Mortality Outcomes by Age in England & Wales, During the "Pandemic Years"

Using a novel, robust model as a function of year of birth to estimate excess deaths between 2020 and 2022, it is apparent that the "vaccine" epoch is worse than the virus.

Results

Figure 1

In absolute terms, annual mortality for each single year of age from 30 up to 75 years, is demonstrably higher in 2021, the first year of the COVID “vaccine” than for 2020, the year of the “novel” virus (Figure 1).

Figure 2

In relative terms, mortality outcomes in 2021, compared to 2020, are worst for the 35 to 60 year olds, the prime of society (Figure 2).

Figure 3

Apart from the 65 to 75 year olds, excess mortality in 2022, appears to have returned to marginally below 2020. However, the data is incomplete, especially in the younger ages, so this outcome may well change over time (Figure 3).

For completeness, here are the percentage results (Figure 4):

Figure 4

Methodology

It has been an arduous and expensive task to get reliable data from the ONS. The dataset used is, however, the best currently available since it is by single day of occurrence and single year of age. Stratification by sex might have been an additional improvement.

Nevertheless, analyses relying on straightforward comparison of age-stratified deaths to historical data to determine excess, even if they correctly adjust for potential trends, are subject to error, because people move between age bands each year.

The number of people born (and still alive) in each cohort has varied significantly. If this is not taken properly into account, results can be subject to error.

Figure 5

In this analysis, I derived annual deaths as a function of year of birth. As can clearly be seen in Figure 5, correct selection of year-of-birth series, according to year of observation will yield significantly different baselines for ages 65 to 80 as a result of large variability in birth rates during and after the Second World War¹.

This effect will also materialise to a lesser extent for other ages and years.

Figure 6

By fitting a parametric function to each year-of-birth series, I was able to reliably forecast annual mortality baselines for the “Pandemic Years”, 2020 to 2022 (Figure 6).

Subtracting these baselines from the actual data and shifting 2021 back one period, and 2022 back two periods, I was able to compare the three years in terms of excess mortality for the same cohort in each period, i.e. a consistent year of birth² (Figures 1 to 3).

When adding data for 2020 to 2022 (Figure 7), it is most apparent how far off expectation the new series become.

Figure 7

It is absurd to include these years in baseline for future excess mortality studies. Criminal, in fact, because it can only serve to deceive - in that, there must be intent. Hanlon’s razor³ does not apply.

Further considerations

The analysis was limited by the availability of full-year data (2015 to 2022). The ONS has mortality data by day of occurrence and single year of age going back to 1970 but expects a substantial fee to release it.

Figure 8

With that data, more reliable mortality distributions than the one depicted in Figure 8, could be derived, allowing the extension of this analysis to cover the entire pre- and post- war period instead of the 5-year fractals since 2015, and also to examine the distributions stratified by month and year of birth, instead of just year.

This subsequent analysis could be used to test the hypothesis that substantial expenditure of public funds on public health measures, e.g. vaccines, has manifested in superior outcomes in terms of mortality - or perhaps not?

1. We can, of course, corroborate this with the birth data:

2. Because all series below 85 years are upward sloping, this may introduce some bias into the results. Even though both baseline and actual deaths increase, absolute excess may well tend to be higher, even at constant rate which is why I also considered the percentage excess. I did not find cause for material concern in this respect.

3. Hanlon's razor is an adage or rule of thumb that states:

"Never attribute to malice that which is adequately explained by stupidity."