November 03, 2022 from Rounding the Earth Newsletter
"It's a great huge game of chess that's being played—all over the world—if this is the world at all, you know." -Lewis Carroll, Through the Looking Glass

Click here for more articles on the Plandemonium.

Apologies for taking longer to push out an article on this interview than usual, but I had more to think through, and a long trip in between. John Cullen (not his real name as he explains) has done some interesting work. He also has a fantastic hypothesis about it. I wanted to think through the implications of the data he presents in order to lay out some basic thoughts that could be built on. I had no idea this would become a long-winded article, so here is…

Executive Summary: By the data, the pandemic is/was an explosion of pneumonia. Counterintuitively, this corresponds with the disappearance of influenza [to surveillance]. We examine a few hypotheses about why this might happen, making what seem like important observations, but without declaring conclusive results.

Sorting Through Hypotheses

John has done some excellent and interesting work. However, I think there are flaws in his story, and I think he made the mistake of aiming his communications early at journalists rather than finding a good pool of smart people to bat ideas around with. This also led him not to tighten his facts at the definition level, which I'll get to.

Here is John's primary hypothesis as I interpret it:

There were two pandemics: one influenza and one coronavirus. The influenza may very well be the Spanish flu strain revived.

Whoa, Bessy!

John has data that is consistent with his hypothesis, but I think that he has not done a good enough job of defining the complete set of hypotheses consistent with his data. Suppose there are numerous hypotheses consistent with the data John presents (and there are), how do we decide which one(s) most likely reflect reality?

The simple answer is that we investigate further, but to the extent that we stop and make subjective estimates on the probabilities of each, we should lean toward the ones that require the least complex conspiratorial machinery—at least at a threshold that seems like an economic balance. In other words, I'm leaving the door open to conspiracy (because you're simply a fool if you believe the word was invented for something that doesn't exist), but I recommend against selecting for hypotheses that require more expensive or complex machinery.

Now, let's consider the following hypotheses:

  • A novel coronavirus spread around the globe.

  • A novel influenza virus spread around the globe.

On a binary yes/no basis, there are four possibilities:

  1. Yes novel CoV. Yes novel flu.

  2. Yes novel CoV. No novel flu.

  3. No novel CoV. Yes novel flu.

  4. No novel CoV. No novel flu.

While I lean toward 2, I do want to do my best to set aside my biases as I think there is an interesting case for 1, and even cases for 3 and 4. Understand that it would take a book to cover the evidence and logic distinguishing all of these, so I'll try to focus on some important thoughts.

My John Cullen Interview

A little over two weeks ago I interviewed John Cullen, and this was an interview that nearly didn't take place. There is a lesson in biases and cognitive dissonance therein.

Click to play full interview.

The reasons this interview nearly never happened are twofold: (1) John's primary hypothesis needs to be generalized and remolded to a class of hypotheses that fit his data, and (2) John gave a first pass at explaining his "two viruses" hypothesis (one influenza, one coronavirus) to Jonathan Couey, Nick Hudson, Duncan Gonchar, and myself nearly a month ago before I (or we?) was ready to take his thought vector and project it onto broader thought spaces. That conversation took place after John first talked with Steve Kirsch on a couple of recorded meetings (here and here). He also talked with Jonathan Couey three weeks ago (here) outlining much of the evidence he has gathered. After all of that, I was not convinced of his hypothesis of a deadly influenza virus circulating largely due to my belief that a large portion of the 2020 carnage was iatrogenocide—planned negligent care combined with directed early virus treatment nihilism. In my mind, we do not need an influenza virus to explain the excess deaths in 2020.

But I had not fully dismissed John's hypothesis at least in part because I believed that some of his evidence actually supported my Big Picture view of the situation. His story of the Spanish flu being a potential culprit triggered my cognitive dissonance shielding, so I did not at first think through how his data stands without that narrative attached. His data does reinforce most of what I've come to believe, but I'll get to that. It is perfectly consistent with the iatrogenocide hypothesis.

Much of the purpose of this article (aside from sharing the interview) is to make some minor corrections or challenges to John's story, then in fairness give a broadened version of his hypothesis the fairest look.

Corrections I would like to make to John's points:

  • John called the Spanish flu the "blue death", but it was actually the "purple death".

  • The PNI category is not defined as he seemed to believe. We'll get to that.

Definitions Matter: What is PNI?

John is absolutely correct that the excess mortality during the pandemic tracks with the CDC's pneumonia and influenza (PNI) statistic very closely.

So, the question is whether the pneumonia cases are due to SARS-CoV-2, influenza, or possibly something else?

Now, John's presentation makes an incorrect assumption that the PNI statistic implies influenza is an ingredient in each PNI case. This is where John's discussion lacks completeness at a foundational level. This does not mean that his hypothesis is necessarily incorrect. It just means that we need to do more work to see what set of hypotheses are consistent with the data. This is not entirely John's fault (except that he should have reached out earlier to more scientists and smart people to discuss the details with). It may be that the CDC creates such an obfuscating categorical definition for the purpose of manipulating public understanding of the actual risks of each. (I think so.)

Is PNI the Venn union, or the Venn intersection?

This whole "X and Y" categorization gets tricky. In logic, we interpret "and/or" as with sets above:

  • The set "X and Y" is the football-shaped intersection in the diagram above.

  • The set "X or Y" is all the colored region (the union) in the diagram above.

However, in conversation, people often use "and" to mean the union. People also use the exclusive "or" to mean the union minus the intersection (just the non-overlapping portions of the circles), often where no intersection is defined (as in "black pieces and whites pieces" on a chessboard, "stars and planets", or "rainbows and unicorns", maybe).

So, which is it?

We get our answer from the CDC. Sorry for the lack of font quality from their site tables:

Let me zoom in on the numbers in the "influenza", "pneumonia", and the "pneumonia and influenza" columns in case you can't see them well:

As we can see, the third column is the sum of the first two! This means that the deaths in the P&I category are not people with both (intersection) pneumonia and influenza, but in fact died of one or the other (as if the intersection is null) of the conditions. This is the exclusive "or", which is the Venn union minus the intersection.

What PNI really means at the CDC

John's presentation demonstrates the general confusion further by showing how the PNI numbers are presented in different ways, at different times. This is important! He shows the CDC modeling PNI mortality by assuming hospitalized and non-hospitalized proportions to be the same—that's quite an assumption! In an interview over at The Defender Show, Meryl Nass explains that the real number of deaths due to the flu may be as small as just 3,000 annually. That's consistent with the proportion in the numbers I found in the one data set above. It's pneumonia that does nearly all of the killing. Further, it's not clear (at least from basic data) how much influenza infection opens the body up to pneumonia, or whether the body being weak and susceptible to pneumonia leads to infection. (I'm open to being wrong about this point, and If I'm wrong, please send me that research that clears up this cause/effect question.)

The Influenza Hypothesis

It is remarkably strange that, according to the World Health Organization (WHO), the influenza virus just sort of…disappeared for a couple of years before coming back later. It beggars belief! The problem in figuring out what happened is that we have so much evidence of lies, misdirection, and deceit that our attention isn't easily kept open to the fact that our explanations haven't yet accounted for all the information.

Why? Why in Pfizer's name did the flu just sort of…take a break?

Well, maybe it didn't!

Okay, okay, I know what many people are probably thinking at this point: "We knew that already. A lot of COVID-19 cases were really just the flu." And I suspected that myself at times, but it's not enough to have suspicions—particularly when there are numerous hypotheses consistent with the known data. Also, there is no doubt that the symptom spectrum—most particularly the loss of blood oxygen—clearly did change. Meanwhile, the number of people suffering respiratory illness actually declined. I'll come back to these points in turn.

John's primary point is that an influenza could have been circulating all of this time that was simply hidden or otherwise invisible to the usual surveillance. And if the circulating influenza changed enough to evade surveillance, it may very well have changed enough to cause different symptoms. Or did the interplay between influenza and bacteria somehow change? I'm not biologist enough to know how perfectly or not that I'm asking these questions…

Forget for a moment the possibility that this might have been the Spanish flu, revived and escaped/released (for which there is only indirect/tertiary evidence). Ultimately, what we need to think through is how the WHO lost track of the flu.

There are a few possibilities:

  • Testing for influenza is centralized enough that assays could have been rigged to miss it.

  • Testing for influenza stopped being conducted.

  • A novel influenza strain appeared that dodges traditional surveillance. This might be the result of a lab leak or release. The goal might even have been to design an influenza that would confound the usual testing methods.

  • Other?

Leaving aside whether or not such an invisible flu is a Spanish flu derivative, specifically, one obvious question that pops up is whether there was a coordinated cessation of influenza surveillance (testing). If this requires conspiracy (hush your mouth!)…I'm happy to entertain conspiracy theories because I believe there are many real conspiracies (we created the word…for a reason). But the broader the requirement of participation for a conspiracy—especially including parties with incongruous goals—the less reasonable I judge the conspiracy theory. In fact, just two parties with disparate goals should tank any subjective probability of the proposition by up to orders of magnitude. But it's possible that many nations were given/sold surveillance systems/kits that were somehow sabotaged? Eh, I still need serious evidence…

While thinking the problem through with friends, including Jonathan Couey and Charles Rixey, we noted differences in specimens tested by the CDC (from here and here):

When I see a single positive test from a four-digit number of tests, I tend to think, "That's probably the false positive. There's probably essentially nothing out there. Why continue conducting more tests?" So, the lower amount of testing could represent a perceived statistical lack of need for further testing. However, it could also represent a cessation of testing in nursing homes and hospitals. But could such a targeted demographic shift in testing happen the same way in every nation on Earth?! That seems unlikely, but if there is evidence, please share it with me.

Next, note how different the 2019-2020 flu season—judged by "influenza-like illness"---is from other seasons.

The triple-peak is weirdly different from almost all other viral wave patterns I've ever seen. Even between the peaks, that was a bad season, as Cullen pointed out. But then ILI moves to levels similar to prior years. The only difference is that the numbers just never come back at all (until two years later). This is consistent with a novel pathogen taking longer to reach rural America after sweeping through more dense and connected urban populations. But nothing in the graph alone distinguishes well between most of the competing hypotheses.

Note that queries from the military health database show ambulatory reports of respiratory illness collapse in 2020 and 2021, even when COVID-19 cases get added into the total (regardless of whether respiratory symptoms are presented). However, hospitalization rates for those illnesses rose a bit from 2019-2021 relative to 2016-2018. This is consistent with other data sets I've seen.

Hospitalizations have been closer to normal, however, with a bit of a spike in 2021. Perhaps more interestingly, hospitalizations per ambulatory report (still DMED) mostly trended upward starting in 2019.

Of course, this may relate to nothing more than telling people not to do anything to treat their viral infection illnesses until they're in need of hospital care. Again, I see nothing in this data that makes me prefer any of the competing hypotheses.

In general, I still prefer the simpler hypothesis of a single novel virus as opposed to two. But if that virus is influenza, it might very well be that guys like Ralph Baric knew how to crank out an infectious coronavirus clone with the spike as an identifying marker in order to confuse everyone. One way or another, we should examine reasons we might prefer the novel flu hypothesis. One of those is that the suppressed drugs of chloroquine and hydroxychloroquine are derived from quinine, which was historically field tested with success against the Spanish flu and other influenza outbreaks.

I am also still trying to interpret the sad case of Tammy Bay who had low oxygen, tested negative for COVID-19, but seemed to be treated like a COVID-19 case at the hospital with what could be interpreted as a disturbingly motivated protocol designed to keep her immobile.

Is it just possible that the hospital had seen some such cases, and somebody there "knew what to do" with her despite her lack of coinfection? Perhaps most people with the novel flu were understood to get a coinfection with the CoV, but a few people were genetically resistant?

Virus Interference vs. Virus Coinfection

I never bought into the "viral interference" story that suggests that SARS-CoV-2 pushed influenza out of human transmission.

"Wow, what a novel virus? Can it do my taxes, too?!"

Viruses move around a body like asteroids in a solar system. Sure, they can come into contact, but they're relatively small objects in a relatively vast region of space. And stifling the ability for a virus like influenza for two full years means smothering transmission receptors to the point that even a segmented virus like influenza can't find a way to permute and mutate for adjustment.

People may think that infection spurs the immune system, which then handles other infiltrators. But those are the cases of people whose healthy immune systems fight off all of both invaders. Infection gets bad (for any virus) precisely when the body is unable to mount the appropriate immune response. Technically, "virus interference" is a term that includes coinfection odds. It makes the most sense that the presence of one pathogenic virus increases the odds of infection by another because either the infected body has compromised defenses (such as disrupted interferon activity) or because the first infection weakens the body's ability to fight off another one properly and completely.

Twitter avatar for @Kevin_McKernan
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