Will Dove 00:00 As we all learn more about the harms being caused by the COVID injections, we must ask why more people don't know. The answer, of course, is that the evidence is being hidden, not just by governments and mainstream media who continue to declare that the shots are safe and effective, not just by big pharma attempting to have records sealed for decades, but by the very agencies whose job it is to protect us from harmful vaccines. Dr. Jessica Rose is a Canadian scientist with degrees in applied mathematics, immunology, computational biology, molecular biology, biochemistry and protein biology. She is also an expert in analyzing VAERS data, the Vaccine Adverse Events Reporting System in the US, Dr. Rose has uncovered proof positive that the CDC is removing important data from the system in order to hide severe adverse reactions, and have even removed 1,000s of actual deaths from the system. Dr. Rose is research is so current, but the interview you were about to watch was our second attempt. We first met in late December. Halfway through the interview, I asked a question about the change in the data, a question which she did not have an answer for at that time. We both considered the answer to be so important that we stopped the interview and agreed to meet again, after Dr. Rose was able to dig further into the data. This is that second interview. Absolute undeniable proof that data, which shows deaths and severe adverse reactions is being intentionally removed from the VAERS system. Dr. Rose, welcome to the show. Dr. Jessica Rose 01:54 Thanks for having me back. Will Dove 01:56 So, as I've already explained to our audience, this is the second time we're doing this. We got partway through last time and then ran into some information that we agreed would be very, very good. If you could find the answer to that question I know that you have. So I'm going to ask you to do exactly what we did last time, please show the presentation that you would have originally shown to the World Council for Health and please explain to our audience what you're finding in the VAERS data. Dr. Jessica Rose 02:24 All right, and feel free to interrupt or interject as per you know, each slide if you have some questions, because I'm pretty sure that if you have questions, the audience might as well. So I'm going to share my screen and make it nice and big so everybody can see. So as well pointed out, I gave this presentation as part of the World Council for Health live seminar series, I guess it was, ah, it was December 12, a couple of weeks ago, then they wanted to know if anything is suspicious about VAERS in terms of data manipulation. And because a lot of people know that there is something strange about what's going on with VAERS data, besides the fact that the data that we are able to download in the first place is not the same data that the government, the CDC and the FDA have access to. They have a much wider demographic base in their version of the data. Besides that, what we have access to does show signs of manipulation. So just for people to be reminded, VAERS is the Vaccine Adverse Event Reporting System for the United States. It's inception was in 1990. And it was kind of a trade off for pharmaceutical companies having complete immunity from liability. It's not really a fair trade, but that's what we have. And it's an early warning system or a signal detection system, otherwise known as a pharmacovigilance database in order to detect safety signals in data that might not have been found in clinical trials or pre market tests. And it is working and it has worked historically. Back in 1999, I believe it was the rotavirus vaccine was given out and a handful of cases of intussusception was seen in children and VAERS. And this was seen as a safety signal being emitted by VAERS and they did a subsequent causality assessment and determined that yes, the rotavirus vaccine was causing these intussusception cases so this product was pulled. So VAERS does function. It's true. just that it's not being used properly since COVID came onto the scene, your guess is as good as mine why that is. So when you go to download the VAERS data, you have access to these two sets of files. And all the historic files like going back 30 years. One is the domestic data, which are the reports filed for people in the US and the other is the non domestic or the foreign data set, which are VAERS reports filed outside of the US to manufacturers who subsequently report these or file these into VAERS. So, the reason I'm mentioning this is because something happened with regard to the foreign data set about a month ago, which I will discuss coming up, but in the meantime, this data is updated weekly. For anyone doing VAERS analysis, you can download this data freely to csv file, it's easy to analyze lots of data in these files right now. Will Dove 06:04 And Dr. Rose, I have to ask, because most of us are under the impression that the VAERS database is entirely for the US. But I'm looking at this. And what I'm seeing is that the size of the non domestic database is much larger than the domestic one. Is this correct? Dr. Jessica Rose 06:21 Yeah, the file size is larger, it goes back just as long, 30 years. That's why it appears larger here. The 2022 data set here is only for 2022. So that's why there's a discrepancy in the file size, because this doesn't, this isn't year delineated. This is all the information so but there is a lot of data in there for 2022. I'll get to that. Will Dove 06:48 And the question I wanted to get to is the number of people in domestic versus non domestic roughly, what are we talking about? Dr. Jessica Rose 06:58 It's not far from a 50/50 split. Like there's probably like, upwards of 750,000 and each, you know, it's not exactly a 50/50 split, but there are a lot of reports in each. The combined total just off the top of my head without looking at my website is just over 1.4 million reports for both and that's only in the context of the COVID products. By the way, we're not talking about all vaccines combined. This is only COVID and right now, that means Modena and Pfizer, that contains the COVID products contains the Moderna, the Pfizer, the Jensen, Novavax and also these 'B.S.' bivalent injections now. So, just so that people know, this has data for the past 10 years, not 30. But it looks the same if you add another 20 years. So this is just for ease of the eye. On the left is file size in there's over the past 10 years, and on the right are the number of VAERS IDs, if you count them. And you can see that it's been really consistent for the last 10 years/ There is a slight increase, because there's an increase in the number of products on the market. So it's a proportional increase, but nothing like what you see in 2021. I mean, anybody who looks at this and doesn't say what the hell happened in 2021 and we need to find out what happened is, I don't, I don't know what to call them, ignoring a serious safety signal. Let's say that let's be polite. You can see I mean, it's obvious on the left, the file size has increased over 1400%. And that's the file size for the domestic dataset alone. And the number of VAERS IDs for the domestic dataset alone in 2021 is compared to the last 10 years is also up 1300%. So yeah, there's nothing similar about what was and what is. Will Dove 08:55 just to be really clear, when you're talking about VAERS ID you're talking about each ID represents one Adverse Event Report or one person? Dr. Jessica Rose 09:03 One person. And that's a very important distinction. Each person can report individually up to 20 different adverse events. And these are reported as something called a medDRA code. So this is like a diagnostic name for something that they report associated with their injection, most people file a VAERS report because they suspect due to temporal proximity to being injected that what they're experiencing is because of their shot. So these are the list of so called symptoms that people report. So what I show here is the number of people I always report on the number of people. If I report for example, in this next slide, the number of adverse events then I separate that out, and this year is just for the first top five, six symptoms reported per ID, which draws a clear distinction between the number of COVID-19 reports and the remaining 24 top adverse event reports. And this here is the total. So like I said, people can have up to 20 adverse event reports per person. So this is a more complete assessment of the total number of adverse event reports per person. And there's over 14,000 different types of adverse events that are being reported in the context of the COVID shots. And that's a really important thing for people to understand. When, when anyone's trying to say, no, no, no, it's just because there are more shots, COVID shots being given out. That's why there are more adverse event reports. No, first of all, that's incorrect. And second of all, it's not just the number of adverse event reports that's very, very distinctively different. Between the COVID shots and all the other shots combined. It's the range. There's no comparison here of the 25,000 or so metric codes that you can use. We're using over 14,000 in the context of COVID. And for flu, I think it's far less than that. So here again, you can see that COVID is number one, remains at number one headache is number two. Interestingly enough SARS COV tests is number three. And I thought this was really interesting, because it's almost as if there's a very strong connection between people who end up going to a doctor or to the hospital or end up in the hospital because of their adverse event. And the first thing they do is test you for COVID. There's no suspicion that it's the injection. No, no, no, it must be COVID. So I just wanted to point that thing out. They're terrible. Will Dove 12:04 I mean, what's going to clarify something Dr. Rose, the first bar, the highest one COVID-19. What you're saying here is that these people had an injection at least one, then they went to the hospital, they were tested for COVID. But that doesn't necessarily mean they had COVID. Is that correct? Dr. Jessica Rose 12:22 Right. Yeah, it's correct. There's no way to know because you, this SARS COV test measure code doesn't say SARS COV test positive. This doesn't distinguish between someone having cold or having a positive PCR test or not, which is all BS anyway. But yeah, the point is that we don't know, if these people actually have COVID, they can be so called diagnosed with COVID and have no COVID symptoms and that can be reported in their VAERS report, they can have a negative SARS test. And it still might be written that they have COVID, it's more likely than not that they aren't written that way, if anyone's doing their job correctly. But the point is that yes, COVID is written down more like many, many, many times, as you can see here, as one of the associated adverse events, when they file a VAERS report in the context of these shots. So these people may or may not have COVID. And they may or may not have developed a susceptibility because of the shots and gotten COVID. So yeah, there's no way to really know. Will Dove 13:35 What I wanted to get at with that was that big red bar, it, it's going to be a blend of things. But if we look at two extremes, It either means what we're seeing is a false signal based upon lousy testing that says that COVID when they didn't, or what we're seeing here is proof positive that the shots make you more likely to get COVID. Dr. Jessica Rose 13:57 Right. Right. So I leave that up to interpretation. I tend toward the latter, because there's a lot of published publications coming out now that actually show an increased susceptibility to developing COVID symptoms, following these shots. So I mean, there's you know, it's sketchy anyway, you can never like bet money on VAERS but you can interpret it either way. But I tend to go with the latter. I think this shows increased susceptibility to COVID. And I think the people who are getting injected are getting COVID more often. And this is a reflection of that. There also is here the metric code SARS COV 2 test positive and it is one of the highest, it's in the top 25. So, you know, there's that too. And there's also vaccination failure, which is also in the top 25. So there are a lot of indications that it is the latter. So in terms of data manipulation, this is something I published a while ago on pharmacovigilance of VAERS. I wanted to actually do some kind of quantitative assessment of you know whether or not it's working now in the context of these COVID shots. So what prompted this was talk of VAERS data, VAERS IDs people being deleted from the system. And what I found was that, yes, that's true. But also, I found that there was a huge backlog, which was resulting in lost safety signals. And I'll explain how I figured this out here. So as I said, every week VAERS is updated, and you can download this data. So if you plot the total number of adverse events reported in the context of the COVID products every week, you'll get a line that looks like this, it looks like an exponential growth curve. So this is the trend of the data, it's still doing this, by the way, it's still growing every week. The other thing that you can do, if you're analyzing this data, is you take the most recent update, and you would assume this is the one you're going to analyze, you would assume that all of the data in the previous updates is contained in that most updated dataset, ie, you would assume that all the people that had filed VAERS reports that were in each of those sequential updates would be contained in this updated file, most recent file, if you make that assumption, which I would, you would see a curve like this, if you plotted the number of adverse events by week you would see the same kind of exponential growth curve. But that's not what I saw, when I checked, I saw something like this. So what that meant and what this black area indicates is that there's a whole bunch of people that didn't make it into the system until later, they were being retroactively added to the front end system, because there was a lack of workforce. So what that meant in terms of watching VAERS and using it as a pharmacovigilance tool is this, let's say you're watching VAERS to try and help your grandma make a decision about whether or not she should get the shot, you're looking at SAE's, which are Severe Adverse Events, and you're plotting the data per week, what you would have seen is this red line. So we can - you'd see about 7,000 events. And let's say that you determine for yourself, because you're able to this, you know, it's not enough of a warning signal for you to warrant telling your grandma to stay away from these products. So that's, that's what you would have ascertained from the data. But once the backlog had been filled, and the total number of entries are not the total, but you know, the updated number of entries had been retroactively added to the database. The actual number of severe adverse events was actually closer to 27,000. So you would have had a false impression of what the data was actually showing, because of this backlog not being filled on time. So this is another example of that showing an earlier time point and week five and the difference between the perceived and the actual. Will Dove 18:08 So Dr. Rose to interrupt, but I want to address that you're not saying that this was done maliciously. They were understaffed. But but the point is, even though it may not have been malicious, it still would have led to people not seeing the actual danger signals because the data wasn't there. And so what it was presenting was a lower risk from the shots than what actually existed. Dr. Jessica Rose 18:33 Yeah. And having said that, you're absolutely right. But having said that, I want to point out something here. As part of the severe adverse event list, death is inside there. So there are six according to VAERS measure codes that indicate a severe adverse event, there's death, a life threatening condition, a birth defect, hospitalization, emergency room visit and disability induced. So any one of these is, is severe, let's just use the word that they use the last time, the number of deaths in the context of a product, a biological or pharmaceutical product exceeded 50, because that's the cutoff for the number allowed people allowed to die in the context of a medical intervention that's supposed to help the last time that happened, the product was pulled, so you exceed 50 deaths in the context of a product that's supposed to be helping you, no more product. So we exceeded 50 deaths in the first month of the rollout of these products. So these numbers here that I used as an example, if you pulled out the deaths, that number is already telling you stay away from these products because if we go by their own definitions of what's the what's the cutoff, what's the safety value, what's the number of people that we consider, you know, okay to die in the context of a medical intervention, we had already exceeded that. So I just wanted to throw that in. I mean, I use these numbers to make a point. But in reality, if you actually saw 7,065 severe adverse event reports at week 10, that's, that's that probably tells you you should stay away from this. Just to make that clear. Will Dove 20:20 Yes, and 26,000 just multiplies that by a factor of and, yes, obviously, anybody who's looking at this is going to say, no, don't let anybody inject you with this stuff. Dr. Jessica Rose 20:32 Yeah. And of course, you can narrow it down to things that make you more susceptible to dying. Like if you're already old, this is just, you know, one of the common sense factors that you can throw in. So interestingly, I went back and I reassessed this with the most recent data from 2022. I mean, I did this recently, not yesterday. And it turns out that the backlog has been taken care of or addressed. And I think the reason for this is because there's contract or hired in order to make that happen. So there was a necessity to get more people involved in processing this data. But the weird part is that they knew that this was going to be a problem in 2020. And they also knew how many excess reports there were going to be ahead of time. How did they know that and it's not close, it's really, really, really bang on the number of reports for 2021, which is about 700,000. You'll notice underlined hidden in red here, they say 770,000 digital reports per year were anticipated. So they hired a, this General Dynamics information technology thing, which you can look up for yourself to deal with this. And I quote from Josh Guetzkow's Substack, he wrote this up, you can look that up at the bottom corner there. In early March 2021, the contract was amended in order to process an estimated 115,000 backlog reports received on February 28, 2021, with an increased capacity to 25,000 reports per week. Here's the important part, the plan, the plan was to have the backlog cleared within six months. And it seems as though they achieved their goal. Now, again, this is just the front end data that we have access to I don't know what's going on with the larger set that they have access to the demographic data, the additional demographic data, etc. But I can only work with what I can see and what I have access to. So it does appear that this has been addressed for now. But that doesn't remove all these disturbing pieces of evidence that are accumulating, that indicates that they knew that we were going to have this excess reporting. How'd they know that? Will Dove 22:49 And folks, this is extremely important to note because as Dr. Rose shows in that slide, there they are hired extra people to process an additional 770,000 reports per year. What Why would they do that? Unless they knew that these shots were going to result in exactly what you saw in one of the early slides, where the line went flat, flat, flat, flat, flat and then just skyrocketed. They knew it was coming. Dr. Jessica Rose 23:14 Yeah, they definitely know a lot more than we do. Huge transparency issues. And not to, you know, go into too much detail that isn't included in the slides. But one of the FOIA requested Pfizer documents or I'm sorry, court ordered released Pfizer documents 5.3.6, etc. Do you have a very long list I think of 1,234 adverse events of interest, they call them listed. For some reason, nobody can quite figure out why these particular things were listed. But it does seem anticipatory. Hmm. And we weren't supposed to see this. Bear that in mind. So this is just a quote from my paper. I mean, it's appalling that data is being manipulated. But it's more appalling that these aren't data points, these are people and they're not just being manipulated, they're being removed. So I really want to nail this point down, it takes about a half an hour to file a VAERS report properly. And when I really do mean properly, it's an online system, multiple e page. If you don't complete each sequential e page on time, it kicks you off, and you have to start again. Imagine you're injured and you have to go through that it must be really annoying. So once you succeed in filing this and pressing send or whatever, you get assigned to temporary VAERS ID, then it gets vetted. You get a phone call, maybe blah, blah, blah, and some long time passes through eight months in some cases, or more. And you eventually get a permanent VAERS ID. That's the ID number that ends up in the front end data set that I think we have access to. It's a big deal. It's a long process and it's really annoying for everyone involved. For that ID to get in to that list, so to have it removed without explanation, without a note, without any information at all as to why it was removed, is not only inexplicable, and therefore requires explanation, It's deplorable, it's fraud, you can't manipulate a government data set like that, especially in the context of it being a missing person. Because for somebody who dies, they are missing. I mean, they, it's deplorable. So my quote ends with they simply can't be deleted, and I stand by that it's fraud to manipulate a government database like this, without an explanation. You have to provide an explanation at the very least. And just to be clear, here, these are not duplicate entries being removed, I checked. The duplicates can occur because two separate people can file the VAERS report for one individual, and those get overlapped and merged. And then one of those numbers is removed. This isn't that, this is following duplicate removal entry, the deletion of a VAERS ID from the system without notification or explanation. Will Dove 26:09 So there's two important questions I have to ask about that before we move on. You're saying that 3% of the death data that is 3% of the people who their adverse reaction was they died, they were removed from the system? How many people are we talking about with 3%? Dr. Jessica Rose 26:22 Oh, gosh, I don't remember this was over a year ago. Will Dove 26:25 Are we talking hundreds 1,000s 10s of 1,000s. Dr. Jessica Rose 26:27 Each week, when I did this assessment of the removed VAERS IDs, it was between 50 and 100, that were being removed every week. So the first thing if I'm getting your question, right, the first thing I looked for was whether there was a trend, or a pattern within these 5,200 people being removed, like were most of them deaths or severe adverse events? And no, I didn't find that. It seemed very random but that doesn't say that there wasn't some kind of reason for these particular people to have been removed. It's just that I didn't find it. So -- Will Dove 27:03 -- the span of time we're talking about 1,000s of dead people removed. Dr. Jessica Rose 27:08 Oh yeah. Yeah, yeah. By now. Yes. Okay. I mean, I'll check that in a follow up interview, I can, or I can send you an email and tell you after I check, but yeah, yep. Will Dove 27:19 Second question I have, because at the beginning of your presentation, you were talking about the domestic versus the non domestic data. Is this just from domestic? Or was this from everything? Dr. Jessica Rose 27:29 This was from domestic only. Will Dove 27:32 Okay, so these are people in the US 1,000s of people in the US who died as a direct result of the shots, and they've been removed from the VAERS database. They're just not there. Dr. Jessica Rose 27:41 Yeah. And even if their death wasn't causally affected by these products, the report was filed in the context of the products. And this is a government database. You can't just remove these. You can't. It's fraud to do so. I'm not a lawyer but I think I understand that that's fraud. Yes. So that's the very first thing about data manipulation. So this is the second more recent item, which is where we stopped last time. So when I went to download the VAERS data, it was November 18, I noticed something strange about the size of the form data file. So I'll just give some background here. Again, like I said, every week, the numbers are going up, the curves are, you know, trending up in these exponential ways and the file sizes continue to increase. So I noticed that the file size for the foreign data set had not just decreased, it had decreased by more than half. And I'm like, Whoa. And this is something you know, if you're looking at these numbers all the time, you just see it right away. And my first instinct was they removed more than half of the people. So I went into the data set. And that wasn't what it was. So I'll tell you what it is now after giving you some more background. So there was a letter written to HHS, which is one of the owners of this VAERS data, HHS, CDC and FDA requesting some answers to some questions pertaining to VAERS data. And this was one of the answers that they sent back to this very important person. And specifically they write for example, VAERS reports can log laboratory results that help establish a rule out of diagnosis. And I'm like, huh, yeah, and especially now. So on Friday, the 18th. This was the day that I noticed that there was something strange going on in the forum dataset. spile size wise, there was a disclaimer written underneath the VAERS data that said that they had basically purged all the free text fields in the foreign data set. Now the free text is very, very, very important. There's a column in VAERS as part of the data frame, the table, whatever you want to call it, called 'Symptom Text', and this is like the doctor's notes, or the reporter's notes, which gives you additional information that you wouldn't get from, say, a pulldown menu, it's like the extra words that really matter. And from those words, you can obtain and fill in field entries for all the other variables. If they're missing, it's very important. And not only symptom texts was purged, the history, the allergies, and this the lab results like they point out. So it wasn't the number of people that had been lessened, it was the data as per person extraordinary. So there's this massive purge for a set number of individuals just over 101,000 individuals in the form dataset. This took a lot of sleuthing to figure this out. I think I know why. I have an idea which I will try and explain. But it's not just that they did this. And by they I'm referring to some entity called the European regulators. It's that what do they have to do with anything? First of all, who are they? Why are they ordering the CDC and the FDA to remove this specific data, the free text from these specific people? And what does it mean when they say the reason they have to do this is because it may not comply with European regulations? We don't have answers to any of these questions, at least I don't. And I'm pretty much doing this all the time. So there's so many unanswered questions. That's one thing that's for the investigative mind to ponder. The thing that bothers me here is always the result. How does this affect the people? And how does this affect the analysis when you do it? So Will Dove 31:40 There's a question I just have to ask, if you just back up one more slide, because you're an expert in VAERS, I am not. But there's something here that just jumps right out at me. And so I have to ask this question. It's immediately following the stuff that you highlighted in red up there at the top. And it says VAERS is not designed to assess causality. I'm sorry, I thought that's exactly what it was for. That once you get enough data, you can draw a causal connection between adverse reactions. And the shot itself, is that not what it's designed to do that this is this is a bald faced lie. That's they're saying not designed to assess. But that's exactly what it was for. Dr. Jessica Rose 32:18 Well, actually, on the VAERS website itself, there's a disclaimer that says, you cannot use VAERS data to assess causality. And I mean, it's absolute BS. And here's why. Like I explained before, this is a pharmacovigilance tool, which you can do causality assessments on. And that's what's traditionally been done. And it has worked, like I said, in the case of the rotavirus vaccine, The WHO, specifically, and these three letter organizations do causality assessments. And they do this using something called the Bradford Hill criteria, it's one of 10, that you have to satisfy up to 10 criteria that provide very strong evidence of a cause/effect relationship between A & B from extracted biological data or from biological or epidemiological data. So if you can provide, if you can check these criteria off, especially if you can check 10 of them off out of 10, you have very strong evidence of a causal relationship. And that's the best we can do with biological data, it's the best, we can never say with certainty, never say with certainty that this cause this, because there's too many confounding factors. And biology is biology. But we can provide very strong evidence. And when you're talking about a useless medical intervention, that might cause harm, you have to exercise the precautionary principle. And if you even see signs of a causal effect, with evidence, you have to stop giving that product to people and investigate. That's the point. Will Dove 34:02 But I think we have to clarify something that you've said for the viewers, because you said you can never say with absolute certainty this cause this, but what you mean is in an individual case, you can't say take one person who dropped dead within three hours of getting the shot, and say it was the shot that caused it. In that one case, that could have been a coincidence, could have been something else. But when you start looking at hundreds of 1,000s of these reports, there's a causal relationship there, you have sufficient data now to draw a conclusion that it is the shots that is causing these adverse reactions. So you can't say in one individual case for certainty, it was the shot that killed them. But when you look at the totality of the data, you can say, no one should be injected with this. It's dangerous. Dr. Jessica Rose 34:39 Well, I certainly would say they're causing many of these problems. So but it's still coming from my subjective opinion, but I think I'm more than qualified to give mine. So yeah, you're right. And this also comes down to common sense. I mean, nobody would refute that if somebody suffered an anaphylactic reaction within 15 minutes before or after getting a shot, that that shot didn't cause the reaction because of the nature of anaphylaxis. It's an acute reaction to the trigger. What's the trigger? Let's give someone a shot and then they go into anaphylactic shock. Nobody's going to say that this didn't cause this, nobody. So this is the same as that, because temporality is actually one of the really, really important criteria in this Bradford Hill list, among another nine, which are, you know, it really does provide very strong evidence. I mean, yeah, so there's a lot of dodging of this issue. And the main thing I want to point out on the causation thing is that they're meant to be doing these causality assessments and seeing this how there are so much atypicalness in VAERS in the context of the shots. Or even if you want to take out the shot since 2021, why aren't they doing any causality assessments? Why have they always been doing it? Why did they stop? I want that answer. So that's, that's probably the most important thing to point out here. It's just the trend. You know, that we've been seeing what once was done is not being done now. There are no regulatory bodies anymore. So on that subject matter, the purge, I wrote this up on November 19th basically, the day after, I noticed this, I'm pretty fast. And I just did a really rough kind of surface analysis on some of the things like three of the things that really bothered me about this. And one of them was this myocarditis thing. I mean, I have an attachment to myocarditis, because I published a paper that was censored, which was just a descriptive analysis. It wasn't controversial or anything. Just descriptive analysis of myocarditis reports in VAERS in the context of the COVID shots, and it found, you know, you can go read my paper to find out, but it relates to this, actually. I'm going to tell you all about it. Now anyway, there's a dose two response in the context of the domestic dataset. If you look at only the domestic data, and you pull out all the myocarditis reports, and you plot them against age, and then the absolute number on the Y axis, age on the X, and you separate out by dose 1, 2, 3, let's say you're going to see more reporting in a younger age group following dose two, which means that there are like four times more reports being filed following dose two and kids 15 years old, for example, that's what you see in green here. This is a combined portrait though, the reason I'm putting this up is because there's dose three signal in the foreign data set seen in blue here. So you see the dose two signal from the domestic data set. This is combined, I'm sorry, this isn't combined, but you do see the signal in the foreign data set. But more prominently, you see this non age restricted signal following dose three. And this is very important. This isn't just young kids, which is horrific enough filing more reports in the context of dose two, this is all ages, filing more reports in the context of dose three. And this was confirmed by a presentation given by Guy von Luke Vasek, this ESD Congress in 2022. Recently, showing that there was the incidence of myocarditis following dose three was also higher. So this is confirmed by this guy's work, Peter McCullough is also talking about this. So it was very validating for VAERS to have this report out there. So this is what it looks like. Now following the purge, the myocarditis signal in the foreign data set is completely gone. So this is November 11th on the left, that was the week before the purge. And this is December 12, I think on the on the right, and you can see there's no comparison, there's a loss in magnitude of the signal, and there's a complete loss in the dose three signal. So the reason why this is really disturbing to me is because if you're a new analyst, and you go into the VAERS data set now and you look at the foreign data set, looking for a myocarditis dose response, you're not going to see it. And if you're not doing this diligently every week and screenshotting every single little thing and writing up every single thing that you see, like I'm doing, it would be lost, no one noticed this, except for me and a couple other VAERS analysts it would have been lost. And it's really significant. As I said, it's been pointed out in the literature to be a real phenomenon clinically. So you can see here the numbers, comparison of the numbers, the ends reflect the fact that there are more people, you know, n is equal to the number of people that are reporting so it did increase and then you have the myocarditis reports overall, which is just gutted, I mean from 40,000 to 16. So then the percentage of the total number has gone way down, and then that represents a 60% decrease in the percentage of myocarditis reports. So it's really staggering what they did. It's staggering the effect of what they did. And as I got deeper into this, I started realizing that they might even, they might have no idea. This might have just come down from the top. And they said, We got to shift some data do this, you know, and nobody even knew that this would be the result. I'm giving a lot of benefit of the doubt, because I always do that. But I'm making a valid point, they might not even be aware, which is why it's important for 'nosy nellies', like me to get up in their data and tell everyone about it. I've written a couple of articles, where I went a little bit deeper into this, and I found something really disturbing, actually. It's on the subject matter of deleted cases or safety signals now might look obvious that these signals got deleted. But let me explain to you one level deeper, like what happened here. The questions I wanted to ask when I went into this, okay, first of all, what I did was I had both of the files that were bookending, the purge, right? So I have an ability to extract the population of people whose data was purged. And here's a neat piece of information that people need to know 99.8% of the people whose data was purged represented the yellow card entries in VAERS. So -- Will Dove 41:15 -- I think we have to stop and explain what yellow card is. I had to look it up. So please correct me if I'm wrong here. This is specifically Great Britain, and has to do with their reporting system. Is that correct? Dr. Jessica Rose 41:26 Yeah. So it's the -- Will Dove 41:29 -- adverse event reports from Great Britain, these are the yellow card reports that are in the non domestic database in VAERS. That's what got purged? Dr. Jessica Rose 41:38 Right. So for one reason or another, you know, the data wranglers, or the submitters of the reports in the process of submitting to manufacturer and then to VAERS, over 101,000 of them all 'accidentally' got put into VAERS. I don't care why I don't care how whatever, that's what happened. 101,000 Something reports in VAERS were Yellowcard reports, and they don't belong in VAERS. So those are the people except for five, and I can't explain that. And I'm not even going to try, whose data was purged. So that list of people have some very special qualities. First of all, I wanted to ask and this, this is in the context of myocarditis, I kept it simple in the beginning, what cases first of all, before I even say that, when I do a search for myocarditis, I look in all the symptom columns. And I also look in the symptom text for signs of myocarditis. Because a lot of data is hidden in there, which I think becomes real obvious when you think about what I'm telling you here. It's really important to query -- Will Dove 42:43 -- because I've been reading your Substack. I know what you mean by symptom, text and symptom columns. But I think you should explain that for our viewers. Dr. Jessica Rose 42:50 All right. So when you download the VAERS data, you have, I think 52 columns of data once you merge the files, so like I said before, one person can file up to 20 different symptoms or adverse events as her MedDRA codes, that's the label that's given for recognition of what they have. So those fields, the symptom fields, symptoms, one through 20, or whatever, most people only file five can be filled from the information from the symptom text field, which is the free text, this is the data that was purged from this list of people. So these are the doctor's notes. Like I said, the reporters notes, for example; reporter suspects myocarditis, okay, so it's really important to query this symptom, text file Will Dove 43:38 Symptom text can be quite extensive. And you showed an example of an earlier slide, that was that block of text that you showed that had certain things highlighted in red, so that can have an awful lot of information in it. That's extremely important, Dr. Jessica Rose 43:50 Huge amount of information. And what I'll point out here is that it doesn't get translated a lot of the time, I always remove my my overlapped entries. So I'm not going to double count something that's in the symptoms and the symptom text just so that people who are actually paying attention understand. So what I found in this case, we have to ask because there's symptom text data was removed. Was there a signal omitted in the symptom text that doesn't exist when the symptom text was removed? Because it wasn't transferred to the symptom columns? Or what? Anyway, the question is, what percentage of those people didn't get their data transferred to symptom to medDRA code official medDRA code? I know this is confusing, but if you read my Substack, it'll become clearer, and what percentage weren't. So I found that there were a huge chunk of people whose myocarditis signal was absolutely lost. And that's what you see in that plot, because it was not filled in as a medDRA code in the symptom field. I hope that you know, what I'm describing is clear, because it took me a long time to figure this out. You can have measure code in the symptom columns. You can have signal in the symptom text, you can have medDRA code in the symptom columns, no myocarditis, or signal in the symptom text. You can have myocarditis in symptom text and not in the symptom columns. If you're getting my drift, there's going to be permutations and combinations of all of these things. So the reason why it's relevant to look at this is because their symptom text data was purged. And there was this huge dramatic effect, as we saw on that plot -- Will Dove 45:29 -- as you're trying to explain is that you've got, in this case, four possible combinations you could have. And you're talking about signal because you're a data analyst, but let's put that into terms that people understand. Let's talk specifically about myocarditis. So what you could have is you could have myocarditis showing up in the symptom text, and in a symptom field, you could have it showing up in neither, or you could have it showing up in one and not the other, and you get four possible combinations. So what you're talking about here is when they remove this data, now you're looking for places where it might have been there before in both of them. Now maybe it's gone in both, or it was there, and both of them now it's gone in one. So that's what you're tracking down here. Dr. Jessica Rose 46:05 That's right. And again, just to be clear, it's not right to do this, because I wrote a follow up Substack and I didn't make a slide here. So I really recommend that everybody go read that. I'm gonna reiterate this: the more I looked at this data, the more it became questionable that this was done for any specific reason, I think I concluded my Substack because I've really gone into another realm of research in the last few days. But I think I concluded that I think that there was somebody acting with intention, but not necessarily so. It wouldn't have to be the case that somebody saw a myocarditis signal in the symptom text field prior to it being deleted, and then just decided not to transfer it to a medDRA code and official medDRA code, they might just not have looked, they might not have thought to query the symptom text field prior to deleting it to make sure that those signals got transferred to medDRA codes. Either that or they intentionally looked, queried the symptom text field saw the myocarditis signals and decided not to put them as medDRA codes (wink wink). That's just as possible. Will Dove 47:19 Dr. Rose, I think this is the point where I'm not going to put words in your mouth, because you've made it clear that you don't want to draw a conclusion. But I'm going to draw one because I believe these signals were removed intentionally. And I think the reason why is very obvious, because something you taught me in our previous interview that we didn't really discuss in this one is that when people get entered into the system with an adverse reaction, and then later on, they die, that record gets updated with a death. So now we've got all these people getting myocarditis that that data is removed, so they no longer show up as having myocarditis, then later on when they die, because the fact that many of my viewers know is that 50% of people who get myocarditis are going to die within five years. And now there's nothing in there to tie their deaths to the myocarditis itself. And that is the conclusion. Dr. Jessica Rose 48:01 Oh yeah, it's even worse than that though, because the data is not being updated. I have inside information on that, too. So once you file a VAERS report, and you get a permanent ID, even if you try to update, it won't get updated. That's not being done. Will Dove 48:17 Right. So we've got two. So we've got two things going on here. My own belief that they did this intentionally so that you wouldn't be able to tie the two things together. And second, as you're not doing. So people are dying, people are dying. And it's not getting recorded. Dr. Jessica Rose 48:32 Yeah, that's exactly right. So -- Will Dove 48:36 -- let me I'm sorry. Just to interrupt with one more thing, that's just hit me. That means that even a data analyst such as yourself, one of the few people in the world who's doing deep dives into this VAERS data, even you can't tell that they died, because it was never entered. Dr. Jessica Rose 48:49 No. Exactly. Right. And it's funny because this circles back to the whole under reporting thing. I never report numbers with an under reporting factor included in the context of these COVID things because there's no need to but the under reporting factors are real thing. It does, you know, amplify the signal to something more akin to a real number of people who are suffering from say, myocarditis or death, but this also what you just described in the context of death in the context of VAERS is underreporting on another, you know, level. Those people who have myocarditis, who are there subsequently died or will, won't be reported as deaths in VAERS. That's almost 100% known. And if Walensky, I'm wrong, please write me an email back. I wrote to the Walensky and she never answered me. I'm so sad. I was very polite. Will Dove 49:48 I think we have to explain to our viewer to Walensky is? Dr. Jessica Rose 49:51 Oh, she's the Director of the CDC. Yes, she doesn't know how many people in VAERS have died. Will Dove 49:57 Right. And they're supposed to be responsible for the system. Yeah. That's her data. So even the Director of the CDC doesn't know? Dr. Jessica Rose 50:03 No. Well, she claims not to, right? There's a video of her saying that and I made a Substack about it. And it's really funny. So back to our last safety signals, it wasn't just the dose response that was lost. I mean, I showed you before the magnitude of the signal is much reduced. This isn't normalized to total number of shots per age, it's just to give everyone an idea of the distributions being the same before and after, but the magnitude being much reduced. This is myocarditis before and after. It's not just myocarditis, I looked at the miscarriage safety signals, stillbirths and, and things associated with fetal abnormalities. And it's reduced by about 1,000, as well, cancer signal reduced quite a bit, distribution of reports same, but the signal is almost gone. And it's interesting that this is - I saw this in cancer, although I will, you know, disclaim that I didn't look at many standalone adverse events. This could be the case for many others and probably is -- Will Dove 51:07 -- Dr. Rose can I get you to back up one slide, as there is something important to explain to the viewers, for people who are not accustomed to looking at data in in charts, I happen to be myself, I won't go into the reasons why. What you're seeing here, you look at these two charts side by side, and you say, well, the bars look about the same, what you have to look at is look at that Axis to the left, the number of reports on the first one, it goes up to 2,000. On the second one, it goes to 600. So if we put these side by side on the same scale, the bars on that right hand chart are going to be much, much lower. Dr. Jessica Rose 51:39 Yeah, and you're right, I probably should have put them on the same axis. My apologies. I did that here. But I should have done that here. Because then yeah, you're right, the visual would be much stronger. So yeah, signal much reduced here they're on the same axis, good for you Jess. So you can see that the signal is reduced, just like Will just described, same distribution, but yeah, much reduced signal. So yeah, I recommend number one go to I'm not plugging myself. I literally just want people to understand what I was trying to describe because like I said it went out of my brain since I did it. I know it was only four days ago. But still, I wrote it all down in a follow up Substack to the original one that I wrote, which really breaks down for here, just let me show everyone because this is important. Will Dove 52:28 And while Dr. Rose is looking that up, she may not be wanting to give a plug, but I will. Most of you know I have very little time. I often work 14 hour days, six, seven days a week, and I don't have nearly as much time for reading as I wish I did. One of the few things I do read on a regular basis is Dr. Rose's Substack because it is chock full of damning information that tells you exactly how far these people are gonna go to hide what they're doing. Dr. Jessica Rose 52:54 Well, thanks for that plug. Here's, here's what I was talking about. It's more it's what's that word, any elaboration on what I found. So this went into death, neuropathy and pulmonary embolism as examples. And you can actually see how the numbers changed the proportions in terms of what was there before the purge and what was left after and therefore how many of those safety signals were lost. So it's long. But like I said, it has a lot of examples of the symptom text written by these people. And I plotted in the, where I highlighted the some of the text in red that I thought was the most important, I really think everyone should read this to get a really good idea of what the effects of what they did is in the context of the people, like that's the - it killed me to do this by the way, I'm now, I'm remembering it now that I'm looking back at it because a lot of this is a really horrific text. But this is what you know, this is how you have to find out what happened, you have to read. So -- Will Dove 54:00 -- what you are seeing there, folks, those big blocks of text, that's the symptom text field that Dr. Rose was referring to. Dr. Jessica Rose 54:06 That's right. So each one of these VAERS IDs is - has one of these and these are, they provide a lot of the information that become the symptom medDRA code entries. So for example here if you want to look at this one, it says an 85 year old female, so if the person who filed the VAERS report forgot to enter the age of this person, person scanning the symptom text here says Oh 85 And they can enter that data in the age and then you have another data point. So this is why it's so important. That's with age, but imagine - look at this, look at this list: death, electrocardiogram, ST segment elevation hemiparesis, right side facial reason, a lot of it just goes on and that's why I highlighted it. These are this is invaluable information to get to a diagnosis to get to the bottom of what actually happened to this person. So -- Will Dove 54:57 -- and as you pointed out with your text there, Dr. Rose, it's an 85 year old female. But as you pointed out, about a third of the way down, she's fully active and mobile. This isn't somebody who's, you know, in a wheelchair, on death's doorstep, okay, she's 85 a few problems, but she's still functioning, she's still able to look after herself. She's still active. She takes one shot, and she dies. Dr. Jessica Rose 55:17 That's why I chose her. I was actually, you know, in the beginning when I was looking, because, you know, you read, I didn't read them all, but I read a lot of them. And I was actually looking for examples of people who were younger, because it looks more suspicious without biasing myself. But then I was like, No, don't do that. You know, dissemble everyone. That's, that's how you should do it. Because I thought, okay, there's no reason why I should exclude people by age that's 'ageist'. And then I noticed that they had actually written that she was fully mobile and active. And these are even more important to report. So yeah, good for noticing that. This guy was 27. This one was 30. I mean, there are a lot of young people here, you know, middle aged, whatever you can find anyone of any age. So that's another point of evidence, though, these people are all suffering really bizarro weird stuff all at once, right after their shots. And they're healthy beforehand. By the way, one of the purged columns that they decided was a good idea to leave out was the history. So you don't know if the person had something going on before, which is like really important diagnostically. Because if someone had, you know, a connective tissue disease before, and it's written down, and then you know, it's written up and the symptoms associated with the product, you know, you can't tell if they had Ehlers-Danlos before, you know what I mean, it's like, it's really important to have all this information to make a proper assessment. But you know, there is right there. 'Whoop, there it is'. It's like they don't want us to get to the bottom of what's actually happening. That's what it seems like to me. So that's pretty much it. I just want to remind everyone that we're still ... this data were collection collecting now, not just the adverse event data, but all of the journal articles being published now, which are confirming what a lot of us have been saying was potentially going to be a problem for like a year and a half now, it's all it's all the results of this experiment were in these are the results. These things were fast tracked like nobody's business. Takes five to 15 years, typically, for a biological, like a vaccine, pardon me, a conventional vaccine to go from concept to arm, there's a reason for that. It's because we don't want to mess that up. And here, we took a total of one year, six months for the phase three trials, not for conventional product for a product that contains two novel technologies, not one. And these aren't vaccines, these are gene therapies. And I'm not being litigious or contentious right now, these are gene-based therapies, its mRNA, which is messenger RNA, which is the template for your own body, once it's injected into your body to produce a foreign protein, which happens to be truly inflammatory. It produces massive inflammation, inflammatory responses in people. So it's funny to me, it's not funny, haha, it's funny how people are injecting themselves over and over again, with an inflammatory foreign protein that is being mass produced by their own body cells. So it's insane that the safety testing was skipped. There's no safety data out, there's no long term safety data or short, we're collecting it now. That's the truth. It's not a conspiracy theory. That's the truth. Anybody saying this is safe for pregnant women is lying. They're not wrong, they're lying. Because there is no safety data collected for pregnant women. There hasn't been enough time passed, simple as that. The precautionary principle has not been exercised here, which is the status quo, especially when you're dealing with new technologies and gene-based therapies, which we've never deployed on a mass scale before, let alone into over 5.8 billion people. And just as a point of interest, if you go to the this particular clinical trial listing at clinicaltrials.gov, you'll notice that they're not sharing individual patient data anymore. I'm not exactly sure what that means, but doesn't sound good. I'm not a clinical trial person. But that sounds to me, like they're not sharing data anymore. Go figure. So this is just about VAERS data, I want to, you know, drive that home. I know for a fact because I'm not just looking at VAERS data that other datasets are being manipulated, definitions are being modified to, to fit the data. Uh. what a joke. Like, it makes me my ancestors roll over in their graves. I swear, you can't do that, but they're doing it. I don't know how else to say it. I'll give you a specific example. So people know what I'm ranting about. As per Ontario, Alberta, the UK and probably a number of other people, places, statistics sets, data collection systems define an unvaccinated person in the context of the COVID shots as someone who's had no dose or one dose and is within a 14 day window of getting their next one, or within a 14 day window of getting their second one. Yes, that's what the call by definition, you can go to their websites, that's what they call an unvaccinated person. So imagine headlines, the unvaccinated are hospitalized out the yin yang in the UK. And they show these graphs and there's this big hump. You know, hospitalizations is on the Y axis and the unvaccinated number of people in the hospital are being shown by this huge curve, as opposed to the people who've gotten one dose and two doses and three doses of these products. But what they don't tell you is that most of that hump most of that area under the curve -- Will Dove 1:01:12 -- yes, I'm sorry, I knocked, you out of screen sharing, because what we're discussing is very important, because I want to add something to what you've just said. I learned recently from looking directly at the Health Canada website, that Health Canada is no longer using the term fully vaccinated. Now they've replaced that with something much more disturbing: "completed the first series", I mean, everything. They've done it on purpose. They've done it on purpose, so they can keep moving the goalposts. And for those of you who don't know, Justin Trudeau purchased 100 million doses last year, he's purchased 95 million for next year, you don't purchase doses you're not planning to use. So when they talk about next year 2023. Yes, he's already committed to 95 million doses for 2023. Dr. Jessica Rose 1:01:52 Why? Because Will Dove 1:01:55 it depends, doesn't it, because if they bring in Central Bank, digital currencies and digital IDs, so they can control you, if you don't take your shots, because some people are going to take them. Now, of course, there's the other theory, one that we have never been able to prove. And I want to make that very clear, folks, I am very reluctant to talk about things that I cannot prove. But we have strong evidence that Trudeau holds shares in a company that makes components for these injections. And so every time he purchases 10s of millions of doses, he's making money. We can't prove it. We do not have any documentation to prove it. But I've heard it from multiple sources. So take it as you like. So that could be another reason why he keeps ordering these doses. He's making money off of it. It's a possibility. Dr. Jessica Rose 1:02:40 What do you think? What do you think? I think you should stop talking mommy. He always says that. Will Dove 1:02:50 So Dr. Rose If you have any closing thoughts for our viewers based upon what you're findings, analyzing the data? Dr. Jessica Rose 1:03:00 Well, I do have some, like I've alluded to a couple of times, I am so deep into my new, it's not new, it's just more like a connection of all or many of the things that I've been researching for like a year and a half now, a paper got published that I wrote up on Substack, showing a very skewed ratio of a specific type of antibody called IgG, toward a subclass of IgG. There are four that is rare, and it has implications, I refer to it as the tolerizing antibody. And I've been thinking about that a lot today. And I'm gonna stick with that. It's not that this antibody induces tolerance. And if you want to find out what tolerances go, it's that it is associated with T regulatory cells which induce tolerance. So this is all coming back to another issue that I've been researching. And I found this all comes back to what VAERS reveals specifically, which is trends, magnitude of reporting being higher for really rare things like, things that we really shouldn't see a lot of reports for coming up. I'm going to be very lucid now because I'm not finished writing my article and I don't want to say things that I'm not ready to say yet. I'm literally processing and formulating as I'm writing. I want to get this right. So bottom line is I'm finding some really rare things in VAERS, sometimes you don't think to look for things especially if you don't know they exist. This is another problem with everything that's going on. You're not going to find what you're not looking for. So sometimes you need someone to publish something to help you connect some dots and then you can look for leaves rustling in the wind or some evidence from databases like VAERS. So but for now, I mean I know that was long and rambly you know, the most important thing I suppose that I've discovered in VAERS is this purge and the effect on what it did, what it did to the myocarditis safety signal. I mean, it's just appalling. Will Dove 1:05:13 There's one question that I that I wanted to ask because I got 90% of the way there during your presentation and I forgot to ask this question, because we talked about the fact that those myocarditis data, that data was taken out, but it was taken out from the Yellowcard system from the non domestic records. So the question I forgot to ask is, if you go, when you look at third dose domestic data, are you seeing the same pattern? Dr. Jessica Rose 1:05:39 No, that was the whole point. You only see it in one data, and you're what Will Dove 1:05:45 I was, before they removed it. What your data showed was that first dose, mostly young people second dose, most of the young people, third dose, okay, now we're getting a huge range of people of ages that are getting myocarditis. And that signal has been removed. But if you look at third doses in the domestic data, do you see that same thing of that huge range of ages are getting myocarditis? Dr. Jessica Rose 1:06:11 No, that's the thing. I mean, I shouldn't be so definitive, because I haven't looked in two weeks, but not that I have seen, which is why it was so interesting to me that it was sticking out like a sore thumb in the foreign data. And on that subject, I want to make another interesting point here. The foreign and the domestic data is basically like a 50/50 cut for most standalone adverse events, like you asked before, what's the ratio of reports, as per this file and this file, it is not exactly 50/50 but it's close. You pull out any standalone adverse event, you're going to find about half of them are here and half of them are here. Not so for myocarditis. Nobody knows why, maybe it's because there were a whole bunch of reports from Yellowcard in there, I don't know. I'll have to look at that. But the ratio was about I think, one to six. So there were always like many times more myocarditis reports in the foreign data set as for the domestic data set. And that wasn't just a magnitude thing that was reflected in this, this dose number response. So the way that reflected dose-wise in the domestic data was the signal in the young people for dose two. And in the foreign data across all ages for dose three, I'm not saying there wasn't a signal, but it was not definitive like it was in these two cases. So I'll go back. And I'll look at that, though. Because it's a good point. I mean -- Will Dove 1:07:42 -- not to put words in your mouth. But here's the conclusion I draw. There's absolutely no physical or physiological reason to assume that people in the US would have a different response to these injections than people in the UK Dr. Jessica Rose 1:07:56 unless they were getting different products, which they are. Will Dove 1:07:59 So let's put a few facts together. These myocarditis cases across a broad age range showed up in the Yellowcard data, but doesn't show up in the domestic data. Then we've got the CDC telling us that they removed that data at the request of European Union authorities. But we don't have any independent corroboration of that. We just have them telling us that. So now that's it. Dr. Jessica Rose 1:08:26 And nobody reads Will Dove 1:08:27 Right. So now that signal is gone. And so that signals not showing up in the domestic data. My conclusion would be it's not being entered. It's simply not being entered, allowing that to be put in in the first place. And they removed it from the foreign data, because that would have revealed what they were hiding. But you caught it. Dr. Jessica Rose 1:08:49 Listen, it's even worse, because I don't know the answer to the question. Did those? Did these people? This is this is in that Substack, I told everyone to go read. My question is did those people's data get transferred to Yellowcard? Because as I say, in the Substack, I'm remembering what I wrote. Now, it would make a lot more sense to me. If there wasn't something fudgy weird going on here. If 101,000 odd people were just taken out of VAERS and put into the Yellowcard system. I wouldn't have a problem with that. They could just say, well, we apologize. These weren't supposed to be here. We took them out. I would be satisfied with that. hand to heart but that's not what happened here. They didn't take out the people. They removed their data. And we don't know if we can only suspect because they're maintained as VAERS IDs in VAERS, that they weren't transferred to Yellowcard. Maybe they were maybe the safety signals being detected in their system. I don't know. I didn't look but maybe someone can look but that's the third question for me. I mean, was the signal lost entirely like, Did it go into the ether? Will Dove 1:10:08 You are excellent scientist, Dr. Rose, and you do not draw conclusions where you do not have data. But I'm not a scientist. And I'm pretty damn sure that that signal has been lost entirely, because they're wanting to hide what they're doing. Because there's no, no doubt about the comparison between the Yellowcard data and the domestic data showed a discrepancy, a very, very big one. And they had to take it out. They had to hide it. And so the question that then comes to my mind is, so they hired all these extra people to catch up on filing these reports. But we're not seeing that myocarditis signal showing up in the domestic data. Are they being instructed not to enter it? Are they being instructed to reject reports that show it? Something's going on? I don't have an answer to that. But there's, there's no possible way it's by fluke that those reports aren't showing up. Someone, no, it's instructing people not to put them in. Dr. Jessica Rose 1:11:06 It's just I think it's going to come down to the discrepancy between the magnitude, the division, the ratio of myocarditis reports in either dataset. There's something really weird about that. I wouldn't have suspected weirdness if I'd seen differences in ratios among all of these standalone adverse events, but it's really consistently, you know, half-half, not so. And I haven't been able to explain to this day, I mean, granted, I haven't looked very deep. And maybe I will now once I finished this new article, but I just like to point out again, this is this is not my job, I'm just like doing this, and they should be doing this, the onus is not on the public, the injured, the data scientists who aren't getting paid to do this, to bring this stuff to light. This is the job of the people who are paid to use VAERS to assess safety signals to do causality assessments to do all the things they're meant to be doing with this invaluable data. So they're not even looking, let alone ringing the bell, ringing the alarm? Yes, they're not even looking. They're looking the other way, actually. Will Dove 1:12:30 And has been pointed out many times. And as you pointed out, in this interview, any injection that's caused 50 deaths or more, should be automatically pulled. And we have far, far more than that from these injections. They should be the ones saying, wait a minute. Stop. You can't keep injecting people with this stuff. They're dying. Dr. Jessica Rose 1:12:51 Yeah, it's the deaths safety signal has exceeded 40,000 now it's and that's without the underreporting factor. So it's like so far exceeded the, the so called limit. And I've been asking this for two years to these owners of the data literally me and a whole bunch of other people, by the way, emails, phone calls, public announcements, it's like, what's the cutoff? How many more people have to die in temporal association with these products in order for you to do a safety assessment exercise? You know, use the precautionary principle, do what you've always done. We're not in an emergency, in my opinion. And I'm very, very, very like sure about this. We never were in an emergency. The whole thing's been a fraud. I think it's very clear that the whole thing was fraudulent. And I think it's also really clear how devastating to a lot of people this has been not just I'm not talking about the shots, I'm talking about the whole bloody thing, these ridiculous mass masks these lockdowns, this insanity that just swept our entire species and kind of like railroaded a whole bunch of us. I mean, it's ... Will Dove 1:14:00 Thank you very much for sharing this data. Folks. As I said, I am reading Dr. Rose's Substack. And it's despite the fact she's very, very busy. She has been kind enough to give us her time. This is our second interview. She's done with me. I'm going to be pursuing her for more as she uncovers information. This is why yes, definitely it is our third Yes, it is because we got halfway through this interview, we can go and then decided to drop it so that we can bring you the information that Dr. Rose has revealed. And this is by the way, aside from her Substack the first place where you're going to see this information. So I wanted to reference a couple of other things in regards to comments that Dr. Rose has made. First of all, there is no pandemic and never was. If you have any doubts of that, please watch my recent interview with Dr. Denis Rancourt, who proves by looking at the all cause mortality data around the world that COVID-19 did not result in any extra deaths. Any extra deaths were a result of government actions. If you want more information on these clots, these long fibrous clots that are forming in peoples' bodies, please watch my recent interview with Undertaker's John O'Looney and Richard Hirschman. Dr. John O'Looney was the first Undertaker in Great Britain who started blowing the whistle finding these huge blockages in the cadavers. We go a great deal of depth in that interview, not just what they're finding what and how the government's hiding these deaths, especially among stillborns among miscarriages, and how they're hiding those. And finally, Dr. Rose has referred to the inflammation that's resulting from these shots. Please watch my recent interview with Dr. Stephanie Seneff where in plain English, you don't have to be an immunologist to understand what she's showing you. She goes into a great deal of depth on a microscopic level of just exactly how the shots are harming the body. And it is horrific what is happening. Once again. Dr. Rose, thank you for your time. Dr. Jessica Rose 1:16:14 My pleasure. And I love Stephanie, she's like, just so brilliant. Will Dove 1:16:18 And yes, one of those very humble people who she doesn't talk about it. She's collaborating folks on several papers with Dr. Peter McCullough. She is absolutely one of the most qualified people out there to understand what's happening at a microscopic level. And even she is still trying to track down just everything that's going on. But that recent interview will tell you a great deal.