For over two years, I and many others have argued that natural immunity acquired from COVID-19 infection is likely to be far more protective than the COVID jab. Our arguments, despite being based on published research,1 were widely dismissed as dangerous misinformation and a right-wing conspiracy theory.
But now, even NBC News is reporting2 on research showing that natural immunity is "at least as high, if not higher" than that provided by two mRNA injections, and "provides strong, lasting protection against the most severe outcomes of the illness."
Sustained Protection Following Natural Infection
The systematic review and meta-analysis3 in question, published in The Lancet February 16, 2023, included retrospective and prospective cohort studies and test-negative case-control studies that estimated the reduction in COVID-19 risk among those with previous infection, compared to those without previous infection.
Sixty-five studies from 19 countries published prior to September 30, 2022, were included. People with immunity from both infection and the COVID jab were excluded. As reported by the authors:
"Our meta-analyses showed that protection from past infection and any symptomatic disease was high for ancestral, alpha, beta, and delta variants, but was substantially lower for the omicron BA.1 variant.
Pooled effectiveness against re-infection by the omicron BA.1 variant was 45·3% … and 44·0% … against omicron BA.1 symptomatic disease. Mean pooled effectiveness was greater than 78% against severe disease (hospitalization and death) for all variants, including omicron BA.1.
Protection from re-infection from ancestral, alpha, and delta variants declined over time but remained at 78·6% (49·8–93·6) at 40 weeks. Protection against re-infection by the omicron BA.1 variant declined more rapidly and was estimated at 36·1% (24·4–51·3) at 40 weeks.
On the other hand, protection against severe disease remained high for all variants, with 90·2% (69·7–97·5) for ancestral, alpha, and delta variants, and 88·9% (84·7–90·9) for omicron BA.1 at 40 weeks."
So, to reiterate in summary, protection against reinfection among those with previous infection was "very high" and remained high after 10 months. Protection was "substantially lower" for the omicron BA.1 variant, and declined more rapidly than previous variants, but protection against SEVERE disease was still high.
All Is Not as It Seems
While it's good that mainstream media are finally reporting some basic truth, this review, positive as it is, may have intentions other than confirming what many have known all along. The Bill & Melinda Gates Foundation funded this study, and parts of the final interpretation highlights their influence.
"The immunity conferred by past infection should be weighed alongside protection from vaccination when … providing guidance on when individuals should be vaccinated," the authors state.
The findings are also to be taken into account when "designing policies that mandate vaccination for workers or restrict access, on the basis of immune status, to settings where the risk of transmission is high, such as travel and high-occupancy indoor settings."
In other words, while those with natural immunity may be granted a slight reprieve from jab mandates, eventually, this review makes it clear that any such mandates will eventually apply to them as well. It's rather easy to see why Gates might want a study like this.
As time goes on, COVID jab mandates are looking more and more irrational, as the vast majority of people have already been exposed at one point or another and natural immunity has more than likely surpassed the herd immunity threshold already.
People who have gotten the jabs are also starting to realize that they're not working, as many have gotten COVID more than once since getting the shots.
Gates is part of the globalist cabal that intends to implement vaccine mandates worldwide anyway, and this review helps put a time limit on how long unjabbed individuals with natural immunity might be allowed to remain free once vaccine mandates are issued and justifies the need for the COVID jabs even in the face of widespread natural immunity.
Overall, infection-acquired immunity decreased the risk of hospitalization and death from a COVID reinfection by 88% for a minimum of 10 months. For comparison, previous studies4 have shown the efficacy of two COVID shots wanes to BELOW zero by the sixth month, meaning the effectiveness becomes negative, making you more prone to infection than you were before. What's more, the effectiveness of the first booster drops from 57% to 41% within a single month.
Still, senior study author Dr. Christopher Murray, director of the Institute for Health Metrics and Evaluation at the University of Washington — another Gates-funded outfit5,6 — stressed that getting the COVID shot is still preferable to natural immunity, and this, to me, is a telltale sign that Gates is influencing how the results are interpreted and presented.
"The problem of saying 'I'm gonna get infected to get immunity' is you might be one of those people that end up in the hospital or die. Why would you take the risk when you can get immunity through vaccination quite safely?" Murray told NBC News.7
So, while NBC is now reporting what "misinformation spreaders" have been saying all along, they're probably doing so because Gates funded the study and has ulterior motives, and the slant of the reporting still leans pro-jab. Several times, the article stresses that the shots are safe, when real-world data clearly disprove such claims.
COVID Jab Increases All-Cause Mortality Among the Elderly
For example, in a February 25, 2023, Substack article,8 Steve Kirsch reviews U.S. Medicare data — given to him by an unnamed whistleblower — showing the COVID jab increases the all-cause mortality risk among the elderly rather than lowering it.
"The CDC [Centers for Disease Control and Prevention] lied to the American people about the safety of these vaccines. They had access to this data the entire time and kept it hidden and said nothing," Kirsch writes.
"Last night, I got a USB drive in my mailbox with the Medicare data that links deaths and vaccination dates. Finally! This is the data that nobody wants to talk or even ask about.
I was able to authenticate the data by matching it with records I already had. And the analysis that I did on the data I received matches up with other analyses I have received previously.
The nice thing about this Medicare data is that nobody can claim that it is 'unreliable.' Medicare is the unassailable 'gold-standard' database. It's the database that the CDC never wants us to see for some reason. They never even mention it. They pretend it doesn't exist. So you know it is important.
Do you want to know what it shows? It shows that these shots increase your risk of dying and once you get shot, your risk of dying remains elevated for an unknown amount of time. And that's in the very population it is supposed to help the most! …
If nobody can explain how the 'slope goes the wrong way,' then this should be GAME OVER for the vaccination program … The results simply cannot be explained if the vaccines are safe. And the numbers are huge. You don't need a peer reviewed study on this one."
In his article, Kirsch walks you through the data analysis so, for details, please read his original Substack.9 You can download the data in Excel spreadsheet form from Kirsch's article, or play around with it on Alberto Benavidez' Public Tableau. Here, I will simply highlight the key finding, which is that mortality among the elderly rose abnormally after the rollout of the COVID jabs in the first quarter of 2021.
Had the shots been harmless, deaths in the following nine weeks would have declined, as that's the seasonal norm, after which the number of deaths should have stabilized for the next 15 weeks.
As it stands, the mortality risk went up and never came down. The same happened after the second and third doses, although the risk of death after the third dose was not as pronounced as after doses 1 and 2.
According to Kirsch's calculations, the two-dose regimen raised the risk of death by 50% for the first 200 days post-jab. "This is a DISASTER and it's also going to be impossible for the CDC to explain away," Kirsch writes. Cardiac events post-jab were also abnormally high.
UK Data Confirm COVID Jab Harms
Similarly, analysis of data from the Office of National Statistics (ONS) in the U.K. reveals the shots increase all-cause mortality for all age groups, and it's only getting worse over time, all while doing nothing to reduce deaths from COVID specifically.10,11,12,13,14,15,16
According to Kirsch, this is yet another "nail in the coffin" for the COVID jab. Alas, there are major errors and flaws17,18 in the data that allows the British government to claim the jabbed are doing better than the unjabbed, so this nail is still unlikely to seal the proverbial COVID casket shut.
For example, the unjabbed are undercounted by about 50%,19 so in the ONS report, it appears they have somewhat higher mortality than those who got one or more injections. Once the data is corrected, the boosted actually have higher non-COVID mortality than the unjabbed.
In summary, the key findings from the U.K. ONS data set are that excess mortality has steadily risen in 2022 while the attribution of deaths to COVID-19 has steadily declined. So, something other than COVID is killing people at an exaggerated rate, and no one in government can figure out what that is.
A Master's Course in Data Manipulation
The data manipulation that doggedly persistent analysts have unearthed over the past three years truly boggle the mind. Governments around the world have been caught using every conceivable trick to obscure data that would otherwise break the narrative that COVID-19 is a significant threat, early treatment doesn't work and the experimental COVID jabs are safe and effective.
I've covered many (but certainly not all) of these tactics as they were discovered. In closing, here's yet another one.
In the Substack, "Where Are the Numbers?" Norman Fenton (a mathematician and computer scientist) and Martin Neil (a computer science and statistics professor) provide20 a step-by-step guide on how to manufacture "high-efficacy illusions" such as a study that claims the COVID shot is 90% effective even when the jabbed end up getting infected. As noted by Fenton and Neil:
"A major study claimed the COVID vaccines are over 90% effective. But when you look at the details of the study you find that a whopping 37.2% of all vaccinated participants who were tested within 14 days of the first dose were confirmed as COVID cases. None of these 'cases' were counted in the efficacy calculation.
Also, out of the subset of 1,482 participants with confirmed symptomatic COVID, that were part of the study, not a single one died, despite 812 of these being unvaccinated."
Guide to Deceiving the Public About Vaccine Effectiveness
Here's a summary of Fenton's and Neil's five-step "fool proof method to ensure a vaccine will be accepted as highly effective":
1. Employ statistical tricks and biases that result in exaggerated claims, and suppress legitimate criticism.
2. Select a study method that is easier to manipulate, such as test-negative case-control studies, which, by the way, was one of the three types of studies included in the Gates-funded Lancet study above. Then, publish in a "reputable" yet "bought and sold" journal.
3. Ignore COVID infections that occur within 14 days of getting their first jab. These people are not even counted as "partially vaccinated" as they're only partially vaccinated at Day 14 after their first dose. As noted by Fenton and Neil:
"Imagine the most extreme case in which every vaccinated person gets COVID within the first two weeks of their first dose. Then, assuming (as is likely) that none get infected a second time within the 19 weeks, according to the study definition no vaccinated people ever got COVID over the whole period of the study.
If only one person in the the unvaccinated comparative cohort had got COVID, over the same period, the vaccine efficacy (defined as one minus the proportion of vaccinated infected divided by the proportion of unvaccinated infected times 100) will be reported as 100%."
4. Don't test for COVID and/or ignore test results.
5. And lastly, "ignore outcomes that make your vaccine look ineffective." For example, in the study used for this "guide," 1,482 participants tested positive for COVID and had at least one symptom; 812 of them were unvaccinated. Only 2% required hospitalization and there were no deaths, giving us a total infection fatality of zero percent. This important outcome was ignored throughout the paper and was only mentioned once in the detailed results section.
Systematic Biases
Fenton and Neil also list systematic biases that most if not all COVID jab studies suffer from:21
Misclassification — An example of this would be to classify those who tested positive for COVID within 14 days of their first shot as "unvaccinated." Another strategy would be to simply not count them at all. |
Delayed reporting — For example, by delaying the reporting of COVID cases by a week or two during the rollout of the shots, they were able to achieve the same illusory exaggeration of effectiveness as misclassification does. |
Illegitimate comparisons — An example of this is comparing the unvaccinated against the "fully vaccinated" only (based on the definition of fully vaccinated being two weeks or more after the second dose), rather than comparing them against everyone who had received the shot, regardless of time interval since the injection. |
Having different testing protocols for vaccinated and unvaccinated — Such as testing the unvaccinated at more frequent intervals than the vaccinated, and/or testing them even if they're asymptomatic, whereas the jabbed are only tested if they're symptomatic. |
Survivor/selection bias — Neil and Fenton explain: "People who were symptomatic or PCR positive when called for vaccination were recommended to wait until they were PCR negative before being vaccinated; this means that all such people had natural immunity when they did get vaccinated and hence were less likely to subsequently get COVID." |
Study took place during period of naturally falling infection rate — Performing the efficacy study at a time when infection rates are already decreasing creates the statistical illusion of efficacy. |
Vaguely defined outcomes — As noted by Neil and Fenton, "By not being explicit about the outcomes and end dates for the study, many studies can simply choose which outcome makes the 'best case' for the vaccine.
So, in the above example, only in the detailed results do we find there were no deaths (in either the unvaccinated or unvaccinated) and almost no hospitalizations; hence the impact of the vaccine on these key outcomes were conveniently ignored." |
Create the Virus and Get Paid for the Vaccine
In related news, Moderna recently agreed to pay $400 million to the National Institute of Allergy and Infectious Diseases (NIAID) for the patent it holds to its mRNA shot. The patent process is a part of the COVID mRNA shots that the media haven't really addressed.
As it turns out, behind the scenes, the manufacturers not only are fighting with the federal government over the core technology's origins but have been in ongoing litigation over it. Now, Moderna has finally agreed to pay.
According to Fierce Pharma,22 Moderna revealed in its latest earnings statement that the company had agreed to "a $400 million 'catch-up payment' under a new royalty-bearing license agreement between the parties."
So, does the payment hit the company hard? "Moderna pulled down around $36 billion in COVID-19 vaccine sales across 2021 and 2022, its two big launch years," Fierce Pharma said, adding, "While the $400 million payment represents only around 1% of the company's total COVID-19 vaccine sales over that span, the lump-sum nature of the 'catch-up payment' drove up Moderna's fourth quarter's costs."
So, this is quite the racket the NIAID has going. First, it helps create the virus, and then it gets royalty payments for the supposed "vaccine"!