Mid-COVID-19 Update On Death Statistics For England And Wales


About a year and a half ago, I wrote a blog post about some death statistics for England and Wales as COVID-19 started to kick-off. Now that some time has passed, I decided to revisit the subject and update my plots to include the recently released 2020 death statistics.

The statistics that I am using in the following discussion have all come from the Office for National Statistics (ONS). The single specific data source (fetched at approximately 11AM on 24th October 2021) that I have used is:

As before, a word of caution: just because I can find an historical event that aligns with a peak or a trough on a curve does not necessarily mean that the historical event caused the peak or trough. Correlation ≠ Causation; see Spurious Correlations for some hilarious examples that underscore this statement. The rest of this blog post is arranged like:

  1. Total Deaths
  2. Crude Mortality Rate
  3. Age-Standardised Mortality Rate
  4. Excess Deaths
  5. Observations

§1 Total Deaths

The plot below shows the total number of deaths in England and Wales since 1838. As a reminder, 1918 was the most deadly year with 611,861 deaths. 2020 was only the second year on record where the total number of deaths exceeded 600,000 (at 607,922 deaths).

  1. 512 px × 283 px (0.1 Mpx; 61.5 KiB)
  2. 1,024 px × 567 px (0.6 Mpx; 150.9 KiB)
  3. 2,048 px × 1,134 px (2.3 Mpx; 374.3 KiB)
  4. 3,094 px × 1,713 px (5.3 Mpx; 307.1 KiB)

It is unequivocal that something occurred in 2020 to result in a significant increase in the total number of deaths in England and Wales. As in my previous discussion though, the above plot is largely pointless as it is susceptible to underlying population changes (because it is a simple total count).

§2 Crude Mortality Rate

A better metric to describe deaths in England and Wales is a crude mortality rate, i.e., “the total number of deaths” divided by “the total population”, which is shown below.

  1. 512 px × 294 px (0.2 Mpx; 42.5 KiB)
  2. 1,024 px × 587 px (0.6 Mpx; 109.8 KiB)
  3. 2,048 px × 1,174 px (2.4 Mpx; 281.6 KiB)
  4. 2,988 px × 1,713 px (5.1 Mpx; 222.7 KiB)

For example, in the first plot, the total number of deaths increased by 11.81% during austerity; however, in the second plot, the crude mortality rate only increased by 6.98%. This indicates that roughly half of the increase in the total number of deaths was simply due to an increasing population.

More interestingly, 2020 is no longer as severe. The mortality rate in 2020 is the same as what it was in 2003, and it is lower than any value in the 20th Century (on record).

§3 Age-Standardised Mortality Rate

During my previous discussion, I talked about how the UK has an ageing population, and how the crude mortality rates for each age group did not increase during austerity, leading to the conclusion that the increase in the overall crude mortality rate is simply due to there being more old people in the population. Well, it turns out that the ONS produce a mortality rate statistic for a “standard” population, so as to not be susceptible to an ageing population: this is shown below.

  1. 512 px × 288 px (0.1 Mpx; 43.9 KiB)
  2. 1,024 px × 577 px (0.6 Mpx; 106.8 KiB)
  3. 2,048 px × 1,154 px (2.4 Mpx; 274.5 KiB)
  4. 3,041 px × 1,713 px (5.2 Mpx; 229.9 KiB)

During austerity, the age-standardised mortality rate actually fell by 1.35%.

Again, 2020 is no longer as severe. The age-standardised mortality rate in 2020 is between the values for 2008 and 2009, and it is lower than any value in the 20th Century (on record).

§4 Excess Deaths

An awful lot of the discussion about COVID-19 in the past year has centred on the idea of “excess deaths”. This statistic is quite simple: what is the difference between the current number of deaths and the arithmetic mean of the number of deaths for the preceding 5 years? As this uses the total number of deaths, then it is susceptible to both a changing population size and an ageing population. Hopefully though, as 5 years is a fairly small window to average over then it shouldn’t be overly susceptible. I have gone through and calculated it for every year since the mid-19th Century, shown below.

  1. 512 px × 290 px (0.1 Mpx; 48.1 KiB)
  2. 1,024 px × 580 px (0.6 Mpx; 100.5 KiB)
  3. 2,048 px × 1,161 px (2.4 Mpx; 216.5 KiB)
  4. 3,023 px × 1,713 px (5.2 Mpx; 173.3 KiB)

Clearly, 2020 is an outlier; however, it is not as much of an outlier as one might think. 2020 was +14.3%, but 2015 was +6.6% and no-one batted an eyelid (just think about that for a moment…). 2020 was the highest for excess deaths since 1940. Furthermore, all years since 2012 have been positive (due to the ageing population). Therefore, whilst +14.3% is high one would not have had the expectation that it would’ve been +0% for 2020 had COVID-19 not happened.

What is also clear from the above plot, is that there have been many years that have had excess deaths in the same ballpark as 2020. The table below lists the top six years, with my very crude attempt to find a historical event that correlates with the year.

YearExcess DeathsCorrelated With …
1940+18.120%The Battle Of Britain (and The Blitz)
1847+18.071%… famine? (due to potato failure)
1918+18.069%Spanish Flu
1849+14.817%… famine? (due to potato failure)
1929+13.544%Wall Street Crash

I think that it is clear that there is a lot of noise in the above plot (especially before WWII), and I am hesitant of correlating the peaks with domestic events.

§5 Observations

If you have got this far reading my blog post, then: thank you. Overall, I have a few summarising observations to make:

Never forget that:

Both of these events eclipse COVID-19.