The best way to begin might be to say that there are three distinct categories of Olympic games sites that the City of Paris wants to make ultra-safe for visitors and athletes, each with its own unique security challenges. 

First, there are the many official, already-existing sporting venues (stadiums, arenas, tennis courts, aquatic centers, etc.) located throughout Paris and France. These require the least amount of novel security measures, whether in the form of protective perimeters or the (unusual) methods used to maintain them. 

Included among these is the historic Grand Palais, an architectural jewel from 1900 located at the foot of the Champs-Elysées. A monumentally massive building with a marvelously versatile interior space, it regularly plays host to museum exhibitions of all types, in addition to galas, elaborate fashion shows, concerts, conventions and even an ice-skating rink. Turning it into an Olympic sporting event site won't have been very difficult. 

Second, and complementing these dedicated sporting facilities, are several famous outdoor public monuments and historic landmarks that have been transformed into temporary games sites. 

These comprise, most notably, the Trocadero and area next to the Eiffel Tower, the Château de Versailles, the Place de la Concorde, the Alexandre III Bridge, and the expansive lawns in front of the Hôtel des Invalides. 

Massive amounts of bleachers and facilities for ticketed spectators have been brought in and creatively set up to adapt to the often unusual contours and spatial constraints of these areas. Seeing the obelisk at la Place de la Concorde hidden behind a patchwork of crisscrossing bars and stands was strange indeed. From the outside, the expansive fenced-in area, with giant stands rising out from the emptied out streets, looks like a curious sort of fairground. 

Third, and arguably most importantly, there is the Seine river itself, which will be the location of the opening ceremony as well as several aquatic competitions. 

From a security standpoint, the first category of venues is the most straightforward because entrances and exits are already part of the structures. All that is necessary to guarantee spectator and athlete safety is to set up slightly expanded perimeters around the buildings and flood the access points with staff and security guards so that no one -- or anything -- dangerous gets through. 

Think of the Barclays Center on game night. Plenty of space to accommodate the crowds at the entrance waiting to go through security, with minimal disruptions to the immediate surroundings. 

The second category of event sites, as mentioned above, significantly modify public spaces outdoors; they pose greater security and logistical challenges, as the physical enclosures separating "outside from inside" -- separating the ticketed spectators from the unticketed -- have to be brought in on trucks and set up. 

These barriers are made up of hundreds of miles of what are essentially chain link fence units (about 10-feet long and 7-feet high) set into concrete slabs that can be moved around and connected as needed. 

They wrap around the temporary outdoor sporting event sites in odd, unsightly ways and, notwithstanding the considerable effort to line them up neatly, look to many like human kennels. (Upset Parisians are referring to them as cages.) 

The last site/category of Olympic events, and the location of the opening ceremony, the Seine river, is the most problematic in terms of security perimeters. 

In fact, in order to meet the endless safety, commercial, and sanitary needs associated with the many uses to which the river is being put, an unprecedented thing has taken place: for 8 days leading up to the opening ceremony (tomorrow), the Seine and its immediate surroundings have undergone a form of privatization that has kept almost the entirety of the Parisian population off its riverbanks and away from its nearest surrounding streets and bridges. 

Implementing this shutting down of the river has involved widespread use of the aforementioned chainlink-type moveable fences -- thousands of them -- along with a novel but not entirely unfamiliar technological device: the QR-coded pass. 

To help explain what this is looking like on the ground, I'll attempt to draw a hypothetical analogy with NYC. 

It's a highly flawed comparison due to the very different layout and features of the two cities, with the proportions off, but it's the best I could come up with under pressure to illustrate the point. 

Imagine that 42nd street in NYC was the Seine River, and that all of the Avenues slicing through it were Paris' many bridges connecting the North and South sides of the city. 

Now picture the sidewalks of 42nd street as Paris' Right and Left banks, or riversides, and all the buildings on the North and South side of 42nd street, extending down its entire length, like the rows of charming old Parisian apartment buildings you see overlooking the Seine in postcards. 

Okay, now think of what life would be like in Manhattan if, for 8 days, all of 42nd street (street, sidewalks, avenues, entire blocks of buildings) was completely off limits to all motorized traffic and most foot and cycle traffic, with only two avenues -- one on the East side (say, 2nd avenue), and one on the West side (say, 8th avenue) -- left open to handle all of midtown Manhattan's North-to-South movements: foot, bicycle and motorized traffic. 

On top of these restrictions on 42nd street, imagine the entire area encompassing 41st and 43rd streets -- cross streets and all -- every inch, being cut off to all motorized traffic for 8 days, except for emergency and police vehicles. Buses would be rerouted out of the area. 

Random pedestrians and cyclists approaching from Uptown or Downtown could move freely within this outlying area immediately to the North and South of 42nd street, but they could still not access 42nd street itself, and as they entered into the outlying pedestrian areas through police checkpoints, they would be subject to random bag searches by a police presence resembling that of an occupying army. 

Subway service would continue to run uninterrupted through the zone, but would not make any stops on 41st, 42nd and 43rd streets. All major subway hubs in the area would be completely closed for those 8 days, including MetroNorth and LIRR trains running into and out of Grand Central. 

Drivers wishing to travel from, say, the Upper East Side to Kip's Bay might find it faster and easier at rush hour to take the Queensborough Bridge to the Queens Midtown Tunnel, swinging back again into Manhattan, rather than sitting in the bottleneck forming for blocks and blocks along the approach to the 2nd Avenue 42nd street southbound crossing. 

Imagine in addition that more than half of the width of 42nd Street sidewalks was completely taken up with metal stands and bleachers in preparation for an opening ceremony parade of slow-moving trucks that would traverse 42nd street from East to West all the way across. 

(In Paris, the opening ceremony will feature decked out boats gliding down the river representing the participating nations, so in addition to the river banks, most of the bridges in the center of Paris are also filled with empty steep metal bleachers. 

My fanciful comparison with NYC unfortunately doesn't allow the avenues to behave like bridges, but if you can picture the Park Avenue Viaduct over 42nd street filled with empty seats and benches stacked high and looking down over the street, you can get a sense of how this vitally important public space has been turned into one vast seating area, sitting idle for 8 days.)

Controlled access to the thousands of residences, businesses, and shops on 42nd street via the many otherwise closed-off avenues would begin as far away as 41st and 43rd streets (and sometimes one or two streets farther removed) behind hundreds of feet of the aforementioned chainlink barriers and through select access points guarded by police units 24/7. 

Entry would be granted only to authorized individuals in possession of a special QR-coded "Games Pass." 

The "authorized" individuals allowed to enter this area, on foot or on bicycle only, would be: local residents, owners or employees of shops and businesses on 42nd street, and/or tourists and others with valid reasons for needing to be there. 

The latter reasons would include and be essentially limited to: medical appointments, lunch/dinner reservations in restaurants, and the need for guests staying at hotels or airbnbs within this "secure" perimeter to return to their accommodations. 

The QR-coded "Games Pass" itself would be issued to applicants only after successful submission of detailed personal information and supporting documents to the NYPD well in advance of the shutdown period. 

The NYPD would record all the personal information about who lived and worked within this soon-to-be shut down perimeter, presumably verify the accuracy of the information provided, and then give, or withhold giving, the green light for issuance of the "Games Pass."

For reasons unknown, many employees of small businesses would never get their QR-Coded "Games Pass" after correctly providing all necessary personal information to the authorities. 

(In Paris, this inexplicable failure to issue "Games Passes" to employees whose workplaces were inside the locked-down areas, whether due to human or machine error, initially created much tension between cops and workers at numerous access points, as the latter tried by many means (getting their bosses on the phone, showing proof of employment, providing friendly assurances, etc., often in vain, to justify their right and need to enter the area.)

On the afternoon of the opening ceremony, the bleachers lining the sidewalks of 42nd street, along with the rows of stands looking down  from the Park Avenue Viaduct, would slowly fill up with the more than 300,000 ticketed spectors allowed to watch the Olympic Parade. 

No one else in NYC -- unless they happened to be lucky enough to live in a building on 42nd street with a window facing the street -- would be allowed to get close enough to the event to see it with their own two eyes. 

It's hard to capture the universal exasperation caused by this 8-day near total shutdown of the Seine River, its upper and lower riverbanks, the buildings all around it, and most of its bridges. 

The rerouting of motorized traffic and resulting colossal bottlenecks around this central part of the city have been an absolute nightmare to taxis and commuters at rush hour -- even after the significant reduction in the number of vehicles on the roads following the seasonal exodus of Parisians fleeing the city for summer homes and foreign vacation destinations.

But it's the restrictions on pedestrian and cyclist movements around the water and riverside areas that have enraged Parisians the most. 

Hemmed in and funneled through long narrow spaces between sidewalks and empty roads, local residents and visitors to Paris alike are bristling at the intrusive, intimidating metal fences, which are more in line with the types of structures you would see at a detention center or migrant camp than at an international sporting event. 

It's hard to overstate how violently these unsightly barriers clash with the otherwise beautiful surroundings they are keeping people out of. 

All of these restrictions have, not surprisingly, led to a serious drop-off in tourist activities in the area. Restaurants within the cordoned off "security perimeters" are making 30%-70% less than this time last year. This is the case even in the buffer zones leading up to the river where motorized traffic is prohibited but foot and bicycle access is allowed without restrictions. Terraces and restaurant interiors are empty here too. 

(Fortunately, the many other stadium/arena/transformed venues around Paris that will be hosting events in the days following the opening ceremony will not cause similar disruptions to neighboring businesses, interrupting traffic flows in the immediate area only for a few hours preceding and following the events. 

In such spots, the QR-Coded Games Pass will play a less important role, and won't be needed by local residents or shopkeepers because no shops or businesses open to the public will be located on the same site as the sporting venue. Only visitors/spectators to these sites will have to worry about QR-codes and QR-coded tickets.)

But to return to the river opening ceremony "security" preparations, in order to monitor the hundreds of access points along the North and South banks of the Seine (as well as to monitor the many other Olympic Game venues around the city), 45,000 police and gendarmes have been mobilized, with thousands pouring into Paris from all over France. 

I spoke with about a dozen such officers stationed at checkpoints all along the river, and I asked them how things were going. Most -- in carefully chosen words and professional tones -- said it was a shitshow. 

Interestingly, all the police I happened upon were from other parts of France and most were not at all familiar with Paris and its streets and bridges. So when asked by annoyed locals or confused/lost tourists about how to navigate around the off-limit zones, such officers were often of little-to-no help. 

On the two occasions I witnessed local Parisians ask how to get around a closed-off area, the out-of-town police shrugged and apologetically explained how they weren't from Paris and didn't know.

Standing for hours on end at the hundreds of cordoned off access points, they would repeat calmly and patiently that they were stationed there solely to check passes and make sure unauthorized persons did not get beyond them. It was unreasonable to expect anything more of them, they seemed to be saying. 

This led me to ask how the actual process of checking the "Games Pass" -- their primary responsibility -- was unfolding. 

It turns out that the way things were supposed to happen was that a person in possession of a "Games Pass" seeking access to the restricted area also needed to show police a separate ID, and sometimes further proof of what they claimed to be doing in the area (if they didn't live or work there), at which the police could cross-check the name with the information called up by the QR-code scanner. 

But it seems there are not (or at least weren't as of Monday) enough scanners to go around, and, making matters worse, the scanner screens can't be read properly on sunny days due to the glare. 

So in such situations -- which also include instances of people not receiving their "Games Pass," or having lost their paper copy -- the police have to "use their best judgement," and let people through on the basis of simple ID checks and the believability of the person's story for needing to be in the off-limits area. 

The police officers I spoke with said a small number of people, like myself, objected to the use of QR-coded passes on principle, saying that it reminded them of the health and vaccine pass nightmares, and that hosting an international event was no justification for denying freedom of movement in this way. 

When I asked what they themselves thought of the kennel-like security restrictions, and if they agreed with any of the freedom of movement concerns raised by angry residents, most seemed to miss the point entirely. They would invariably utter something about the size and scope of the event requiring the extraordinary security measures, that terrorists would be plotting, etc. Almost like a pre-recorded message (though eloquently conveyed). 

But one cop I spoke to at length raised another issue I hadn't thought of: keeping the entire city away from the Seine for 8 days and nights was also aimed at preventing the newly cleaned river from filling up with human garbage again. 

The banks of the river in the warm summer months are thronged with revelers all through the evenings, and this leads to tons of junk and pollution ending up in the water. 

It turns out that 1.4 billion euros went into a massive 6-year river clean-up project, beginning in 2018, to make the Seine safe enough to swim in for the handful of aquatic events set to take place in it this summer. 

E coli and other bacteria seem to have disappeared (or at least no longer pose a threat to human health) and the number of fish species has made a huge comeback, jumping from 3 to 30 in the last few years due to the significant increase in oxygen in the water. 

Understandably, the Olympic Games organizers and City of Paris didn't want flotsam in the form of empty wine bottles to be seen bobbing up and down between the parade boats on the opening night, so they decided not to take any chances and simply banned everyone from getting within spitting distance of the water. 

This got me thinking. 

This whole 8-day Seine shutdown -- which in some ways amounts to privatizing the river, making access available to only a fraction of the tax-paying population -- could not have been imaginable without the availability of digital passes such as this QR-coded "Games Pass," which can store and instantly call up huge amounts of pre-vetted personal data. 

Though there aren't enough of the scanners to go around, there are enough to just about make it all work. 

Without such on-the-spot digital data-storage technology, the thousands of local residents and other "authorized" persons needing to access the areas around the river on a daily basis would have to carry around with them at all times: IDs, proof of residence and proof of employment papers. And they would need to show them all every day to every cop they came across at the checkpoints.

Police stationed at these checkpoints, in turn, would have to spend endless time cross-checking all these documents, and querying every non-resident about their purpose for being in the area -- a mini-interrogation each time a local resident or worker sought to cross an access point. 

It's hard to imagine the proposal to shut down the Seine river for over a week being taken seriously even in an informal spitballing session of city counselors (let alone in a national-level ministerial meeting) if it involved local residents living by the river having to produce reams of documentation every time they came back from work or the supermarket. 

One would hope that such an imaginary discussion, after eliciting groans at the idea of such intrusive on-the-spot background and ID checking by police, would have quickly led to other considerations being raised, such as freedom of movement and the unreasonable obligation to justify one's presence in public areas.

So there had to be a way to streamline such an extensively coordinated, large-scale shutdown of a heavily populated urban area requiring such tight control of people and their movements, ideally, without people taking too much notice of the personal intrusions and infringements on certain rights and freedoms. 

Cue the QR-coded "Games Pass."

Had there been no sophisticated QR-coded tools to facilitate such an undertaking, it's likely the hairbrained and outrageous idea of emptying out and privatizing the center of a major metropolis -- with all its attendant civil rights questions -- would have been immediately apparent. 

One wonders if questions over the feasibility and legality/constitutionality of such a proposal were ever brought up in official discussions in 2016. Perhaps, instead, the fascination with the vast organizational and control/surveillance potential of the QR-coded "Games Passes" caused such concerns to be dismissed or downplayed -- or eclipsed entirely -- once again revealing the dangerous hidden biases of these digital technologies.  

In my experience, asking proponents of surveillance/control tools like QR-Coded "Games Passes" or Health/Vaccine Passports about the totalitarian nature of the use cases that such technologies inevitably give rise to typically elicits ironic eye-rolling and accusations of alarmism, followed by reassurances about the benefits of enhanced security on a limited time scale. 

In the case of the Paris "Games Pass," such enthusiasts are also quick to highlight the added bonus of having a cleaned up river to enjoy going forward. The 100-hundred-year ban on swimming on the Seine is set to be lifted after the Summer Games, with the opening up of select swimming areas along the river next summer.

But those of us who lived for two-plus years under the totalitarian corona regime, with its QR-coded health and vaccine passes, see this as a clear attempt to continue testing out these technologies in new contexts involving restrictions on basic rights and freedoms, slowly and steadily conditioning public acceptance of their use in preparation for the inevitable roll out of digital IDs in France and the EU (unless the Europeans start organizing to oppose these out-in-the-open Orwellian plans).

Indeed, it seems the French government misses no opportunity these days to insinuate QR codes into large-scale public celebrations and gatherings where they are not needed. 

To wit, the annual Bal des Pompiers (Fireman's Ball) this year (a uniquely French outdoor celebration held inside the courtyards of Fire Stations all over France on the 13th and 14th of July, which is free and open to the public and draws massive crowds of revelers, featuring the presence of French Foreign Legionnaires and other elite military personnel), for the first time ever, prohibited the use of cash and credit cards for purchases of food and drink, and instead required partygoers to buy a QR-coded "credit card" at the entrance.

In order to consume food or alcohol within the firehouse, one had to line up at a special booth and exchange money for a special one-off QR-coded plastic card (the size and shape of a credit card) which then became the only accepted form of currency for purchases during the all-night outdoor celebration. 

Unlike previous years, where the firemen serving food and alcohol also handled cash and credit cards, this year they were armed with little scanners, with which they beeped and deducted credit from these disposable digital money cards. 

It introduced a wholly unnecessary, illogical, time-wasting step into the normal "money--food" transaction process on the grounds that it would streamline the handover of food and drink in an extremely busy and crowded space by freeing vendors from the need to handle money. 

It of course did exactly the opposite, causing people to waste more time standing in the QR-coded card line each time they wanted to buy or top up their card. Worse still, drunk party goers undoubtedly lost hundreds, if not thousands of euros, from putting more money on their QR-cards than they were able (or remembered) to spend on food and alcohol during the rollicking festivities. 

To those of us still reeling from the use of the health passes, it was a terrifying, flagrant further example of the incremental social engineering that has been going on in Europe for the last 4 years, with its two-fold aim of phasing out cash while preparing the public for a sudden shift to a digital euro during the next manufactured emergency. 

I can only hope the uproar caused by the Summer Games' disruptions to people's ability to live and work in and enjoy their city will shine a light on these dangerous technologies of control and surveillance that I believe are irreconcilably incompatible with the values and principles of a free society.

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Now for a bit of backstory:

John Beaudoin - on substack - petitioned the state of Connecticut for their death certificates and received them under certain conditions. Until now we were unable to publish data from CT death certificates. Recently this changed, but I will refrain from elaborating on this further out of an abundance of prudence borne from a deep and abiding respect and appreciation for the rule of law and our magnificent judicial system1. (He also challenged the state of Connecticut rather bluntly over their complicity in hiding evidence of excess deaths from... causes…)

Hopefully we will be able to publish Connecticut data unfettered by any unforeseen constraints indefinitely, but this is not guaranteed.

Returning to the mass Bidenization of Connecticut during his presidency, for a number of reasons, such a trend is very unlikely to represent the stipulated nominal increase of deaths involving a heretofore unknown mysterious unclassified ‘senile brain degeneration’. The simple fact is that the trend itself belies reality. Even in the present climate, it is difficult to imagine a new clinical phenomenon going from functional nonexistence to accounting for almost 2% of deaths each year (!!):

And even if such were the case, for it to happen without anyone noticing is implausible - there would be simply too many clinicians on the ground actively documenting instances of this new disease for it to completely escape notice for the general public. And the clinicians definitely noticed this - the deaths with the G311 code all have the text “senile brain degeneration” on them, so the doctors who were writing these words instead of “Alzheimer’s” or “Dementia” made the conscious choice to do so.

Fortunately, this is something we might be able to flesh out a bit from the data. If the staggering supernova of fatal brain degenerations was the result of a change in coding policy or documenting conventions by coroners, we should be able to see a concurrent deficit in deaths involving ‘senile brain degenerations’ that are elsewhere classified - like Alzheimer’s, which is denoted by the ICD10 code G30 - and is something we do indeed see, at least superficially:

2020 shoots up because there was such a massive increase in brain degenerations overall that even pushing a number of them into the ‘other’ category, there were still plenty left to be coded as Alzheimer’s.

If we combine the Alzheimer’s deaths with the ‘other senile brain degeneration’ deaths, we get the following trend which is far more ‘normal’:

Now we see pretty even trends both before the pandemic (grey bars 2015-2019), and then during the pandemic (colorful bars, 2020-2023), albeit running at about 50% excess.

In essence, what seems to have happened - at first glance - is that some number of deaths that used to be classified as Alzheimer’s were instead classified as ‘other senile brain degeneration’.

But does this hold up? Let’s see.

Why the crazy trend though?

Just because there was an ‘administrative phenomenon’ doesn’t explain *why* a novel policy or coding algorithm change was made. Furthermore, it is definitely possible that there was a change in the characteristics of people with Alzheimer’s-like conditions which led to doctors writing down a different text formulation in some instances.

Nursing Home Residents (NH) vs NON-NH Residents

Our first clue comes from looking at the breakdown between NH/NON-NH deaths.

Whereas the increase in G311 ‘Other Senile Brain Degeneration’ deaths is roughly the same for both -

- the trend in Alzheimer’s deaths is not:

Whereas there is an immediate decrease in Alzheimer’s deaths in NH residents from 2021 onward, there is no such drop in the non-NH residents until 2023.

To better visualize this, the charts below show side by side the number of Alzheimer’s deaths (left) and the number of ‘other SBD’ deaths (right) in NON-NH residents:

It doesn’t seem like the novel ‘senile brain degeneration’ deaths are coming out of Alzheimer’s deaths in this group. Rather there is a stable jump in Alzheimer’s from the pre-pandemic clustering around the 500-600 range to around 800 for the next three years before finally coming back down to 681 such deaths in 2023.

Yet the stark explosion of mysterious ‘other senile brain degeneration’ deaths not only occurs but has a more dramatic increase compared to the nursing home residents (!!).

Number of ICD Codes per Death Certificate

One of the variables I like to keep track of is the number of ICD codes on each death certificate. It’s a useful tidbit of information to have, and could be a harbinger for suspicious coding practices or unknown pathologies wreaking havoc.

Typically, we should see more ICD codes the older the decedent, simply because older people tend to have mor medical conditions compared to younger people. We also shouldn’t see a significant deviation in the number of ICD codes on death certificates with any specific condition if there was no change in the coding practices or pathology of that condition.

With that in mind, let’s take a look at the ICD averages for Alzheimer’s and Other SBD deaths.

First for some context we need to see the average number of ICD codes for *all* deaths among seniors (NH left, NON-NH right):

The average number of ICD codes is remarkably similar for NH and NON-NH residents alike, except that the average for the NON-NH deaths dips sooner and a bit steeper after 2020 compared to the NH deaths, but not by much. Interestingly there is a noticeable drop in both in 2023 where the average # of ICD codes is well below the 2015-2021 baseline.

Basically we see an average of about 2.8-3 ICD codes until 2023 where it drops to ~2.55-2.65.

This is actually quite shocking in itself. In other states, the average # of ICD codes we see in the other states we have data for is well into the three’s and over *4* by the pandemic years. (And that is despite some Medical Examiners who handle a lot of deaths each year in these states averaging under *TWO* ICD codes per senior death, which basically means they’re engaging in fraud. Hopefully will have an article out on that eventually, because it is quite scandalous and calls into question the integrity of all the national mortality data even before covid.)

Averaging under three conditions per death for seniors seems to me like there is massive failure to document relevant conditions on death certificates in Connecticut.

Compare that to the average number of ICD codes on death certificates with Alzheimer’s (top) or Other SBD (bottom):

Immediately we can see that the average number of ICD codes on these deaths are well below the average overall.

• The top left chart which shows Alzheimer’s deaths in NH residents is the closest to the average for all deaths, with each year being about .1-.15 below the average for all deaths that year. This by itself is a bit surprising for me, because I would have thought that patients with Alzheimer’s have a ton of other stuff going on, not less than the average number of conditions for seniors dying. The trend before the pandemic is going down year over year (which itself is curious), then ‘resets’ in 2020 before dropping each subsequent year in a steeper trend compared to pre-pandemic.

• The top right chart - Alzheimer’s deaths in the NON-NH population - shows a dramatic drop off in the average # of ICD codes starting in 2020, and it plummets well below the rate of the average # of ICD codes for all deaths among NON-NH resident. This is immediately suspicious - if nothing changed about the people dying with Alzheimer’s, then why are they dying ‘healthier’?

The real action is in the bottom charts showing the average # of ICD codes for the ‘Other SBD’ deaths:

• The bottom left chart - ‘Other SBD’ deaths in the NH population - is consistently about .5 to .8 less than the average (that’s a big number in this context), with the weird exception of 2021 where it jumps to within about .2.

• The bottom right chart - ‘Other SBD’ deaths in the NON_NH population - is well over a FULL ICD code lower, and almost a full 50% drop off from the average number of ICD codes for each year. This is staggering, especially considering that there are a substantial number of these deaths so the average is not reflecting a few weird death certificates:

  

The fact that there is a marked difference in the # of ICD codes between the Alzheimer’s deaths and the ‘Other Senile Brain Degeneration’ deaths suggests that the choice by doctors which one to write in was not random. The difference between NH & NON-NH residents in the proportion of Alzheimer’s deaths to Other SBD deaths suggests likewise. Rather, it seems that ‘senile brain degeneration’ is the text of choice where there were fewer or no additional conditions to document. This suggests that these were likely deaths where the coroner was less confident and/or the decedent was otherwise healthy (compared to the general population of decedents each year).

The average of ~1.6 ICD codes per death certificate means that about half of seniors who die of ‘senile brain degeneration’ have *NO OTHER CONDITION* that contributed to their deaths. But are there really hundreds of seniors dying of ‘senile brain degeneration’ with no other conditions? Dementia like diseases rarely develop in someone long enough to kill them without there being any accompanying conditions or comorbidities. So what is going on here?

There is one hypotheses that to me at least seems plausible and is able to explain what’s going on here, pending further research and analysis. The wild jump in what essentially amounts to ‘unidentified dementia of some sort’ - particularly in the NON-NH residents - reflects doctors erroneously attributing a different condition to Alzheimer’s/dementia. I suspect these misattributed deaths are probably cancers. An undiagnosed cancer in an otherwise healthy elderly patient, particularly a rapidly metastasizing cancer, would probably cause a general decline in the health of the patient. In older people, a general deterioration in health is frequently accompanied by mental or cognitive decline. Without a cancer diagnosis, a doctor could easily infer from the state of the patient that given his or her advanced age it is probably some kind of dementia but lacking a firm diagnosis write down “Senile Degeneration of the Brain”.

The reason these deaths spiked in 2020 would be that there were a bunch of cancer deaths where the cancer wasn’t diagnosed because of lockdowns and other policies, and potentially even a few extra helped along by covid disease itself. Also coroners during the manic panic phase might have been less meticulous about making sure to get the patient history and records.

The continued increase in these deaths after 2020 would reflect a new surge of ‘mystery misdiagnoses’ caused by a novel something introduced to the population en masse.

There seems to be a lot of “missing” cancer deaths in the national mortality data (which is built from state death certificates like these), especially after 2020, such as what is documented by Ethical Skeptic on Twitter/X. This would dovetail nicely with the ‘senile brain degeneration hiding cancers’ hypothesis.

It also could be that some of the increase after 2020 was actually correctly diagnosed - a ‘novel’ form of dementia that kills rapidly from the time of diagnosis, striking down otherwise healthy people, caused by the covid vaccines. Since we know that they can cause neurological and brain injuries, including brain degeneration, it stands to reason that rapidly fatal dementia following vaccination could be responsible for such a thing. However, this can’t explain what happened in 2020 where there were no vaccines, and since the increase clearly starts in 2020, it cannot be the primary explanation for this phenomenon.

Whatever the explanation is, there is definitely something weird going on that indicates a more widespread public health crisis in Connecticut, which in a sane world would be investigated with an eye towards getting to the bottom of this. Alas public health authorities are afflicted with moral dementia so such spasms of sanity remain unlikely to ever materialize.

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The point of this article is not to delve into the details of the actual event, nor to highlight the insidious, Orwellian and frankly evil nature of how the media and many politicians/pundits attempted to spin this. There are an endless array of other sources one can easily access especially through Twitter/X and adding another article to the burgeoning cavalcade of what is now mostly repetitive pieces regurgitating the same series of observations adds no value to anyone. That there was a shocking and profound failure of security for the rally is anyways an unimpeachably established fact at this point, something that has been already widely covered in the public domain from every conceivable angle. (The rest of the explanation of the objectives of this article is at the end of the article.)

I. Relating to assassination attempt itself

The following points are all in themselves uncontroversial as a factual matter, and materially relevant to assessing the collapse of security at the rally:

1) The entire federal govt bureaucracy has been rotted out with numerous DEI hires across all levels of all agencies, including protective service depts and intel. This is also true on a state level, although the extent and impact depends on the state, and I can't tell you which states are worse than others (California seems a good bet to be bottom 5 at least).

So undoubtedly a substantial % of the personnel responsible for security lack the proper qualifications and competency for the jobs they are doing.

This is aptly personified by the images of the female Secret Service agents on Trump's protection detail - one was clearly not tall enough to shield him (a must for agents on the protection detail); one could be seen fumbling around attempting to reholster her weapon; and a third was visibly flustered and unsure of what to do.

2) The bureaucratic regulations and policies are a product of the same DEI conventions and philosophy that governs personnel choices. Rules of Engagement for using force in woke doctrine can't even be properly conveyed with the word 'insane' (this actually goes back all the way to the Vietnam War).

To both of these points, consider the numerous “minor” Secret Service screwups over the past decade where they allowed threats to percolate and advance far more than is reasonable, that they could have shut down at the onset by the immediate and appropriate use of force. Think of the White House riot in 2020 where they allowed it to build up to the point they evacuated Trump to the bunker out of caution, or the miscreants who managed to penetrate the outer security perimeter of the White House.

The general incompetence of the Secret Service has also been a longstanding issue since Obama’s tenure.

Anyone remember the unvetted fellow who ended up on an elevator with then-president Obama *WITH A GUN* who was (for real) a “security contractor with three prior convictions for assault and battery”?

Or the time someone managed to “park his car on a street near the White House (on a night Obama was staying there), fire a semiautomatic rifle multiple times and inflict damage on the president’s home, and then flee the scene”, and the Secret Service didn’t even realize this happened until *FOUR DAYS LATER*? This was such a profound lapse by the Secret Service it managed to elicit a scathing condemnation from even the Washington Post, which reported “[t]his reconstruction of the events of that night shows the confusion and lapses in security — never previously reported — amid an attack that the Secret Service failed to properly identify and investigate.” Um, what now??

Another policy point to keep in mind is that even though for example official policy permits preemptively shooting at a potential threat, an agent on the ground may fear that the politics of the situation mean that following correct protocols will result in his imprisonment and his life ruined, or in the case of a less serious infraction which could still be a career-ender under the critical gaze of a woke manager or political opportunist, and might be reluctant to proactively engage a potential threat.

DEI - and the woke/leftist culture more generally - also implicates value judgements both because of its ideology and because of the differences in the personnel.

A somewhat hyperbolic (for now) caricature of the former is ChatGPT’s insistence that in a hypothetical situation where a nuke was launched at a populated metropolis that could be deactivated only by broadcasting the N-word, it is immoral to do so, meaning the moral calculus is that the nuke otherwise killing millions of people does not justify broadcasting a racial epithet. While this cartoonish example is not a realistic scenario (yet), lesser degrees of such dysfunctional morality are. Woke value considerations are already dictating many decisions, policies and protocols, where technical soundness and reliability are being sacrificed on the altar of some progressive principle or diversity mandate.

Regarding personnel shaping values, an easy example that is not at all hypothetical are differences between men and women. For instance, women are generally more risk averse and prone to ‘safetyism’ than men. So what happens when a traditionally male dominated enterprise is flooded with female managers and personnel? This is not a criticism of women. Some things by their nature require a higher risk tolerance, aggressiveness, and other masculine characteristics - such as security and protection services of high profile persons. But the reality is that there are differences that are relevant and affect the performance and effectiveness of an agency like the Secret Service.

A particular insidious influence of DEI on values and organizational management is the elimination of accountability. While a proper examination of this would require a lengthy article in its own right, we can make several generalized observations as to why this is (non-exclusive list).

Firstly, “DEI hires” by definition can’t be fired because that is inherently a form of repugnant discrimination/oppression within DEI epistemology.

Secondly, admitting that DEI hires or values led to bad outcomes concedes that DEI is a parasitical ideology foisted on society that drags down performance and leaves people worse off.

Thirdly, and perhaps most importantly, replacing DEI polices or personnel within an organization weakens the woke control and hegemony over the organization. Possession of the institutions and organs of society is one of the key pillars of practical Marxist strategy to conquer and subjugate society, one which it is worth sacrificing everything about the organization in order to maintain if necessary. (Consider how they wrecked the expertise, functional capacity, and credibility of public health institutions like the CDC by their unrestricted promotion of things that were widely seen by the public as absurd or evil.1)

The deleterious impact of a culture which instinctively eschews accountability as a mortal threat to its existence is hard to overstate. It fundamentally rejiggers the basic incentive structure facing employees and managers alike. Since this permeates all throughout an organization, its effects are additive as people at all levels are engage in hazardous behavior and decision-making where there are no consequences for doing so, until the organization becomes a corporate Swiss cheese riddled with DEI bullet holes.

3) We don’t know that this is the first functionally unsecured Trump event. It stands to reason there were similar security failures at previous Trump events, but nobody took advantage to attempt an assassination. If every Trump event lacks proper security, the law of probabilities submits that eventually the chickens will come home to roost. A prudent deliberate actor/s could therefore simply rely on this statistical near-guarantee that eventually someone will take advantage of the lackadaisical security.

4) It is necessarily true purely as an ironclad law of human nature that many of the thousands of personnel in government who are a part of what we’ll just call the ‘security apparatus’ (in the sense of being relevant to some aspect of the provision of security) are apathetic to their job, especially as it relates to Trump. Imagine how you would feel about your job if your job involved providing security for Hitler. That’s quite literally what such an assignment is to many of the personnel who have been steadily indoctrinated over the past 10 years to believe that Trump is Hitler reincarnated. Even seasoned professionals are human and would not be immune to this. (And even those who don’t internalize the Hitler/Nazi comparisons still internalize a sense of Trump’s wickedness, danger to society, and most importantly the shared ubiquitous instinctive revulsion of Trump among the various cliques of ‘elites’ and other tribal leftist affiliations.)

Furthermore, a higher percentage of people in the government whose work relates to security are anti-woke, or at minimum are not woke themselves compared to other government workers or agencies. This is largely because security and the related fieldwork typically appeal to masculine instincts but not to liberal sensibilities, and that they are jobs where there is little margin for error so less room exists for free-wheeling implementation of DEI mandates over meritocracy and outcome-oriented decisions and policies. The SJW-types / DEI hires in these agencies inevitably are more prone to feel “unsafe” and stressed out because they have to be around and interact with “hostile” people and work environments (to them anyway). This also leads to apathy about the job, and in the case of employees feeling resentful against their employment also tends to breed animosity and a greater willingness to proactively sabotage the objects of their resentment.

Moreover, as mentioned above, a fundamental tenet of modern practical Marxist doctrine is the conscription and redirection of every agency, organization and institution into espousing and championing woke virtues and ideology combined with the relegation of the core mission of the agency as secondary importance to implementing woke principles on society. Usually this also involves repurposing the specific work that is the raison d'etre of an organization’s existence into promoting the woke principles (e.g. the CDC using public health as a vehicle to push CRT or gun control by framing racism and gun violence as a public health crisis). An inevitable consequence of this is that people care less, or not at all, about the core functions of the organization or agency.

Apathy breeds shoddy work, inattentiveness to detail, complacency, emotional divestment, and laziness (among other negative work traits).

5) An unappreciated aspect of human nature - especially these days - is that people are very susceptible to their own propaganda. Literally. If you constantly proclaim or listen to a blatantly delusional idea, you will begin to internalize it until you come to truly believe it. We’ll highlight a couple of examples to illustrate the point.

First off, and an easy target in light of the widely observed morbidly comical deficiencies of the female Secret Service agents on Trump’s protection detail, it is hard to overstate how much woke propaganda that ‘anything a man can do a woman can do just as well’ has saturated the culture especially on the left. Inevitably, many if not most of the people living within this bubble imbibing a constant stream of “Mary Sue” “girl boss” clichés cannot help but to internalize this masculinized muscled up version of women at least to some degree (obviously different people internalize things differently and to different extents). So we can confidently assume that for at least some of the folks in the federal govt, a part of them actually thinks that female agents are just as capable as male agents (yes this is even as these same people also water down the standards for women in order to increase female recruitment, which is a massive contradiction).

Woke propaganda about the inherent virtues of a ‘diverse’ workforce has likewise saturated the culture to the point that there are bound to be plenty of genuine adherents to this principle. (This idea has become so hardwired into the woke weltanschauung that the lawyers defending the colleges racially discriminatory admission practices explicitly invoked it during oral arguments before the Supreme Court.)

To be clear, this is not to say that someone who falls for the relentless propaganda about these topics (or any other propagandized topic) cannot also be a deliberate malicious actor, nor even that they cannot simultaneously appreciate that “hey if we assign a bunch of women to Trump’s detail that will mean weaker security”. On the contrary, people are very much capable of holding and acting on multiple irreconcilable beliefs or ideas simultaneously. I’m simply highlighting that many people buy into their own propaganda (especially when they’ve been exposed to some version of it throughout their formative years being indoctrinated in the education system).

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These five points can be summed up as ‘DEI weaponization of incompetence’ into a nuclear level threat - this sort of institutionalized malignant incompetence has a limitless capacity to destroy or ruin everything it touches, so it is not a possibility that can be lightly dismissed.

6) A substantial portion of the federal govt workforce - including the agencies tasked with intel, security, and protective services - fantasize about Trump’s death, and some actually harbor a genuine desire to for his death (such as this compilation of thugs dug up by Libs of TikTok). This can be seen by the numerous govt personnel (elected officials, their staff, and govt employees) who posted on social media some version of "darn he missed" in the hours following the rally. This is also something which can be seen from the endless trove of similarly aspirational social media posts over the past 8-9 years prior to Saturday.

The FBI and intel agencies are notoriously among the worst government agencies exhibiting an exceptionally blatant and shocking degree of outright weaponization against Trump and people who oppose leftist/woke ideology or policies. This includes the brainwashing and self-sorting that keeps contrarian or dissenting political views out while radicalizing those who remain in these agencies to think of political dissent as treasonous and a “danger to Democracy”. The recent slide from a Fort Liberty military base ‘sensitivity training’ labelling pro-life organizations as literal domestic terrorists is a good example:

7) The level of rhetoric against Trump for the past 8 years - especially combined with the general support for violence and riots by the Democrats/left/woke brigade - means that a substantial portion of the Democrat/leftwing base has been propagandized to truly and sincerely believe that Trump is literally the next coming of Hitler. Thus there are literally millions of people radicalized to accept violence as legitimate "resistance" against the new 'Fuhrer'. If even 0.1% have the type of personality that is disposed to acting on ideological approbative violence, that amounts to tens of thousands of potential assassins walking around. So it is plausible both that a lone wolf type would try something like this independently, and that people in power aware that they already have an army of potential assassins could subtly alter security protocols or take other actions (such as a strategic personnel replacement at a critical juncture) that simply raises the likelihood of one of them successfully prosecuting an assassination, and need not do anything glaringly overt to accomplish this.

8) If Trump were to be assassinated, the guaranteed ensuing chaos would provide the necessary pretext for the left to (try to) impose draconian marshal law where they could attempt mass gun confiscation, summary arrests of high profile personalities deemed "dangerous", etc. So there undeniably exists political incentive for this to happen. This is true even though there also exists plenty of political incentives to avoid such a political earthquake. The question is who faces what balance of incentives - something that varies widely from person to person depending upon a whole host of factors.

9) The following actions/policies were all already implemented prior to Saturday that all aimed to restrict the degree of security provided to Trump or RFK:

• (a) Biden admin (still) denied RFK Secret Service protection despite his obvious prominence, ongoing threat level to RFK, and the uncontested tradition of far less relevant candidates receiving Secret Service protection

• (b) Trump's team had asked for his security package to be beefed up but the Secret Service refused

• (c) Democrats in Congress filed legislation to strip Trump of his secret service detail altogether (under the pretext of his being a felon).

All the above points taken together suggest that there is not only a desire but the will to diminish Trump's security that was acted upon at least to some extent. It is incontrovertible that the importance of Trump’s personal security was as a practical matter politically toxic and under real pressure to be kept to a minimum.

Additionally, there was already a precedent for reducing security ahead of an event where the necessity of enhanced security is self-evident in the ‘Trump era’: the rejection of Trump’s offer for 10,000 national guardsmen for January 6.

II. Relating to the investigation

1) The FBI for now is the lead agency tasked with "investigating" the assassination attempt. 'Weaponization' isn't sufficient to capture the extent of the woke infestation and partisan capture of the agency - the FBI is basically a Stasi without the torture chambers. So you can bet that this investigation will maximally conform to political control and necessity, facts be damned.

Moreover, even those who aren’t militant apostles of woke ideology nevertheless still identify with or at least feel somewhat partial to the perpetrator here. This in itself is a major bias that would be acutely manifest in the findings and whatever reports are ultimately issued.

2) All social media of the alleged shooter have been completely scrubbed from the internet, so the cover up is already in full force.

3) Although the uniquely high profile and importance of this case might force authorities to reveal more than they would like, the Vegas shooter offers an instructive case study demonstrating that they can lockdown information and investigation results as hard as they locked down the whole of society for covid. Of note is that the FBI in particular has been ruthless in destroying the lives of internal whistleblowers, so even if there are well-intentioned people on the inside, it is a very good possibility that they would choose to not come forward or leak information.

4) Republicans in Congress are at best functionally useless and often have conspired with Democrats in the House to pass abominations funding all of the tyranny, abuses, weaponization, wokeness and general insanity of the Biden regime for over 18 months. It is far from certain (charitable framing) that Republicans in the House will be willing to use actual leverage to compel forthrightness or transparency from the federal government regarding this investigation.

III. Political Consequences / Impact

This section is inherently more speculative. However, it is useful to raise awareness of oft-ignored aspects of the political system that play a tangible role in shaping political outcomes.

1) Trump will get a boost from a "sympathy vote" (this description is a bit of a misnomer because it encompasses multiple distinct types of voters who are animated by different emotions and logic but conveys the basic idea)

2) The image of Trump is probably going to be one of the defining iconic images and political moments of this century. Besides for the intrinsic power and allure of the photos of Trump standing tall, bloody and defiant - people naturally gravitate to boldness and courage in a leader - the fact that it is already widely presumed that it will be one of the most iconic political moments itself exudes a mystique that people innately want to feel like they were a part of, which means more people voting for Trump on the margins. Additionally, the contrast of Trump's defiance and courage in the face of death with Biden's feeble disposition and cognitive dementia will also likely be a powerful influence in favor of Trump - Trump took a live bullet better than Biden can take a live question. Ouch.

3) That said, it is still far from certain that he wins in November:

(a) Democrats already had a massive election operation that can generate a few million 'excess' votes that are illegitimate. This edge has been enhanced to some degree by adding some portion of the ~10,000,000 new illegal aliens to voter rolls. (It is not important that the illegals themselves vote, just that they exist in the system and generate a ballot that will be mailed out to an address from where activists/organizers can collect them, fill them out and mail them back in (or put them in drop boxes).)

(b) The Democrat base will never vote for Trump or abandon Biden (or whomever is the nominee) in the face of an impending ‘Fourth Reich’. At best some may choose to sit out the election.

The GOP base however could also suffer a bit of a depressed turnout - even a small difference here can make a huge difference in election results not only for president but for the thousands of down ballot races across the country as well - because of Trump's adopting a series of leftist policies, such as jailbreak (let the criminals out of jail) or being openly pro-abortion (excluding the last trimester) / jettisoning the pro-life language and policy aspirations from the GOP platform and media. (I apologize to anyone offended by this critique, however it is true and is the sort of thing to overlook at your own peril.) On the other hand, some of the ‘anti-woke’/anti-far-left who might have voted for RFK or not at all might find a new willingness to vote for Trump because of the assassination attempt and the subsequent fallout.

(c) Republicans have been on a massive losing streak in actual elections, significantly underperforming both expectations and polling since 2020. This is especially peculiar and troubling because there has never been a political climate so toxic to the party in power, but it has (so far) failed to reverberate in electoral outcomes at all. It remains to be seen if this can fundamentally change the political climate.

(d) Four months is a lot of time for something equally unorthodox and unexpected to happen. I would not be surprised if there was at least an attempt on Biden’s life. The FBI already conceived, funded, organized and managed a faux attempt to kidnap Michigan governor Gretchen Whitmer in 2020 in order to hurt Trump’s election prospects. So it certainly stands to reason that they would deploy this sort of entrapment scheme again to at least lessen the impact of the failed assassination of Trump by swooping in to prevent “in the nick of time” an assassination of Biden (or another prominent Democrat).

Any of these could reset the political environment in unpredictable ways.

4) The Democrats will definitely attempt an 'October surprise'. Their activists and antifa-Brownshirts are clearly willing to do anything to keep Trump out of office. So it's hard to predict the future. That said, there does seem to be a greater degree of immunity in the water table of the culture against spurious Democrat insinuations or faux-scandals targeting Trump or Republicans.

5) Democrats/DC establishment are presumably going to redirect some of their resources and energy into hardening the bureaucracy against a potential Trump victory, so that they can thwart personnel, policies and directives designed to purge or at least weaken the hold of woke ideology or personnel, mooting much of the victory of the election itself. This is something that if not appropriately managed threatens to render moot any attempts to purge wokeness out of government. Also critical to remember is that any anti-woke policies can be annulled as soon as they reclaim the White House.

(As a general matter, I don’t think people appreciate how daunting and severe the obstacles for a successful Trump second term are. Every policy and action will be enjoined and/or struck down by the lower federal courts, and SCOTUS will at best only partially pare back reckless judicial activism from the bench (see: first Trump term). Plus the savage propaganda and probably outright violence from the left in response to, say, a mass-deportation program will be like an unending tsunami of ‘resistance’. We will be treated to an unending stream of heartbreaking tragedies of emotional trauma, distress, cruelty etc that are the unavoidable byproduct of rounding people up and deporting them over the border, especially in the hands of pathological liars and sociopaths in the media who will distort, contort and weaponize every picture to look like literal concentration camp imagery. Which would in turn lead to a cratering in the currently broad population consensus for such a policy.

Then there’s the potential for ‘violent resistance’ - if they see they are losing policy-wise, the rational response (in their position) would be for instance to sabotage infrastructure (e.g. logistics for deportation, drilling rigs). And so on.

Additionally, it remains to be seen if Trump would actually implement his policy visions. His personnel choices during his first term were mostly disasters, and he had little if any control over the federal bureaucracy. Any action he takes to reign in and control the executive branch will be immediately challenged and enjoined by federal courts, where they will be bogged down for years as the various cases plod along indefinitely. The economy is likely to tip into a depression sooner or later - which will be an albatross around Trump’s neck - and the Fed will be more than happy to turn the screws during a Trump presidency. And so on. This is just a couple of examples of the obstacles and savagery a second Trump presidency would face.

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Objective of writing this article

The purpose of this article is to highlight and organize a series of relevant premises into a coherent structure that makes it easier to think through and analyze the myriad takes and hypotheses about the assassination attempt and its political significance. Obviously, I have no claim of special knowledge and could be just as wrong as the next guy. The value here is primarily in pointing out and organizing various premises/facts/history that are (1) widely acknowledged to be true; (2) are obviously relevant to the issues at hand; (3) incorporated by most people into their thinking without realizing it; (4) but also easy and likely to be overlooked at a conscious level; and (5) taken together help to organize and structuralize thinking about this matter. Thinking about something from the vantage of having a conscious awareness of concretized facts and premises is incomparably superior to muddling through relying on a quasi intellectual-emotional hybrid intuition that mushes all the various points into a blob that “feels” a certain way without having clarity about how all the pieces fit together. And it’s much more satisfying.

I am not asserting any conclusion or theory about the assassination attempt here, the point is to assist others (and myself) to reach their own conclusions.

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The central issues here - certainly those of critical importance - are:

1. The intent of the culpable/relevant actors involved (including *everyone* even marginally involved with designing and implementing security for Trump and other protectees of the Federal government)

2. The practical state and disposition of the various relevant governmental and social agencies/organizations.
   (For the record, much of the evils perpetrated by massive bureaucratic entities are the result of inertia holding in place decades of incremental changes that collectively add up to a seismic recalibration of an institution into an unrecognizable entity compared to e.g. 50 years ago (or these days sometimes even compared to 10 years ago). Basically the banality of incremental evils.)

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As we saw previously, although Vermont had relatively little excess mortality in 2020, 2021 and 2022 were much worse:

So how did 2023 go? Let’s see:

Although the raw total is down from the highs of 2021/22, it is still well above 2020.

Also ominous is that 2024 through May is basically where 2023 was at - in other words, worse than 2020 (and even 2021 which saw a surge in the latter part of the year):

Vermont has a very aggressive deviation between the deaths in nursing home residents (left) compared to non-NH residents (right):

While NH deaths are down a bit, deaths in non-NH residents are still about 20% excess over the pre-pandemic baseline - in 2023 (!!).

(To be intellectually honest, I wonder if there was a drop in the NH census in Vermont or misclassification of NH residents as non-NH residents after 2020, because 2020 didn’t have noticeable excess yet NH deaths still dropped into mortality *deficit* territory in all three years since.)

The vast majority of excess mortality is driven by the seniors - especially the nonagenarians (??):

So the topline numbers are not looking good.

There was one condition in particular I really wanted to see how it fared in 2023:

Blunt Force Injury Deaths

The most immediate wild trend I saw however is the number of deaths involving “blunt force” or “blunt trauma” (i.e., one of these phrases was used to describe a Cause of Death condition).

This was so eye-popping to me that I am going to try and recreate the experience for you here.

The following chart shows the number of deaths involving “blunt force/blunt trauma” through 2022:

The right side of the chart - particularly 2022 - looks like Mt Everest towering over its lilliputian compatriots of the other years. 2022 had more than 125% more deaths than *2020* - which itself showed zero deviation from the pre-pandemic trend.

This wild anomaly prompted me to discover that there was indeed a spate of excess deaths in the other states we had data for as well (Nevada, Massachusetts, Minnesota).

Naturally, this was the first condition I looked for in the new 2023 data.

I figured that at best 2023 would be in the ballpark of 2022, and probably at least a little bit below - the vast majority of these deaths were in seniors, mostly above the age of 80, so there should have been a severe depletion of the reservoir of the crotchety seniors susceptible to suffering serious kinetic accidents available to die.

This was not what I found.

So without further ado, behold:

2023 literally had MORE THAN TRIPLE THE NUMBER OF BLUNT INJURY DEATHS of 2020 (!!!). That this occurred in the face of overwhelming excess in 2022 is all the more shocking.

This excess mortality is seen in both men and women, with the sole distinction being that men had zero excess in 2020 but substantial excess in 2021 compared to women who saw slight excess in 2020 and more moderate excess in 2021 compared to men:

Underlying Cause of Death (UCoD)

The vast majority of these deaths list the blunt force injury as the UCoD, i.e. the condition judged by the coroner to be the primary cause of death:

This is a key detail, because it heavily implies that these deaths are not people who suffered a physical trauma injury but died of something else, rather the physical injury played a key role in causing the death.

Also noteworthy is that if we look at only the deaths where the blunt injury was the UCoD, 2023 is QUADRUPLE the ‘expected’ number of such deaths in a year (!!).

Age stratification of blunt force injury deaths

Also surprising is the age breakdown of these deaths. We typically see the greatest concentration of excess deaths in ‘young’ seniors, i.e. those ages 65-84. While there is definitely significant excess blunt injury deaths in these seniors (top chart below), there is a shocking degree of excess death in the older seniors, particularly those *over 90*(!!):

Also curious is that in the 70-74 cohort the first year of significant excess blunt force injury deaths is 2023, zooming to more than triple the prior 4 years. Another ‘anomaly’ here is that this cohort went from 2 such deaths in 2018 to 28 such deaths in 2023 - a 14x increase. More on this in a bit when we get to the non-seniors.

Nursing Home vs NON-Nursing Home Deaths

Another ominous clue about the nature of these deaths lies in the comparison between nursing home vs non-NH resident deaths - the trend exists in both:

However there is a key difference - whereas among NH residents, 2023 was only slightly above 2022, for NON-NH residents, 2023 towers over 2022, eclipsing the 2022 total by almost 70%.

Moreover, if we look at the age breakdown of blunt injury deaths among NON-NH residents, we see the following:

In the aggregate, seniors who reside outside of a nursing home or similar type facility are healthier and more mobile and functional compared to their peers living in a nursing home. They also typically have a greater degree of independence and familial support, which are hugely impactful for both cognitive and physical health. This is not a population where you would expect a sudden plague of physical incoordination, and if anything, decreasing physical mobility and coordination should result in these seniors being placed in a nursing home. This in turn would be expected to lead to an increase in deaths involving a physical injury among nursing home residents (a few of whom the physical accident occurred prior to their internment in a nursing home), as nursing home populations took in new members because they were at heightened risk of suffering a fall or tripping on the stairs.

What about the non-seniors?

There is a distinct trend of substantial excess deaths involving blunt force injuries among younger people as well. The following chart shows the number of such deaths for the population ages 0-64:

Here 2020 was right in line with the previous five years, and was not even the highest total - 2018 saw four more such deaths -37- compared to the 33 in 2020.

Then 2021 almost doubles the number of deaths in 2020, is basically double the pre-pandemic baseline in 2022, finally reaching triple the normal number of such deaths in 2023.

And these deaths are not skewed to the ‘almost seniors’, rather they are more concentrated in the *younger* side of non-seniors, especially the 18-34 year old cohort:

What about 2024?

Since we have the deaths from the first five months of 2024, we can see how 2024 is shaping up to be… which is a big YIKES:

On the bright side, Vermont may finally be running out of physically unadroit seniors to fall down the stairs.

Covid clown world

it would be criminal to ignore the 12 deaths that list covid and a blunt force injury:

“Covid deaths” indeed.

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Today we will look at cancer deaths where cancer is the UCoD.

The significance of the UCoD

It is critical to understand the following specific definitions to follow this article:

This is what it looks like on an actual death certificate (see the instructions on the top):

In short, the UCoD designation is meant to highlight the condition or injury that was the primary catalyst or cause of the death, or the chain of events directly culminating in the death.

Cancer Data

Cancer is the UCoD in the overwhelming majority of deaths that document a cancer as a CoD (hereafter we’re going to simply call these “cancer deaths”), visualized in the following chart that shows the % of cancer deaths where a cancer is identified as the UCoD:

This makes sense - when someone afflicted with cancer dies, the death is usually caused by a pathology initiated by the cancer.

However, there is an open question about the accuracy of UCoD/MCoD designation with cancers (and to be frank with most other conditions too). So we must keep that in mind as we analyze the cancer UCoD/MCoD data here.

Cancer UCoD Deaths

Deaths where the UCoD is a cancer (hereafter “cancer UCoD deaths”) is useful to us because it shows the incidence of deaths that ostensibly died because of - and not “died with” a la so many ‘covid deaths’ - a cancer. Again this is not to say that the cancer MCoD deaths are necessarily “died with cancer” and not because of cancer, merely that for these deaths it was adjudicated and determined that a cancer was the primary cause of death.

This is helpful because it establishes a baseline minimum for the trend of genuine cancer deaths.

The following chart shows the total number of cancer UCoD deaths in Minnesota per year:

In this grand total combining all demographic cohorts, you can see that in 2020 there is no increase, but all three subsequent years are clearly above the expected number, and gets worse each year.

However, like we saw in part 1, this is misleading, because nursing home resident deaths (NH deaths) and non-NH deaths cancel each other out, illustrated by the charts below (left side NH deaths, right side non-NH deaths):

In what might initially seem surprising, NH cancer UCoD deaths are running a mortality deficit in every pandemic year (although they seem to be recovering somewhat in 2023, which is not a good sign).

What happened is that NH residents were killed off by a bunch of other stuff in 2020, including, and perhaps especially, NH residents with cancers. In other words, the reservoir of potential NH residents with cancers was depleted by mass deaths in 2020, so many of the NH residents who were “supposed to” die in 2021-2023 from cancers were instead killed off early by something else.

Additionally, it is highly probable that some number of deaths where the real UCoD was cancer were attributed to something else, like covid. We actually discovered thousands of deaths where the condition labeled by the coroner filling out the death certificate as the UCoD was replaced by the CDC with covid. This is true even for deaths in the non-NH residents, meaning that the cancer UCoD deaths in the non-NH residents is also likely missing cancer deaths with the UCoD misattributed to a different condition.

NON-NH Cancer UCoD Deaths

Since the real trend of increasing cancer UCoD deaths is in the non-NH residents, we’ll focus there.

The following chart shows the # of cancer UCoD deaths in non-NH residents:

Here the excess cancer UCoD deaths is obvious starting in 2020 and continuing through 2023 which is still somehow running higher than 2020 (!!).

There is another major Simpson’s Paradox hiding here, caused by differences in the various age cohorts.

If we break apart the cancer UCoD deaths by age, we get the following:

You can see that various age cohorts show drastically different trends.

Particularly bizarre is the 50-59 year old group, who lose 150 deaths in 2019 from 2018, but both periods - 2015-2018 and then 2019-2023 - are pretty flat and level. This seems more than a bit incredulous - it is implausible that we cured overnight 15% of cancers among a narrow 10-year band of people, while at the same time cancer UCoD deaths rose in other age groups. (I have entertained many possible explanations for this but none really seem all that credible or reasonable to me.)

Moreover, there is a marked difference in the general trends between the seniors and ‘juniors’ (<65 years old).

These have the effect of distorting the trend of cancer UCoD deaths when we combine all age groups.

If we focus on the senior population - where the excess deaths overwhelmingly are located -, the degree of excess cancer UCoD deaths is largest in the 65-84 year old groups. If we combine those into one chart, we get the following:

There is almost 10% excess in 2020, and 2021-2023 are all in the 15%-18% excess range. Also strikingly, in this age cohort every pandemic year increases over the prior year. Considering that this chart represents the minimum baseline for cancer UCoD deaths, and that there is reason to believe that some % of cancer deaths are going unnoted or inappropriately not being identified as the UCoD, the number of true cancer UCoD deaths is likely higher.

If we break this down further by sex, among men ages 65-84 (left) 2023 actually eclipses 20% excess from 2019:

Summary

Deaths where the UCoD is attributed to a cancer are well above normal in Minnesota for all four ‘pandemic era’ years. This excess is mostly driven by the excess deaths in the 65-84 year old people who are not nursing home residents.

Next article, we look at MCoD Cancer Deaths (to be explained)…

Note: I made this article shorter than I usually make these types of articles, to see if readers like this format better, where there is less information to absorb in one shot, so -

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Rasmussen recently released a new poll asking people about vaccine safety:

They found that a substantial percentage of respondents claimed to know someone personally who was killed by a covid vaccine:

(The other slides about the breakdown of how respondents answered this question are below)

Mass amnesia about your own vaccine status

The most unexpected and bizarre finding to me was the following slide showing the % of respondents who were vaccinated vs unvaccinated:

Four percent of respondents overall - and a mind-blowing FIFTEEN PERCENT of 40-64 year old’s - claimed they were “not sure” if they got vaccinated.

The 15% # is probably a typo (see above), but 4% overall is still a shocking number if it holds true for the entire population.

This is wild.

Nobody (except perhaps Biden) ‘forgets’ whether they got a covid vaccine. So this is basically an obvious and open lie to the pollster.

Moreover, all of the ‘unsure’ people were either Republicans or Independents - among Democrat respondents, 86% said they were vaccinated and 14% said they weren’t, but 0% couldn’t recall:

So basically, we’ve got a bunch of people who on the one hand are too embarrassed to admit that they got a covid vaccine, but on the other hand can’t bring themselves to openly lie that they didn’t get a covid vaccine, leading them to go for the middle ground of lie that they don’t remember if they got a vaccine.

In other words, the subject of covid vaccines has become so toxic that - if this poll’s results are to be believed - a sizeable minority not only regrets getting vaccinated but feel ashamed for having done so.

Moreover, when people lie blatantly and anonymously, they are usually doing so in order to deceive themselves in order to maintain a fiction in their own self-image or identity. There are many reasons why people could have psychological difficulty with their vaccinated status, including:

• They don’t want to admit they were inept or gullible enough to get manipulated and tricked into getting vaccinated which in hindsight is now both a very significant decision an a colossal failure of their judgement

• Coercion to get vaccinated left them feeling abused/violated/traumatized, something which they would rather push out of their consciousness, but admitting they are vaccinated forces them to relive the abuse and maintains or anchors these feelings in their conscious mind. Other bullying or abuse associated with the vaccines could also lead to this.

• Similar to the previous one, they are afraid for their own health going forward, and would rather not contemplate their own potential risks from the covid vaccines, and so deny their own vaccination status in order to push it out of their consciousness

The fact of so many “defections” indicates that a great many more people feel similarly - the defectors are the tip of the iceberg who feel strongly enough to tell an readily obvious lie on a poll, but most people who harbor resentment, anger or trauma about getting vaccinated are not going to lie about their vaccination status on an anonymous poll.

The primary takeaway to me is that covid vaccines have incredibly toxic culturally, which is good news.

Breakdowns on covid vaccine death question:

Here are the other slides from the Rasmussen video on this subject.

This time there was a wider gap seen based on political party affiliation:

Unsurprisingly, there were a higher % of younger people compared to older people who claimed to know someone personally who was killed by a covid vaccine:

Also unsurprisingly, a higher % of unvaccinated people said they knew a covid vaccine fatality compared to vaccinated, and a higher % of unboosted compared to boosted folks:

This is in addition to their earlier polls on this issue:

They also asked if people knew anyone killed by the covid virus:

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Public Health is a vast sprawling enterprise funded to the tune of hundreds of billions of dollars each year by the federal government, plus substantial private donations by non-profits and some of society’s wealthiest people. We are scolded that such a robust well-funded behemoth is absolutely vital and indispensable to maintaining and promoting the general health and welfare of the population. But what if there is an extraordinary, once-in-a-lifetime type of excess mortality that dwarfs the scope of drug overdose deaths, affecting the whole of society across all age and demographic strata, and. . . is totally ignored by public health authorities??

Shockingly, this is actually happening in real time. We managed to obtain the death certificates representing all deaths covering 2015-2023 in four states that we can publicly publish data from, and they show a disturbing story of continuing pandemic-level excess deaths still ongoing today among a variety of conditions, in many at even higher levels than we saw in 2020.

To be sure, death certificates are a flawed tool for data construction. They are rife with errors, prone to biases, subject to capricious and sometimes deliberate manipulative policy changes from on high, and rarely tell the complete story of the decedent’s demise. They are under the aegis of state health departments and the CDC, which doesn’t exactly inspire confidence about their quality or integrity. But neither is it an indefatigable Sisyphean task to extract useful, useable data from the information logged and recorded on these indubitably wanting instruments, although progress often creeps along slowly enough to give the illusion that Zeno’s motion paradox accurately describes reality. (It definitely describes how I’m feeling after sinking almost 15 hours putting this albatross together.)

The point of this article is to show the public actual trends of excess mortality in the following conditions or Causes of Death (CoD):

1. Acute Renal Failure (ICD Code N17)

2. Pulmonary Embolism (ICD Code I26)

3. Hypertension, and specifically the subset of Hypertensive Heart Disease (ICD Codes I11 & I13)

4. Physical Trauma Injuries (Various ICD Codes)

5. Diabetes (ICD Codes E10-E14)

6. Protein Calorie Malnutrition (ICD Codes E43-E46)

7. Sepsis (ICD Code A41)

These are far from the only conditions where there is clear excess mortality. However, these conditions are unique in that there is clear excess mortality in these conditions in every single state for which we have death certificates, and they affect a substantial number of deaths per year and are thus of great importance for public health.

Alas, if only we had public health authorities more interested in looking at evidence than deleting evidence.

Note: For some reason, Florida has refused to allow anyone access even to deidentified versions of their death certificates. Florida is the motherlode of mortality data, because of the population size and high concentration of seniors, the vast majority of whom were vaccinated with the mRNA covid vaccines. It seems very odd that the FL Department of Health continues to restrict public access. If we refuse to be transparent with the data in our possession, we cannot complain about the lack of transparency by the establishment. We thus call on Dr Ladapo and/or the DeSantis administration to allow public access to deidentified death certificates that will allow the public to see for themselves what the mortality data actually looks like. How can it be that the far-left states of **MASSACHUSETTS** and Vermont allow full unrestricted access to their death certificates by any citizen, but Florida won’t even allow access to redacted versions that don’t risk violating the privacy of decedents or their families??

I. ALL CAUSE MORTALITY

The starting point for any exploration into potential excess death phenomenon is first to see if there is actually excess death overall - are there more people dying than we would expect? If the answer is no, then excess deaths found within individual conditions or categories of disease may well be an ‘administrative phenomenon’, i.e. they do not reflect a change in the circumstances of people’s health or deaths, rather a change in how CoD’s are recorded.

Conversely, if there is excess mortality occurring, concomitant excess deaths found in specific CoD’s are presumptively representing an actual increase in the incidence and/or rate of death from these conditions.

All cause mortality - in other words, all deaths from all causes - also provides a bird’s eye view of broad trends of who is dying at what rates, which can help identify novel factors affecting population mortality, which is very relevant for parsing mortality trends.

*******

How to read the charts

The bulk of this article is the charts, which follow the same basic design:

--each chart has a title on top that describes the parameters or conditions of the deaths shown by the chart
--charts can show deaths for a specific condition/s either by ICD 10 code, or by the text written on the death certificate itself
--"All ICD Codes" / "All Deaths"/ "All Text CoD's" in the title means that the chart shows deaths from all causes
--each bar represents the tally for one year
--the various shades of grey bars are for the years 2015-2019 (left to right)
--blue bar = 2020
--yellow bar = 2021
--red bar = 2022
--purple bar = 2023
--the number on the top of each bar indicates the number of deaths in that year that fit the conditions articulated in the title of the chart

*******

Massachusetts All Cause Mortality

The charts for each state are the same series, so we’re only going to explain them for MA in each condition (unless there’s a difference).

The following chart shows the total # of deaths in MA each year:

You can see right away that from 2020 onwards, the number of deaths is above the range in the pre-pandemic years (2015-2019). In other words, there were excess deaths in each year.

This is especially striking because of something colloquially referred to as the “pull-forward effect” (PFE). We would expect to see a mortality *deficit* following a year of substantial excess mortality if the “excess” deaths were predominantly people dying who were going to die very soon anyways. The average age of covid deaths being roughly the life expectancy is a good illustration of this - the people killed off especially in 2020 were those who were frail and predisposed to die soon. Had they not died in 2020, they would have overwhelmingly died over the next few years. So in essence, 2020 “stole” deaths from 2021, 2022, 2023 (in decreasing amounts from each successive year). This means that there is a greater portion of the deaths in 2021-2023 that are above the expected total than merely following the pre-pandemic baseline would yield.

Next up, we have a chart showing the average age of decedents in MA:

Whereas the average rises in 2020 well above prior years, the average age of death drops sharply in 2021 to lower than any of the prior five years (dropping more than a full year in the average age is bigger than it seems because it takes a lot of younger people dying to drag the average down when the vast majority of deaths are people in their 80’s and 90’s).

In other words, whereas 2020 deaths were old and frail people, in 2021 the characteristics of decedent’s markedly skewed to younger people more than any prior year.

The most shocking and revealing conundrum of mortality trends - which we see in every state for which we have this data - is comparing deaths in nursing home residents (also includes similar type facilities such as assisted living or long term care) to non-nursing home residents.

The following two charts show the total number of deaths of nursing home residents (left) and non-nursing home residents:

Separating them out shows that there is a far higher degree of excess mortality occurring in 2021-2023 outside of nursing homes that you can’t see in the total death count for the state because the depletion of nursing home deaths mostly cancels out the increase in deaths outside of nursing homes.

Keep in mind also that with the exception of Minnesota, we can only identify nursing home residents who died in the nursing home, but if they died elsewhere like in a hospital or hospice their nursing home residency is undocumented, so the discrepancy seen above is likely even larger in real life.

This dichotomy is also seen in the mortality trends for the majority of conditions, which we will document.

Minnesota

Minnesota’s overall excess mortality is more evenly spread out among the pandemic years compared to MA:

The average age of MN deaths however is even more anomalous:

NH/non-NH:

The following charts show side by side (1) the total number of deaths in non-NH residents (left), and (2) the total number of deaths in non-NH residents *excluding all deaths which list covid as a CoD*:

This is especially jarring, because there is clear rising excess death that has nothing to do with covid disease every year. This is not to say that all deaths that list covid as a CoD are caused by covid, which is patently false, but it highlights that even using the most upper limit of covid deaths possible, there is still marked excess mortality occurring.

(I didn’t include this chart for MA because they over-attributed so many deaths to covid that there is literally a mortality deficit in every year if you exclude all the covid deaths. However as we’ll see later we can show excess death in MA in individual conditions without covid.)

This final chart for MN ACM breaks down the non-NH resident deaths by men (left) vs women (right):

(I will include this chart where there is a substantial difference in the trends or overall number of deaths between men and women.)

Nevada

(Since we don’t have complete 2023 data from Nevada, we will only include 2023 where relevant.)

It’s interesting that the average age if death in Nevada is 3-4 years below the other states:

Vermont

Vermont has the fewest deaths overall by a wide margin, but has one of the worst post-2020 trends of excess death (Hopefully we will get the 2023 deaths soon, and we’ll be able to update this):

Even removing the covid deaths there is clear excess mortality going on:

The upshot from all these states is that mortality levels have still not yet come back down to the old baseline, and this trend is especially pronounced in non-NH deaths.

II. ACUTE RENAL FAILURE (ICD 10 code N17)

The most dramatic trend of excess mortality in any specific condition is probably deaths involving acute renal failure (ARF). The degree of excess is wildly elevated, and this condition accounts for >60,000 deaths annually in the US (extrapolated across the whole US the rate of excess we’re going to see would equate to ~150,000 *excess* deaths involving ARF)

Despite the variety of idiosyncrasies and customs unique to each state’s methods of documenting causes of death, the trend of excess ARF is visible across the country.

I recently wrote an article for Trial Site News documenting ARF excess deaths on a more granular level.

It is especially damning to Public Health that this signal was first noted by John Beaudoin – a private citizen with no connection to or training in public health or epidemiology - when he obtained Massachusetts’ death certificates back in 2022. It’s now 2024, and all we have are the crepitations of public health officials trying to FOIA-proof their emails but apparently cannot be bothered to investigate a doubling of ARF deaths in the span of a mere two years.

Massachusetts

The following chart shows the total number of deaths that list N17 as a CoD:

This trend speaks for itself.

The next chart shows the % of all deaths in MA each year that have N17 as a CoD:

A change in the % of deaths with a given CoD is a good indication that there is probably excess morbidity and mortality from that condition, especially if the % of deaths increases more than the rate of excess deaths increases overall.

When we look at the non-NH resident deaths (right), 2022 reaches well above double the baseline to a nearly unthinkable 250% excess (!!)":

Critically, even in MA, the trend of ARF deaths looks almost identical even if we exclude all deaths that have both N17 *AND* U071 (covid) on the death certificate:

In other words, these are overwhelmingly deaths that have nothing to do with covid, or even covid treatments (any patient treated for covid who died would definitely have covid on the death certificate).

Minnesota

We see a remarkably similar trend of ARF deaths in Minnesota:

And also a similar trend in the % of deaths with ARF each year:

Minnesota has the dubious distinction of reaching *300%* excess in 2022 in the non-NH residents (it’s possible that MA would as well if we could exclude the NH residents who died in hospitals):

And also like in MA, the shocking scope of the excess persists even excluding all of the ARF deaths that also list covid as a CoD:

Nevada

Nevada looks just as bad:

The following chart shows the total number of ARF deaths each year in Nevada from Jan-July, for which we have 2023 death certificates - which shows that so far 2023 is shaking out to be worse than 2021 albeit at least in NV 2023 seems noticeably lower compared to 2022:

Nevada claims the prize for highest total % of deaths in any one year with N17 (2022) out of all the stated we have:

Vermont

Since Vermont doesn’t have the ICD codes assigned to the death certificates, we are forced to use text parameters instead, which are usually not ideal for comparing states to each other.

Vermont shows the overall weakest trend in excess deaths with acute renal/kidney failure -

- although it becomes stronger once you exclude the NH ARF deaths (left) from the non-NH ARF deaths (right):

Clearly there is something causing a spectacular increase in the incidence of deaths with acute kidney failure….

PULMONARY EMBOLISM (ICD Code I26)

We chose Pulmonary Embolism - a blood clot in the lungs - in part because it is a common complication attributed to both covid and covid vaccines, and there is clear excess going on in all of the states we have death certificates from.

Massachusetts

The following chart shows the total number of deaths with I26 listed as a CoD each year:

Surprisingly we can even see clear excess in the NH PE deaths (left) in all pandemic years, although it’s nowhere near as sharp as the non-NH PE deaths (right):

If we exclude covid deaths, the excess trend almost vanishes. However, does it make sense (using official narrative premises) that after vaccinating almost all the seniors and the substantial majority of adults, the mildest covid variants cause a higher incidence of PE’s? (Again this is even granting that all the “covid deaths” are actually covid deaths, which is presumptively erroneous.)

Minnesota

This is a good illustration of how different states document individual CoD conditions differently (or perhaps simply document a smaller % altogether).

Despite Minnesota having ~15,000 fewer deaths per year than Massachusetts, there are actually more deaths per year in MN with PE listed as a CoD (except for 2015):

Are there “missing” PE’s from Massachusetts death certificates? Does the CDC or other academics using the national mortality data bother to sort out differences in states? How do you even sort out what’s going on here?

All good questions.

If we look at NH vs non-NH PE deaths, we see a similar picture to MA - there’s clear excess even in the NH deaths, but far less pronounced than the non-NH deaths.

Interestingly, there seems to be clear excess PE deaths among NH residents in 2019.

The following chart shows men (left) vs women (right):

Unlike Massachusetts, there is clear excess in MN PE deaths in the non-NH population even if we exclude all the PE deaths with covid listed as a CoD (right):

Another interesting tidbit here is that the contrast between men and women is even greater among the non-NH deaths:

This is noteworthy because typically, disparity between men and women roughly hews to the NH vs non-NH dynamic because women make up a disproportionate % of NH residents (longer life expectancy), yet here the difference between men and women becomes greater by excluding NH resident PE deaths.

Nevada

The left chart shows total # of PE deaths for the entire calendar year each year, the right chart shows the total number of deaths from Jan-July each year to normalize for 2023 as we showed for ARF deaths before:

The excess exists even excluding all the PE deaths with covid, although much more muted:

(Keep in mind that rampant over-coding of covid on death certificates artificially deflates the degree of excess when you exclude covid.)

Vermont

For Vermont, we tried to capture deaths with a PE by using the text of “Pulmonary*Embol”, which allows for variations of embolism, emboli & embolus. (Unfortunately we can’t use “PE” or even “PE ” because many other words that appear in CoD fields have ‘pe’ or ‘pe ’ in them, e.g. “type”):

Unlike the other states, in VT there is no significant excess of PE deaths in the NH pop (left), which accentuates the degree of excess in the non-NH resident population (right):

Notice also how there are no excess non-NH PE deaths whatsoever in 2020. It is exclusively a 2021- phenomenon.

The men vs women in VT is also remarkable, skewing the opposite direction from the other states:

III. HYPERTENSION

Hypertensions are one of the most frequent conditions listed on death certificates, far more than ARF.

I was going to only focus on a subset of Hypertensions - Hypertensive Heart Disease, which shows a considerably more rapid rate of escalating excess. However, in order to normalize a comparison with Vermont where HHD isn’t really a thing, I also generated charts for all states using a text parameter of any death that had *either* “hypertension” OR “hypertensive” in a text CoD.

Massachusetts

The following chart shows the total # of deaths each year with either the text “hypertension” or “hypertensive” as a CoD:

NH vs non-NH deaths:

“Hypertension”/“Hypertensive” deaths total (left), and excluding all such deaths that also had ICD code U071 [covid] (right):

The following stat is probably instructive. This chart, covering only the years 2020-2023 for NON-NH deaths, shows:

• LEFT SIDE: the % of deaths with text of hypertension/hypertensive that also have covid as a CoD

• RIGHT SIDE: the % of covid deaths that also have the text of hypertension/hypertensive

Minnesota

Same parameters as for MA:

NH residents vs non-NH residents - the trend in MN for the non-NH residents (right) is more dramatic compared to MA:

“Hypertension”/“Hypertensive” deaths total (left), and excluding all such deaths that also had ICD code U071 [covid] (right):

This is a very worrying trend even after excluding all the “covid” deaths.

Finally, while the % of hypertension/hypertensive deaths with covid in Minnesota (LEFT SIDE) is pretty similar to Massachusetts, the % of covid deaths that have a text of hypertension/hypertensive in Minnesota (RIGHT SIDE) is about DOUBLE the % of covid deaths with this language in MA:

Lastly, in Minnesota, if we focus on the 18-44 year old’s, we find something very shocking illustrated by the following chart that shows the number of deaths with the text hypertension/hypertensive *in 18-44 year old’s* for men (LEFT) and women (RIGHT):

This seems like a disturbing trend, to say the least.

Nevada

Nevada is hard to find a clear signal because the difference between any two years is so big:

However, if we only look at such deaths in 18-39 year old’s, we do see a very clear sudden spike of excess deaths with the language “hypertension”/“hypertensive”:

Vermont

Finally, we have Vermont:

Where the excess is entirely from the non-NH deaths:

And vanishingly few of these deaths have any text variation of “covid” (we went through all the potential covid deaths individually by hand to calculate this):

HYPERTENSIVE HEART DISEASE (ICD Codes I11 & I13)

Massachusetts

Minnesota

In Minnesota, the excess deaths with HHD is almost as bad and extreme as the excess ARF deaths:

Which is reflected in the % of deaths each year that have either I11 or I13 as a CoD:

Very shockingly, there is a massive spike in these deaths even in NH residents (!!) (left), roughly tracking with the dramatic spike in non-NH deaths (right):

We can see the extraordinary degree of excess in young people we saw in the text deaths of “hypertension”/ “hypertensive” above in this age group, illustrated in the following chart showing the # of deaths among 18-49 year old’s with HHD:

And almost every single one of these deaths did NOT have covid - you can barely see a difference between the two charts below showing the total HHD deaths including those with covid (left) and excluding those with covid (right):

Nevada

Nevada pretty much parallels the text version above:

IV. KINETIC INJURIES / PHYSICAL TRAUMAS

Kinetic injuries is just a name for all sorts of accidents involving physical trauma of some sort.

This is the only category in this article where for the most part it is hard to find, and there certainly isn’t really a commonality between states.

Physical injuries are spread out over dozens of different ICD codes, and the increases which we’ll show don’t really show up as well using an ICD code or combination of codes.

For each state, we will use a unique combination of text and/or ICD codes, the fruits of surveying thousands of death certificates to get a sense of the different phrases and ICD codes used to identify physical trauma injuries.

Vermont

We’re going to start with Vermont, because it is the simplest state and it was the genesis of discovering this trend.

I was shocked to discover the following trend when I searched for blunt force traumas in Vermont - the chart below shows the number of deaths that contain either the words blunt & trauma, or the words blunt & force (sometimes ME’s write “Blunt Trauma”, and sometimes they write things like “Blunt Force Injury”):

This trend is eye-popping.

Moreover, it is also present in the NH deaths (left) in 2022, not just the non-NH deaths (right):

It affects both men and women:

Strikingly, for the vast majority of these deaths, the physical injury is documented as the Underlying Cause of Death [UCoD] (left), which is basically the primary cause of death; however there is also excess seen among deaths where the physical injury is listed as a “Multiple Cause of Death” [MCoD] (right), i.e. any additional cause of death that isn’t the UCoD:

Massachusetts

Massachusetts was a big mess for the most part, with lots of different phrases used.

The following chart shows the total # of deaths each year with at least one of the words or phrases indicated by the title:

There is a subset of deaths in Massachusetts that show a very clear and obvious trend of excess mortality: deaths that use the word “fracture” in a CoD description:

This trend eclipses the rate of All Cause Mortality:

And most surprisingly, we see excess in the NH population starting in 2022 (left), closely mirroring the excess of 2022/23 we see in the non-NH deaths (right):

Minnesota

Minnesota actually has a few ICD codes that do show a clear trend - the W18/W19 combo that indicates unspecified falls. I wrote an article about this a while back before we had complete 2023 data.

Here are the salient charts for W18/W19 deaths -

NH vs non-NH:

Men vs women:

When we use the same wide-ranging text search as we did in MA, we see the following:

We see excess in both the NH and non-NH deaths:

However, when it comes to the text of blunt force or blunt trauma - the parameters we used in Vermont - we only see excess in the non-NH deaths (right):

Nevada

I previously wrote about Nevada and physical trauma injuries.

Here’s the basic idea:

Nevada is like Vermont, where there is no excess in 2020 but 2021 spikes up; and so far, in Nevada this trend of excess mortal kinetic encounters continues through 2023 at an even higher clip than 2022 through July.

Physical trauma injury deaths in ages 30-49 stands out in Nevada:

Nevada also shows clear excess in deaths with the word “fracture”:

V. DIABETES (ICD 10 Codes E10-E14)

Diabetes is one of the leading killers of Americans every year. Which would make a dramatic boondoggle of extra diabetic fatalities noteworthy.

Massachusetts

The following chart shows the total # of deaths with one of the diabetes ICD codes:

Splicing out the NH from the non-NH levels out the excess in the non-NH deaths after 2020 (right):

Non-NH diabetes deaths, men vs women:

Here’s the kicker: if we exclude the deaths that list covid as a CoD from the diabetes deaths in the non-NH deaths, we see a pretty consistent substantial excess starting in 2020 and continuing through the present (right):

In other words, this looks like a lot of excess diabetes deaths in 2020 and even 2021 were people killed by covid/covid policies (and maybe also covid vaccines) where the diabetes was a comorbidity that predisposed them to bad outcomes, but in 2022/23, the excess might be attributable to increased diabetes incidence itself .

Minnesota

Minnesota diabetic deaths are far more even overall compared to MA before we start disaggregating deaths into subgroups:

NH vs non-NH shows a very stark difference here:

Within the non-NH diabetes deaths, if we exclude covid deaths, we still see a glaring trend of excess mortality (right) continuing after 2020 through 2023:

Nevada

I used the text of Diabetes/diabetic for Nevada, because it caught a significantly larger number of deaths (Nevada has a unique issue that a bunch of the death certificates are missing the ICD codes. While this doesn’t always make issues, here there was a substantial difference, so I went with the text instead):

Nevada also shows quite a startling trend of excess in the 30-59 year old’s (and what’s with the first half of 2021??)

Vermont

Vermont trend speaks for itself:

NH vs non-NH:

And when we exclude covid deaths, we still see lots of excess even in 2020 (right):

VI. PROTEIN CALORIE MALNUTRITION (ICD Codes under E4)

This condition struck me as completely random to manifest the craziest pound-for-pound degree of excess mortality of any major condition.

Then I came across a study containing the following line:

So it may not be so random after all.

It is also significant because there was a massive increase in deaths listing PCM as a CoD *BEFORE* the pandemic hit… in every state we have (!!).

Massachusetts

From 2015 to 2019, the number of PCM deaths almost *doubled*, from 370 to a staggering 623.

Then it actually doubled from 2019 to 2023 cresting at an earthshattering 1,222 (!!)

This should have raised a few eyebrows over at the CDC???? (And as we’ll see, every state is like this):

This chart shows the total # of deaths each year where the UCoD (primary CoD) was PCM:

And here’s the UCoD deaths broken down between NH vs non-NH - the trend is identical (!!!):

Minnesota

Minnesota saw an even zanier staircase from 2015 to 2019, going from 367 PCM deaths to more than 250% increase of 858 by 2019.

Which then itself nearly doubled to hit 1,623 by 2023:

Deaths with PCM as the UCoD at least show a more level trend before the pandemic:

When we break apart the NH vs non-NH UCoD PCM deaths, in Minnesota, the NH has a FAR MORE DRAMATIC INCREASE (?!?!?):

This is completely crazy…

Nevada

Nevada has the same dynamic:

Here’s UCoD vs MCoD deaths in Nevada - UCoD PCM deaths actually go down (??) from 2015-2018 before shooting up in 2019 and exploding forth in 2020:

Vermont

Even Vermont. But Vermont takes the cake with a >1,300% increase in PCM deaths from 2015 - FIVE total deaths - to 2019 - **67** total deaths.

Followed by the obligatory boom in 2021/22.

I wonder what 2023 will look like….

Vermont however has a somewhat more moderated excess swing in the NH deaths (left) not seen in the non-NH deaths (right):

SEPSIS

The Sepsis charts are all charts used for the other conditions, and don’t really require further commentary.

Massachusetts

The other states are much worse then Massachusetts.

This chart is showing the non-NH death in ages 65-84, where the excess is a bit clearer:

Minnesota

This excess is very substantial:

If we exclude covid deaths from the Sepsis deaths, we still see mounting excess (right):

Nevada

I would bet that if we could separate out the Nh vs non-NH deaths, excluding covid deaths wouldn’t mostly vanish the excess trend, and anyways covid deaths are massively inflated:

Vermont

We conclude with Vermont, which shows a wild reversal of five consecutive years of decreasing Sepsis deaths:

In Vermont, excluding covid deaths barely dents the excess Sepsis deaths:

Caveats:

Now for the really boring disclaimers…..

• This is NOT intended to represent a final or conclusive analysis of excess mortality. The point is to show that there are glaring signals which appear to be extremely disturbing trends of substantial excess death, that are being completely ignored by the public health establishment. (However, it is my contention that even upon robust analysis, the vast majority if not all of the signals documented herein will ultimately pan out.)

  For more specific or granular information and analysis about death certificate data, check out John Beaudoin’s book “The Real CDC” which has a lot of charts and exhibits (and a bunch of VAERS reports he matched up with actual death certificates, another elementary failure by the CDC/FDA to do the most rudimentary pharmacovigilance).

  You can also see what we’ve written previously on Trial Site News, and I will be writing additional articles there to further elucidate the data and information contained in this article, which are mostly bird’s eye view summaries of trends.

  Ed Dowd’s group also should be releasing a preliminary report on excess deaths with Acute Renal Failure in a few weeks.

• We don’t have 2023 death certificates for Vermont, and only through July for Nevada.

• Vermont only gave us the Text CoD’s, without the ICD codes, so we are forced to use pure text parameters for all Vermont data.

• Nevada only gave us age & sex, so we were limited how we can parse the Nevada deaths compared to the other states.

• Each state has their own idiosyncrasies about how they describe and document various conditions contributing to death. This makes direct comparisons difficult. The conditions we chose are unique in that there is a consistent trend across all the states we have in our possession. (There is one exception to this, where we went on a deep dive to sort out how kinetic injuries (e.g. falls, blunt force traumas) are written and categorized in each state and show the trends we were able to isolate.)

• An increase in deaths from any given condition is not in itself proof of that condition being the cause of those deaths because it is possible that more people are being killed by something else but “dying with” this condition. Furthermore, some conditions are themselves really proxies for other pathologies and are not on their own primary instigators of disease or death. However, an increase in deaths involving a condition or disease, especially one that outpaces overall excess mortality, is definitely a signal that there might be something to the correlation - something which public health must investigate and resolve.

• The trends seen in the nominal number of deaths are reflected in population-adjusted rate per 100K (using US Census #’s)

• Cancers are up significantly, however it is a very complex endeavor to show and is not something that amenable to framing as a simple trend.
  Also, since there is already widespread recognition even in the mainstream that cancers are up (“mysteriously”), I figured that it was better to focus elsewhere on conditions with clear excess (And that are also less contentious).

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Background: I participated in a survey of my community (Orthodox Jews) about climate change. The questions were gauging (1) what your views of the climate change science are, and (2) how that fits into your religious/theological worldview.

(*Note: This is lightly edited for clarity and form)

While the meta-narrative of climate change is definitely a scientific fraud, most scientists are not corruptly manipulating scientific field work or analysis, but rather are themselves victims of the fraud.

There are a lot of incentives, pressures, influence, from a variety of sources that all play a role in distorting science, some of it fraud, but a lot of it is simply the systemic inbuilt biases.

For instance, because of the imbalance in funding and social acceptance within the research community, there is a lot of work being done to elucidate and discover new warming mechanisms in nature that have to do with the concentration of carbon in the atmosphere, but not to discover cooling mechanisms or nature’s self-contained feedback loops that can modulate excesses. This leads to models being programmed with lots of warming inputs but a dearth of cooling inputs (and the models always, mysteriously, somehow overshoot the temperature even in the near term).

Regarding the fraud, instead of a whole disquisition, simply consider that the same data that in the 1970's was showing a cooling trend that led to a "scientific consensus" that we're heading for an ice age somehow now shows there was really a warming trend the whole time. This should be sufficient to demonstrate that the data is not remotely “objective”, but rather at minimum is dependent to a very significant extent upon human calculations and input on top of the raw recorded data, so much so that decades of a trend in one direction can be retrospectively flipped to show the exact opposite trend. And because the incentives are very much aligned to produce warming trends, we cannot trust that the adjustments are being made based on any objective formula or in good faith.

Climate change doesn’t qualify as a scientific discipline in any event – science is a process of observations, hypotheses, and reproducible experimentation to verify or refute theories. Climate change has none of that – they cannot predict anything specific, and as stated already every model ever released failed to accurately predict even the near term temperature trends correctly. Instead, literally every single major climate model ever released overestimated the temperature to be hotter than even their warped adjusted datasets that falsely add warming into later years and lower the temperatures of earlier decades to create the “warming” trend. Consensus is not a scientific concept any more than Anthony Fauci is the living incarnation of Science.

It’s also worth pointing out that climate scientists resolutely ignore other potential sources of warming and cyclical phenomena that can affect the climate, such as undersea volcanoes or the spectacular heterogeneity of the Sun’s surface.

It is tremendous hubris – something that is rather typical of modern day scientists in contrast to their predecessors from prior centuries or even the first half of the 20^th century - that we can exert such control over the climate at all. The amount of carbon emitted throughout all of human history pales in comparison to one big volcano eruption. People don’t have any sense of the scale of the Earth, and how insignificant humans and our actions are by comparison.

As far as the political interference with climate science is concerned, to pretend that there is no political movement nowadays that is at least trying to capitalize on crises in order to arrogate more power to centralized government control is to deceive yourself or be a remarkably stubborn ostrich. This is hardly a “conspiracy theory”. Public officials such as the UN Climate Czar have openly expressed that communism is a superior system of governance necessary in order to combat climate change.

Furthermore, institutional science is now openly a corrupt cult of insanity - the fact that "science" holds that there are limitless genders; homosexuality is normal/healthy; chemically, emotionally and surgically mutilate confused children; and so on is incontrovertible evidence to any religious adherent in the Judeo-Christian tradition who is rational & follows the Bible that Institutional Science is clearly beholden to other considerations besides objective scientific inquiry about objectively observable phenomena in the physical universe, to which objective science is of secondary importance or not a consideration altogether.

There are also far more scientists than people are aware who dispute the fundamental premises of anthropogenic climate change, including Nobel laureates. But they are mostly afraid to speak out publicly because of the climate of fear, reprisals and cancellation they know will ensue should they openly buck the orthodoxy. This in itself also debunks the ‘scientific’ character of assertions made by people in the name of science that comprises the climate change narrative – where dissent is stifled and dissidents are quashed, by definition the open and honest debate which is the lifeblood of objective scientific inquiry is not taking place. Censorship is irreconcilable with the scientific method.

Lastly, there is no religious commandment or theme of safeguarding the planet from planetary doom. As a religious matter, the [Oral tradition of the Old Testament] actually states that the state of the physical world is dependent upon the moral virtue of humanity. The Sages of the Talmud relate that in the Generation of the Flood, the animals themselves were corrupted because of the sins of that generation (you can use your imagination as to how that was manifest). So if someone wants to worry about the state of the planet, then start with making sure that you are living properly according to the Bible and G-D’s actual Commandments, which is hard enough.

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The above chart looks mighty impressive, almost as if challenging you to deny the self-evident morbid reality of a cataclysmic cancer calamity. But is this chart - which accurately depicts the data indicated by the chart’s title - telling us the whole story, or is it cherry picked parameters to make it appear as if there’s a massive surge in cancer mortality that isn’t really there?

I recently published an article highlighting that there are a surprising number of case reports documenting cancers arising after vaccination with a genetic covid vaccine, which apparently has gotten around. Moreover, the notion that there is an issue - of course a “mysterious” issue, to be sure - of rising cancer incidence, morbidity and mortality in the general population has (finally) trickled up into the mainstream. But how big is the increase? And how confidently in whole or in part can we attribute it, or preclude attribution, to/from anything specific?

Death certificates are a flawed tool for data construction. They are rife with errors, prone to biases, subject to capricious and sometimes deliberate manipulative policy changes from on high, and rarely tell the complete story of the decedent’s demise. They are under the aegis of state health departments and the CDC, which doesn’t exactly inspire confidence about their quality or integrity. But neither is it an indefatigable Sisyphean task to extract useful, useable data from the information logged and recorded on these indubitably wanting instruments, although progress often creeps along slowly enough to give the illusion that Zeno’s motion paradox accurately describes reality.

To our good fortune, cancer is not a condition that would be documented without an official diagnosis, so we can at least be confident that a decedent recorded as having died with cancer did indeed die afflicted by cancer.

To our less-good fortune, the inverse is also true - undiagnosed cancers will not appear on death certificates. Furthermore, sometimes even a diagnosed cancer can be omitted by an unscrupulous or cowed coroner. This is not hyperbole - Ethical Skeptic had a relative killed by colon cancer but the ME refused to put it on the death certificate.

There are other confounding factors and messiness which we’ll see as we try to sort out what is going on in Minnesota with cancer mortality. Because of the complexity and breadth of information, this is going to take a few articles to cover.

This article will broadly overview cancer mortality in the Minnesota death certificates, and provide some essential background to unpacking the various trends.

It still feels bizarre and surreal that there is such glaring signals in publicly available mortality data completely ignored and disregarded by public health. It’s their own data! (Yes they’re evil and complicit etc., but still.) So fasten your seatbelts and get on the Magic School Bus as we explore the otherwise dull and droll intricacies of number crunching (I have fond memories of watching this show as a little kid, back when kids shows taught real sciency science, not woke gibberish indoctrination).

Background

We must begin with some eye-glazing but necessary basic pointers about how death certificates work (**Click here to skip straight to the data below**).

When someone dies, there is a death certificate that is filled out for official / legal purposes. Death certificates contain a lot of information (some states include more than others), including the causes of death (CoD).

Causes of death refer to the medical conditions that ultimately played some role in the demise of the decedent. To qualify as a CoD, a condition only needs to contribute to the medical decline of the decedent in some way, but doesn’t have to be directly responsible for whatever ultimately killed the person. If someone had high blood pressure, and subsequently suffered a heart attack that led to cardiac arrest which killed them, all three conditions qualify as CoD. On the other hand, this unfortunate fellow’s ingrown toenail is not a cause of death, because it didn’t contribute to their demise.

The sample death certificate below is from the CDC’s own guidance explaining how to properly fill out CoD’s on a death certificate (you don’t need to understand the difference between Cause A, B, etc for this article):

ICD 10 Coding System for CoD’s

There is a fancy coding system that is used to classify the many thousands of medical conditions that can play a role in death known as the International Classification of Diseases. Every few years, it is updated/revised to keep up with new medical (or bureaucratic) developments, as new conditions are discovered (created?) and old conditions are reorganized or reclassified.

The current iteration of the ICD that was used for the deaths we’re looking at is the ICD 10 (so named because it is the 10th edition). It is basically a hierarchical classification system:

There are codes for practically every random weird thing you can think of:

There are two types of tumors - malignant and benign. Malignant cancers are the kind that spread rapidly destroying everything in their path like a horde of marauding Orcs. In the ICD 10 coding system, malignant neoplasms - i.e. malignant cancers - are indicated by a ‘C’ code:

Thus we’re going to be looking at the ‘C’ codes, used to indicate “malignant neoplasms”. (The benign tumors are ICD 10 Codes D00-D48.)

Cancer Death Data

Now for the exciting part….

The following chart shows the total number of deaths each year in Minnesota:

The next chart shows the total number of deaths each year in Minnesota that have at least one ‘C’ code on the death certificate:

So just by immediate first impression, while both show excess mortality in every pandemic year, the trends are going in opposite directions - overall mortality going down after 2020, cancer deaths nominally rising after 2020. This is a good lead indicator that there are disproportionate excess cancer deaths compared to the overall mortality burden in the pandemic years.

We can see that the total number of deaths with a cancer code goes up over the trendline that existed pre-pandemic by a very slight margin - somewhere in the ballpark of 300-600 extra cancer deaths, or around 0.025%-0.05% increase above what we would expect to see if cancer deaths kept to their pre-pandemic trend.

If we separate men and women, we see that the women had a flatter trend pre-pandemic with more pronounced excess during the pandemic years (2020-2023), although the 2023 total number of cancer deaths are lower than in 2022.

The men have a steeper rising trend pre-pandemic, but still are in excess, and notably unlike the women the 2023 total is higher than the 2022 total:

If we look at other characteristics, we see the same basic pattern, slight excess that is mostly unremarkable given the excess death in the population overall.

If this were the whole story, then it might stand to reason that cancer isn’t actually killing more people, because the slight excess can be explained by the fact that there is excess mortality in the state in the pandemic years from other reasons, which inevitably would tend to kill of some people with cancers who would have otherwise survived.

Of course, there is more to the story.

Nursing Home vs Non-Nursing Home

There is a major Simpson’s Paradox affecting the cancer mortality data driven by NH residents.

Minnesota helpfully identifies both the place of death and the type of residence before death, which is useful because it allows us to see NH residents who die elsewhere (mostly in a hospital), not just those who died on the NH grounds.

The following chart shows the number of cancer deaths of NH residents:

There’s not only a deficit post-2020, there’s also a deficit in 2020 too (!). This is probably a result of a mass culling of NH residents in the 2020 covid waves (covid + policies) - it is likely that some portion of these deaths would have been diagnosed with cancer and died shortly thereafter had they not been killed by covid first. Additionally, there were probably a lot of missed cancer diagnoses in NH residents who did die because Nursing Homes locked down more than any other sector of society - most of the services and healthcare normally provided for the residents was simply canceled.

Either way, there is a statistical cancer mortality deficit in NH residents for the pandemic years.

Now let’s look at cancer deaths in the non-NH residents:

Notice how the pre-pandemic trend is pretty flat, and there is a very sizable increase in all pandemic years.

(*Note: It is important to keep in mind that the NH population is dynamic rather than static, and it is possible that after 2020 people were a bit more reluctant to go to a NH after seeing the brutal carnage of covid policies in Nursing Homes. However, I don’t think that this can come close to explaining the entire discrepancy between NH vs non-NH residents.)

There’s a few thousand excess cancer deaths combined, or about 7%-10% excess depending on the year.

We can further disaggregate the non-NH resident cancer data to look at age. The following charts show the number of cancer deaths in Seniors (right) vs non-Seniors (left):

Again we can see a Simpson’s Paradox, where the non-seniors have a far more muted trend compared to the Seniors.

Furthermore, the trend of cancer deaths pre-pandemic are opposites between the non-seniors and seniors - whereas there is a clear downward trajectory for the non-seniors, there is an upward trajectory for the seniors

I added a black line to show approximately where the cancer deaths in the non-seniors should be for the pandemic years had the trend continued. Superficially, the portion of the bars above the black line is the excess above the trendline. In other words, it is likely that there is excess cancer deaths in the younger people even though the total numbers are actually lower than 2015/16 and about the same as 2017. However this might be very misleading because of a strange anomaly in the 50-59 age cohort which we’ll hopefully get to in a future article.

If we zoom in on the senior non-NH deaths, we can see that there is a big difference between the age cohorts 65-84, and 85+:

Firstly, cancers are a far smaller proportion of deaths in non-NH seniors 85+ (right) compared to non-NH seniors 65-84 (left):

Secondly, the smaller % of excess in the 85+ cohort might also be attributable at least in part to a pull-forward effect from the substantial excess mortality in that group in 2020.

If we focus on the 65-84 cohort within the non-NH residents, we see the following:

Now this looks like a devastating trend - far clearer than the grand total of all cancer deaths that we started with:

Another way to visualize the unique trend seen in the 65-84 yo non-NH residents is to look at cancer deaths as a % of all deaths each year in Minnesota.

The % of all deaths that involve a cancer actually decreases during all pandemic years -

- the % of all MN deaths that are a cancer death in the 65-84 year old non-NH resident seniors goes *UP* significantly, in 2021 but not 2020:

This is doubly impressive because these deaths comprise a larger portion of a pie that is itself larger because there is a lot of excess mortality from a variety of causes, not just cancer.

*******

Up next: UCoD vs MCoD, and looking at individual types of cancer

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The point of this article is to present the bird’s eye view of overall mortality in Minnesota, and to highlight a few of the important confounders that skew the topline total numbers to misrepresent the underlying reality.

I. Total Deaths

First we will look at a few stats about deaths from all causes (usually referred to as “All Cause Mortality”)

The following chart shows the total # of deaths each year in MN1:

You can see that starting in 2020 there is a lot more deaths compared to previous years. This trend continues for all years after 2020 so that we are still today suffering from excess mortality.

This trend remains when we adjust for population growth, which you can see in the following chart showing the *# of deaths per 100K people* in MN:

This trend is manifest regardless of sex:

We can conclude even from just the topline numbers that there’s definitely more people dying than we would expect starting in 2020 and continuing through today.

Other Stats

Average # of ICD codes on the death certificate

The vast, vast majority of people who die have multiple Causes of Death documented as contributing to the death (see here for more). Each one gets assigned the ICD code corresponding to that condition. The following chart shows the average # of ICD codes on each death certificate:

Marital Status

There are a few conditions where there are big differences in trends between these categories, but not so much in the ACM, with the exception of widowed being a partial proxy for nursing home residents:

(I left the other/unknown off because there are so few of them.)

Average age of death

There’s one stat that even in the combined all-cause mortality is bizarre - the average age of the decedent, visualized by the following chart:

The average age of deaths dropped almost a year and a half. This is actually a massive drop even if it superficially may not sound like much. To move the average age down by such a margin, you need a *lot* of extra deaths in young people to balance out the octogenarians and septuagenarians who comprise the overwhelming majority of deaths each year, as we’ll see later when we look at distinct age groups.

This dramatic shift is a good signal that the driver of excess mortality changed between 2020 & 2021.

II. Simpson’s Paradoxes

One of the biggest confounders of data is something called “Simpson’s Paradox”. Basically it’s when the subsets of a group cancel each other out into an average that hides the differences in each subset.

There’s one *massive* Simpson’s Paradox in the mortality data that is relevant in almost every condition that we’ll use to illustrate: Nursing Home / Long Term Care residents vs the non-NH/LTC resident population.

The following chart shows deaths from the NH (left) vs non-NH (right) populations side by side:

The number of deaths per year actually go *DOWN* - quite substantially - in the NH population after 2020. Conversely, the number of deaths in the non-NH population goes up in 2020, but then even more in 2021, and stays elevated above 2020 in 2022.

But when you combine them into a single group of ‘everyone who died’, the sharply contrasting trends blend into a trend that averages them both, which we saw in the first chart above that makes it look like the excess deaths peaked in 2020 and then went down from there:

This particular paradox becomes far more critical and disruptive when it comes to certain conditions, such as cancers.

Age

Age cohorts pose another Simpson’s Paradox, where the cumulative total swamps out strong signals in younger age cohorts because there are >100x as many deaths in seniors as in teens.

The following charts show all cause mortality for each age cohort.

Ages 0-4:

Ages 5-11:

Ages 12-17:

Ages 18-29:

Ages 30-39:

Ages 40-49:

Ages 50-59:

Ages 60-64:

Ages 65-69:

Ages 70-74:

Ages 75-79:

Ages 80-84:

Ages 85-89:

Ages 90+

‘Pull Forward Effect’

Notice in the last two charts showing the deaths for 85-89 & 90+ year old’s, there doesn’t seem to be any excess death after 2020, rather the number of deaths seems to return to normal.

This however is an illusion. After the substantial excess mortality in 2020, in 2021 we should see a mortality deficit - i.e. lower than normal - because a substantial % of the excess deaths in 2020 were people who were otherwise going to die in 2021. (How many of those deaths were “stolen” from 2021 is a good question, and has no definitive answer, although honest competent experts can create mathematical models to give an approximate range where the number is likely to be.)

*************

Next article will start to address cancer mortality in Minnesota, which should be a bit more exciting than this one.

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1

How to read the charts

--each chart has a title on top that describes the parameters or conditions of the deaths shown by the chart
--each bar represents the tally for one year
--the various shades of grey bars are for the years 2015-2019 (left to right)
--blue bar = 2020
--yellow bar = 2021
--red bar = 2022
--purple bar = 2023
--the number on the top of each bar indicates the number of deaths in that year that fit the conditions articulated in the title of the chart

Cancers are probably pound for pound the least documented side effect of the genetic covid vaccines in the case report literature.

Firstly, the nexus between covid vaccines and cancer is inherently far murkier and harder to spot on an individual basis, for two reasons:

1. On the whole, there’s going to be a substantial time gap between vaccination and clinical manifestation of the cancer

2. Partly because of #1, and also because of the uncharted pathological territory for the novel mRNA platform, doctors are less likely to think there may be a connection between their patient’s cancer and vaccination.

Secondly, even if a doctor thinks that there might be a connection between some aspect of a cancer’s pathology and the patient’s covid vaccines, it is not the sort of thing that lends itself to being written up as a case report:

1. Because of the time gap and lack of direct pathological evidence, it is intrinsically more speculative and less grounded in discrete evidence that you can identify, and so less likely to be written up as a case study

2. The censorship regime, and the culture of golden calving the covid vaccines more generally, regards criticism of the covid vaccines with a very wary eye, something that is especially intense when it comes to the potential genotoxicity of the covid vaccines which is a very big deal.

Thus doctors and clinicians are less likely to even entertain a possible relationship between a cancer and the vaccination status of a covid patient, and much less submit a study with their name attached claiming the possibility of a covid vaccine-induced cancer.

Conversely, there is substantial evidence both anecdotally and in population and economic data that there is ongoing widespread excess cancer incidence, morbidity and mortality especially in highly vaccinated countries.

https://twitter.com/EthicalSkeptic/status/1786115396870746541

There are also multiple well-grounded hypotheses for the mechanistic plausibility that the covid vaccines possess substantial oncogenicity, including the likelihood of reverse transcription of mRNA or contaminant DNA into cellular DNA, the interference of the spike protein with the P53 tumor suppression gene, and the dysregulation of critical TLR’s critical for cancer surveillance, among others.

(Both of these points I presume anyone reading this are already quite familiar with so we needn’t belabor the point further here.)

So I decided to check how many case reports were there that I could identify as documenting a cancer case possibly related to vaccination, which resulted in the list below:

• 29 case reports that documented a cancer whose genesis and/or metastasis was potentially attributable at least in part to vaccination.

• Seven additional case reports documented a cancer, but framed it as an incidental or background phenomenon. I included these because while it may be that these cancers were truly “with” vaccination and not “because” of vaccination (like the with/because of covid dichotomy that created hundreds of thousands of phantom covid deaths and millions of phantom cases), it may also very well be the case that these cancers were impacted by vaccination. The fact that the case report authors did not think so is immaterial, because of the widespread ignorance about the carcinogenic potential of the covid vaccines and that doctors are heavily biased to avoid drawing such a connection.

• Three case reports I found documented benign tumors that were judged possibly attributable to a covid vaccine. These are significant because the ability to cause benign tumors - especially in light of the broader evidence base here - implies the potential to cause malignant tumors, plus benign tumors can sometimes turn malignant.

• Finally, there are two case reports where the covid vaccine led to a spontaneous and unexpected regression of the cancer. Although superficially these case reports might seem to reflect favorably upon the covid vaccines, the fact that the covid vaccines can spur tumor regression points to something far more ominous - that the covid vaccines interfere with or reprogram the immune system in unanticipated ways, including the mechanics of how the immune system deals with cancers. There’s an old medical adage “a cure for one is poison for another”. The fact that the covid vaccines can interfere with the immune system’s cancer-fighting ability in a positive way suggests an ability to do so in a deleterious manner as well in others.

I also included a quote from each case report discussing the potential causal role of the covid vaccine if there was one that was written in clear enough language inside the study.

So without further ado….

1. A Case of Chronic Myelomonocytic Leukemia Unmasked After Receiving J&J COVID-19 Vaccine (Veerballi et al)

https://pubmed.ncbi.nlm.nih.gov/35865440/

"Our case suggests the possibility of developing CMML associated with limited scleroderma after receiving the J&J COVID vaccine."

2. Anaplastic large cell lymphoma at the SARS-CoV2 vaccine injection site (Revenga-Porcel et al)

https://pubmed.ncbi.nlm.nih.gov/36166359/

*paywall*

3. Bell's palsy or an aggressive infiltrating basaloid carcinoma post-mRNA vaccination for COVID-19? A case report and review of the literature (Kyriakopoulos AM et al)

https://pubmed.ncbi.nlm.nih.gov/37927346/

"Overall, the short time frame and extremely invasive characteristics of BCC metastases in our patient suggest that immune system disturbances by the mRNA anti-COVID-19 vaccination may have led to the accelerated progression of the disease."

"A serious limitation in the case we report is the refusal of the hospital that performed the biopsy to provide the histopathological images or perform immunohistochemical staining for the spike protein."

4. COVID-19 Vaccine-Induced Expansion of Pituitary Adenoma: A Case Report (Srimanan W & Panyakorn S)

https://pubmed.ncbi.nlm.nih.gov/38229808/

"Pituitary gland tumors are slowly growing, primarily asymptomatic, with incidental findings. Early detection, reduced aggravating factors, and specific treatment are essential. The COVID-19 vaccine represents a novel potential contributor to the enlargement of the pituitary gland. Individuals with preexisting pituitary adenomas should be particularly vigilant regarding the possible side effects associated with this vaccine."

5. Development of High-Grade Sarcoma After Second Dose of Moderna Vaccine (Bae E et al)

https://pubmed.ncbi.nlm.nih.gov/37197108/

"Based on an extensive search, we describe the first case of rapidly progressive, high-grade undifferentiated sarcoma that seems to have a strong association with the Moderna vaccination."

[Bonus: "It is well-documented in the literature for over 20 years that high-grade sarcomas have been linked to vaccine administration in felines."]

6. Newly diagnosed extranodal NK/T-cell lymphoma, nasal type, at the injected left arm after BNT162b2 mRNA COVID-19 vaccination (Tachita et al)

https://pubmed.ncbi.nlm.nih.gov/37093551/

"Although the lymphoma lesions of previous reports were not observed at the vaccine injection sites, our case had a lymphoma lesion in the skin and muscle at the BNT162b2 mRNA-vaccine injection site. It is possible that our case is of different pathogenesis from previous reports, in that the disease occurred relatively late after vaccination and at the site of vaccine injection." "There was no evidence of causal relationship between BNT162b2 mRNA vaccination and ENKL in this case, but we speculated that vaccination might lead to the development of ENKL in a manner similar to severe mosquito bite allergy (SMBA)."

7. Non-Hodgkin Lymphoma Developed Shortly after mRNA COVID-19 Vaccination: Report of a Case and Review of the Literature (Cavanna et al)

https://pubmed.ncbi.nlm.nih.gov/36676781/

8. Ph-Positive B-Cell Acute Lymphoblastic Leukemia Occurring after Receipt of Bivalent SARS-CoV-2 mRNA Vaccine Booster: A Case Report (Ang SY et al)

https://pubmed.ncbi.nlm.nih.gov/36984629/

"Therefore, this case report might present a possible correlation between the development of Ph–positive B-cell acute lymphoblastic leukemia and bivalent mRNA vaccinations."

9. Primary Cutaneous Adenoid Cystic Carcinoma in a Rare Location With an Immune Response to a BNT162b2 Vaccine: A Case Report (Yilmaz A et al)

https://pubmed.ncbi.nlm.nih.gov/38608126/

"The BNT162b2 mRNA vaccine has been associated with a multisystem inflammatory syndrome (MIS-V). A comparable immune reaction could potentially enhance tumor growth rate." [paywall]

10. Rapid Progression of Angioimmunoblastic T Cell Lymphoma Following BNT162b2 mRNA Vaccine Booster Shot: A Case Report (Goldman S et al)

https://pubmed.ncbi.nlm.nih.gov/34901098/

"To the best of our knowledge, this is the first observation suggesting that administration of a SARS-CoV-2 vaccine might induce AITL progression. Several arguments support this possibility. First, the dramatic speed and magnitude of the progression manifested on two 18F-FDG PET-CT performed 22 days apart. Such a rapid evolution would be highly unexpected in the natural course in the disease. "

11. Rapid progression of marginal zone B-cell lymphoma after COVID-19 vaccination (BNT162b2): A case report (Sekizawa et al)

https://pubmed.ncbi.nlm.nih.gov/35979213/

"In our case, the same mechanism by which T-cell lymphomas are induced by the COVID-19 vaccine could be considered for the pathogenesis of MZL. mRNA COVID-19 vaccines are reported to induce T follicular helper cells with a Th1 functional profile, which is associated with selective generation of neutralizing antibodies, and stimulate germinal center B-cells, long-lived plasma cells, and memory B-cells. Therefore, these vaccines induce a stronger germinal center reaction than recombinant protein vaccines (11). However, the continuous stimulation of T- and B-cells by mRNA COVID-19 vaccines can trigger aberrant inflammatory responses, leading to lymphoma or accelerating its progression."

12. Recurrence of cutaneous T-cell lymphoma post viral vector COVID-19 vaccination (Panou et al)

https://pubmed.ncbi.nlm.nih.gov/34628691/

"The question which is raised in these cases is whether and via which pathway the vaccine has caused the MF CD30+ LCT and the reappearance of primary cutaneous CD30+ lymphoprolipherative disorder.

According to the literature, the education of CD4+ T, CD8+ T and B cells against SARS‐CoV‐2 S protein appears to be the most feasible way for COVID‐19 vaccine production. Both cancers and coronavirus provide a persistent and chronic antigenic load, amongst which PD‐1, resulting in T‐cell exhaustion. Therefore, it is important to assure the vaccination would not cause a further T‐cell exhaustion state which may have already been induced by tumour cells."

13. Recurrence of primary cutaneous CD30-positive lymphoproliferative disorder following COVID-19 vaccination (Brumfiel et al)

https://pubmed.ncbi.nlm.nih.gov/33974494/

*paywall*

14. Solitary Eruptive Keratoacanthoma Developing at Site of COVID-19 Vaccine Injection (Yumeen S et al)

https://pubmed.ncbi.nlm.nih.gov/38015786/

"Our case report adds to the literature by describing development of a malignant lesion that may occur following COVID-19 vaccination, and warrants prompt recognition and treatment."

15. Two cases of axillary lymphadenopathy diagnosed as diffuse large B-cell lymphoma developed shortly after BNT162b2 COVID-19 vaccination (Mizutani et al)

https://europepmc.org/article/pmc/pmc9114986

"Thus, it might be conceivable that pre‐existing or subclinical DLBCL may rapidly grow in a specific condition induced by BNT162b2 vaccination." "In conclusion, DLBCL may rapidly grow after BNT162b2 vaccination. Dermatologists should pay attention to enlarging LNs or mass near the injection site of BNT162b2 vaccine."

16. Unilateral conjunctival Classic Kaposi Sarcoma following a COVID 19 booster (White E et al)

https://pubmed.ncbi.nlm.nih.gov/38601193/

"In that the vaccine booster preceded the cancer, it appears etiologic to the appearance of Kaposi's sarcoma. The patient's monocular vision and glaucoma complicated her treatment. This case expands on current concepts of cofactors needed for the development of Kaposi's sarcoma in that vaccine booster administration was relevant to tumor progression and both clinical and mechanistic evidence is presented to support this hypothesis." "In this particular case, it appears that COVID19 vaccination acted as one of the additional co-factors necessary to induce KS in that there was no other clear cause other than the temporal relationship between booster vaccine and development of KS."

17. A Case Report of Posttransplant Lymphoproliferative Disorder After AstraZeneca Coronavirus Disease 2019 Vaccine in a Heart Transplant Recipient (Tang WR et al)

https://pubmed.ncbi.nlm.nih.gov/34702598/

"In summary, we hypothesize that the vaccine may contribute to B lymphocyte tumorigenesis via the reactivation of latent EBV." "We report a case of PTLD after COVID-19 vaccination in a heart transplant recipient, which might show a possible pathogenic link. Although we are not able to exclude the coincidence of COVID-19 vaccination and the development of PTLD in this case, transplant surgeons should be aware of the immunomodulatory effect after COVID-19 vaccination and always think the worst until proven otherwise."

18. Case report: A case of metastatic BRAFV600-mutated melanoma with heart failure treated with immune checkpoint inhibitors and BRAF/MEK inhibitors (Nishizawa A et al)

https://pubmed.ncbi.nlm.nih.gov/38529375/

"In the present case, the vaccine might have elicited a strong immune response, leading to the spontaneous resolution of the primary tumor while simultaneously promoting the axillary lymph node metastasis."

19. Fatal hemophagocytic lymphohistiocytosis with intravascular large B-cell lymphoma following coronavirus disease 2019 vaccination in a patient with systemic lupus erythematosus: an intertwined case (Ueda Y et al)

https://pubmed.ncbi.nlm.nih.gov/38619098/

"We  speculate  that  the  COVID-19  vaccination  and    our    patient’s    autoimmune    condition,    which    predisposes   her   to   develop   lymphoma,   may   have   contributed  to  IVLBCL  development.  The  activation  of  the  B  cell  activating  factor  belonging  to  the  tumor  necrosis  factor  family  (BAFF)  pathway  was  seen  in  aggressive  B  cell  lymphoma"

20. Hematologic Malignancies Diagnosed in the Context of the mRNA COVID-19 Vaccination Campaign: A Report of Two Cases (Zamfir et al)

https://www.mdpi.com/1648-9144/58/7/874

"To our knowledge, this is the first report of a severe post-vaccination oral manifestation, immunohistochemically confirmed as T/NK-cell non-Hodgkin lymphoma, emerging within days after mRNA COVID-19 vaccination."

21. Hematopoietic Adverse Events Associated with BNT162b2 mRNA Covid-19 Vaccine (Erdogdu B et al)

https://avesis.hacettepe.edu.tr/yayin/64667112-eb73-4bd3-b8c5-d5df96cc4e09/hematopoietic-adverse-events-associated-with-bnt162b2-mrna-covid-19-vaccine

22. Indolent cutaneous lymphoma with gamma/delta expression after COVID-19 vaccination (Hobayan CG & Chung CG)

https://pubmed.ncbi.nlm.nih.gov/36530557/

"Our patient’s presentation is unusual as it arose at the site of a COVID-19 vaccination several days after vaccination." "Since this presentation and course are not typical of PCGDTCL, it is unclear if his lesions represent an indolent variant of PCGDTCL or other lymphoma with gamma/delta expression. It is unknown if the COVID-19 vaccine directly contributed to his presentation or disease course. One additional case report shows an atypical lymphoproliferative lesion with features mimicking lymphoma following the vaccine booster, monotypic proliferation of B-cells was found histologically."

23. Primary cardiac mesothelioma presenting with fulminant recurrent pericarditis: a case report (Schwartzenberg et al)

https://pubmed.ncbi.nlm.nih.gov/36937239/

"To the best of our knowledge, this is the only second case of pathologically confirmed pericarditis that transformed into mesothelioma,17 in this case within only 4 months. It is unlikely that an earlier correct diagnosis would have made a clinical difference in this case in view of the accelerated disease course."

24. Sporadic Kaposi Sarcoma Following a COVID-19 Vaccine: Mere Coincidence or Something More? (Martínez-Ortega JI et al)

https://pubmed.ncbi.nlm.nih.gov/38465101/

"KSHV is an absolute requirement of oncogenesis and is a direct carcinogen, so when we are looking into the relationship between the AstraZeneca vaccine and Kaposi sarcoma, we may focus on the reactivation of KSHV [1].

Studies have shown that spike proteins of SARS-CoV-2 can reactivate the lytic phase of KSHV. The ChAdOx1 nCoV-19 vaccine contains DNA eDNA-encoding proteins. If these spike proteins encounter HHV8-infected cells, it could potentially trigger the reactivation of the virus, leading to the lytic phase." "While more research is needed to establish a definitive connection, the evidence discussed in this report points to potential mechanisms involving KSHV reactivation, the influence of adenovirus-induced inflammation, and spike protein-related effects."

25. Subcutaneous panniculitis-like T-cell lymphoma after COVID-19 vaccination (Kreher et al)

https://pubmed.ncbi.nlm.nih.gov/35966352/

"In this manuscript, we present a case of SPTCL that developed following the Ad26 viral vector–based COVID-19 vaccine (Janssen Pharmaceuticals). Although causation cannot be established in this single case, this case supports the understanding that certain immunologic triggers, such as a modified adenovirus vaccine, may contribute to the development or exacerbation of SPTCL. Aberrant immune function or lymphocyte hyperstimulation may also be responsible. For example, an association has been established between SPTCL and systemic lupus erythematosus, Sjögren’s syndrome, type 1 diabetes mellitus, and juvenile idiopathic arthritis."

26. Subcutaneous panniculitis-like T-cell lymphoma post-mRNA-1273 COVID-19 vaccination (Ukishima et al)

https://pubmed.ncbi.nlm.nih.gov/37035606/

"Overall, more research is needed to examine possible associations between COVID‐19 vaccination and SPTCL. In this case, COVID‐19 vaccines may cause SPTCL, and skin biopsy at an early stage may help in the diagnosis of erythema nodosum."

27. The case of T-ALL presenting with NK phenotype after COVID-19 vaccination (Yanagida E et al)

https://pubmed.ncbi.nlm.nih.gov/36706586/

"Although the presence of a direct causal relationship between T-ALL and COVID-19 vaccination is unclear, the immunization could be directly related to the immune response of the host." "Although the relationship between vaccination and the onset of this case is unclear, we have reported that careful observation of similar cases is required in order to elucidate the pathophysiology."

28. The first autopsy case of Epstein-Barr virus-positive marginal zone lymphoma that deteriorated after COVID-19 vaccination (Wang Z et al)

https://pubmed.ncbi.nlm.nih.gov/38116849/

*paywall*

29. Unusual Clinical Presentation of Clear Cell Sarcoma in a Young Woman (Asif S et al)

https://pubmed.ncbi.nlm.nih.gov/37877807/

Documented as Incidental/Background in the Case Report

30. Axillary lymphadenopathy in a high-risk breast screening patient following the COVID-19 vaccine: a diagnostic conundrum (Musaddaq et al)

https://pubmed.ncbi.nlm.nih.gov/35300233/

31. Breast Cancer Screening and Axillary Adenopathy in the Era of COVID-19 Vaccination (Wolfson & Kim)

https://pubmed.ncbi.nlm.nih.gov/36219117/

32. Hypermetabolic lymphadenopathy following the administration of COVID-19 vaccine and immunotherapy in a lung cancer patient: a case report (Tripathy et al)

https://pubmed.ncbi.nlm.nih.gov/36434709/

33. Lymphedema of the Arm after COVID-19 Vaccination in a Patient with Hidden Breast Cancer and Paraneoplastic Dermatomyositis (Aimo et al)

https://pubmed.ncbi.nlm.nih.gov/36016107/

34. Metastatic melanoma in the breast and axilla: A case report (Barnett C et al)

https://pubmed.ncbi.nlm.nih.gov/35255441/

35. Metastatic prostatic adenocarcinoma presenting as generalized lymphadenopathy unmasked by a COVID booster vaccine (Bharathidasan K et al)

https://pubmed.ncbi.nlm.nih.gov/38033690/

36. Progressive multifocal leukoencephalopathy in a patient with B-cell chronic lymphocytic leukemia after COVID-19 vaccination, complicated with COVID-19 and mucormycosis: a case report (Amirifard H et al)

https://pubmed.ncbi.nlm.nih.gov/38704555/

Benign Tumors

37. Pilomatricoma Growing at the SARS-CoV-2 mRNA Vaccination Site (Erkayman MH et al)

https://pubmed.ncbi.nlm.nih.gov/38099131/

38. Reactive Angioendotheliomatosis Following Ad26.COV2.S Vaccination (Faulkner C et al)

https://pubmed.ncbi.nlm.nih.gov/38290076/

39. Development of Pilomatrixoma at the Vaccination Site: A Rare Complication of COVID-19 Vaccination - A Case Report (Yang Z et al)

https://pubmed.ncbi.nlm.nih.gov/38055654/

Vaccine Cured Cancer

40. Primary cutaneous anaplastic large-cell lymphoma with marked spontaneous regression of organ manifestation after SARS-CoV-2 vaccination (Gambicher et al)

https://pubmed.ncbi.nlm.nih.gov/34228815/

41. Spontaneous tumor regression following COVID-19 vaccination (de Sousa LG et al)

https://pubmed.ncbi.nlm.nih.gov/35241495/

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The following compilation of studies are all surveys of a defined cohort of vaccine recipients where the rates of severe adverse events - or something that is a good proxy for a severe adverse event - are orders of magnitude greater than the proffered “exceedingly rare” rates in the ballpark of something like 1/100,000 proffered by the medical establishment.

For each study I am including the title, link, the highlights, and a screenshot/s of the highlighted data in the study (if one is readily available).

At the end of the article there is a more detailed explanation of the virtues and limitations of these studies.

One point before we begin, 0.1% = 1/1000. If 1/1000 vaccine recipients suffer a major adverse event, that would mean worldwide approximately 5.5 MILLION people suffered this severe adverse event (5.5 billion vaccinated people / 1000) - and this is only for the ONE adverse event that is showing up as .1%.

• 1% = 1/100 people, extrapolated worldwide this would equal 55 MILLION people;

• 2% = 1/50 people, extrapolated worldwide this would equal 110 MILLION people;

• 5% = 1/20 people, extrapolated worldwide this would equal 275 MILLION people;

A while back I put together a list of 21 such studies that captured high rates of these severe adverse events that we are constantly assured are very, very “rare” by public health authorities. Here are another 15 studies (hence the ‘36’ in the title; Study #’s 1-21 are included at the bottom):

22. Side Effects and Perceptions Following COVID-19 Vaccination in Jordan: A Randomized, Cross-Sectional Study Implementing Machine Learning for Predicting Severity of Side Effects

https://pubmed.ncbi.nlm.nih.gov/38332047/

We’ll begin with this gem of a study which is notable for more than just the wild rates of systemic side effects and the 3.1% of respondents who suffered “chest pain” following vaccination.

This epitome of erudition opens with the following declaration:

“Apart from the inequality in vaccination, war zones and areas where communication is disrupted are affected by myths and misconceptions about COVID-19 vaccines, heightening vaccine hesitancy.”

This stands out even from the typical odes to the awesomeness of vaccines and the like found in any paper that dares to publish even the most anodyne of criticisms of the golden jabs.

The lunacy of such a sentiment is belied only by the impracticality of doing anything about it. To use the incredibly limited and valuable logistical infrastructure of backwards war-torn countries for covid vaccines means displacing much more necessary things, like food or antibiotics. (Don’t get me wrong, I’m all for the CDC sending a team of their top “experts” into South Sudan or Haiti to vaccinate the warring tribes or roving gangs, especially because of the distinct possibility of them being eaten, which would provide a real-world experiment of sorts for what happens when you vaccinate the food.)

23. Association Between Pfizer COVID-19 Vaccine Adverse Effects and Diabetes Mellitus: A Prospective Multicenter Study

https://pubmed.ncbi.nlm.nih.gov/38054118/

This study is officially comparing the rates of various side effects in diabetic vs non diabetic people, which seems to be missing the more important point that in both groups the rates of various nasty vaccine injuries were off the charts.

The rates for every listed side effect here are off the charts, so I only highlighted Shortness of Breath & Chest Pain, which are proxies for cardiovascular problems.

(Note: the p-values in the tables below are for differentiating diabetic vaccine recipients from non-diabetic vaccine recipients, not the association of the side effect with the vaccine.)

Dose 1:

Dose 2:

24. A Study to Describe the Pattern of Cutaneous Adverse Effects of COVID-19 Vaccines (Covishield and Covaxin)

https://pubmed.ncbi.nlm.nih.gov/38099027/

“In our study, a total of 12,196 (62%) jabs of Covishield vaccine were administered and 7,476 (38%) were given Covaxin jabs constituting 19,672 total vaccine administrations. A total of 296 (1.5%) patients developed cutaneous adverse effects to COVID-19 vaccines.”

25. NEURO-COVAX: An Italian Population-Based Study of Neurological Complications after COVID-19 Vaccinations

https://pubmed.ncbi.nlm.nih.gov/37897023/

“It is noteworthy that about a third of our sample developed manifestations after COVID-19 vaccinations (so-called symptomatic group).”

“Results: The NEURO-COVAX-cohort included 19.108 vaccinated people: 15.368 with BNT162b2, 2077 with mRNA-1273, 1651 with ChAdOx1nCov-19, and 12 with Ad26.COV2.S who were subsequently excluded. Approximately 31.2% of our sample developed post-vaccination neurological complications, particularly with ChAdOx1nCov-19. A vulnerable clinical profile emerged, where over 40% of the symptomatic people showed comorbidities in their clinical histories.”

Of note, we found novel neurological post-vaccination symptoms, which expanded the clinical spectrum related to COVID-19 vaccines. This could be mainly due to the different methods of investigation used.

This goes to show what you can find when you simply ask the right questions.

26. Side Effects of COVID-19 Vaccines in Pregnant and Lactating Mexican Women and Breastfed Infants: A Survey-Based Study

https://pubmed.ncbi.nlm.nih.gov/37631848/

27. COVID-19 Vaccine Impacts in Saudi Arabia: A Cross-Sectional Study

https://pubmed.ncbi.nlm.nih.gov/37456436/

Saudi Arabia comes through again with an epic survey for vaccine side effects (N= 492).

Highlights:

• 17.7% shortness of breath

• 31.7% hand/leg numbness

• 2.6% chest pain

Kicker:

6 vaccinees suffered **Heart Attacks**

In other words, a whopping 1.2% of all vaccinees had a heart attack in the months following vaccination.

28. Common Side Effects of Pfizer COVID-19 Vaccine: An Experience From Pakistan

https://pubmed.ncbi.nlm.nih.gov/37492805/

29. Safety of ChAdOx1 nCoV-19 vaccination in patients with end-stage renal disease on hemodialysis

https://pubmed.ncbi.nlm.nih.gov/36084024/

30. COVID-19 Vaccination Trends and Side Effects among Egyptian Hemodialysis Patients: A Multicenter Survey Study

https://pubmed.ncbi.nlm.nih.gov/37302919/

31. The Prevalence of Immediate Hypersensitivity Reactions to the BNT162b2 mRNA Vaccine against SARS-CoV-2: Data from the Vaccination Campaign in a Large Academic Hospital

https://pubmed.ncbi.nlm.nih.gov/37243007/

“We analyzed the responses of 3112 subjects subjected to the first dose of the vaccine; among these, 1.8% developed symptoms compatible with allergic reactions and 0.9% with clinical manifestations of possible anaphylaxis.”

32. BNT162b2 immunization-related myocarditis in adolescents and consequent hospitalization: Report from a medical center

https://pubmed.ncbi.nlm.nih.gov/37302919/

“681 children presented with discomfort after BNTI and visited our PER. The mean age was 15.1 ± 1.7 years. Three hundred and ninety-four (57.9%) and 287 (42.1%) events were after 1st and 2nd dose, respectively. 58.4% (n = 398) were male. The most common complaints were chest pain (46.7%) and chest tightness (27.0%). The median (interquartile range [IQR]) interval of discomfort after BNTI was 3.0 (1.0-12.0) days. BNTI-related pericarditis, myocarditis and myopericarditis were diagnosed in 15 (2.2%), 12 (1.8%) and 2 (0.3%) patients, respectively. Eleven (1.6%) needed hospitalization in PICU.”

This one is included because it offers a window into the true magnitude of vaccine injury prevalence.

33. Clinical Effects of BNT162b2 Vaccine on the Short-Term Course of Chronic Spontaneous Urticaria Patients

https://pubmed.ncbi.nlm.nih.gov/36998869/

“Among the 90 study participants, 14 (15.5%) experienced exacerbations in their urticarial activity after the first or repeated doses of BNT162b2 vaccinations. The demographic, clinical, and laboratory features were similar between the exacerbated and non-exacerbated CSU patients. However, the rate of adverse reactions within 48 hours, such as hives, injection site reactions and wheals lasting <1 hour, were significantly higher in group A than in group B”

34. Adverse Effects of Pfizer (BioNTech), Oxford-AstraZeneca (ChAdOx1 CoV-19), and Moderna COVID-19 Vaccines among the Adult Population in Saudi Arabia: A Cross-Sectional Study

https://pubmed.ncbi.nlm.nih.gov/36851109/

35. Safety, effectiveness and hesitancy of COVID-19 vaccination in children: A cross-sectional study in Pakistan

https://pubmed.ncbi.nlm.nih.gov/36733278/

12-18 year olds

36. A Study on the Self-Reported Physician-Diagnosed Cardiac Complications Post mRNA Vaccination in Saudi Arabia

https://pubmed.ncbi.nlm.nih.gov/38344510/

For more on this study, see here.

***********************************

1. Adverse drug reactions from two COVID-19 vaccines reported in Saudi Arabia

https://pubmed.ncbi.nlm.nih.gov/35095267

Highlights:

• 16.8% of Pfizer recipients, and 18.5% of AstraZeneca recipients, suffered neurological symptoms

• 1.5% of Pfizer, and 1.4% of AZ, suffered anxiety (the vaccines can cause psychosis and other alterations of mental/emotional state)

• 1.3% of Pfizer, and 0.9% of AZ, suffered heart palpitations (indicating likely cardiac damage of some sort)

• 7.2% of Pfizer, and 4,5% of AZ, suffered an allergic reaction

2. Side Effects of COVID-19 Pfizer-BioNTech mRNA Vaccine in Children Aged 12–18 Years in Saudi Arabia

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8621258/

Highlights:

• 18% of Pfizer recipients experienced shortness of breath and chest pain after dose 1

• 23% of Pfizer recipients experienced shortness of breath and chest pain after dose 2

• 5% of Pfizer recipients were hospitalized following dose 1

• 12% of Pfizer recipients were hospitalized following dose 2

Results: The study recruited a total of 965 eligible participants. Overall, 571 (60%) of the study participants reported at least one side effect following Pfizer-BioNTech (BNT162b2) mRNA vaccination. The most frequently reported side effects were pain or redness at the site of injection (90%), fatigue (67%), fever (59%), headache (55%), nausea or vomiting (21%), and chest pain and shortness of breath (20%). Joint or bone pain were reported less frequently among our participants (2%). Our data showed that more female participants reported side effects compared to male participants, with 52% and 48%, respectively. Side effects were more common after the second dose compared to the first dose in our study cohort.

3. BNT162b2 and ChAdOx1 SARS-CoV-2 Post-vaccination Side-Effects Among Saudi Vaccinees

https://pubmed.ncbi.nlm.nih.gov/34692740/

Highlights:

• 13.1% of females / 6.6% of males, experienced heart palpitations

• 11.6% females / 6.2% males, experienced chest pain

• 8.1% females / 5.2% males, experienced shortness of breath

• 21.1% of females / 17.4% of males, experienced “impaired concentration”

4. Evaluation of Short-Term Symptoms Associated With COVID-19 Vaccines Used Among Adolescents in Saudi Arabia

https://www.cureus.com/articles/114641-evaluation-of-short-term-symptoms-associated-with-covid-19-vaccines-used-among-adolescents-in-saudi-arabia

Highlights:

• 2.3% of vaccine recipients were hospitalized

Side effects reported after getting the COVID-19 vaccine

Among participants who experienced COVID-19 vaccination adverse reactions (54.9%, No.= 554), 87.5% had pain at the site of injection, 84.5% reported fatigue, 69% had a headache, 67.5% had a fever, 39.7% had chills, and 19.1% had nausea and vomiting (Figure 1). Other adverse effects had been recorded by the participants such as menstrual disturbance, lymph node enlargement, muscle and bone aches, runny nose, red eye, flu, and drowsiness. Of note, 75.6% of the participants reported using medications to avoid or mitigate vaccination side effects; however, about 9% of those participants had to visit the doctor after the onset of symptoms, and only 2.3% needed admission to the hospital because of the symptoms associated with the received vaccine. The vaccine side effects lasted from one to two days in 67.1%, three to five days in 25.8%, and more than five days in 7.0% of the participants (Table 3).

5. Study of the Side Effects of Pfizer and Oxford COVID-19 Vaccines in the Eastern Province of Saudi Arabia

https://pubmed.ncbi.nlm.nih.gov/36196371/

Highlights:

• Following Pfizer dose 1, 9.3% experienced irregular heartbeat; 7.3% chest pain; and 7.3% shortness of breath

• Following Pfizer Dose 2, 10.5% experienced irregular heartbeat; 6.9% chest pain; & 6.9% shortness of breath

6. Prevalence of side-effects associated with the booster dose of Pfizer-BioNTech (BNT162b2) of COVID-19 Vaccine among vaccinated adults in the Eastern province of Saudi Arabia

https://pubmed.ncbi.nlm.nih.gov/36276167/

Highlights:

Following a Pfizer booster:

• 0.81% reported myo/pericarditis (!!!) (which would have to be clinically diagnosed)

• 16% reported delayed menstruation

• 1.1% were hospitalized

Conclusions

Our study showed that participants in the Eastern province of Saudi Arabia receiving a booster dose of the Pfizer-BioNTech (BNT162b2) COVID-19 vaccine commonly experienced short-lived side effects, especially pain or redness at the infection site, but also fatigue, body pain, fever and headache. 2.4% of recipients had sought medical attention for their side effects, although only four participants (1.1%) were admitted to the hospital after experiencing side effects. Findings from this study support the vaccine's safety as well as provide important baseline data for healthcare workers and the general public to be aware of possible side effects following the COVID-19 vaccine. In light of the current study, its results support the vaccine's safety and provide important baseline data that will raise healthcare workers' and the general public's awareness of COVID-19 vaccine expected side-effects. In this way, vaccine-hesitant individuals and pessimists might be convinced to accept the COVID-19 booster dose.

The authors’ contentions of vaccine safety despite the alarming rate of SAE’s they themselves documented here is worth repeating:

7. Cognizance, adverse effects and motivation regarding COVID-19 vaccination amongst health care professionals: A cross-sectional study

https://dmp.umw.edu.pl/pdf/2022/59/1/13.pdf

Highlights:

• 4.4% experienced a fever that was ABOVE 104

8. Investigating trends in those who experience menstrual bleeding changes after SARS-CoV-2 vaccination

https://www.medrxiv.org/content/10.1101/2021.10.11.21264863v2

Highlights:

• 42% who had regular menstrual cycles experienced heavier bleeding

• 66% of post-menopausal people reported breakthrough bleeding (!!!!!)

• 71% of people on long-acting reversible contraceptives reported breakthrough bleeding

Abstract

Early in 2021, many people began sharing that they experienced unexpected menstrual bleeding after SARS-CoV-2 inoculation. We investigated this emerging phenomenon of changed menstrual bleeding patterns among a convenience sample of currently and formerly menstruating people using a web-based survey. In this sample, 42% of people with regular menstrual cycles bled more heavily than usual while 44% reported no change after being vaccinated. Among respondents who typically do not menstruate, 71% of people on long-acting reversible contraceptives, 39% of people on gender-affirming hormones, and 66% of post-menopausal people reported breakthrough bleeding. We found increased/breakthrough bleeding was significantly associated with age, systemic vaccine side effects (fever, fatigue), history of pregnancy or birth, and ethnicity. Generally, changes to menstrual bleeding are not uncommon nor dangerous, yet attention to these experiences is necessary to build trust in medicine.

9. Blood pressure increase after Pfizer/BioNTech SARS-CoV-2 vaccine

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8206586/

Highlights:

• Following Dose #1, 6.19% experienced tachycardia; 5.3% experienced a rise in blood pressure

• Following Dose #2, 2.65% experienced tachycardia; 1.8% experienced a rise in blood pressure

Adverse reactions occurred in 87% of subjects after the first dose and 83% after the second dose of vaccine. Most reactions were mild and none of the subjects discontinued normal daily activities. There was transitory loss of taste and smell in 1 subject. Body temperature >38.0 °C, tachycardia, or a rise in BP occurred in 13% and 27% of subjects after the first and second dose, respectively.

The subjects with documented infection by SARS-COV-2 over the previous year showed a higher frequency of systemic reactions to vaccine when compared with those without history of documented infection (38% vs 10%, p = 0.004).

Overall, 6 subjects (5.3%) showed an average rise in systolic or diastolic BP at home by ≥ 10 mmHg during the first 5 days after the first dose of vaccine when compared with the five days before the vaccine. Table 1 shows the main characteristics of these subjects. The BP rise required an intensification of BP-lowering treatment in 4 subjects. Two of the subjects with a BP rise after the first dose experienced a BP rise also after the second dose. Of note, history of COVID-19 was associated with a higher incidence of rise in BP when compared with subjects without previous exposure to SARS-CoV-2 (23% vs 3%, p = 0.002).

10. Israel Ministry of Health Pfizer Booster Survey

Hebrew: https://drive.google.com/file/d/1NyMrHRTO-SLvygWtPmA39QlgqCE_GbsP/view

English: https://t.me/MOHreport/9197

Highlights:

• 4.5% experienced a neurological side effect following a booster

• 3.4% experienced paresthesia

• 17.1% experienced shaking

• 5.5% experienced chest pain

11. Adverse reactions to the BNT162b2 and mRNA-1273 mRNA COVID-19 vaccines in Japan

https://pubmed.ncbi.nlm.nih.gov/35058126/

Highlights:

• 1% following Pfizer dose 1, and 1.6% following Pfizer dose 2, reported suffering from an adverse event not included in the survey questionnaire

• 3.6% following Moderna dose 1, and 4.2% following Moderna dose 2, reported suffering from an adverse event not included in the survey questionnaire

• Following Pfizer Dose 1, 2.4% suffered a skin rash; 39.9% suffered muscle or joint pain

• Following Pfizer Dose 2, 3.4% suffered a skin rash; 49.8% suffered muscle or joint pain

• Following Moderna Dose 1, 5.3% suffered a skin rash; 52.3% suffered muscle or joint pain

• Following Moderna Dose 1, 6.5% suffered a skin rash; 59.7% suffered muscle or joint pain

12. Adverse Events Following COVID-19 Vaccination in Rivers State, Nigeria: A Cross-Sectional Study

https://pubmed.ncbi.nlm.nih.gov/35488575/

Highlights:

• 3% were hospitalized following vaccination

• 1.5% suffered a life-threatening condition following vaccination

Results: In this study, 50.5% of respondents reported post-vaccination adverse events out of which 10 (4.6%) were severe (30% of the severe cases were life-threatening, 60% were hospitalised and 10% were placed on bed rest). The most common side effects were fever (73.0%), pain at the injection site (41.2%), fatigue (33.3%), body ache (17.5%) and headache (13.8%).

13. Adverse Reactions Following the First Dose of ChAdOx1 nCoV-19 Vaccine and BNT162b2 Vaccine for Healthcare Workers in South Korea

https://pubmed.ncbi.nlm.nih.gov/33942579/

Highlights:

• Following vaccination with AstraZeneca, 28.3% experienced heart palpitations; 18.1% hypertension; 18% hypotension; 17.1% paralysis; 18.6% paresthesia; 6.4% wheezing (shortness of breath); 6.3% chest pain

• Following Pfizer vaccination, 4.3% experienced heart palpitations; 3.6% hypertension; 3.6% hypotension; 36% paralysis; 4.3% paresthesia; 0.7% wheezing; 0.4% chest pain

14. Side effects of the Pfizer BioNTech vaccine in health workers of a hospital in the southeast of Mexico

https://pubmed.ncbi.nlm.nih.gov/36223615/

Highlights:

• 6.14% experienced cheat pain following vaccination

• 8.9% experienced hypertension following vaccination

15. Prevalence of severe adverse events among health professionals after receiving the first dose of the ChAdOx1 nCoV-19 coronavirus vaccine (Covishield) in Togo, March 2021

https://pubmed.ncbi.nlm.nih.gov/34819146/

Highlights:

• 13% of vaccine recipients were unable to go to work the next day following vaccination

• 7.52% went to the doctor

• 0.72% were hospitalized

Results

A total of 1,639 health professionals (70.2% male) with a median age of 32 (interquartile range: 27-40) were enrolled. At least one adverse event was reported among 71.6% of participants (95% CI = [69.3-73.8]). The most commonly reported adverse events were injection site pain (91.0%), asthenia (74.3%), headache (68.7%), soreness (55.0%), and fever (47.5%). An increased libido was also reported in 3.0% of participants. Of the participants who experienced adverse events, 18.2% were unable to go to work the day after vaccination, 10.5% consulted a medical doctor, and 1.0% were hospitalized. The SAEs’ prevalence was 23.8% (95% CI = [21.8-25.9]). Being <30 years (AOR = 5.54; p<0.001), or 30-49 years (AOR = 3.62; p<0.001) and being female (AOR = 1.97; p<0.001) were associated with SAEs.

16. Determining the Health Problems Experienced by Young Adults in Turkey, Who Received the COVID-19 Vaccine

https://pubmed.ncbi.nlm.nih.gov/36146604/

I wrote up a partial explanation of this study’s findings here.

Highlights:

Of 590 undergraduate university students surveyed:

• 2.7% of vaccine recipients were newly diagnosed with diabetes

• 10.52% of females suffered a menstrual issue severe enough to require medical intervention shortly after vaccination

17. Side Effects of mRNA-Based and Viral Vector-Based COVID-19 Vaccines among German Healthcare Workers

https://pubmed.ncbi.nlm.nih.gov/34439984/

Highlights:

• 12.4% suffered an oral injury following Pfizer vaccination; 37.6% following AZ

• 2.3% suffered paresthesia following Pfizer vaccination; 1.6% following AZ

• 3.7% of females suffered a Skin condition following Pfizer (compared to 0 males)

18. Menstrual cycle disturbances after COVID-19 vaccination

https://pubmed.ncbi.nlm.nih.gov/35796571/

Highlights:

• 42.93% of women reported irregular menstrual cycles post-vaccination

• 5.97% reported amenorrhea (missing their periods altogether)

• 26.08% reported longer duration of bleeding

• 31.36% reported decreased quality of life after vaccination

Post-vaccination changes: regularity

Overall, 94 women (51.08%) reported regular cycles after vaccination, 79 (42.93%) noted irregular cycles after vaccination (variation > 9 days), and 11 (5.97%) of them reported having amenorrhea after vaccination. The vaccine that most frequently affected cycle regularity was Pfizer and Sinovac; however, for the J&J/Janssen vaccine more women reported irregular cycles (n = 19) than normal (58% versus 42%).

Post-vaccination changes: duration

In relation to the duration of the menstrual cycle, 120 women (65.21%) mentioned a duration in normal ranges (<8 days), 26.08% (48) commented a prolongation of the cycle (>9 days), and only 16 women (8.69%) reported amenorrhea/absent.

Post-vaccination changes: volume

The volume variable was reported as abnormal by 127 women (69.02%), being heavy in 41.84% (n = 77), light in 20.65% (n = 38), and absent in 6.52% (n = 12). Overall, 30.97% (n = 57) of the women described the volume as normal. When discriminating by biologics, 17 women (9.23%) vaccinated with Pfizer reported light volume, while the others reported predominantly heavy cycles (J&J/Janssen n = 18, Sinovac n = 21, Moderna n = 9, others n = 7, AstraZeneca n = 6).

Affectation in the quality of life

Of the 950 women who answered the survey, 31.36% (n = 298) commented that their QoL was affected after vaccination. Likewise, of the 184 who reported alterations in their menstrual cycle, 55.97% (103) stated a deterioration in their QoL after having been vaccinated in all the standard indicators evaluated perception of wealthiness, physical and mental health, pain.

19. Side effects of BNT162b2 mRNA COVID-19 vaccine: A randomized, cross-sectional study with detailed self-reported symptoms from healthcare workers

https://pubmed.ncbi.nlm.nih.gov/33866000/

This study in particular shows it’s amazing what you can find out when you just ask - this is an impressive amount of individual side effects that you won’t find in almost any other survey or study of vaccine ‘safety’.

Furthermore, this is a survey of healthcare workers, who are better trained to be observant of, & be able to describe with technical precision, clinical changes or side effects that occur, lending more credence than merely surveying a bunch of random laypeople who are more easily confused, susceptible to suggestion, and less precise in their observations and recall of clinical symptoms.

Highlights:

• Psychological: 9.04% suffered dizziness after vaccination; 5.85% reported brain fog (!!!); 6.35% reported some form a euphoria following vaccination; 5.35% reported decreased sleep quality; 2.49% reported anxiety; 0.75% reported memory impairment

• Neurological: 4.86% reported tingling; 2.86% numbness; 2.49% vertigo; 0.62% paralysis / extreme weakness; 0.5% lack of physical coordination; 0.12% seizures; 1.99% tinnitus (!!); 0.5% visual blurring

• Cardiovascular: 4.36% reported heart palpitations; 1.12% chest pain; 0.87% changes in blood pressure; 1.99% shortness of breath; 0.25% wheezing

• 0.62% had to go the ER & 0.25% were hospitalized

20. Safety and side effect profile of Pfizer-BioNTech COVID-19 vaccination among healthcare workers: A tertiary hospital experience in Singapore

https://pubmed.ncbi.nlm.nih.gov/34625758/

Highlights:

• 2.5% suffered chest pain, palpitations or shortness of breath following dose 1

• 3.9% suffered chest pain, palpitations or shortness of breath following dose 2

• 2.5% suffered a skin condition following dose 1

• 5.3% suffered a skin condition following dose 2

• 5.9% suffered an injury not specified in the survey following dose 1

• 8.2% suffered an injury not specified in the survey following dose 2

21. Side Effects and Perceptions Following COVID-19 Vaccination in Jordan: A Randomized, Cross-Sectional Study Implementing Machine Learning for Predicting Severity of Side Effects

https://pubmed.ncbi.nlm.nih.gov/34073382/

Highlights:

• 25.2% suffered cold, numbness or tingling

• 13.96% suffered irregular heartbeat

• 13.51% suffered a vision impairment

• 12.47% suffered chest pain

• 8.94% suffered abnormal blood pressure

Background

1. This is only including formal academic literature.

2. Obviously, there are a number of technical qualifiers that are relevant to properly parse any study individually. They are not of uniform quality and have widely ranging characteristics. Therefore, one cannot simply run with the topline numbers presented for any individual study and assume that they are definitive proof or statistically accurate by themselves.

   However, they are reporting much higher rates of SAE’s then is claimed by the mainstream narrative. (Most severe adverse events will not show up for a few reasons, such as that they are not solicited; people with severe injuries are usually incapacitated and unable to participate in surveys; and the failure or refusal to diagnose severe injuries, among others.)

3. I am hoping to write future posts to unpack some of these surveys individually, because there is a lot to say about many of them that cannot be included in a massive compilation for brevity’s sake. I did try and highlight the most relevant bits of information from each.

4. The rate of so-called ‘routine’ side effects (systemic and local) are themselves off the charts - regular medicines and vaccines do not cause anywhere near this degree of unpleasant reactions.

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COVID-19 Vaccine Cardiac Complications: A Case Series on Implications of Marijuana in Adolescents With Myopericarditis

https://pubmed.ncbi.nlm.nih.gov/35663665/

Case Presentation:

An 18-year-old previously healthy male with a past medical history of asthma presented to the emergency room for a sudden onset of chest pain. The chest pain started 30 minutes before arrival while he was vaping marijuana. He reported using increasing amounts of cannabis and vaping in the preceding few days.

Urine toxicology reports revealed marijuana was positive, and SARS-CoV-2 polymerase chain reaction (PCR) was negative. He had received his Pfizer COVID-19 vaccination two months prior to the presentation.

(Despite the implication of the title, only one of the two patients was noted for marijuana use.)

There are three significant dimensions of turpitude showcased by this case report:

• Failure of scientists and regulators to “do the science”

• Pathology of vaccine injuries - is drug use a risk factor or actively involved in the pathology of vaccine side effects?

• Epidemiological implications of contaminated data - were deaths or injuries misattributed to drug OD’s?

1. Is drug use a risk factor for vaccine injuries?

This case report suggests a possibility that recreational drugs might adversely interact with the covid vaccines. Though the authors hypothesize that the myocarditis might be exclusively attributable to the marijuana, it is irrelevant. While their suppositions might have been honestly conceived, speculative claims in an evidentiary vacuum, even unchallenged by contraindicating data hardly constitute formidable evidence. Were expert opinion a viable standard to adjudicate safety concerns, the FDA could be retired in the face of the ubiquitous claims of implausibility for unexpected adverse effects to occur prophesized for every novel product introduced to the market. Regrettably, experts seldom recognize the limits of their expertise, and vis-à-vis covid seem unaware that any exist altogether (and in the case of the FDA ought be retired regardless for incorrigible moral corruption).

It must be noted that myocarditis has been associated with marijuana use before, such as the following examples:

The authors report an 11-month-old male who, following cannabis exposure, presented with central nervous system depression after seizure, and progressed to cardiac arrest and died. Myocarditis was diagnosed post-mortem and cannabis exposure was confirmed. Given the temporal relationship of these two rare occurrences - cannabis exposure and sudden death secondary to myocarditis in an 11-month-old - as well as histological consistency with drug-induced myocarditis without confirmed alternate causes, and prior reported cases of cannabis-associated myocarditis, a possible relationship exists between cannabis exposure in this child and myocarditis leading to death.

Myocarditis has also been associated with other recreational drugs besides marijuana, such as cocaine:

In a series of 40 autopsies with cocaine-associated deaths, Virmani et al. (1988) demonstrated that myocarditis with mononuclear infiltrate was nearly 10 times more common than acute thrombotic coronary occlusion. This case illustrates such presentation of acute cocaine-induced myocarditis with aggressive myocardial necrosis and unfavourable cardiac remodelling clearly demonstrated by serial CMR studies. In the absence of coronary artery disease, the CMR study should be considered in symptomatic patients following acute cocaine use and positive biomarkers to assess the extent of myocardial injury that could be prognostically important.

However, even granting that recreational drug use can by itself instigate myocarditis, common sense cautions that exposure to multiple myocarditis antagonists might compound the risk for subsequently developing myocarditis or increase the severity in patients who subsequently develop myocarditis. It is certainly plausible that there might be unique adverse pathological potential posed by the combination of recreational drugs and the mRNA vaccines.

Moreover, the risks are not limited to myocarditis. Various recreational drugs have been associated with other toxicities that might be triggered or aggrandized in the setting of concomitant exposure to a covid vaccine. We also don’t know what we don’t know, and there is probably a vast expanse of vaccine pathogenicity we have yet to explore.

Ultimately, absent more data it is difficult to draw firm conclusions from a solitary case report, but there is undeniably mechanistic plausibility for potential toxic drug interactions between recreational drugs and the genetic covid vaccines.

Which brings us to our next point:

2. Failure of The SCIENCE™️

When releasing a new medical product onto the market for public use, it is insufficient to only test it on physically fit people who live a healthy lifestyle or in sterile laboratory conditions. If you don’t study potential interactions of environmental effects of personal behavior on a novel drug, you won’t know if there are any, unless you boldly charge forth and release it anyways. As the chief editor of the NEJM put it during the Vaccines and Related Biological Products Advisory Committee meeting to approve the covid vaccines for children, “we’re never going to learn about how safe this vaccine is unless we start giving it.” (Points for honesty at least.)

It is common knowledge that a substantial portion of the US population - especially younger people - are drug users, particularly of marijuana which has become a common and easily accessible amenity in society today. According to a Gallup poll in 2022, nearly half of all Americans have tried marijuana, and 16% are “smoke marijuana” - i.e. use marijuana with some degree of regularity:

Frequent marijuana use is notable concentrated in young adults (and presumably to a similar extent in teenagers who are not included in this survey):

Forgoing testing to discover potential toxic interactions of marijuana with the covid vaccines constitutes dereliction sufficiently egregious to disqualify everyone embroiled or responsible from any further involvement in trialing or interrogating medical product.

Some readers are probably thinking - or feeling exasperated - “they are far more evil, and did much worse deliberately, than merely failing to conduct proper science and regulatory oversight, so why are you .” The reason I am highlighting this is twofold:

1. There is still a not-insignificant group of people who are not exactly disposed to our side, but are susceptible to an argument that relies on one of their own self-professed premises, in our case that “they didn’t follow fundamental scientific protocols”.

2. As a moral concept, a murderer does not get a free pass for shoplifting a $20 trinket (legal system nonchalance notwithstanding). The failure to do proper science is a distinct crime apart from the active and deliberate evils inflicted by the establishment et al (and might well prove to be easier as a practical matter to hold them accountable for at some point).

3. Epidemiological implications of recreational drugs predisposing to vaccine injuries

The drug overdose crisis in America is one of the foremost political issues today. The number of deaths attributed to OD’s has skyrocketed over the past few years. But what if some % of the increase in ostensible OD deaths from 2021 onwards actually resulted from the lethal combination of covid vaccines and recreational drugs?

There is already some evidence to suggest that this might well be the case. One of the preeminent data geniuses of the covid era - - has been suggesting for a while that over-attributing deaths to OD’s has helped to conceal the true scope of the increase in ‘unexpected’ or ‘sudden’ deaths (#3):

If recreational drugs could trigger or exacerbate vaccine injuries, then doctors would be expected to organically attribute the death to the drug use in cases where recent drug use was noted - most doctors wouldn't dream to conceive that there might be a universe where there was the faintest possibility of adverse drug - vaccine interaction, and would therefore chalk it up to OD without any malicious intent.

I asked Ethical Skeptic about this hypothesis and he agreed, noting that “doctors are sincerely attributing vaccine deaths to overdose - because they are ill equipped to detect the difference. Until we advocate for the CDC to change the diagnostic protocol - these deaths will be inflated.”

Another observation made by Ethical Skeptic was that the number of US deaths attributed to unspecified or unidentified drug OD - i.e. where the specific drug was not indicated meaning there is a lack of clarity about the role of drug use in the death - has been markedly elevated since around March of 2021 (2020 saw a noticeable spike coinciding with the advent of lockdowns that mostly receded prior to the resurgence in 2021). ES provided an annotated chart to illustrate along with the following explanation:

These excess deaths might represent what essentially amounts to people ‘dying with’ drug usage where the doctor filling out the death certificate figured something like “well it says here that he used recreational drugs, and now he’s dead [possibly killed by a condition that could be caused by drug use], so probably an OD”.

This is not limited to mortality data. It follows that the same misattribution of deaths to drug OD would occur in morbidity data as well - doctors are equally liable to misattribute a vaccine condition to drug OD for live patients as they are for dead patients.

Either way, it must be acknowledged that at minimum there is a potential hazard of contaminated drug OD data (in addition to the other myriad taints in the morbidity and mortality datasets).

Since so little is known about the potential for toxic interaction between recreational drugs like marijuana and the covid vaccines, we are left groping about in the dark until the necessary studies and data accumulate that can resolve this issue. In the meantime, the ramifications for people who are vaccinated, and clinicians treating patients with conditions presumptively attributed to either drug use or vaccines remain quite real.

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“Prenatal Exposure to COVID-19 mRNA Vaccine BNT162b2 Induces Autism-Like Behaviors in Male Neonatal Rats: Insights into WNT and BDNF Signaling Perturbations”

https://pubmed.ncbi.nlm.nih.gov/38198049/

I suppose it was only a matter of time before we finally got a study potentially linking autism to the mRNA jabs.

The potential significance of such findings speak for themselves.

For some reason, Turkey seems to be uniquely willing to do the sort of blunt studies that are persona non grata in Western academia.

Also, the name of the study’s lead author is Erdogan:

Short Summary

The study found significant differences between rats born to mothers vaccinated during pregnancy versus a control group of rats born to unvaccinated mothers in the following areas:

• Motor coordination & balance (males)

• Social behavior (males)

• Quantity of Purkinje cells and other neural cells (males)

• Brain-derived neurotrophic factor (BDNF) protein levels (males & females)

• m-TOR & WNT gene expression levels (males & females)

Long Version

The objective and design of a study determines the nature of your results - you won’t find what you don’t look for. This study immediately stands out for its straightforward and honest inquiry to determine if the Pfizer vaccine might be affecting the neurodevelopment during gestation in rats vaccinated during pregnancy:

“This study aimed to investigate the gene expression of WNT, brain-derived neurotrophic factor (BDNF) levels, specific cytokines, m-TOR expression, neuropathology, and autism-related neurobehavioral outcomes in a rat model.”

There’s a Talmudic aphorism, “the question of a wise man is half the answer.” Ask good questions, get good results:

“Our findings reveal that the mRNA BNT162b2 vaccine significantly alters WNT gene expression and BDNF levels in both male and female rats, suggesting a profound impact on key neurodevelopmental pathways.

Notably, male rats exhibited pronounced autism-like behaviors, characterized by a marked reduction in social interaction and repetitive patterns of behavior.

Furthermore, there was a substantial decrease in neuronal counts in critical brain regions, indicating potential neurodegeneration or altered neurodevelopment.

Male rats also demonstrated impaired motor performance, evidenced by reduced coordination and agility.”

There are a number of fascinating details to unpack here. (For the academically adventurous, this study is written with an organized structure and in accessible English.)

Behavioral / Clinical differences

The study performed four behavioral tests, of which #’s 1 & 4 showed meaningful differences between the vaccinated and unvaccinated male rats:

1) ‘Three-Chamber Sociability and Social Novelty Test’

This test gauged the rats’ inclination to socialize. It is a bit long-winded to explain in detail, but the basic setup is that each rat was placed between two chambers, one with a ‘stranger’ rat and the other either without any rat or with a ‘familiar’ rat, with the amount of time the rat spent in each as the measured variable.

2) ‘Open Field Test’

Rats were placed in a closed enclosure for five minutes and monitored to see how much it wandered around or explored.

3) ‘Novelty-Induced Rearing Behavior’

Similar to the open field test, rats were placed in a transparent cage they had never been placed in before (a “novel” experience for the rats) and monitored to see how many times “the creature stood erect on its hind limbs, leaned against the enclosure walls using its forelimbs, or a combination of both”.

4) ‘Rotarod test’

This is a standard test used to assess physical coordination of rats and mice:

Significant Behavioral Differences

Vaccinated male rats were significantly less sociable than unvaccinated male rats or both vaccinated and unvaccinated female rats:

In the Rotarod test, they observed that the vaccinated male rats performed significantly worse - i.e. they were unable to maintain their balance on the wheel as long - compared to both the unvaccinated male rats and the vaccinated female rats.

As described by the study, “motor performance was significantly affected in a sex-dependent manner in the vaccinated group.”

Histological Differences

Unlike the behavioral tests, the study documented significant differences in vaccinated female rats for some of the histological parameters they looked at.

Brain-derived neurotrophic factor (BDNF) levels

BDNF is a protein that “plays an important role in neuronal survival and growth, serves as a neurotransmitter modulator, and participates in neuronal plasticity, which is essential for learning and memory.”

The study found that levels of BDNF were significantly lower (seen by the large discrepancy between the numerical measurements) in both the male and female vaccinated rats compared to the unvaccinated rats:

Quantity of neural cells

Purkinje cells “have a vital role in motor movement and coordination, spatial memory and learning, and even certain cognitive behavior.”

The authors observed a significant decrease in the quantity of neuronal counts and Purkinje cells (a type of nervous cell) in vaccinates male rats but not female rats:

This fits with the observed differences in motor coordination of the vaccinated male rats but not the vaccinated female rats.

They also found “dysmorphological changes” - i.e. abnormalities - in the tissues of the brain regions they sampled for counting these neural cells in the vaccinated male rats but not the vaccinated female rats.

Gene expression

m-TOR is a gene that encodes for the m-TOR protein, which “coordinates eukaryotic cell growth and metabolism with environmental inputs including nutrients and growth factors”.

WNT is a gene that encodes for the WNT protein, which are “secreted, lipid-modified glycoproteins that allow for communication between cells. They regulate cell growth, function, differentiation, and cell death. WNT proteins play a central role in bone development, modeling, and remodeling.”

Quantification of gene expression is overly wonky and technical, so we’ll just present the topline results.

In vaccinated male rats, in one of the methods they used to quantify gene expression, they observed a significant increase in the expression of the m-TOR gene and a significant decrease in the expression of the WNT gene compared to unvaccinated male rats.

In vaccinated female rats, in one of the methods they used to quantify gene expression, they observed a significant decrease in expression of the WNT gene. They also observed a non-significant increase in expression of the m-TOR gene for the vaccinated female rats.

Significance of the findings

You don’t need to be a rocket scientist to appreciate that significant differences in behavior or in the expression of critical genes in fetal development can manifest as or indicate significant clinical conditions. It is equally obvious that this study - and others like it - are a clarion call for further *honest and open* research into these issues, even - especially - for people who still believe in the mainstream narrative about the covid vaccines.

The authors do provide us with a more in-depth explanation of what their findings might portend, written in fairly readable English:

The COVID-19 mRNA vaccine seems to induce autism-like behaviors in male rats, impacting the WNT and BDNF pathways in both genders [2]. This gender-specific outcome emphasizes questions on the vaccine’s influence on brain function and structure. There’s a notable higher prevalence of ASD [Autism Spectrum Disorder] in males than females, pointing to innate biological factors affecting the manifestation of neurodevelopmental disorders differently between sexes [28].

In our study, vaccinated groups showed no detectable inflammation markers, leading to speculations. One possibility is the timing of vaccination during pregnancy, implying the inflammatory effects might have waned by the 50th day [1]. Prior research, such as Smith et al. (2018) and Jones et al. (2020), suggests transient inflammatory responses post-vaccination, which return to baseline in a few weeks [29, 30]. This aligns with our observations, hinting that pregnancy-related vaccination inflammation might be short-lived.

On the other hand, the vaccine might prompt neuronal apoptosis [cell death by “suicide”] without evoking notable inflammation. Even though we didn’t utilize apoptotic staining, apoptosis might have taken place and concluded during pregnancy. Apoptosis maintains the central nervous system's normalcy [31]. Previous work, like Wang et al. (2015) and Zhang et al. (2018), found certain vaccines could induce neuronal apoptosis in animal models [32, 33]. This raises the possibility of mRNA vaccines having similar effects. Nevertheless, the complexity of apoptosis demands deeper research to grasp the nuances of vaccine-triggered apoptosis.

Both genetic and hormonal elements play roles in these sex differences. Several studies have pinpointed sex-specific genetic variants linked to ASD, with particular genes on the X and Y chromosomes potentially causing a higher male prevalence [34]. The brain also exhibits sex-specific gene expression patterns and epigenetic changes, underlining the significance of sex chromosomes in brain function and growth.

Additionally, sex hormones like testosterone and estrogen significantly impact brain development. While prenatal testosterone exposure can elevate the risk of neurodevelopmental issues, estrogen might offer protection [35]. The interplay between hormones and genetic predisposition shapes the gender-based differences observed in neurodevelopmental outcomes.

Environmental factors, including prenatal stress, maternal immune activation, and chemical exposures, can interact with genetic and hormonal elements, leading to gender-specific susceptibilities in neurodevelopmental disorders. These environmental influences might differently impact males and females due to their interaction with genetic determinants, causing varying results.

Several studies shed light on how viral infections and vaccines affect the central nervous system. Bohmwald et al. (2022) highlight the importance of neurotrophins in the CNS function, with viral infections impairing their signaling [36]. Azoulay et al. (2020) underscore BDNF's role during recovery from SARS-CoV-2 infection [37], while Demir et al. (2022) delve into COVID-19’s prolonged cognitive effects and the possible involvement of BDNF [38]. These researches frame the wider implications of viral infections and vaccines on neurotrophic factors and cognitive outcomes.

Existing literature also reinforces the WNT pathway's significance in neurodevelopmental disorders. Bocchi et al. (2017) show how disrupted WNT signaling results in various neural impairments [39]. Cho et al. (2018) relate the PI3K-Akt-Wnt pathway to improvements in short-term memory after exercise [40]. Mulligan and Cheyette (2012) overview WNT signaling’s importance in vertebrate neural processes [41]. Lastly, Yi et al. (2012) illustrate the close relationship between BDNF expression and the WNT signaling pathway [42].

Research on autism spectrum disorder (ASD) provides insights into potential underlying mechanisms. Ma et al. (2023) studied the effects of reduced BDNF signaling on autism-like behaviors in mice [28]. Krumm et al. (2014) highlighted the intricate genetic aspects of ASD [43], and Dong et al. (2016) discussed the significance of the WNT pathway, particularly CTNNB1, in autism-related behaviors [44].

These studies underscore the importance of the WNT pathway and BDNF signaling in neurodevelopmental disorders, especially in light of observed autism-like behaviors in male rats post-COVID-19 mRNA vaccination. The reported reduction in neuronal counts in these male rats suggests possible vaccine-induced structural brain changes [36, 41, 45, 46].

However, drawing conclusions from animal models has its limitations, and human studies are essential to confirm these findings. Long-term studies on the effects of COVID-19 vaccination on neurodevelopment, especially considering potential gender differences, are needed [36].

The literature underscores the significance of neurotrophins and the WNT pathway in neurodevelopmental disorders and how viral infections affect the CNS. Bohmwald et al. (2022) and Azoulay et al. (2020) highlight neurotrophin signaling disruptions during viral infections like SARS-CoV-2 [36, 37]. Demir et al. (2022) link potential prolonged cognitive effects of COVID-19 to BDNF [38], emphasizing neurotrophins’ pivotal role in neurodevelopment.

The WNT pathway’s importance in neurodevelopment is evident. Bocchi et al. (2017) show that disrupted WNT signaling leads to neuronal migration issues and social behavior deficits [39]. Cho et al. (2018) connect the PI3K-Akt-Wnt pathway to exercise-induced memory enhancements [40]. Mulligan and Cheyette (2012) and Yi et al. (2012) delve into WNT signaling's crucial role in neural development and its interplay with BDNF [41, 42]. Such findings suggest that WNT pathway dysregulation might be linked to the behavioral changes seen in vaccinated male rats.

Research on ASD offers insights into mechanisms behind observed effects. Ma et al. (2023) emphasize BDNF's role in ASD through its impact on autism-like behaviors [28]. Krumm et al. (2014) detail ASD's intricate genetic factors [43, 47], while Dong et al. (2016) pinpoint CTNNB1, a WNT pathway component, in autism-related behaviors, reinforcing the WNT-ASD connection [44]. These studies enhance our comprehension of the molecular intricacies of neurodevelopmental disorders, particularly concerning the effects observed in vaccinated male rats.

Conclusion

In conclusion, our study presents evidence that the COVID-19 mRNA BNT162b2 vaccine impacts the WNT pathway and BDNF levels in rats, with particularly pronounced effects observed in males. These male-specific outcomes, including autism-like behaviors, reduced neuronal counts, and impaired motor performance, emphasize the potential neurodevelopmental implications of the vaccine, aligning with existing literature on the roles of the WNT pathway and BDNF signaling in neurodevelopmental disorder

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Mechanistic foundation for the hypothesis

One of the facets of this study I appreciated was that it presented a bold (by mainstream literature standards), well-reasoned hypothesis for a species of harm caused by the genetic covid vaccines.

A sound hypothesis rationally extrapolates from what we already know or observe, something that is sorely absent from the mainstream literature when it comes to the covid vaccines. Even case reports of covid vaccine injuries sometimes obscure instead of flesh out the potential pathological link between the vaccine and the subsequent injury.

In contrast, the authors of this study begin by explaining why it is logical to suspect the spike protein produced by the genetic covid vaccines could cause or lead to neurological damage1:

“Notwithstanding, apprehensions have been expressed about the plausible effects of the spike protein and its resultant immune response on the central nervous system (CNS). There are theoretical postulates suggesting that the biosynthesis of the spike protein, either through natural viral infection or post-vaccination, could induce neuroinflammation and elicit alterations in synaptic plasticity [5, 6]. These proposed changes might exert effects on brain development and have potential contributions to neurodevelopmental disorders, including autism [7].

Neuroinflammation, typified by the activation of CNS-resident immune cells and the subsequent release of pro-inflammatory cytokines, has been implicated in a gamut of neurodegenerative and psychiatric disorders [8, 9]. Various studies have demonstrated that viral infections, encompassing those triggered by the Coronaviridae family, can initiate a neuroinflammatory response [10]. The spike protein, owing to its interface with the ACE2 receptor, might cross the blood–brain barrier or indirectly induce neuroinflammation through peripheral immune signaling [11, 12].

In addition, there is burgeoning evidence suggesting that perturbations in synaptic plasticity—the inherent ability of synapses to strengthen or weaken over time in response to increases or decreases in their activity—may be implicated in neurodevelopmental disorders [13]. Preliminary preclinical research investigating the potential effects of the spike protein on synaptic function has delineated possible disruptions in neuronal connectivity and synaptic transmission [14, 15].”

The following two studies - ‘studies’ - perfectly illustrate the limitless intellectual and moral depravity that has taken root in academia. These papers highlight the two types of ideological or scientific derangement afflicting academia - the first showcases intellectually vapid nonsense masquerading as scientific erudition, the second highlights the blatant moral wickedness of modern-day woke ideology in academic institutions.

At the bottom is an additional 31 published studies in the medical literature demonstrating the subjugation of medical science to CRT/DEI/Woke precepts, showcasing how even the “hard science” medical domains have been conquered by the woke parasite. This is particularly relevant in light of the pandemic policy atrocities perpetrated by the fruits of the medical schools and institutions.

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1. Glaciers, gender, and science: A feminist glaciology framework for global environmental change research

https://journals.sagepub.com/doi/abs/10.1177/0309132515623368

This exegetical work of modern art from the University of Oregon by Mark Carey, M. Jackson, Alessandro Antonello and Jaclyn Rushing is probably the looniest [real] paper I have ever seen, which is definitely saying something. Funded in part by your taxpayer dollars of course.

⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐

YOU ARE ENTERING THE TWILIGHT ZONE

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Abstract

We’ll begin with the abstract which does a pretty good job succinctly summarizing the content of this study:

This gibberish is indecipherable even to seasoned academics, who are unlikely to make it past the second sentence where they encounter phrases like “the relationships among gender, science, and glaciers”, or “epistemological questions about the production of glaciological knowledge”, the scientific meaning of which are challenging to comprehend.

The authors then turn to the study’s raison d'être, a proposed “feminist glaciology” framework with four tenets that will fundamentally reset the epistemology of ice studies.

The most charitable reaction to this sentence is that at least we know what they mean to convey by “knowledge producers” - more “diversity” in glaciology.

Gendered science, on the other hand, oh boy. “gendered science”. what even is “gendered science”? Is gendered science a distinct concept apart from “feminist glaciology”? Good questions.

Later we come across what appears to be the mission statement of this incoherent academic albatross:

“Merging feminist postcolonial science studies and feminist political ecology, the feminist glaciology framework generates robust analysis of gender, power, and epistemologies in dynamic social-ecological systems, thereby leading to more just and equitable science and human-ice interactions.”

“merging feminist postcolonial science studies and feminist political ecology” (there’s an oxymoron for you)

They are the literal incarnation of every mocking stereotype of woke professors.

Next question: How does a ‘feminist glaciology framework’ generate robust analysis (or any analysis for that matter) about gender, power or epistemologies? The nexus between the study of ice and novel modern political/social theories about intersectional identities and oppression seems nonexistent.

Moving from the merely absurd to the fantastical lunacy, we are informed that reimagining glaciology using this proposed feminist framework will lead to “more just and equitable science and human-ice interactions.”

Just reading that sentence costs you IQ points each time.

More ‘just’ or ‘equitable’ science = replacing objective truth and observation with objectively false assertions to support preferred political/social ideologies.

But what takes the cake is the more just and equitable “human-ice interactions.” Seriously, what the devil is this??? “human-ice interactions is Human-ice interactions are not a moral concept or action.

This paragraph can be said to be avant-garde in a way. Until now, we had the Turing Test to determine if a machine could imitate a human well enough that a human would not be able to discern if he was conversing with a machine or person. This unique scholarship is unambiguous proof that the converse is true as well: a human can imitate an algorithm to the point that it becomes difficult to distinguish whether the author is a human or an algorithm. Perhaps we can call this the “Carey-Jackson Test”. It brings to mind the hilarious but darkly true SCIgen program and Sokal Affair. Since these historical events offer some insight into the present intellectual decay in the academic world, let’s digress a bit to explore these comedic fiascoes:

SCIgen

SCIgen was a computer program that famously conjured up academic papers by cobbling together random scholastic-sounding sentences, wreaking havoc for some time on the “softer sciences” and extracting significant casualties from a variety of journals. The fallout was documented in a real paper published in the prestigious journal Nature titled ‘Publishers withdraw more than 120 gibberish papers’.

Yes, that’s *more* than *120* papers withdrawn because they were total gibberish (much like the ramblings of Fauci or Eric Feigl-Ding or famed Eugyppius “mentally vacant covid astrologer” Eric Topol).

So did this precipitate more careful peer review that involved at least one real person actually reading a submission before accepting it?

Nope. That would be too much work. Instead, they created a counter-AI designed to detect incoherent babbling - Springer and Université Joseph Fourier release SciDetect to discover fake scientific papers.

(Left unanswered was how a computer program would be able to effectively distinguish between the incoherent verbal diarrhea of woke professors and the incoherent verbal diarrhea of computer programs. But hey, at least they were nice enough to offer it free of charge to the broader scientific community.)

The Sokal Affair

We’ll just plagiarize from Wikipedia for this one:

In 1996, Sokal submitted an article to Social Text, an academic journal of postmodern cultural studies. The submission was an experiment to test the journal's intellectual rigor, specifically to investigate whether "a leading North American journal of cultural studies—whose editorial collective includes such luminaries as Fredric Jameson and Andrew Ross—[would] publish an article liberally salted with nonsense if (a) it sounded good and (b) it flattered the editors' ideological preconceptions."[2]

The article, "Transgressing the Boundaries: Towards a Transformative Hermeneutics of Quantum Gravity",[3] was published in the journal's spring/summer 1996 "Science Wars" issue. It proposed that quantum gravity is a social and linguistic construct. At that time, the journal did not practice academic peer review and it did not submit the article for outside expert review by a physicist.[4][5] Three weeks after its publication in May 1996, Sokal revealed in the magazine Lingua Franca that the article was a hoax.[2]

The hoax caused controversy about the scholarly merit of commentary on the physical sciences by those in the humanities; the influence of postmodern philosophy on social disciplines in general; and academic ethics, including whether Sokal was wrong to deceive the editors or readers of Social Text; and whether Social Text had abided by proper scientific ethics.

Yup, gravity is a social construct. Like gender. At least it’s internally consistent.

Main body of the study

Moving past the abstract, we find the following:

You have to marvel at their adroit linguistic gymnastics to frame the lack of politicization of glaciology - seemingly a straightforward and uncontroversial proposition - as a “perspective” which “appears consistently in public discourse”, as if science sticking to the science is somehow a novel or unexpected paradigm. After all, from a scientific perspective, ice is ice, nothing more.

Alas what follows is precisely what one would expect from woke luminaries:

🤣🤣🤣🤣🤣🤣🤣🤣🤣🤣🤣

So.

. . . . . . .

. . . . . . .

“asks if glaciers listen”

Yes, someone indeed did write a whole book, entitled - well, just see for yourself:

The rest of this emoting mumbo-jumbo attempting to insert the cultural significance of glaciers into the official scientific discourse, in order to expand the scientific knowledges of ice. Needless to say, there is no place in the scientific - i.e. empirical - study of ice for feelings about the big, beautiful and endangered glaciers.

Next comes this little tidbit:

Nüsser and Baghel (2014) also reject the ‘ice is just ice’ assertion. Glaciers, they argue, ‘have increasingly become contested and controversial objects of knowledge, susceptible to cultural framings as both dangerous and endangered landscapes’ (Nüsser and Baghel, 2014: 138).

So our esteemed titans of erudition here reject the assertion that “ice is just ice”. Really now. This is even more intellectually deranged than the growing number of genders expanding at a faster rate than the physical universe.

What do the authors mean by “susceptible to cultural framings”? That we need to incorporate indigenous people’s mythologies about glaciers into scientific knowledge, something to which they later refer to by way of “folk glaciologies”.

We can go on for dozens of pages cataloguing the numerous craters of delusion pockmarking this scholarly work like Swiss cheese.

Here are a few more highlights:

🙄🙄🙄🙄🙄🙄🙄🙄🙄🙄🙄🙄

I wonder how much of this paragraph was plagiarized - it’s just an ode to the transcendent wonders of wokeness applied to glaciology.

Here’s more:

More inverse-Turing test material this is.

And finally, we have…

*Folklore Is Science*

That’s right, we need to integrate *folklore* into science. Ya know, such as mythical “ice-gods” of indigenous worship.

This would make Orwell proud.

Another feature of this study that stands out is the sheer number of papers they cite to buttress various elements of crazed woke lunacy - it at least gives you a sense of just how far and deep woke anti-science has permeated and saturated [what used to be] actual scientific disciplines.

There’s lots more in this stupefying morass of intellectual luddism, but since it’s behind a paywall and I don’t want to run afoul of a copyright issue, we will leave it here.

2. On Having Whiteness

https://pubmed.ncbi.nlm.nih.gov/34039063/

For the second study, instead of the twilight zone, we are heading off to Reich-stan:

This study call to genocide written by one Donald Moss - a white guy, by the way - surely ranks as one of the most morally deranged papers written by modern academia.

In essence, what Moss is putting forth is that all White people intrinsically suffer from a clinical condition that makes them evil and oppressive. He even goes as far as to claim that this affliction is the central defining characteristic of “whiteness”. This is so eerily on point that I genuinely wonder if he is plagiarizing translated Nazi polemics and swapping out the identity of the Untermenschen.

Worse, it was actually published in the Journal of the American Psychoanalytic Association. So we at least know that JAPA is a load of demented psychobabble.

Ask yourself: just how rotten does the culture in academia have to be for an actual journal to publish these rabid deranged rantings of an unhinged lunatic? (Just imagine if someone tried to publish this sort of vile screed about “Jewishness” or “Blackness”...)

Let’s see a few more ‘treasures’ from Donald Moss:

This is the stuff of genocidal regimes, which is not an exaggeration. Dehumanization and portraying a group as a mortal peril to society are recognized as key steps toward the eventual perpetration of genocidal extermination. The Nazis are famous for getting this down to a science.

Even the babies are not safe from this ‘disease’:

And of course, it’s basically incurable:

Donald Moss is a repulsive Nazi wannabe and a demented evil sociopath, yet his racist screed was published nonetheless. This is a testament to the moral depravity that has infested academia that someone could write such a vile philippic masquerading as a ‘study’ in the first place and feel accepted by his peers for it. With educators like this person, it is not unsurprising that hordes of college & university students agree with Osama Bin Ladin’s objectives or overtly support terrorism like the Hamas 10/7 attack and are even willing to give money to the Taliban.

You also have to wonder how many other Donald Mosses are entombed within the halls of the Ivory Towers of academia. The state of campus culture surely means there are many others of the same mindset.

Conclusion

What I have marshalled here is but a drop in the ocean of academic activism and ideological capture of the Ivory fortresses of academia, including the medical fields, something manifest quite sharply throughout the pandemic. The same culture rot visible in the abovementioned papers has poisoned every level of every discipline of medicine and replaced the ancient medical ethos with an ideological perversion of healthcare that has no place in a civilized society.

One need look no farther than the subjects having to do with sexuality or lifestyle, where radical activists have succeeded in suppressing and censoring all scientific research in order to maintain the numerous fictions necessary to propping up their tangled and conflicting mess of incoherent and contradictory conceptual frameworks (something brilliantly demonstrated by Matt Walsh’s documentary “What is a Woman”).

Whether higher education is salvageable at this point is unclear. What is beyond doubt is the total systemic corruption and capture of the culture and institutions of higher education.

**************************

Here is a selection of 31 papers documenting CRT in the medical community, literature, and schools:

1. Making science and doing justice: The need to reframe research on racial inequities in oral health
pubmed.ncbi.nlm.nih.gov/33780174/

2. The Role of Emotion in Understanding Whiteness
pubmed.ncbi.nlm.nih.gov/33415593/

3. The effects of whiteness on the health of whites in the USA
pubmed.ncbi.nlm.nih.gov/28716453/

4. Racism and Kidney Health: Turning Equity Into a Reality
pubmed.ncbi.nlm.nih.gov/33639186/

5. Visions by Women in Molecular Imaging Network: Antiracism and Allyship in Action
pubmed.ncbi.nlm.nih.gov/33754293/

6. White dominance in nursing education: A target for anti-racist efforts
pubmed.ncbi.nlm.nih.gov/32881135/

7. Rooting Out White Supremacy and Implementing Antiracism in Nursing Education
pubmed.ncbi.nlm.nih.gov/33574169/

8. Achieving Health Equity Through Eradicating Structural Racism in the United States: A Call to Action for Nursing Leadership
pubmed.ncbi.nlm.nih.gov/33002309/

9. Diversity, Equity, and Inclusion in Nursing: The Pathway to Excellence Framework Alignment
pubmed.ncbi.nlm.nih.gov/34469389/

10. Transformative dissonant encounters: Opportunities for cultivating antiracism in White nursing students
pubmed.ncbi.nlm.nih.gov/34350660/

11. How to Be An Antiracist Hand Surgery Educator
pubmed.ncbi.nlm.nih.gov/33762091/

12. From Diversity and Inclusion to Antiracism in Medical Training Institutions
pubmed.ncbi.nlm.nih.gov/33637659/

13. Academic Medicine's Journey Toward Racial Equity Must Be Grounded in History: Recommendations for Becoming an Antiracist Academic Medical Center
pubmed.ncbi.nlm.nih.gov/34432719/

14. Approaching the COVID-19 Pandemic Response With a Health Equity Lens: A Framework for Academic Health Systems
pubmed.ncbi.nlm.nih.gov/34705750/

15. Understanding Racism as a Historical Trauma That Remains Today: Implications for the Nursing Profession
pubmed.ncbi.nlm.nih.gov/33574167/

16. Entrenched White Supremacy in Nursing Education Administrative Structures
pubmed.ncbi.nlm.nih.gov/33574166/

17. A Nurse Educator's Perspective About Institutional Racism and White Supremacy in Nursing Education
pubmed.ncbi.nlm.nih.gov/33574170/

18. Professionalism: The Wrong Tool to Solve the Right Problem?
pubmed.ncbi.nlm.nih.gov/32134778/

19. Student-Led Efforts to Advance Anti-Racist Medical Education
pubmed.ncbi.nlm.nih.gov/33711839/

20.The White/Black hierarchy institutionalizes White supremacy in nursing and nursing leadership in the United States
pubmed.ncbi.nlm.nih.gov/33867099/

21. The lived experience of teaching about race in cultural nursing education
pubmed.ncbi.nlm.nih.gov/24682320/