Exposing Scientific Fraud and Cover-up – the Case of a Recent CDC-Funded Study
A call for retraction of the article and exposure of academic misconduct
Recently, the Journal of the Pediatric Infectious Diseases Society published some astonishing study results that should immediately merit a moratorium on the genetic injections. The “peer-reviewed” study, funded by the CDC and others, reveals that kids who got the mRNA Covid-19 “vaccines” were, according to almost all metrics used, more likely to get COVID than the unvaccinated.
The study was conducted from Sept 1,2022 to April 30, 2023 in the United States in a prospective manner. Examined were children aged 6 months to 4 years who received various types and doses of the gene-therapy products. Median follow-up time was 154 days, during which they were compared to the unvaccinated peers in terms of either contracting (1) SARS-CoV-2 infection or (2) symptomatic COVID-19. The role of prior infection was also examined.
The authors conclude that, based on their data,
COVID-19 vaccines are recommended to reduce severe illness; the overall risk of infection may not differ substantially between vaccinated and unvaccinated naïve children <5 years.
While the study was circulated and discussed on various social media platforms, I realized that there is likely much more to it. It began to increasingly look like serious scientific fraud. Aiming to investigate if there is something to it, I recently published a preprint on this (NB: the paper by Feldstein et al. is Ref [4] in the preprint).
My preprint begins with the following Abstract (emphasis added):
In the United States, mRNA COVID-19 vaccines were first authorized in June 2022 for children aged 6 months - 4 years with the aim of preventing severe outcomes from COVID-19. However, data on the actual safety and efficacy to prevent infection or severe disease, also in the context of prior exposure to the virus and the emergence of new viral variants, are scarce. To address this extremely urgent issue, Feldstein et al. [4] recently published merged data from 3 prospective cohort studies in children <5 years of age. The information provides valuable insights into the real-world performance of the injections in this age group. In contrast to the author’s highlights of their potential to reduce severe disease, here, an independent analysis that examines the totality of data identifies important insights missed before. The critique done here is exclusively based on the information provided in [4] and identifies the radically opposing narrative given by Feldstein et al., in sharp contradiction to their own findings. This investigation concludes with potential underlying mechanisms to explain some of the underappreciated data by Feldstein and collaborators.
I then also contacted the journal editorial office and the editor-in-chief. Much to my surprise, when I pointed out the actual data, as taken directly from the paper by Feldstein et al., I was told they took issue with these data, the statistics, and the logic I used. My letter to the editor was therefore rejected, even though it used the very same data that were buried in the article.
The main concerns of the article
In my preprint, I highlight the following major concern with the article.
Even though the authors conclude that, based on their data, “COVID-19 vaccines are recommended to reduce severe illness; the overall risk of infection may not differ substantially between vaccinated and unvaccinated na¨ıve children <5 years,” it is found this conclusion is not supported by the information provided in the article.
The more I looked into it, the more I am convinced they must have known their recommendation is not at all aligned with their own findings. In fact, it’s rather the opposite.
Source: https://blog.fdik.org/2024-12/piae121.pdf (pdf of the accepted manuscript)
Based on my analysis, I conclude with the following estimation, contrasting the fabricated statements (see above for a sample from their article) made by the authors with what their study actually showed.
The analysis done above belies the main conclusions made by the authors:
“There was no difference in incidence by vaccination status.” This assertion does not align with the study data which clearly demonstrates the opposite.
“While COVID-19 vaccines reduce severe disease, they may not reduce overall SARS-CoV-2 infections in young children.” Even though the latter part somewhat resembles their actual findings, it is a huge understatement. The data in the paper highlight the antagonistic effects of the injections, displaying negative immune protection.
Likewise, the assertion about severe disease prevention is contradicted by the data provided as the study even showed a further increase in the risk of contracting symptomatic COVID-19 than merely indicating a positive SARS-CoV-2 test. The impact on “severe” disease was not even studied in the paper as “symptomatic” COVID-19 was merely defined as “a positive RT-PCR test and ≥2 COVID-like illness symptoms reported within seven days before or after the specimen collection date). Moreover, as explicitly stated in the paper, “Importantly, the outcomes of infection and symptomatic COVID-19 as defined in these cohorts represent predominantly non-severe disease,” meaning that the authors repudiate their own conclusion.
Details
My preprint lists various stunning details of the scientific misrepresentation by the authors of their own findings. In the article by Feldstein et al.,
The outcome of various study interventions was first determined in terms of incidence of infection/symptomatic COVID-19 per 1000. To further highlight the impact of vaccination, these data are then converted into their respective hazard ratios (HR). These measures delineate the relative risk of an event occurring in one, compared to another, group, such as a control group and a treatment group. (For example, an HR of 3 means that three times the number of events are seen in the treatment group, whereas an HR of 0.333 indicates that the hazard rate in the treatment group is one-third of that in the control group.)
What did I find?
In the study, while some of the HR values were smaller than 1, the majority, including those with greatest relevance, were substantially greater than 1, demonstrating the significantly elevated risk that the vaccinated kids experienced relative to their unvaccinated peers.
As noted, I tried to make the editorial office aware of these concerns, first by sending them my preprint and offering to discuss what I found with the authors. After I had alerted the editor-in-chief about the potential issues, I was told to shorten my preprint and provide a 500-word summary.
I emphasized that my critique solely and exclusively relies on the data provided in Table 2 in the article by Feldstein et al. (NB: in the shortened version, this is Reference [2]).
The core of the short summary, sent as a letter to the editor, is as follows:
Below, only those study results are highlighted where the estimates rely on reasonably justified baselines (Fig. 1(a)). The underlying hazard ratios (HR), which indicate the relative risk of an event occurring in one compared to another group, are taken from Table 2 in [2].
Natural immunity was strong even after 1 year and seems crucial. However, there was no differentiation according to vaccination status.
Vaccination either led to a minimally positive or substantially negative protection (Figure 1(b)).
Compared to Moderna, the Pfizer-BioNTech injection showed an even more negative outcome to get a (symptomatic) COVID-19 infection (Figure 1(b),(c)). For Moderna, kids without prior infection seemed to experience a slightly positive protective effect for symptomatic COVID-19. Yet, as the Adjusted HR (95% CI) was 0.67 (0.16, 2.83), the very large CIs indicate negative protection for some. Notably, Moderna and Pfizer-BioNTech required a disparate number of doses for the primary series (at least 2 vs. least 3), but the drastically disparate outcome between the manufacturers was not explained.
For those without prior infection, the impact of vaccination was essentially always negative (Figure 1(d)).
Ongoing vaccination and rollout of the bivalent boosters 2 months after the study begin obfuscate the durability of vaccine-immunity.
Bivalent boosters did not help against severe disease either: Any protective effect of bivalent boosters was only seen for SARS-CoV-2 infection, but not even for symptomatic COVID-19 (Figure 1(d)).
With time, the protective effect against COVID-19 decreased and their propensity for negative protection increased (Figure 1(b),(d)).
Gigantic Confidence Intervals reaching upper limits of 5, 6, 7, or even over 11, demonstrating extraordinarily elevated risk for some vaccinated kids.
The negative effect may be worse for “prevention of symptomatic COVID-19” than that of SARSCoV-2 infection alone (Figure 1(b)).
The figure mentioned above, which just summarizes the main data by Feldstein et al. is the following:
(For a more in-depth analysis, please see my preprint: https://osf.io/preprints/osf/ek4yv)
For clarity, as also sent in the letter to the editor, a figure legend was added:
Figure 1: Summary of the main findings by Feldstein et al. [2]. For details, including the corresponding CIs, see Table 2 in [2]. (a) Baselines used by Feldstein and colleagues [2]. In the study, not all relevant comparisons are given (missing ones are in red) while some use an inappropriate reference population (indicated in violet). (b) Hazard ratios (HR) by manufacturer and time since last injection: The HRs explicitly show how “vaccination” decreased or increased the risk of getting (symptomatic) COVID-19 when contrasted with the unvaccinated (baseline indicated in red). (c) Analogous to (b), with no participants having any prior immunity (“na¨ıve”). The HRs explicitly show how “vaccination” of kids without prior infection decreased or increased the risk of getting (symptomatic) COVID-19 when contrasted with the unvaccinated without prior infection (baseline indicated in red). (d) Analogous to Figure (c), involving immune “na¨ıve” participants, by the timing of receipt/utilization of bivalent boosters.
Conclusion
I cannot believe Feldstein et al. had not understood about the damning reality of their own findings. The data in their publication are crystal clear. Altogether, they have 2 detailed tables. Perhaps they count on the fact that people no longer have time to read details, let alone scrutinize what can be found in those tables — which the authors purport to summarize and explain in their article!
It’s impossible to believe they did not know their data revealed the exact opposite of what they wrote in the text.
That they knowingly covered up and skewed their findings is even more likely considering who funded the study. Indeed, it is worth noting the long list of authors and funders. Stunningly, there is also one full page filled with names that are acknowledged for support. I have never seen such a long Acknowledgment section! No way that there was not at least one person who realized the radical misrepresentation of their data.
I am also pretty sure that the editorial office of the journal must have received some push-back after the paper was published. Ironically, after it first appeared, the paper was still freely accessible, including the tables. The article was soon withdrawn from free access. Yet, the abstract of their article is still openly accessible. And sure enough, it concludes with
“There was no difference in risk by vaccination status. While vaccines reduce severe disease, they may not reduce SARS-CoV-2 infections in naïve young children.”
This is a grave understatement as their data clearly demonstrated the opposite. No need to say that something may or may not happen if the study findings were extremely clear. The first claim is a lie altogether.
In all, the actual data by Feldstein et al. unambiguously reveals:
(1) Overall, a negative effect of the injections when it comes to protection against SARS-CoV-2,
(2) which is even further pronounced in the case of protection against symptomatic COVID-19.
(3) The inability of bivalent boosters to make a positive difference.
(4) A marked difference between Moderna and Pfizer/BioNTech.
In my preprint, I suggested several mechanisms that may help explain some of the above. When shorted and summarized some in the letter, the EiC took offense, among others, as I relied on a preprint as a literature source.
When presented with the very same data as in the published paper, my letter was rejected, essentially on the grounds that it lacked clear statistics and baseline determinations, etc. Did they really not believe I had taken the data exclusively from the Table in the paper?!
I wrote a rebuttal to the EiC. Will he read it and respond?????
What I find truly astonishing is that the very same data – clear numbers – can be interpreted in such a radically opposing way, and the elite seems to believe that nobody will notice.
(Sample table entries copied from from https://blog.fdik.org/2024-12/piae121.pdf)
For those interested, the accepted manuscript by Feldstein et al. can be found here.
In sum: the study by Feldstein et al. revealed what they did not like. Instead of telling the truth, they falsify these unwanted facts. When exposed, the journal rejected the facts that expose the very same data, possibly believing I made these up.
All these are very strong indicators of scientific fraud and collusion between the authors, funders, and others. If you agree, please share and help expose this apparent deception.
You're not alone in what you describe! My sincere wish is that you all hook-up and find the support you need/deserve & hopefully this link provides something towards that.
Respect♥️….
https://jessicar.substack.com/p/university-institution-intentions