"Don't let anyone gaslight you on VAERS" by Steve Kirsch

 

Click here for Exit the Cuckoo's Nest's posting standards and aims.  Click here to sign the People's Proclamation and send it to everyone you know. Source: Steve Kirsch's Newsletter Don't let anyone gaslight you on VAERS The data in VAERS can be used to prove the vaccines are killing people. Don't let anyone tell you otherwise. Here's how to respond to all their arguments and turn the tables on them. STEVE KIRSCH MAY 3   SHARE   Figure 1. Death reports in VAERS. Can you spot the unsafe vaccine? If you can’t, you can get a job as a “fact checker” for any mainstream media. Or a job in safety monitoring at the CDC! Despite what the CDC wants you to believe, the higher red bars are not due to social media hype, more doses, or different reporting requirements. I can’t get anyone on the record to explain the cause of this. Executive summary The single most devastating piece of evidence showing that the COVID vaccines have killed hundreds of thousands of Americans is the data in the VAERS system. Why? Because it’s the ground zero reporting system for adverse events for vaccines in the US. This is why fact checkers are so diligent in attacking any articles that use the VAERS data to make a claim that is counter-narrative. In this article, I will arm you with the tools you need to debunk the fact checkers and turn the tables on them so they are caught in their lies. They will claim this is just over-reporting of “background events” caused by a rule change and social media exposure in combination with more people getting vaccinated and a shift to older people who are more likely to die. It sounds plausible, but they never provide the math to “check” that their explanation can explain the data. The key word is NEVER. They basically hope that everyone buys the hand-waving argument and nobody actually checks the math. While all of those statements are true, you have to show causality. For example, just because there is a rule change doesn’t mean that anyone notices it and actually changes their behavior to produce a different outcome. Can you name a single hospital which instructed doctors on the new VAERS rules and required them to report all the new incidents? So basically, debunking these “fact checkers” is as simple as calling their bluff and asking to see the evidence for their claims and asking them to explain other observations that are easily verifiable that are inconsistent with their hypothesis. Keep in mind that you cannot have it both ways. There is only one truth here. The correct hypothesis is the hypothesis which is a better fit to all the available evidence from all sources. The counter-arguments demonstrating VAERS is not simply “over-reported” How can you prove the data in VAERS shows the vaccines are killing people? Because there is simply no other way to explain the massive number of death reports. Here are a few argument that their claims that the vaccine is perfectly safe don’t match up with observations: In 2021, there were 525 deaths reported for all vaccines combined (which was atypically high), but 22397 for the COVID vaccine alone. So that’s a 42X differential. Show me the data you have explaining how you can close that gap based on the reasons you cited. I had an independent survey of healthcare workers (who are responsible for the majority of the reports in VAERS) done and it showed that their propensity to report events to VAERS didn’t change over time. So the behavioral change you thought was there, wasn’t actually there. Is there data showing my survey is wrong? If you read the text of dozens of death reports in VAERS (something few people take the time to do; they prefer to opine definitively on VAERS without spending hours doing searches and reading the records), you find that some people died, who would not be normally expected to die, right after the injection. While that might happen by chance, it’s happening at a higher frequency than would normally be expected. You can see the difference in this chart which is flu vaccines over the entire 30 year history of VAERS vs. the COVID vaccines: The adverse event report mix in VAERS doesn’t match what would be expected if these are just background deaths (the plot of AE’s on the X axis and event count on the Y axis doesn’t have the same shape as a “safe” vaccine). So you clearly are not reporting background deaths. I don’t see how you can counter this argument, but I’m willing to be educated. Over 770 safety signals were triggered (including death) which is unprecedented. And the CDC didn’t notify the public. The mainstream media and medical community didn’t think this was a problem. Do you have an issue with that? Did you speak out about it? Note that safety signals are only triggered when there is a significantly disproportionate increase in an adverse event. So if these are all just background events and there is just an increase in the rate of reporting, there would be no triggering of safety signals at all. This should have set off alarm bells, but the medical community and the CDC looked the other way. Why did they ignore it? The CDC could make a hand-waving argument that the EUA reporting requirement shifted the mix of reports to certain types of events (thus generating a safety signal because of the disproportionality), but where is the evidence that anyone’s reporting behavior was skewed by that requirement? Instead, doctors simply continued to report what they saw, regardless of the rules (required vs. optional). Kid deaths reported to VAERS don’t match the normal way kids die. The reporting requirements cannot skew this because this is not a safety signal test; this is a comparison with the normal causes of death of young people. Here, teenagers are dying from bleeding the brain as a common cause of death. Since when has bleeding in the brain been one of the top causes of death for kids? There is no explanation for this. The CDC reported the mix of causes and refused to comment on how abnormal the mix was. This should be very troubling to everyone because it shows that the CDC has a blind eye when kids are killed by the vaccine. Everyone looked the other way. Explain to me how this is normal. The ratio of male-to-female deaths doesn’t match the underlying male:female death rate for a given age range that existed at the time of the death (either for all deaths or non-COVID deaths). There is no male vs. female bias in making VAERS reports. How do you explain this? Doctors are noticing a 10X higher rate of AEs in vaccinated patients vs. unvaccinated patients. There is the issue of doctor observations where some doctors who never needed to file a VAERS report in the past, now are seeing over a 1,000-fold increase in reportable events (and not because of the rule change). If the vaccine is safe, how do you explain this? This is not over-reporting because the doctor is reporting more because there are more events. Explain how this can happen. The gold-standard CMS data shows that deaths in people who were vaccinated don’t match background deaths. It’s supposed to “flatten” any COVID humps, i.e., decrease deaths. But the CMS data shows deaths go up after vaccination when the background death rates are going down. If the vaccine is safe, how do you explain this? I’ve made the Medicare data public and nobody has come forward to explain that the data is showing the vaccine is safe. Why not? If nothing is wrong, why is CDC withholding the autopsy reports as requested by Aaron Siri? Shouldn’t the death investigations be made public? Is there a benefit to keeping these investigations secret? We were told by the CDC that the vaccine is safe to take in pregnancy. That’s nice. But the Pfizer study of the vaccine for use in pregnancy didn’t conclude until July 15, 2022. Shouldn’t the CDC have waited? And why haven’t the results of that trial been made public yet since it’s now been nearly a year since the trial completed? Surely, they must know something by now? Why the silence? How come menstrual issues for the COVID vaccines are off the charts in VAERS (around 1,000X normal)? That cannot be just elevated background reporting because it is disproportionate. Please explain. Pulmonary embolism rates are about 1,000X normal. How can that be just “over-reporting”? If nothing is wrong, why has the CDC NEVER done the proper stains on the tissue samples of people who died after they got vaccinated? That would be dispositive. Why doesn’t the NIH fund a study to look at 100 bodies of people who died within 30 days of their last COVID vaccination. They’d do the proper stains on each body and report the results. We’d know instantly. Is it really better to not do this study and see if people can guess who is right? The Schwab study showed at least 14% of the people who die within 20 days of the vaccine were killed by the vaccine. Peter McCullough believes the rate could be higher than 70%. If this is just over-reporting, then how come multiple polls of households done by different organizations all find the same thing: that the vaccine has killed a comparable number of people as the virus. The latest poll was done by Rasmussen. Why do large scale studies (such as Rancourt, Skidmore) show the VAERS estimated death rate is the same as the death rate estimated from the VAERS data? Why is there a male/female skew if the vaccine isn’t killing people? Extended: Analysis of COVID-19 Vaccine Death Reports from the Vaccine Adverse Events Reporting System (VAERS) Database showed the following for the cases they analyzed (fewer in 2021 than the latest analysis in 2022): 2021 female deaths 96, male deaths 154 2022 female deaths 457, male deaths 544. The biggest disparity in favor of males is as you get into the younger age groups. Every death below 15 years of age in the dataset at the time was male. So this can’t be over-reporting since it would have a more even mix of males and females. There are no positive anecdotes. We couldn’t find a single funeral home, nursing home, or geriatric practice anywhere in the world where adverse events and deaths went down after the vaccines rolled out. The negative anecdotes are stunning. For example Wayne Root held an event attended by an equal number of vaccinated and unvaccinated friends. A year later, there were 52 serious injuries/illnesses (including 12 deaths) in the vaccinated group vs. 3 deaths in the unvaccinated group. In the Pfizer Phase 3 study, the people in the vaccine group were 31% more likely to die than those in the placebo group (all-cause mortality). Why didn’t Pfizer do the proper stains on the people who died in the vaccine arm to assess whether or not the vaccine killed them. Instead, they took the advice of the investigators who had a clear conflict of interest. This is irresponsible. The FDA should have demanded to see the histopathology on everyone who died, but instead the FDA chose to look the other way. The precautionary principle of medicine requires us to take all of these observations above seriously and consider that the vaccine is unsafe until proven otherwise. All you have to do to figure out whether the vaccine is dangerous or not is to pick up the phone and talk to an honest doctor who trusts you (otherwise, they’ll play it safe and say nothing). In my case, I chatted with a neurologist with a 20,000 patient neurology practice close to where I live to get a sense of what is going on. She said that in the 11 years of the practice, they’ve never needed to file a single VAERS report. This year, they need to file over 1,000. Why? Because the side-effect profile of the vaccine is off-the-charts, not because of a rule change or social media. I spoke to another doctor who has been in practice for 35 years and he’s never in his career seen anything like this vaccine in terms of negative impact on his patients. He spent the next 15 minutes rattling off the adverse effects of at least 23 of his vaccinated patients that started after they got vaccinated. He said, “Thank you for listening, there are so many, these are just some of what I recall.... I know statistically things happen in life, but in 38 years I’ve never seen so many conditions in a condensed time, that right there tells us the answer!!!” Those were his exact words. He estimated that 10% of his 300 patients who took the vaccine were adversely impacted by the vaccine. This is simply not consistent with a “safe and effective” vaccine that is simply being over-reported to VAERS. Understanding how fact checkers work In general, most of the arguments used by fact checkers in the COVID era are hand-waving arguments or expert opinion with either absolutely no evidentiary basis or references to a flawed study without mention of contradictory studies. For example, the CDC used the same technique (“it’s just over-reporting”) with the HPV vaccine and the authors of Turtles All the Way Down mentioned this as well. The fact checkers talk to experts who will say something like “the association between death and the COVID vaccine has never been established” even when it pops out like a sore thumb if you do a VAERS query. The COVID narrative “fact checkers” never consult with experts on both sides of the issue in doing their fact check. They will only quote experts who oppose the fact being checked, never any experts who support the fact. I’m not aware of a single counter-example. So it will always be a one-sided presentation. This isn’t journalism; it’s “propaganda.” In general, to counter their argument, you simply say, “Oh really? What actual evidence do you have in support of the statement you just made? Opinions, even when from experts, don’t count. Can you show me the actual data that backs up what you just said?” Don’t let them get away with an insufficient answer. For example, they’ll say “it’s overreporting” and you’ll ask for proof and they’ll say “rule change.” Sounds good, but insufficient. You have to prove that it was the rule change that caused the over-reporting. They never do that. And they never fact check themselves on their explanation. A WORD OF CAUTION When you insist on seeing the data rather than trusting experts like they want you to do, you can get hit pieces written about you like the one that I got that appeared in MIT’s Technology Review . On the other hand, thanks to that one article, I’m now the top hit on Google when you type “misinformation superspreader.” It’s nice to be the best in the world at something! And all I did to get there was to insist on seeing the data as the basis for my opinion rather than trusting people’s opinion! It was so easy. An example: A VAERS fact check from factcheck.org Consider the following VAERS “fact check”: Increase in COVID-19 VAERS Reports Due To Reporting Requirements, Intense Scrutiny of Widely Given Vaccines The essence of the fact check is that all the huge numbers of adverse event reports in VAERS is because: The reporting requirements for the EUA vaccines are more inclusive so more reports will be filed. Note: the first part of this sentence is true (see link to the VAERS reporting requirements), but the second half is an assumption with no evidentiary support. Due to social media, people are more aware of VAERS so they’ve reported more More people were vaccinated in total More elderly and sick people were vaccinated than normal and so there is absolutely nothing to worry about. This sounds plausible if you don’t ask the next level of question which is: “Does this explanation fit the observed data?” The fact checkers never go there. Once they have their hand-waving argument that sounds good, there is no need to actually ask to see if it actually can explain the data (a 42X higher death rate than all other vaccines combined in the same year). For example, can they show that healthcare workers are now making 42 death reports when in the past they only made 1? Some more insight into VAERS Some people have claimed that VAERS numbers are up because social media attention is causing individuals to report at a huge rate. These claims always come without any evidentiary support. VAERS actually has a field for the reporter type, but this field is not exposed to the public! Apparently, the CDC has determined that providing greater transparency into the reporter mix is not beneficial to public health outcomes. I have no clue why they think this and of course, they never answer any of my questions. To find out the mix of consumer reports for domestic VAERS reports, we can do VAERS queries such as asking for “father” or “mother” in the body of the report. These keywords are typical of a self-report. The percentages of such reports are very small. In addition the ratio of domestic to foreign reports has remained constant and the foreign reports are around 96% from healthcare providers. So that’s further confirmation. So it doesn’t appear that there has been a huge influx of consumer reports into VAERS. If there was, I’m open to seeing evidence of that. Summary I made a list of over 25 items that would have to be explained away in order to convince me and my colleagues that the COVID vaccines are safe and that there is nothing to see in VAERS. I’m hoping someone will answer these questions and show me how I got it wrong. The sooner the better.

Click here for Exit the Cuckoo's Nest's posting standards and aims.  Click here to sign the People's Proclamation and send it to everyone you know. CDC Finally Released Its VAERS Safety Monitoring Analyses for COVID Vaccines via FOIA Popular Rationalism cross-posted a post from Jackanapes Junction James Lyons-WeilerJan 4 · Popular Rationalism Josh summarizes the jaw-dropping findings that CDC had - but didn't share - that Epoch Times had to FOIA for. This is HUGE. Epoch Times has made the data files available. CDC Finally Released Its VAERS Safety Monitoring Analyses for COVID Vaccines via FOIA And now it's clear why they tried to hide them. JOSH GUETZKOW JAN 4   SAVE   SUMMARY CDC’s VAERS safety signal analysis based on reports from Dec. 14, 2020 – July 29, 2022 for mRNA COVID-19 vaccines shows clear safety signals for death and a range of highly concerning thrombo-embolic, cardiac, neurological, hemorrhagic, hematological, immune-system and menstrual adverse events (AEs) among U.S. adults. There were 770 different types of adverse events that showed safety signals in ages 18+, of which over 500 (or 2/3) had a larger safety signal than myocarditis/pericarditis. The CDC analysis shows that the number of serious adverse events reported in less than two years for mRNA COVID-19 vaccines is 5.5 times larger than all serious reports for vaccines given to adults in the US since 2009 (~73,000 vs. ~13,000). Twice as many mRNA COVID-19 vaccine reports were classified as serious compared to all other vaccines given to adults (11% vs. 5.5%). This meets the CDC definition of a safety signal. There are 96 safety signals for 12-17 year-olds, which include: myocarditis, pericarditis, Bell’s Palsy, genital ulcerations, high blood pressure and heartrate, menstrual irregularities, cardiac valve incompetencies, pulmonary embolism, cardiac arrhythmias, thromboses, pericardial and pleural effusion, appendicitis and perforated appendix, immune thrombocytopenia, chest pain, increased troponin levels, being in intensive care, and having anticoagulant therapy. There are 66 safety signals for 5-11 year-olds, which include: myocarditis, pericarditis, ventricular dysfunction and cardiac valve incompetencies, pericardial and pleural effusion, chest pain, appendicitis & appendectomies, Kawasaki’s disease, menstrual irregularities, vitiligo, and vaccine breakthrough infection. The safety signals cannot be dismissed as due to “stimulated,” exaggerated, fraudulent or otherwise artificially inflated reporting, nor can they be dismissed due to the huge number of COVID vaccines administered. There are several reasons why, but the simplest one is this: the safety signal analysis does not depend on the number of reports, but whether or not some AEs are reported at a higher rate for these vaccines than for other non-COVID vaccines. Other reasons are discussed in the full post below. In August, 2022, the CDC told the Epoch Times that the results of their safety signal analysis “were generally consistent with EB [Empirical Bayesian] data mining [conducted by the FDA], revealing no additional unexpected safety signals.” So either the FDA’s data mining was consistent with the CDC’s method—meaning they "generally" found the same large number of highly alarming safety signals—or the signals they did find were expected. Or they were lying. We may never know because the FDA has refused to release their data mining results. INTRODUCTION Finally! Zachary Stieber at the Epoch Times managed to get the CDC to release the results of its VAERS safety signal monitoring for COVID-19 vaccines, and they paint a very alarming picture (see his reporting and the data files here, or if that is behind a paywall then here). The analyses cover VAERS reports for mRNA COVID vaccines from the period from the vaccine rollout on December 14, 2020 through to the end of July, 2022. The CDC admitted to only having started its safety signal analysis on March 25, 2022 (coincidentally 3 days after a lawyer at Children’s Health Defense wrote to them reminding them about our FOIA request for it). Like me, you might be wondering why the CDC waited over 15 months before doing its first safety signal analysis of VAERS, despite having said in a document posted to its website that it would begin in early 2021—especially since VAERS is touted as our early warning vaccine safety system. You might also wonder how they could insist all the while that the COVID-19 vaccines are being subjected to the most rigorous safety monitoring the world has ever known. I’ll come back to that later. First I’m going to give a little background information on the analysis they did (which you can skip if you’re up to speed) and then describe what they found. BACKGROUND ON SAFETY SIGNAL ANALYSIS Back in June 2022, the CDC replied to a Freedom of Information Act (FOIA) request for the safety signal monitoring of the Vaccine Adverse Events Reporting System (VAERS)—the one it had said it was going to do weekly beginning in early 2021. Their response was: we never did it. Then a little later they said they had been doing it from early on. But by August, 2022, they had finally gotten their story straight, saying that they actually did do it, but only from March 25, 2022 through end of July. You can get up to speed on that here: Jackanapes Junction The CDC Gave Me Whiplash Here’s a long overdue update on the ongoing saga with the CDC’s safety signal fiasco. Strap in—it’s a rollercoaster of a ride. To refresh your memory, on June 16 , in a response to a FOIA request I submitted together with Children’s Health Defense, the CDC admitted that they had not monitored VAERS for safety signals from the COVID-19 vaccines, although… Read more 4 months ago · 87 likes · 20 comments · Josh Guetzkow The analysis they were supposed to do uses what’s called proportional reporting ratios (PRRs). This is a type of disproportionality analysis commonly used in pharmacovigilance (meaning the monitoring of adverse events after drugs/vaccines go to market). The basic idea of disproportionality analysis is to take a new drug and compare it to one or more existing drugs generally considered safe. We look for disproportionality in the number of adverse events (AEs) reported for a specific AE out of the total number of AEs reported (since we generally don't know how many people take a given drug). We then compare to existing drugs considered safe to see if there is a higher proportion of particular adverse events reported for the new drug compared to existing ones. (In this case they are looking at vaccines, but they still use PRR even though they generally have a much better sense of how many vaccines were administered.) There are many ways to do disproportionality analysis. The PRR is one of the oldest. Empirical Bayesian data mining, which was supposed to be done on VAERS by the FDA, is another. The PRR is calculated by taking the number of reports for a given adverse event divided by the total number of events reported for the new vaccine or the total number of reports. It then divides that by the same ratio for one or more existing drugs/vaccines considered safe. Here is a simple formula: So for example, if half of all adverse events reported for COVID-19 vaccines and the comparator vaccine(s) are for myocarditis, then the PRR is 0.5/0.5 = 1. If one quarter of all AEs for the comparator vaccine are for myocarditis, then the PRR is 0.5/0.25 = 2. Traditionally, for a PRR to count as a safety signal, the PRR has to be 2 or greater, have a Chi-square value of 4 or greater (meaning it is statistically significant) and there has to be at least 3 events reported for a given AE. (This also means that if there are tons of different AEs reported for COVID vaccines that have never been reported for any other vaccine, it will not count as a safety signal. I found over 6,000 of those in my safety signal analysis from 2021. Of course a safety signal does not necessarily mean there is a problem or that the vaccine caused the adverse event. But it is supposed to set off alarm bells to prompt closer inspection, as in this CDC pamphlet: Ah yes, shared with the public — after first refusing to share the results and months of foot-dragging following repeated FOIA requests! We will see that the CDC has not done a more focused study on almost any of adverse events with “new patterns” (AKA safety signals). SO WHAT DID THE CDC ACTUALLY DO? The Epoch Times obtained 3 weeks of safety signal analyses from the CDC for VAERS data updated on July 15, 22 and 29, 2022. Here I will focus on the last one, since there is very little difference between them and it is more complete. The safety signal analysis compares adverse events¹ reported to VAERS for mRNA COVID-19 vaccines from Dec. 14, 2020 through July 29, 2022 to reports for all non-COVID vaccines from Jan 1, 2009 through July 29, 2022. PRRs are calculated separately for 5-11 year-olds, 12-15 year-olds and 18+ separately. For each age group, there are separate tables for AEs from all reports, AEs from reports marked serious and AEs from reports not marked as serious.² Recall that a serious report is one that involves death, a life-threatening event, new or prolonged hospitalization, disability or permanent damage, or a congenital anomaly. I will focus on the reports for all AE’s. They also have a table that calculates PRRs by comparing reports for the Pfizer COVID-19 vaccine to reports for the Moderna vaccine and vice versa, again for all reports, serious reports only and non-serious reports. There were no remarkable findings in those tables, so I will not discuss them. This isn’t that surprising since both vaccines are very similar and so should present relatively similar adverse events when compared to each other, and any differences are likely not large enough to be picked up by a PRR analysis. The CDC seems to have calculated PRRs for every different type of adverse event reported for all the COVID vaccines examined - though it’s possible they only analyzed a subset. What seems clear is that, among the AEs they examined, the only ones included in the tables satisfy at least one of two conditions: a PRR value of at least 2 and a Chi-square value of at least 4 (Chi is the Greek letter χ and is pronounced like ‘kai’). When both conditions were met, they highlighted the adverse event in yellow, which appears to indicate a safety signal. There were no COVID vaccine AEs listed with fewer than 3 reported events, though for non-COVID vaccines there were many AEs listed that had only 1 or 2 reported since 2009. The CDC tables still include these and highlight them in yellow when the PRR is greater than 2 and the Chi-square value is great than 4, indicating these events are counted as safety signals. WHAT SAFETY SIGNALS DID THE CDC FIND? I’m going to divide this up by age groups and the Pfizer v. Moderna comparison. Let’s start with the 18+ group. There are 772 AEs that appear on the list. Of these, 770 are marked in yellow and have PRR and Chi-square values that qualify them as safety signals. Some of these are new COVID-19 related codes, and we would expect those to trigger a signal since they didn’t exist in prior years to be reported by other vaccines. So if we take those off, we are left with 758 different types of non-COVID adverse events that showed safety signals. I grouped these 758 safety signals into different categories. The figure below shows the total number of AEs reported for each of the major categories of safety signals: Let’s dig into some of these categories to look at what types of AEs generated the most number of reports:³ You can peruse the adverse events using the Excel tables provided by the CDC, which were posted by The Epoch Times and Children’s Health Defense at the links at the top of this post. What about The Children? If there is anything that looks remotely like a bright spot in all of this is that the list of safety signals for 12-17 and 5-11 year-olds is much shorter than for 18+. There are 96 AEs that qualify as a safety signal for the 12-17 group and 67 for the 5-11. When we take out the new COVID-era AEs, there are 92 safety signals for 12-17 year-olds and 65 for 5-11 year-olds. Here are the most alarming ones: I don’t know why the list of AE’s is so much shorter for these age groups. It could be that the list of AE’s for other vaccines for these age groups is much shorter, so in a case where AEs have been reported for the mRNA COVID vaccines but not for other vaccines, it will not be counted as a safety signal by definition. COMPARISONS TO MYOCARDITIS & PERICARDITIS We are told that the existence of a safety signal doesn’t necessarily mean the AE is caused by the vaccine, and I accept that premise. But the current practice seems to be to ignore safety signals, dismiss them as noise without any evidence, and stall any investigation into them as long as possible. The precautionary principle, however, dictates we should presume that a safety signal indicates causality, until proven otherwise. Since, it has been acknowledged that the mRNA COVID vaccines can cause myocarditis and pericarditis (often referred to as myo-pericarditis), we can take those AEs as a kind of benchmark, and propose that, at minimum, any AE with a signal of equal or greater size should be considered potentially causal and investigated more thoroughly.⁴ After dropping the new COVID-era AEs, there are 503 AEs with PRRs larger than myocarditis (PRR=3.09) and 552 with PRRs larger than pericarditis (PRR=2.82).⁵ This means that 66.4% of the AEs had a bigger safety signal than myocarditis and 77.3% were larger than pericarditis. You can see what those were by use this Excel file provided by the CDC and sorting the 18+ tab by the 12/14-07/29 PRR column (Column E). Then just look at which AEs have PRRs larger than the ones for pericarditis and myocarditis. For 12-17 year-olds, there is 1 safety signal larger than myocarditis (it’s ‘troponin increased’) and 14 safety signals larger than pericarditis (excluding myocarditis), which include: mitral valve incompetence, bell’s palsy, heavy menstrual bleeding, genital ulceration, vaccine breakthrough infection, and a range of indicators of cardiac abnormalities. For 5-11 year-olds, the comparison to myo/pericarditis is less germane, as they seem to suffer less from this side effect. But we can still make the comparison: there are 7 safety signals larger than pericarditis, including bell’s palsy, left ventricular dysfunction, mitral valve incompetence, and ‘drug ineffective’ (presumably meaning they still got COVID). There are 16 safety signals larger than myocarditis (excluding pericarditis), which in addition to those listed above also include: pericardial effusion, diastolic blood pressure increase, tricuspid valve incompetence, and vitiligo. Sinus tachycardia (high heart rate), appendicitis, and menstrual disorder come in just below myocarditis. Now if we think of a safety signal as having both strength and clarity, then the PRR can be thought of as an indicator of how strong the signal is, while the Chi-square is a measure of how clear or unambiguous the signal is, because it gives us a sense of how likely the signal is due to chance alone: the larger the Chi-square value, the less likely the signal is due to chance. A Chi-square of 4 means there is only a 5% chance the observed signal is due to chance. A Chi-square of 8 means there is only a 0.5% chance of it being due to chance.⁶ For the 18+ group, there are 57 AEs with a Chi-square larger than myocarditis (Chi-square=303.8) and 68 with a Chi-square larger than pericarditis (Chi-square=229.5). Again, you can see what these are by going the Excel file linked above and sorting on Column D. For the 12-17 group, there are 4 AEs with a larger Chi-square than myocarditis (Chi-square=681.5) and 6 larger than pericarditis (Chi-square=175.4). For the 5-11 group, there are 22 AEs with a Chi-square larger than myocarditis (Chi-square=30.42) and 34 AEs with a Chi-square larger than pericarditis (Chi-square=18.86). RESPONDING TO OBJECTIONS Let’s dispense with some of the criticisms used to dismiss VAERS data, which will undoubtedly be raised if you try to bring the CDC’s analysis to people’s attention. Objection: Anybody can report to VAERS. The reports are unreliable. Anti-vaxxers made lots of fraudulent reports. Nobody was aware of VAERS in the past, but now they are. So many people were afraid of the vaccine so they blamed all their health problems on it. Health workers were required by law to report certain adverse events, like deaths and anaphylaxis. Etc. Etc. All of these objections ultimately rely on the notion that VAERS reports for COVID-19 vaccines have been artificially inflated over previous years for one reason or another. The thing of it is, though, that the CDC has a method for distinguishing between artificial inflation and real signal. The idea is simple: if adverse events are artificially inflated, they should be artificially inflated to the same degree. Meaning, the PRRs for all of these safety signals should be about the same. But even a casual glance at the PRRs in the Excel file show they vary widely, from as low at 2 to as high as 105 for vaccine breakthrough infection or 74 for cerebral thrombosis. This method does not on the number of reports, but the rate of reporting for certain events out of all events reported. If anything, this method would tend to hide safety signals in a situation where a new vaccine generates a very large number of reports. The CDC has even done us the favor of calculating upper and lower confidence intervals, meaning that we can be at least 95% confident that two PRRs are truly different if their confidence intervals don’t overlap. So for example the lower confidence interval for pulmonary thrombosis is 19.7, which is higher than the upper confidence interval for 543 other signals. Artificially inflated reporting cannot explain why so many different adverse events have large PRRs that are statistically distinct from one another. Objection: The safety signals are due to the huge number of COVID vaccines given out. Never before have we given out so many vaccine doses. By the end of July, the US had administered something like 600 million vaccine doses to people aged 18+. But the CDC analysis compares VAERS reports for these doses to all doses for all other vaccines for this age group since Jan. 1, 2009. But from 2015-2020 there were over 100 million flu doses administered annually to this age group alone. In previous work, I estimated 538 million doses of flu given to people 18+ from July 2015-June 2020. The number of flu and other non-COVID vaccines for this age group administered from Jan 1., 2009 through July 29, 2022 must be well over double this number, meaning VAERS reports for COVID vaccines are being compared to reports for at least double the number of doses for other vaccines. In addition to this, as already noted, the PRR methodology does not depend, strictly speaking, on the number of doses, but rather the rate of reporting of a specific AE out of all AEs for that vaccine. Objection: the vaccines are mainly being given to older people who tend to have health problems, whereas other vaccines are given to younger people. This objection is dealt with, since the analyses are stratified by age groups. It might be still be somewhat valid for the 18+ group, except that in the safety signal analysis I did in the fall of 2021, I stratified by smaller age bands and still found safety signals. In any case, this objection is not enough to dismiss the safety signal analysis out of hand, but rather calls for better and more refined research. Objection: The VAERS data is not verified and cannot be trusted. I’ll be the first person to agree that VAERS is not high quality data, but if it is completely untrustworthy, then how is it that the CDC uses these data to publish in the best medical journals such as JAMA and The Lancet? If the data were worthless, then these journals shouldn’t accept these papers. In that JAMA paper, they reported that 80% of the myocarditis reports met their definition of myocarditis and were included in the analysis. Many other reports simply needed more details for validation. Furthermore, the CDC has the ability and budget to follow-up on every report VAERS receives to get more details and even medical records to verify the report. So if myocarditis shows a clear signal in the CDC’s analysis, and 80% of those reports were apparently high quality enough to be included in a paper published in one of the world’s top medical journals, how is it possible that all the rest of the reports are junk? That all of the other safety signals are meaningless? Answer: it isn’t. And since we’re on the topic of safety signals that turned out to be real, it’s instructive to find appendicitis turn up as a safety signal in all 3 age groups, since a study published in NEJM based on medical records of over a million adult Israelis found an increased risk of appendicitis in the 42 days following Pfizer vaccination (but not following a positive SARS-CoV-2 PCR test). That study also found an increase in lymphadenopathy (swollen lymph nodes) after vaccination, but not after positive COVID test. Lymphadenopathy was another safety signal. And that brings us to our last objection to be dispensed with: all of these AEs were due to COVID. There was an epidemic and so people were falling ill due to COVID and having all of these problems that were then blamed on the vaccine. Well to begin with, as we just saw, at least two of them (appendicitis and lymphadenopathy) do not appear to have increased risk ratios following a positive SARS-CoV-2 test, and we know that the mRNA vaccines increase risk of myo/pericarditis independent of infections. So how can we assume the rest of these are and dismiss them with the wave of a hand? We can’t. At minimum, they need further investigation. Furthermore, in the safety signal analysis I did in 2021, I dropped all VAERS reports where any sign of a SARS-CoV-2 exposure or infection was indicated on the report, and I still found large, significant safety signals. PUTTING IT ALL INTO PERSPECTIVE The Epoch Times article quotes my esteemed colleague and friend, Norman Fenton, Professor of Risk Management and an world renowned expert in Bayesian statistical analysis: “from a Bayesian perspective, the probability that the true rate of the AE of the COVID-19 vaccines is not higher than that of the non-COVID-19 vaccines is essentially zero…. The onus is on the regulators to come up with some other causal explanation for this difference if they wish to claim that the probability a COVID vaccine AE results in death is not significantly higher than that of other vaccines.” (See his post on the CDC analysis here.) The same is true for all the safety signals they found. The CDC’s VAERS SOP analysis document lists 18 Adverse Events of Special Interest says they are going to pay close attention to. In their 2021 JAMA paper (and similar presentations to ACIP), the researchers responsible for analyzing the millions of medical records in the CDC’s Vaccine Safety Datalink (VSD) using the ‘Rapid Cycle Analysis’ only studied 23 outcomes. A Similar analysis in NEJM from Israeli researchers focused on only 25 outcomes. Compare this to over 700 safety signals found by the CDC when they finally decided to look—and that’s not even counting all the adverse events that have never been reported for other vaccines so cannot ever show a safety signal by definition. How can the CDC say that these safety signals are meaningless if almost none of them have been studied any further? And yet we are assured that these vaccines have undergone the most intensive safety monitoring effort in history. It’s complete and utter hogwash! 1 To be precise, the 'adverse events' are for 'preferred terms' (PTs) which is a type/level of classification used in the Medical Dictionary for Regulatory Activities (MedDRA), which is the classification system used by VAERS and in other pharmacovigilance systems and clinical research for coding reported adverse events. Not all preferred terms are a symptom or adverse event per se. Some refer to a specific diagnostic test that was done or a treatment that was given. 2 It's not entirely clear how they divided these up, since there are clearly AEs that should be considered serious that don't show up in the serious Excel table — though maybe they don’t come up simply because they are looking within serious reports. I believe that they just filtered the reports to include only serious reports or non-serious reports, then did the safety signal analysis on all the AE's coded in those reports. The reason I think this is that I used the MedAlerts Wayback Machine, selected just the serious COVID-19 vaccine reports, and the numbers of total reports was very close to the one in the table provided by the CDC (MedAlerts actually had a bit less). The files obtained by the Epoch Times do not include much in the way of a description as to how the analyses were done, so I had to infer some details, which might be incorrect. I will try to note when I am drawing an inference about how the analysis was done. 3 Generally speaking, these figures show the top ten AEs in each category. In some cases I combined AEs that indicated the same thing, such as combining ‘heart rate irregular’ with ‘arrythmia.’ 4 Note that using the myo-pericarditis signal as a yardstick doesn’t mean that these are the only signals that matter. To give one example, anaphylactic reactions don’t even show up in the list of safety signals, even though that was one of the very first risk of the vaccine that became apparent from day one of the vaccine rollout. One potential objection to this benchmark is that it is too low of a bar, since myo-pericarditis appears to disproportionately affect younger men and so a proper safety signal should be stratified by age and gender then compared with myocarditis similarly stratified. I agree, and it is the CDC’s job to do that. But the fact is that any adverse reaction might disproportionately affect some subgroup of people, in which case the safety signal for that group would be similarly faint or diluted when we look at everyone together. So objection overruled. 5 In their Standard Operation Procedures document, the CDC said they would combine these and related codes together to assess a safety signal, but never mind – at least they finally got around to doing something. 6 In this context, the Chi-square is largely driven by the sheer number of adverse events: the more adverse events reported, including for the comparator vaccine, the larger the Chi-square. For example, the PRR for pericarditis and subdural haematoma is the same (2.82), but there were 1,701 incidents of pericarditis reported for mRNA COVID vaccines versus 221for the comparator vaccines, with Chi-square of 229.5. For subdural haematoma, these numbers are 162 verus 21, for a Chi-square of 21.2.   LIKE COMMENT SHARE   Originally posted on Jackanapes JunctionJosh Guetzkow truths, self-evident and not-so-self-evident.