Jessica Rose is a Canadian researcher with a Master s degree in Immunology, a PhD in Computational Biology, and two postdoctoral degrees, one in molecular biology and one in biochemistry. Her most recent efforts are aimed at learning to analyze the VAERS data, the vaccine adverse event reporting system, and to make it more accessible to the public and more comprehensible. In this episode, Dr. Rose talks about how she got involved with the project, how she found the data, and why she thinks VAERS is a dysfunctional system. She also talks about her work on a recent paper she co-authored on the topic of pharmacovigilance in the vaccine field, and how she hopes to make the data more accessible and comprehensible to the general public. This episode was recorded at the 2019 ACOG Symposium on Vaccine Adverse Event Reporting System (VAERS) and is sponsored by the ACOG and the Center for Disease Control and Prevention (CDC). Additional funding from the National Center for Safe Vaccination and Research (CNSR) and the National Institute of Occupational Safety and Training (NICE) is being sought for further study of this topic. Thank you for listening and supporting this podcast. Please don't forget to rate, review, and subscribe to our other podcasts, and spread the word to your friends and family about this podcast to let them know what they're listening to you're listening and sharing it on their social media platforms. Thank you to Dr. Jessica Rose for helping us make this podcast a great podcast! and Good Morning America! (c) Dr. John Rocha . , Dr. David Soto ... etc. , & so on and so on & so much so that we can all be a little bit more like that in the next episode of this podcast, in the world, and more so that it can be better than that... (a little more so than that ... ) : ) . , and so much more... ...and so on, etc., etc., and so forth, etc.. And so on. ... etc., so on... , etc. etc. & so forth. etc., & so, etc. ... etc, etc... etc .... etc.... Thanks, etc, ) etc, and so, so on AND so on....
00:00:02.000Jessica Rose, a Canadian researcher with a master's degree in immunology, a PhD in computational biology, and two postdoctoral degrees, one in molecular biology and one in biochemistry.
00:00:16.000Her most recent efforts are aimed at learning to analyze the VAERS data, the vaccine adverse event reporting system data, and to make it more accessible to the public and more comprehensible.
00:00:30.000And you have brought down holy help on yourself in the US and Canada.
00:00:36.000Tell us how you got involved and what did you find?
00:00:41.000Well, first of all, thank you for having me.
00:00:44.000I'm really honored to be here and thanks for the lovely introduction.
00:00:47.000Well, it started, I suppose, at the end of 2019.
00:00:52.000I had just completed my most recent postdoc at the Technion Institute of Technology.
00:00:58.000And after three years of hard work, I decided that it was time to take a trip to Australia and start my career as a professional longboarder.
00:01:07.000My trip was planned to start and continue February, March 2020.
00:01:13.000So that's just about the time when they declared this pandemic.
00:01:28.000I'm still trying to figure out how to become a computer programmer who's actually good, but I decided to start with R. So I needed, where I wanted, a data set that I could use to teach myself how to use R. So I decided to look at VAERS because...
00:01:45.000Based on my background, based on what I was seeing, based on things that weren't adding up, I figured that the data in VAERS would start to accumulate with rapidity, and I was not wrong.
00:01:59.000So that's kind of my involvement here, but interestingly enough, I also have an immunology background and biochemistry, molecular biology, so I come from this from many different points of view, and It seems like any point of view you look at this at, things don't make any sense.
00:02:20.000The Vaccine Adverse Event Reporting System in the U.S. is telling a very, very frightening story.
00:02:46.000They got the Agency for Healthcare Research, which is a sub-agency to an HHS study.
00:02:53.000To design a machine counting system that can accurately assess how many people are actually getting injured by vaccines, they compare that to the results in theirs in one HMO, and they concluded that fewer, fewer than 1% of vaccine injuries are reported.
00:03:12.000What that means in another way, it's obvious, is that more than 99% of vaccine injuries are missed.
00:03:21.000There have been other analyses of theirs that have found similar dysfunction and undercounting the best performances, say that maybe 10 to 20% of injuries are reported, but that means that there's a, you know, five times that number are not reported.
00:03:45.000So nevertheless, and this again is part of the background, we've seen these extraordinary rises and deaths and injuries during the 15-month period since they released the vaccines, COVID vaccines.
00:04:00.000We've seen more injury, more deaths during that period reported to VAERS than all of other vaccines combined since 1986.
00:04:10.000So I think most of the people who follow this podcast are aware of those deficiencies.
00:04:22.000I published a paper that was a critical appraisal of the pharmacovigilance myths of VAERS. So VAERS is designed, this is the brainchild of the FDA and the CDC, as you probably all know, that is designed to detect safety signals that weren't detected in pre-market testing.
00:04:41.000And what's really, really strong about what we're seeing in VAERS in the context of the COVID-19 products are the numbers in contrast to what we've seen in the past, like you said.
00:04:52.000One of the things that I did in this paper, because I was very interested in this backlog that I was hearing about, like all of these VAERS reports that actually were reported that didn't make it to the publicly available data set.
00:05:07.000So I wanted to figure out, like, okay, what's going on there?
00:05:50.000In which somebody makes a determination that this report is real or that this report is not duplicative.
00:06:00.000And they also, I think, if somebody says unfair, if somebody reports that they turn green and turn into a lizard or something like that, I think they get rid of those, too.
00:06:11.000They get rid of ones that are completely wacky.
00:07:30.000Just to follow through with what I did, I plotted a curve, a two-dimensional plot of the number of people who died, for example, per update date based on these weekly update I published this in May, so it was like something that looked like an exponential curve of the data from January through May, based on these points.
00:07:55.000So if you take the latest updated data set that you download from VAERS, you would expect to find all of those data points, those death data points, inside this updated data set.
00:08:08.000So when I plotted the number of deaths Per update date matched to those update dates.
00:08:14.000I imagined I would see the same curve, maybe a little higher, maybe a little lower, but I didn't see that at all.
00:08:20.000I saw a completely different curve with a different shape.
00:08:24.000So what that does, we don't even have to go into interpretation.
00:08:28.000What it does though, to a person who's monitoring VAERS, looking for safety signals, It makes the safety signal disappear.
00:09:24.000So they called a halt to that because they determined that it was too many people to have died as a result or in association with this product.
00:09:35.000So it begs the question, what's the cutoff number for these products?
00:09:39.000Because I'll get to that in a second where we're at.
00:09:42.000If you're watching VAERS data in February for your grandma or something, and you're trying to make a determination as to Risk-benefit analysis.
00:09:50.000How many people are dying in this age group that your grandma's in?
00:09:55.000You would have seen a number that wasn't, you know, too scary when you compared it to the number of people who had been injected in that age group.
00:10:03.000However, based on the updated data, that number was the real number.
00:10:10.000And this isn't the real number either.
00:10:12.000This is just the number of reports that made it into the front-end system without the under-reporting factor.
00:10:20.000So that actual number of deaths or cardiac events or neurological events or Guillain-Barre or Bell's palsy or all of this extraordinary number of adverse events that are Being reported in association with these products, you wouldn't have seen them because the data hadn't been entered at the time that you were looking at.
00:10:44.000So this is one of the things I found, I revealed from the data.
00:10:49.000And I haven't seen anybody else even say this, let alone do a proper analysis, like the owners of the data, for example.
00:10:57.000VAERS could be a better pharmacovigilance tool, but besides being extraordinarily ancient and imperfect, it's not being used as such.
00:11:08.000And it might just be the byproduct of this enormous number of adverse event reports both being filed, not making it into the system, and not even being filed.
00:11:19.000I mean, when I start thinking about this, And I hear the stories from GPs and nurse practitioners saying, after a 12-hour shift, I have 100 suspected injuries in the context of these COVID injections, and I don't have the physical time to enter them.
00:11:35.000You're supposed to do it, but it takes 30 minutes to file a single VAERS report.
00:11:39.000So it's a very scary thought when you start thinking about how many people are actually suffering adverse events in the context of these products when you look at VAERS. There's a screaming, red flags everywhere, on just about every adverse event you can think of.
00:13:10.000And I've also heard that these are reports that might have been made in the UJR system or the yellow card system that are being pushed into VAERS. I've heard these two things, but I don't know.
00:13:21.000There's no field data for the countries or the state, sorry, the location.
00:13:54.000You do have, I think, the symptom measure codes listed.
00:13:59.000But anyway, so I only use the domestic data, but like I said, it's enough.
00:14:04.000By my count, when you merge the three files that you download, which is data, symptoms, and VAX data, we're at 618,548 reports.
00:14:16.000Now, if you consider the underreporting factor, you either have to multiply that by...
00:14:22.000You have to multiply it by something, whatever you believe the underreporting factor is.
00:14:26.000I've made a calculation of this based on the Pfizer Phase 3 clinical data, which is probably questionable data anyway, but based on their own data and their rate of occurrence of severe adverse events, the underreporting factor is at 31, and this is the most...
00:14:46.000Like, the lowest underreporting factor estimate of three that have recently been calculated.
00:14:53.000So even if you take the lowest, the most conservative estimate, you have to multiply 618,000 by 31.
00:17:32.000They report hospitalizations and cases.
00:17:35.000They do not have an adverse event data collection system, which is Appalling, considering that they're the first country to have steamrolled the Pfizer product into the population.
00:17:47.000They just assumed there wouldn't be any adverse events, so there was no need to collect the data.
00:17:54.000But the severe adverse event count, this is really important that people know.
00:17:58.000To qualify as a severe adverse event, you have to have died, undergone a life-threatening event, birth defect, Hospitalization, emergency room visit, or become debilitated.
00:18:10.000This collection of severe adverse events has consistently been above what the VAERS system handbook says is the average percentage of severe adverse events Historically.
00:18:26.000So they say 15% of all reports will be severe adverse events, based on whatever model they chose to use.
00:18:34.000So since the beginning, since January, we've been above that.
00:18:38.000We peaked in February at 57%, which is wild.
00:18:56.0003% might not seem like a lot, but it is when you're considering what we're talking about here.
00:19:01.000Another point, which is a huge sore spot, are the children.
00:19:06.000There are children being inappropriately injected with these products.
00:19:10.000As a matter of fact, there's a metric code, which is the name given to how the VAERS report is filed as per individual, called a product inappropriately given to person of wrong age or something like this.
00:20:26.000In any case, it's an alarmingly high number.
00:20:28.000And again, on the subject of children, the female reproductive issues, which I think everybody has heard about from a family member or a personal experience even, Even in people who haven't been injected and just been in close proximity to someone, these are at over 10,000 reports now.
00:20:48.000And this is based on a limited keyword search.
00:20:51.000So all of my numbers that I'm reporting are very conservative.
00:20:54.000So you can multiply them by whatever you think you need to, but these are very baseline conservative numbers.
00:21:01.000And a lot of these reports are actually miscarriages.
00:21:05.000There's over a thousand of those reports.
00:21:08.000That's just using one Medra code named abortion spontaneous.
00:21:13.000This is another weird thing about VAERS. As this is evolving over the months, the number of Medra codes that mean miscarriage has increased.
00:21:29.000Nowadays, the term SIDS, originally there was once an infidescent It was, you know, if we died of unexplained causes between one and between Earth and two years old, now they have half of the different codes.
00:22:05.000It's just one of the things that I have to know how to do to do what I've done in my career.
00:22:11.000But yeah, it's shocking to see it unfold right before your eyes.
00:22:17.000Because if you're tracking this, this is all I do now.
00:22:20.000I enjoy it in a morbid way, but it's something that somebody needs to explain.
00:22:26.000Another thing that people need to explain is why are VAERS IDs missing from VAERS? Where did they go?
00:22:35.000Because this was also part of my critical appraisal of the pharmacovigilance.
00:22:39.000Because there were a lot of people saying that there were a lot of VAERS IDs going missing.
00:22:44.000So I was like, hmm, how many are actually going missing?
00:22:47.000So I wrote this little algorithm that takes out the VAERS IDs that go missing from week to week.
00:22:55.000I mean, it's not a high percentage, but it is a percentage.
00:23:00.000And my question is, why is there even one?
00:23:02.000And where's the little marker from the person who's hired to vet this data as to where this person, because it's not a VAERS ID, it's a person, where did they go?
00:25:11.000And, you know, the level of intelligence they have in ravens still, and I've had crows and ravens my whole life, but I've seen them do things that are inexplicable.
00:25:22.000I'll tell you, there's a guy who studies ravens in Maine, and he did a series of experiments where he captured all the ravens at one point or another and put telemetry on them.
00:25:37.000He could see where they were, and it was a single roost with about 30 birds on a cliffside in a pine forest, and all the birds would return there.
00:25:47.000So he had about a decade-long study of them.
00:25:50.000He's now been up there for 30 years studying the same group of ravens.
00:25:55.000One of the things he did is he would capture two of the ravens, and then he would take them.
00:26:02.000A raven normally would wander about 50 miles a day.
00:27:21.000Somehow those birds were able to have this very high-level sophisticated discussion where they compare the experiences of two I saw the two things that are amazing in the wild.
00:27:37.000When I'm trapping blocks, we see a lot of things.