PROVEN RELATIONSHIP: COVID Boosters and Excess Mortality in 2022
29 Countries Show Strong Association between "Booster Uptake" and "Excess Mortality"
This article will show that there is a very strong statistically significant association between excess mortality in 2022, and uptake of COVID boosters.
The booster rate as of Jul 1 explains excess deaths in 2022, by country, using linear regression with R^2 = 40% and P-value an incredible 0.0002, giving this relationship ironclad statistical significance!
What is this about?
There is much discussion about excess mortality and elevated cancer rates in 2022. I also wrote about it recently (I am not Gammadion):
Ever since that article, I wanted to see if antivaxxers’ hunches about the cause of excess mortality are true. So, I set out to find data about mortality in many countries and see if I can match it with vaccination or booster uptake data.
Fortunately, I found data for both parameters. Mortality for the last several years, by week, is listed in the Short Term Mortality Database. That database has a CSV file that you can download. Booster and vaccine uptake are in Our World in Data, which I downloaded into a SQL database earlier.
Incidentally, I already used the OWID database to prove that boosters are strongly associated with COVID mortality in Europe. (deaths from Covid)
But what about excess total mortality, not just Covid mortality? This is where we will look today.
Short Term Mortality Database
After downloading the short term mortality data as a CSV file, I wrote a perl script to read the data and analyze it.
The script loads data for two periods: main_year, or 2022, and three base_years 2017 to 2019. The weeks selected for analysis are weeks 10 to 35. It adds, for each country, the subtotal of deaths for every week found, and counts the number of weeks found also (not all countries report exactly the same number of weeks). I had to exclude Australia, Luxembourg, Czechia, and South Korea due to not having enough data. (South Korea has a crazy 50% excess mortality, look it up)
Given what we have, we can compare “deaths per week” (deaths divided by count of weeks) for the 2022 period (main), as well as for 2017-2019 period (base), for the same weeks of the corresponding years. I call the ratio of “deaths per week” for these periods, MINUS ONE, the excess mortality.
NB: Note that this calculation is only a somewhat close approximation of excess mortality that official statisticians calculate because they also take into account small changes in population, etc. While these differences are important in order to do completely proper demographic calculations, they are minor enough to disregard for the purposes of my analysis, in my opinion. I do compare same weeks of all years, to take seasonality into account.
This gives us the “excess mortality” data for each given country.
Our World in Data — Booster Rate and Vaccination Rate
Our World in Data can give us the booster rate and vax rate per country. I can just query my SQL database like so:
Thus, from my OWID database, I get data about “booster per 100 as of Jul 1, 2022”, as well as “vaccination rate as of March 1, 2022”. Just a note, early booster data in OWID is lacking, so I chose booster rate as of Jul 1 just to have valid data to work with. Selecting a booster date late in the period does not, in any way, compromise the integrity of these findings. Quite the opposite, looking at the effect of booster rate close to the end of the period, captures the damage caused by boosters given during the period.
The compiled data, therefore, looks like this:
(Yes, Chile does have more boosters given out than people)
Relationship Between Boosters, Vaccines and Deaths
I then ran a “linear regression” to see if there is a relationship between booster uptake as of Jul 1 2022, and excess deaths in 2022. (things do not change much if I move the date, as long as there is good data as of that date).
The result was shocking!
It shows that booster uptake was extremely strongly (and positively) related to excess mortality, with P value being 0.0002. Mind you, anything with P below 0.05 is considered statistically significant — so P=0.0002 is ironclad.
Since most of my readers are not statisticians, let me explain. The graph above means that the more boosters are taken, the greater was excess mortality for the countries in the graph. The P=0.0002 means that this association is extremely unlikely to be a random coincidence.
More boosters — more deaths!
What is also greatly interesting is that the Y-intercept is so close to zero
Additionally, just one number per country — booster uptake as of a particular day Jul 1 2022 — explains 40% of the variation in excess mortality. This means that vaccination and boosters, likely, were an extremely important factor for every country’s excess mortality.
I ran the same regression for the vaccination rate by March 1. The result is principally the same, but slightly less impressive than for boosters on Jul 1. Still extremely strong statistical significance, but slightly less explanatory power called R-squared.
Disclaimers, Correlation, and Causation
None of the above would validate a simple-minded statement such as “I just proved that boosters make people croak and die”. That would NOT be a correct interpretation. (hello fact checkers).
What is the proper interpretation is that there is an EXTREMELY PROMINENT RELATIONSHIP between boosters and deaths in 2022. This is an alarm signal and food for thought that needs to be analyzed further. We need to search further to understand causality better.
Demographics is a complicated science and there are demographics institutes in each country. I do not personally own a demographics institute and only do what I can, with the skills I have. However, nobody owns me either.
Despite my stating clearly that I uncovered a correlation, not a causation, I personally believe that boosters ARE a cause of increased mortality. There are many reasons to believe this to be highly likely, but they are a topic for another article.
UK’s Regional Data
Our insightful reader Nova pointed out that inside the UK, the same pattern of mortality dependent on the region is evident also and it is also highly statistically significant with P < 0.0001. I have not personally verified this.
My Own Hypothesis
What is the underlying mechanism between excess mortality in 2022 and booster uptake?
Could it be deaths immediately following vaccinations and booster shots?
Could it be that boosters no longer provide “death protection”, but instead increase the chances of dying from Covid?
Could it be greater rates of reinfections of boosted people?
Could it be long-term damage from repeat Covid vaccinations making people more likely to die in general?
Is it possible that people keep producing “spike protein” well beyond the promised “2-3 days”?
My answer is: all of the above.
What do you think? Any other ideas?
This is exactly what I am seeing here in the UK using official government data. The truth is hiding in plain sight.
I've compared excess deaths with triple vaccinated levels in each LTLA (Lower Tier Local Authority) region in England for the most recent 15 weeks and the data is giving a very clear message - more excess deaths are occurring in areas with higher levels of triple vaccination.
My recent plot should be accessible at https://tinypic.host/i/vuzMR
The data have a P-Value of <0.0001 which indicates a significant deviation from the horizontal as can be seen from the linear trend line.
Further analysis of the data indicates excess deaths currently running at 1180 per week in England. Obviously these are disproportionately occurring in areas with higher levels of vaccination which leads me to conclude that the vaccines are playing a role in the current elevated death levels.
Igor, if yours was the only study I would say proceed with caution, however there are a myriad of studies from different angles that all come to the same conclusion. Horrific rise in miscarriages, reoccurrences in cancers that become very aggressive, heart problems, strokes, clots, etc, etc. These injections are deadly & the government knows this. Leaving only one conclusion.