COVID Vaccines: In Search of All-Cause Mortality
Disclaimer: I am not a medical doctor and this is not medical advice. My goal is to empower you with information. I will not take a position on whether you should or should not get vaccinated. Please make this decision yourself, consulting sources you trust, including a caring health care professional.
The most important piece of data we need to evaluate the risk reward of the COVID vaccines is their effect on all-cause mortality. This is important because it is a simple number that summarizes all the different forms of mortality that could occur from COVID, from irrelevant causes, and from the vaccines, but it is especially important because it is subject to the least amount of manipulation and controversy. It can be difficult to agree whether someone died of COVID or with COVID. It can be difficult to agree whether someone died after they were vaccinated or because they were vaccinated. However, with few exceptions, it is not controversial at all whether someone died.
Where there is room for controversy, there is room for manipulation. The definition of dying with or of COVID and the criteria to determine whether someone died after or because of a vaccine can be shifted around by those in charge of the definitions. The definition of death, however, remains largely constant.
All-cause mortality would not be the be-all end-all of risk reward. One can be disabled from a vaccine or develop a long-term complication of COVID. More than mortality is important.
Simply knowing the average risk reward for a demographic group, moreover, doesn't create an objective instruction for what everyone in that demographic must do. Individuals may wish to know whether their genetics, lifestyle, or health status make them more likely to be hurt by COVID or the vaccine than other people in their demographic group. Each individual should have the right to make an informed choice about which risk they are more willing to tolerate.
Nevertheless, all-cause mortality should be the first and primary metric we look at. It is the simplest, most objective, and least manipulable summary statistic of risk reward.
And yet, it is almost nowhere reported.
In search of all-cause mortality, we will look today at two sources. The first is a paper from MMWR, the CDC journal, that came out at the end of October. The second is a data set from the Office of National Statistics in England that Alex Berenson posted about on November 20.
One thing we will see is that the English data appears transparent, whereas the CDC data appears obfuscatory. The English data is not that easy to interpret, but it at least appears to be complete. The CDC, simply put, appears to be hiding something.
Let's dig in.
The CDC Paper
The CDC Paper is published by authors who are mostly affiliated with Kaiser-Permanente. The data is from the Vaccine Safety Datalink (VSD) program, which is run as a collaboration between the CDC and various health care organizations. Most of the VSD sites providing the data from this paper were from the Kaiser-Permanente system, which explains the preponderance of authors affiliated with that organization.
There are two deeply strange things about this paper:
It reports non-COVID mortality, but doesn't report COVID mortality or all-cause mortality.
It compares mortality among those vaccinated to those who were not vaccinated for COVID but who did receive at least one flu shot in the last two years. It does not report the mortality among the general population of people not vaccinated against COVID.
They stated that “In this study, non–COVID-19 deaths were assessed because a protective effect of COVID-19 vaccination for COVID-19–related deaths was expected.”
It was expected, but is that what happened? Why aren't the COVID-19-related deaths reported?
Non-COVID mortality was 46% lower among those vaccinated with J&J, 69% lower among those vaccinated with Moderna, and 66% lower among those vaccinated with Pfizer, when compared to those who did not get vaccinated for COVID but did get vaccinated for the flu at least once in the last two years. Among those aged 12 to 17, however, the mortality rates were not significantly different.
Something looks fishy here.
Why did they use those vaccinated for the flu but not COVID as the control group?
They say it was “to ensure comparable health care-seeking behavior” among the two groups. Yet, this isn't a very good way of doing that. This study had 6.4 million people vaccinated for COVID and 4.6 million vaccinated against the flu but not COVID. How is their health care-seeking behavior similar? Is it because they are all eager to get vaccinated? If so, why did 4.6 million people so eager to get the flu vaccine spend an entire year avoiding the COVID vaccine?
When trying to explain why the mortality would be lower among those vaccinated against COVID, they write, “lower mortality risk after COVID-19 vaccination suggests substantial healthy vaccinee effects (i.e., vaccinated persons tend to be healthier than unvaccinated persons),” and “lower rates of non–COVID-19 mortality in vaccinated groups suggest that COVID-19 vaccinees are inherently healthier or engage in fewer risk behaviors.”
So in these two statements, they admit complete failure in using the flu vaccine “to ensure comparable health care-seeking behavior.” They, in fact, invoke confounding differences in health status or risk behaviors as the primary explanation of their key finding!
Wouldn't the natural thing here be to go back to the drawing board and simply present the mortality among the unvaccinated and throw the whole flu vaccine criterion out? Naturally one wonders if this bizarre criterion is causing the obvious distortion in the data.
What really smells rotten here, however, is the fact that they didn't report the total mortality rates in each group before making their flu vaccine adjustment. Whenever authors report data that is adjusted without reporting the underlying data from which the adjustment came, it is because they don't like how the underlying data look and they are hiding something.
This should always be assumed about every paper that leaves out the underlying, unadjusted data, on any topic.
These authors are hiding something, and I don't know what it is. I am currently working with a lawyer and a data expert with expertise in obtaining datasets like this to try to bring the underlying dataset to light.
The English Data
The English data appears to be much more transparent: it shows all deaths and death rates per 100,000 people in four age groups by vaccination status.
You can download the Excel file from that link, but you need to switch to the “table 4” sheet to find the all-cause mortality. I made all the graphs I show below myself, directly from the data in the file.
As Berenson pointed out out, all-cause mortality is almost twice as high among the fully vaccinated when limiting the analysis to those under the age of 60:
This was not true for the first 13 weeks of the year, but it became true thereafter.
One must keep in mind that this age range is very broad, and is likely confounded by the fact that older people within the group are more likely to get vaccinated and also more likely to die simply because they are older.
However, this is a terrifying signal, especially given what we know about youth being a risk factor for heart trouble. It is unconscionable that the UK would not make it an imminent priority to separate this data into more granular age groups before vaccinating any more young people.
In the over-60 crowd, mortality is lower among the vaccinated:
Nevertheless, the difference is most pronounced in the first three months of the year, and declines precipitously from its peak. This presumably reflects the wave of COVID deaths that occurred in the UK during the winter months at the beginning of this year.
However, we must also consider the waning efficacy of the vaccine over time, and the possibility that the vaccine itself is increasing mortality. That may mean that as COVID cases decline, far before they ever reach zero, the mortality from the vaccine could begin to rival or even exceed the mortality from COVID even in the over-60 crowd.
Indeed, the lines are almost converged in the 80+ crowd, where the ratio of deaths in unvaccinated to vaccinated had been as high as 51 and is now only 1.4.
To make this trend clearer, I graphed the ratios of vaccinated to unvaccinated deaths in each age group:
The wildly high ratio in the 80+ crowd at the beginning of the year makes it difficult to see the separation in the lines in more recent weeks. The next graph takes out the first three months to make the trend clearer:
Here, the solid red line represents 1.0. If the ratio is above this, death is higher among the unvaccinated. If the ratio is below this, death is higher among the vaccinated.
The blue line represents the under-60 crowd, in whom deaths have consistently been higher among the vaccinated for most of the year.
The other lines are all above the red line, which means deaths are higher among the unvaccinated in those over the age of 60, but those lines are all descending toward the red line and getting awful close to it.
Will they stay there?
Or will they cross below?
I don't know. I can't predict the future.
One response to this might be that the vaccines are wearing off, and we need boosters. Another might be that COVID has calmed down and they will shoot back up away from the red line during the next wave.
Those are both possible, yet it is also possible that the vaccines have their own mortality-producing effect that thus far has been hidden by their COVID mortality-reducing effect in those over 60, and that boosters will aggravate this effect. It is also possible that antibody-dependent enhancement becomes a risk after some period of time or with some number of boosters and that the protection against COVID mortality flips and joins forces with the hidden mortality-producing effect of the vaccine.
In other words, it is very possible that after a few more months the over-60 crowd could cross the red line and join the under-60 crowd, where the vaccinated have been consistently dying at a much higher rate.
The fact that this trend is dynamic and that it's going in the opposite direction we would want if we wanted the vaccines to net save lives into the future should give us pause.
This trend is fully supportive of the “but they've only been out for less than a year” crowd. It is reprehensible that someone over 60 should not have the right to look at this data and wonder where the lines will go by next year.
There are limitations to this data. It is not adjusted for comorbidities or for any other confounders. The under-60 group, especially, needs to be broken up into more granular age groups to make proper sense of it. Apart from the criterion of being fully vaccinated, the length of time between vaccination and death is not considered.
Above all, these data are not randomized. New data casts worry, in fact, over the death counts in the Pfizer trial. I will be writing about that tomorrow.
The Bottom Line
Here's the bottom line:
The CDC/Kaiser-Permanente data is obfuscatory. We should not tolerate this lack of transparency from CDC or from our health care organizations. I will be working hard to ensure the underlying data is released so we can find out the truth.
The English data appear transparent, but difficult to interpret. Under-60 folks are dying twice as often if vaccinated, but this might be because the older people in that group are more likely to be vaccinated and more likely to die. We need to demand the data for subgroups in that age bracket before anyone tells us we must vaccinate our children or we, at age 30, must be vaccinated to keep our job.
Older folks seemed to benefit a lot from the vaccines early on but that benefit seems to be disappearing. Whether it will turn net negative soon is anyone's guess, but everyone must have the right to consider that possibility for themselves when deciding whether to get vaccinated.
Please Support This Service
You can support this service by sharing my work with others to spread the word, and by purchasing one of my information products. The most popular are:
The Vitamins and Minerals 101 Cliff Notes
The COVID Guide (free with a paid subscription to my Substack)
Testing Nutritional Status: The Ultimate Cheat Sheet
Vitamins and Minerals 101: (pre-order the book and get the COVID guide for free)
There are many other ways to support this work, some at no extra cost to you, listed at chrismasterjohnphd.com/support.
I am currently devoting my analytical skills to critical questions around COVID risks, vaccine safety and efficacy, and the full spectrum of vaccine alternatives, due to the imminent massive job loss occurring as a result of vaccine mandates. If you would like to support me doing this work you can also make a donation in any amount using this button:
"This should always be assumed about every paper that leaves out the underlying, unadjusted data, on any topic."
This is a salient bias--data hiding bias.
There is also comparator bias--perhaps flu jabs increase mortality more than no flu jabs in the general population.
And healthy vaccinee bias, of course.
See Norman Fenton St Mary UK work on those data .. he explains the higher initial mortality in the unvaccinated as mis classification.. by adjusting it shows that there is higher initial all cause mortality in the vaccinated..