yamada et al. (2023).
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