UVC: Dr. Rob Verkerk: Exploring the Continuum From Causation to Association

The inaugural Understanding Vaccine Causation Conference, convened by World Council for Health Steering Committee Member, Shabnam Palesa Mohamed, took place on Feb. 5, 2022. The WCH Law and Activism Committee brought together legal practitioners, doctors, scientists, and jab victim data and advocacy groups to explore a key question: How are jab adverse events proved?

Dr. Rob Verkerk joined the Science in Action panel for his presentation, Exploring the Continuum From Causation to Association.

Transcript

[00:00:06] Shabnam Palesa Mohamed: Moving then from Canada to the UK, with Dr. Rob Verkerk, and his topic is Exploring the Continuum: Causation to Association. But before we begin, Rob, tell us about yourself and why you think this conference is important. And then of course you have 15 to 20 minutes followed by Q&A.

[00:00:27] Rob Verkerk: Thank you so much, indeed. Oh, Shabnam, what a conference its been. I’ve been on from the beginning and, uh, my goodness, it is great that it’s being recorded. There is so much information that I think it’s this integration between information, coming from lawyers and coming from scientists and doctors. That’s how we’re going to solve it. And too often, we’re in our independent silos and, uh, this has been an extraordinary occasion. So, you know, incredibly well done everyone for this. 

[00:01:00] My own background. I’m a sustainability scientist. I’ve been involved in environmental sciences, agricultural sciences, and the last 20 years in the health sciences. My area is really looking at, um, complexity and interactions.

[00:01:14] I spent 10 years at a place called Imperial college London that we don’t tend to mention so much anymore. Thank you, Dr. Ferguson. Really what I was doing there is looking, looking at, um, very complex interactions within agricultural systems, looking at eco toxicology. And it’s really from that perspective that I’m giving this talk, which, which I’ve prepared specifically for this event.

[00:01:41] I had a feeling, um, you know, where, where Jessica was going to go. Um, so I only have one slide on Bradford Hill. So I’m going to really take a bird’s eye view that is aimed also to help the lawyers that are also going to be all of you are going to be at the coalface in terms of correcting possibly one of the biggest injustices that has occurred, um, you know, maybe, maybe in a few hundred years. Because it involves such a vast number of people. Even if we look at the wars that have occurred in the last few hundred years, they’ve involved relatively small numbers of people by comparison.

[00:02:22] But when you throw in the deception, um, and, and the complexity and the fact that we’re dealing with a moving goalpost and a moving target and a new pathogen, the information is changing so rapidly. Essentially what I’m doing here is, is, uh, and I will attempt to share my screen. Is that all visible? Yeah. 

[00:02:43] What I’m going to be looking at here is this complexity that we deal with the very fact that we have different standards for different people, depending on what you are looking at. So briefly, complexity. I want to talk a little bit about the language, particularly about the use of the term injury, which I think may sometimes get in the way, looking at where we were in terms of consensus, consensus in science is a pretty important concept, then look at the evidence in relation to cause versus correlation or association, and then perhaps looking at a more systematic approach. 

[00:03:20] Before we kick off, this is, uh, a really interesting paper from Friedkin, um, in, in the journal Science, one of the leading journals that was looking really at the phenomenon of weapons of mass destruction. And what it shows you, and I think I really liked to go back to this paper in the sense that, um, you will remember when there were a lot of people on this planet who believed there were weapons of mass destruction and it was appropriate to invade Iraq. And, um, there’s a guy called Tony Blair. Who’s now kind of being found out.

[00:03:57] But if you look at the neural pathways that are engaged, the way in which our views are influenced by the mass media, this paper actually shows you the mechanisms that underlie it. And essentially what, what our brains are tending to want is to develop a consistent logic structure between knowledge, a series of facts that are put together, and a belief system.

[00:04:22] So if you believe something very, very strongly, you’ll be interested to know that most of the people who see a problem with the jabs are probably more open to the idea of say, vitamin D NAC, zinc, maybe vitamin C being important factors in early treat. The people who generally believe that, that the vaccines are both safe and effective, tend to discount that.

[00:04:55] So there is a belief system that plays with the data that shows how bias works. And so, you know, we look, if the data are relevant, what kind of information we have, what’s the quality of that quantitative and qualitative data. We also need to find plausibility. That’s always the problem that homeopathy has had.

[00:05:16] And then we look at this reinforcement and if you just look at simple things like public health messaging on salt intake, you’ll find that actually it has never been proven through RCTs to, to consume less salt, but not too little salt. It’s all been improved through observational studies.

[00:05:36] So again, this idea, this scientific lens that we’ve been given is often not appropriate. It has been tweaked by various special interests. So first of all, addressing the complexity, are we looking at short term effects that are obviously going to be easier to deal with than long-term effects? Are we looking at a single cause a single trigger or are we looking at one of a number of factors working together with injury?

[00:06:02] Is it acute injury that occurs within 24 hours, 48 hours, 72 hours? Is it chronic injury? Jessica’s talked about dose response. Are we going to start seeing people have had more jabs suffering more injury, or we actually looking at disease? Disease that might manifest in a year, two years, five years, 10 years, 20, 30, 40 years.

[00:06:27] And, um, obviously if we have data from millions of people and it is high quality data, or even low quality data by very large numbers of people, it is easier to demonstrate either a cause or an association. And obviously when we get down to the individual, the N equals one, it becomes harder and harder.

[00:06:49] So obviously as we move to the right of this figure it gets ever harder to prove it. And that is kind of well understood by the opponents that we’re dealing with. So we look at a single person that that person has a genome, and that individual has a unique environment, a unique inner and outer environment. And actually their health status at any point in time is really largely an interaction between that genome and that inner and outer environment.

[00:07:22] As you start dealing with communities and whole populations, what happens is you’re looking at this really noisy environment. You’ve got thousands of different genomes interacting with thousands of different environments. That’s why we try and stratify data. We start looking at particular age groups or genders or ethnicities, and we look at particular patterns within co-morbidities, so we can try and reduce some of the genomic variance.

[00:07:49] But we don’t tend to deal so much with the environmental changes. We don’t generally ask people, you know, if you have a jab injury, what has been your diet, what is your underlying health status? Even though we know it is actually probably a very important factor. 

[00:08:07] When we look at the study of populations, we deal with the science, the branch of science called epidemiology. And there are a number of definitions. I don’t think we’ve really discussed this today. Just important again, for the lawyers to understand this, in terms of straight causation production, that’s when you’ve got a very clear cut relationship between, um, a cause and the occurrence of a disease. And let’s look at these things that we call vaccine injuries as diseases, they are dis ease.

[00:08:39] Then you’ve got necessary causes where you have to have that particular cause there to be able to demonstrate that disease. And the example here is, is HIV. You need to show evidence of HIV infection to demonstrate AIDS. Then you have this more important area, which I think is probably very important in the area of jab adverse conditions, is sufficient component causes.

[00:09:09] And that’s where you have, you know that it’s a multifactorial situation, but what you find consistently across many different situations is that one cause is always there. And that one cause may be the jab. It may be five jabs, because we’re looking at dose response. 

[00:09:27] We’ve then got probabilistic causes where you’re looking at the evidence increasing. The probability increases in association with that particular cause. And again, there’s probably this area is going to be pretty important. And then counterfactual evidence is also pretty important. If you take it away it’s a little bit like reversability, the 10th Bradford Hill criteria that Jessica talked to, it might be less of a problem.

[00:09:58] Now we already know there’s a lot that we can draw on for what’s been happening in other areas where we’re dealing with complex causation. A very important one is going to be climate change. And there’s a lot we can draw on, you know, whether you’re looking at, carbon dioxide concentrations, rising sea levels, what is causing it? And of course it is multifactorial. And what we tend to see is important variables missing from the equations, because they want us to look in one particular direction. And two of the really important things that are often missing from the debate is, is for example, the ability for living soils to act as a carbon sink. The other thing is habitat destruction. They don’t really want us to know about the extent of the damage to forest in West Africa or South America or Southeast Asia. 

[00:10:48] Another really important areas, obviously environmental pollution. And obviously there’s a big literature on toxic tort litigation where you’ve got often many factors. And there’s some really complex eco toxicology and law that underpins drawing those sorts of conclusions. 

[00:11:05] And one of the more recent ones that we’re all being contending within in the health area is looking at metabolic diseases like obesity. So the very fact that we still hear arguments over hypothesis, there’s still some people pushing the energy balance hypothesis. You’re eating too much. You’re not moving enough. But there’s also an endocrine hypothesis. There’s that there’s a carb or processed food hypothesis. And increasingly there’s a view that social determinants of health such as obese agentic environments are probably amongst the most important factors.

[00:11:42] So again, the stuff that we can draw there. This is also useful around the same area in healthcare, is this idea that if you look at risk factors of disease, and let’s call the disease type two diabetes, what we’ve been talking about, we tend to focus what, what caused it? But we tend not to look upstream at the causes or the causes of the cause or the cause of the cause of the cause – these distal upstream indicators. 

[00:12:11] And an example here. The distal upstream cause may be child trauma that caused that child to eat a bad diet that resulted in that child developing into an adult that had metabolic syndrome and lo and behold, not until that humanbeing was in the forties did a doctor pick up the HBA1C glycated hemoglobin marker, and said you have the disease. But actually it was caused, it was something that happened way, way, way upstream.

[00:12:44] We’re likely to see a similar kind of problem in terms of the complexity of injuries, damage, and disease that we see through jabs. Where has all of this science around these other areas got to, well, quite simply the understanding is that we’re not generally looking at simple pathways of causation. We’re looking at webs of causation. 

[00:13:09] Yes, there may be some deterministic ideas that come through that are really quite simple, but actually more of the time we’re looking at probability – how probability works with big data sets and with very well stratified populations. 

[00:13:26] A quick 101 by our dear friends in the CDC, quite useful to, to go back to their work simply because they are one of the enemies who keep trying to tell us that these things are safe. And, you know, they talk about the basic epidemiologic triad, whether you’ve got an agent, call it a jab, and then you’ve got the host and the environment. And between those three things disease can manifest. Okay?

[00:13:53] Now you got to know your agent, you got to know your host, and you’ve got to know your environment. Very often we don’t know very much about any of them. That’s part of the problem. We’re just hearing about the huge batch to batch variation with the jabs and then you’ve got Rothman’s causal pies that, that helps you to identify. Anyone who wants to do a, a quick analysis and look at which is the letter that’s common to all of those three sufficient causes. I think you’ll find it’s the A. So that’s the necessary cause. 

[00:14:24] So can we find consistent areas where the jab, even in a multi-factorial environment because we will always be looking at that is always the thing that’s there. Um, Bradford Hill, not going to go into at all because Jessica has done such a great job. 

[00:14:40] I want to just overlay the grade approach that’s been widely used. That’s the grading of recommendations, assessment, development, and evaluation. It can be applied and you can see how it can actually downgrade or upgrade evidence. Something to bear in mind when you’re looking at scientific evidence. 

[00:14:59] Another area to look is what has happened around autism. One of the most studied and evaluated areas around vaccination. And critical here is looking at the Omnibus Autism Proceedings in 2002. The findings came out many years later. That’s how long it took them to try and provide an impossible situation so that the national vaccine injury compensation program would hardly ever have to pay up. And then they do use these notions of moving from mechanistic evidence to proof. And again, as Jessica has said, it is generally almost impossible to prove unequivocably.

[00:15:40] What we’re looking at is a constellation of evidence, a balance of evidence that is pointing strongly, indisputably in that direction. And we’re looking at mechanistic, implausible evidence. 

[00:15:51] So what really happens in the real world? Come back to what the CDC said in terms of their triad. Well, the host, the human being with their genotype and their terrain, generally speaking, what we see is a subset of people who have vaccine triggered harm. And I’m using these terms quite deliberately.

[00:16:14] So there may well be particular subsets within the genome that are more susceptible. We’re dealing with a new jab. We’re dealing with new excipients in the lipid nanoparticles. So we’re still trying to understand where the susceptibility lies. 

[00:16:30] We know that the underlying terrain of the individual can be sub optimal. We know that people have comorbidities or they’re older, that they suffer immunosenescence if they’re older, if they have comorbidities. Multiple systems involved that relate to the immune system don’t work so well and they’re less likely to mount a clearing immune response. And of course the environment is pretty important as well.

[00:16:57] And we have to look at that particularly when you’re forcing people to be jabbed in a highly stressful environment, which happens when you maintain restrictions for long periods of time. So if we move to the basic evidence hierarchy, one of the things that you’ll find, and Michael, you, you talked about the importance of RCTs. Again, as Jessica has mentioned, Because we’re involved in a big experiment we have to kind of live in the world of prospective cohort, longitudinal observational studies. And we’ve got a grin and bear it that from a quality point of view, don’t be put off by the fact that from a statistical validation point of view, in terms of internal validation in statistical analysis, it will always receive a poor quality score. And an RCT will always achieve a high quality score. What it doesn’t mean is in the real world that it’s better to do an RCT. And in fact, one of the big problems you have with doing that is if you’re going to do an RCT, who’s going to do it, who’s going to pay for it. And of course, what you find is the people who will pay for other, the people who are forced to pay for it because they can’t get their emergency use authorization or their license.

[00:18:21] And you’ll see there’s a big queue of them sitting there, um, 140 currently in clinical development, all doing RCTs, um, and, and a bunch in preclinical development. Um, 194. So that’s the problem with RCTs. We have to move more to observational evidence. So this is a reminder you’ll see here. In grading, observational studies will always have a low quality label. That doesn’t mean that they will give you bad evidence. They may be an absolutely key piece of evidence for you. 

[00:18:54] Just taking this idea about validation. This is drawn from some of the work that people like Claudia Witt have done. Who’s trying to look at complex interactions in natural health care, and homeopathy, and complimentary, and alternative medicine.

[00:19:11] You’ll see that they effectively kick the RCTs out of the equation by saying guys, it doesn’t work in the real world. Because in the real world we actually have people who are engaging in multiple things together. They’re not just doing homeopathy. They’re also often eating a healthy diet. The homeopathic practitioner is often also giving advice that has helped them managing stress. 

[00:19:38] So you move in this direction through cohort studies, to pragmatic trials, and then, you know, real world, big data capture where you can get high external validation. And if you start to get a result there in a very noisy environment, actually, you’ve actually proven that the multifactorial system works very, very well.

[00:20:02] Just as we find with a lot of RCTs where you get a nice, significant result from an RCT, put it into the real world – we’ve seen this with Covid jabs – we actually get a pretty shocking result. It doesn’t work nearly as well as it did in the RCT. 

[00:20:18] We’re going to talk very briefly on shark attacks and ice creams. If you want to look at, this as an important example to look at in relation to correlation and cause. Obviously the number of shark attacks are going to be related to the number of people on the beach. And so you can see a clear correlation there. Does it mean there’s a cause? 

[00:20:37] What about ice creams? You have lots of ice cream sales going on, you have more people on the beach. But does it mean that there is a direct relationship between ice cream sales and shark attacks? Actually, statistically you’ll find that they’re correlated, but they’re not causal. 

[00:20:55] So what I’ve done is just taken an example here with Covid jabs to say, right if you’ve got Covid jabs and you start to see more heart attacks and strokes or arrhythmias or whatever, you will find that there may be an association. You may also see a very clear association has been very ,well-proven, between people who are over fat or overweight. I prefer the idea of being over fat. Um, it’s more accurate. They’re also sedentary, they’re also have type two diabetes, and there’s a relationship there. 

[00:21:24] So how do you prove, how do you extract out of that noise, this relationship? And that’s something we’re going to be looking at. So, moving to VAERS. Yes, we see this massive spike that’s occurred, but let’s bear in mind the sheer number of people that has been, um, these, these products have been administered to. 

[00:21:47] In the bottom graph what you’ll see is a very clear response here in terms of how adverse events are reported in the first three days, mainly the first two days, but even three or four days. So the minute you start to report adverse events later, and you’ve been hearing from lots of us saying that we’re really deeply concerned about problems that might emanate in months or even years, it becomes more problematic because that evidence isn’t there.

[00:22:17] But that’s exactly the same issue that you have in relation to acute toxicity, chronic toxicity, and then the relationship between carcinogens in the environment causing cancer many years down the line. So we can use the same kind of reasoning. If we’re going to use this approach, is injury the right thing to be looking for?

[00:22:38] You can see the courts are set up to deal with injury, but are they harms? Are they adverse events? Are they adverse conditions? Are they triggers? Are there mediators? Are they perpetuaters? So we’ve got to think carefully in this multifactorial environment, what are we actually dealing with? 

[00:22:57] So, temporal relationships, we’ve seen the VAERS data very clearly. If you have VITT – vaccine induced immune thrombotic thrombocytopenia, which is very well proven now from the AstraZeneca and the Jensen adeno viral vector jabs, that occurs pretty soon after the jabbing event. Now what happens if you’re then exposed to the virus? We have a really problematic confounding factor here, which is something that was just mentioned in one of the questions just now. The jab shares the very same toxic component as the disease.

[00:23:36] And then what, what happens if someone then has a heparin dose administered? Because, you know, heparin induced thrombotic thrombocytopenia has more or less exactly the same symptoms. So what would a court do with this? It’s a complex situation. How do you unwrap it? 

[00:23:55] Well, one of the things we need to focus on is a whole bunch of different data. All the AR databases, the pharmaco vigilance that the companies are doing, the post-marketing surveillance that governments are doing. We have to look at independent research. We must not ignore anecdotal reports. It’s interesting that the governments are hell bent, the media, believe it or not, are hell bent on us not looking at that, but what happens in science, those are the things. 

[00:24:25] Think back to thalidomide. It was the anecdotal reports that then caused the scientific focus to declare thalidomide a problem. Prospective observation studies are going to be key. We’ve got to look at disease prevalence studies so we can understand what the background levels are. And obviously really important things like all cause mortality and excess mortality, because the one thing we can be sure of generally, is when someone dies. Even though there are a number of papers showing that people have died more than once, which is peculiar to say the least. 

[00:24:56] And then obviously we need to understand all the systems that we need to be looking at. And it’s not just epidemiology we should be looking at. We also should be looking at epigenetics, biomarkers, mechanistic, toxicology, genotoxicology, because we are also dealing with a toxin. 

[00:25:14] Nearly there. The reality is in the real world, we are looking at a slow motion train crash. So how do we unpick that? Well, we have to understand that because Paracelsus told us 500 years ago, it is the dose that makes the poison, we now need to understand how the dose impacts the outcomes. Um, really important that we develop cohort studies.

[00:25:41] I’m involved in such a study right now where we’re looking at a prospective observational study that is based into cohorts that are based on the number of doses. So we can look at the health outcomes in those groups. We have to stratify the sub populations. We have to adjust for confounders.

[00:26:00] Now, confounding factors can be a causative agent. Okay. So we’re dealing with this multifactorial environment. We then must really find ways of showing that these adverse conditions are consistently and statistically, in statistics means that you’re dealing with probability, result in greater number of conditions consistently than you’d get background or in the jab-free population. 

[00:26:29] So you can see there’s a real problem in some countries, as they’re trying to push everyone to be jabbed. Has the word got out that in order to do this work, we absolutely need people to remain jab-free because that is the control group.

[00:26:45] Really important that we, the people, understand that. And that’s why there are groups out there giving people ID cards if they are wanting to be part of a control group and be unjabbed. I’m pleased from the lawyer’s point of view, please don’t accept the fact that observational data are unimportant or relevant.

[00:27:04] When you start to look at excess mortality data, you start to see problems, but it’s complex. So this, this is the EuroMOMO data that is most of the European countries, Israel, Ukraine, a few others. And what you can see in 2021 is actually a pattern for the ages between 15 and 74, where the 2021 excess mortality is significantly above 2020.

[00:27:33] What on earth is going on there? When the most vulnerable populations on the right side actually they’re more or less on par. So what are the drivers? And what’s going on in Italy? Italy, this is bang up to date. Italy is going through an extremely high, a very high excess of mortality. What’s causing it? Is it the pizzas? Um, perhaps, but it could be restrictions. It could be stress. It could be lack of medical care. And it could also be the jabs. 

[00:28:04] So I want to finish just by drawing on a couple of points from Paracelsus, because when you deal with toxicology, he’s kind of an important guy. So he said all those years ago, my accusers complained that I’ve not entered the temple of knowledge through the right door, but which one is the truly legitimate door Galen, a Greek physician, or Avicenna, a Persian physician or nature.

[00:28:28] He says, “I’ve entered through the door of nature. Her light, not the lamp of the apothecary’s shop has, illuminated my way.” And the second one, “The best of our popular physicians are the ones that do the least harm.” You’ve heard that from Hippocrates. “But, unfortunately, some poison their patients with mercury. Others purge them or bleed them to death. There are some who have learned so much,” and this is very pertinent now, “that their learning has driven out all their common sense. And there are others who care a great deal more for their own profit than for the health of their patients.” So on that note, thank you very much. 

[00:29:08] Shabnam Palesa Mohamed: Thank you very much, Rob Verkerk. I think you’ve done such an excellent presentation and for me, the multi-factorial environment is certainly fascinating and needs to be really deeply understood by those of us from different disciplines, intending and walking this path. Certainly a demand for your slides as well. And I’m sure you’d be willing to share that with us. 

[00:29:28] Dr. Robert Verkerk of course, co-chair of the Science and Humanity Committee at the World Council for Health. I believe Megha has to leave. I’m just going to check very quickly. 

[00:29:40] Rob Verkerk: Before Megha goes, can I say, as I was putting the slides together, I was most worried about her view on them and the colors.

[00:29:48] Shabnam Palesa Mohamed: Megha, if you’re still around, I hope you heard that. 

[00:29:51] Megha Verma: Yeah. It was a really great presentation. Thank you so much for sharing that. 

[00:29:57] Shabnam Palesa Mohamed: Thank you. Thanks Megha. Rob, because you’ve got about 20 minutes left on the timer of the recording, can we, to ask you a very special favor and that is to look for questions and comments that are relevant to your presentation in the chat and in the Q&A and engage with them in the way that you know best to do. But thank you once again, we appreciate your commitment and your knowledge sharing above all. And we look forward to hosting you at further Understanding Vaccine Causation Conferences. 

[00:30:25] 


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