Going through Wikipedia's notable deaths, I focus on two numbers. One is the total number of deaths each month, and the other is the percentage of deaths registered by people under 70 year of age.
Deaths among young people are more regrettable than those among older people. Young people have still a lot left to accomplish in life. People in their 50s have on average 30 more years to live, while people in their 80s have on average 5 more years to live. The quality of those last years are are also less. People in their 80s rarely produce much of importance, while those younger than 70 often have much left in them to share with their loved ones and the world at large.
This is the reason I've decided to keep an eye on the percentage distribution of deaths as well as the total. However, when I plot these two numbers into a single graph, I have only subjective measures to use when I compare one month with another. What I need is an objective calculation to denote severity.
The severity index should ideally be calculated in such a way that it fits with the axis denoting total deaths, because that would make for a sensible comparison. We can for instance say that April 2020 have a lot of deaths, but that it wasn't as severe as April 2021, because 2020 had relatively fewer deaths among the young than 2021.
A good severity index should blend in with the totals. It should work as a weighting that adds weight to the young and removes weight from the old.
Having noticed that the average percentage distribution between old and young is around 22% for the young, we see that we can achieve the desired weighting by dividing deaths among the old by 10 and multiplying deaths among the young by 4.
Such a formula will return values in line with the total, and can therefore be plotted against the same axis as the total. However, it values young people 40 times higher than old people, and the question that springs to mind is whether this is a reasonable factor. To answer this, we have to consider the typical situation of the 80 year old as compared to that of a 50 year old.
The typical young person dying is in his mid to late 50s, and the typical old person dying is in his mid 80s. From this alone, we can see that the death of a typical young person can be considered a tragedy, while that of the typical old person is merely life coming to its inevitable end. The life of the old may possibly have been extended by a year or two with additional care. The life of the young was cut short by an average of 30 years, most of them of a high quality.
We can from this conclude that my proposed weighting is in line with our subjective notion of relative value when it comes to years lived.
When we apply this to data collected for April we get the following:
Deaths among those younger than 70 years of age compares to previous years as follows:
- 19.48% in April 2018
- 21.23% in April 2019
- 17.76% in April 2020
- 22.62% in April 2021
- 24.65% in April 2022
When we look at absolute numbers for April we get the following:
- 575 in April 2018
- 617 in April 2019
- 1132 in April 2020
- 964 in April 2021
- 597 in April 2022
Using a severity formula that divides old deaths by 10 and multiplies young deaths by 4 we get the following:
- 494 in April 2018
- 573 in April 2019
- 897 in April 2020
- 947 in April 2021
- 633 in April 2022
When we now compare the absolute numbers with their severity, we get some interesting information:
- April 2020 saw the highest number of deaths. However, April 2021 was more severe.
- April 2022 saw fewer deaths than April 2019. However, April 2022 was more severe.
We are emerging from the pandemic with total deaths back to normal, but with higher severity. If this persists, life expectancy will go down as compared to what it was before the pandemic.
Here are the numbers extracted from Wikipedia:
April 2022:
- 20s = 5 = x%
- 30s = 8 = x%
- 40s = 32 = x%
- 50s = 37 = x%
- 60s = 76 = x%
- 70s = 162 = x%
- 80s = 188 = x%
- 90s = 121 = x%
- 100+ = 12 = x%
Total = 641; Younger than 70 = 24.65%
April 2021:
- 20s = 6 = 0.62%
- 30s = 15 = 1.56%
- 40s = 27 = 2.80%
- 50s = 56 = 5.81%
- 60s = 114 = 11.83%
- 70s = 238 = 24.69%
- 80s = 314 = 32.57%
- 90s = 179 = 18.57%
- 100+ = 15 = 1.56%
Total = 964; Younger than 70 = 22.62%
April 2020:
- 20s = 8 = 0.71%
- 30s = 14 = 1.24%
- 40s = 20 = 1.77%
- 50s = 47 = 4.15%
- 60s = 112 = 9.89%
- 70s = 273 = 24.12%
- 80s = 409 = 36,13%
- 90s = 238 = 21.02%
- 100+ = 21 = 1.86%
Total = 1132; Younger than 70 = 17.76%
April 2019:
- 20s = 9 = 1.46%
- 30s = 12 = 1.94%
- 40s = 11 = 1.78%
- 50s = 28 = 4.54%
- 60s = 71 = 11.51%
- 70s = 134 = 21.72%
- 80s = 203 = 32.90%
- 90s = 138 = 22.37%
- 100+ = 11 = 1.78%
Total = 617; Younger than 70 = 21.23%
April 2018:
- 20s = 9 = 1.57%
- 30s = 11 = 1.91%
- 40s = 12 = 2.09%
- 50s = 21 = 3.65%
- 60s = 59 = 10.26%
- 70s = 124 = 21.57%
- 80s = 189 = 32.87%
- 90s = 134 = 23.30%
- 100+ = 16 = 2.78%
Total = 575; Younger than 70 = 19.48%
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