I watched a recent video life expectancy: a counterfactual example, from Prof. Norman Fenton of Queen Mary University in London. For those of you who don’t know who he is, Norman Fenton is a Professor of Risk and Information Management. He has a passion for quantitative methods and has a channel on Rumble, which is well worth looking at and has appeared on TV here in the UK.
In the video, he worked through a model looking to calculate the number of years a person might have lived, who had actually died from SARS-CoV-2, had they not died from the disease. For those interested in that subject, head on over to Rumble or follow this tweet.


After watching the video, it got me thinking about how many Years of Life Lost (YLL) have been due to the so-called ‘vaccine’ and not to SARS-CoV-2.
Deaths after ‘vaccination’
Open VAERS (as of the time of writing) reports that 10,316 people have died in the US following the injection. We know that the majority of these have been elderly, so let’s start by delving into some summary statistics before looking at how much ‘life’ has been lost. I consider ‘life lost’ to be the number of years lost had the person not died after the injection.
After updating my local VAERS database (US domestic) to the end of 2021 and removing records where the sex of the individual was undefined as well as unknown vaccine manufacturer records, I calculated 9,306 deaths - so about a thousand difference from what Open VAERS reports. These are shown below distributed by ‘vaccine’ manufacturer (vertically) and sex (horizontally).
The median age of a person dying after the injectable was 75 irrespective of age or manufacturer with the interquartile range being 64-84. There were 5,268 men who have died with women making up the remaining 4,038.
But how does this translate to loss of life? Especially, when considering younger people have lost far more life than those who were older.
Years of Life Lost (YLL)
One way to quantify the YLL is to calculate how long the person ‘might’ have lived had they not had the injection. Of course, this doesn’t account for unknown or underlying conditions that may have been exacerbated or even catalyzed as a result of the injectable product but does provide an indication as to the magnitude of the overall amount of life lost in years.
There are a number of ways to approach this, but I chose to use the actuarial life expectancy table from the US government.
The table provides an expected number of years left given a person’s age and gender as well as a probability of dying in 1 year. For example, I’m 55 and male, so I have a predicted 25.7 years left and a probability of dying within 12 months of 0.007627.
Using this information, we can calculate the YLL for each person in VAERS by looking up their age and sex and adding a column to hold this data.
Doing this for all 9,306 people in the VAERS database I have produces the following.
The distribution of YLL has shifted slightly left compared to the distribution of the number of those who died showing that the young have lost more years than the old.
Think what over 130,000 years of life could have contributed to humanity.