The 2020 “Dry Tinder” Effect

2 min read


This is an important observation – one which has been hypothesised since the spring by leading epidemiologists and statisticians👇🏼

The below graphs map England death rates data from 2001 to 2020, where ONS age-standardised the rates to the 2013 European Standard Population. The top graph plots the crude sum of 11 monthly death rates (Jan-Nov).

👇🏼You can check out the underlying data set, plus an understanding of Age-Standardised rates and other epidemiological mortality metrics within the link below.

Tomorrow, we’ll share data on the Leading Causes of death between Jan-Nov 2020, but first we MUST cover the overall dataset.

UK Jan-Nov Dry Tinder Effect

Understanding the Graphs

🔝The top graph very clearly demonstrates what Epidemiologists call the “Dry Tinder” effect (aka Kindling/ Harvesting), where a soft year creates a larger group of susceptible the following year.

It stands to reason. If the current UK Life Expectancy is ~81.5, and many 80+ year olds avoid death in 2019, they will statistically be more likely to die the following year.

👀 If you observe the average age of COVID-related death in the UK, you will find it is HIGHER than the life expectancy (~82), which further supports the above hypothesis.

👌🏼 Furthermore, if you take the mid-point between End Nov 2019 to End Nov 2020, you find it maps perfectly to the 2016-2018 data, showing an equilibrium formed between 2019 and 2020.

👌🏼 Taking that one step further, we can apply the same logic between 2015 and 2016 and plot a trend line between the last 5 years (using mid points of swing years), and 2020 data maps perfectly.

😳 As a final observation, you may say “the overarching trend line is lower than what we have been seeing in recent years”. Well, yes, but it’s VERY IMPORTANT to note that it’s been observed that we have reached a point of declining health and life span…

😬 Given the poor and declining state of health due to chronic diseases caused by worsening lifestyle and nutritional choices (thanks processed food and Govt), we can expect to see younger generations live shorter lives – unless there is drastic change.

This can be seen in the data – the levelling off of an otherwise declining death rate in most recent years. 

4 Variables to consider

❌ All that said, this post is NOT about denying the Pandemic. Something happened that caused the expanded susceptible population to come unstuck quickly and all together – this happened in the Spring for the UK.

However, we now have 4 variables to consider for the non-dramatic (yet still concerning) excess being witnessed in the winter. Loss of Health & Life due to:

  1. Significantly reduced access to healthcare – Triage, Screening, Diagnosis, Treatments, Surgery  (Policy-induced)
  2. Prolonged Stress & Poor Wellness decisions (Policy-induced)
  3. SARS CoV2 and other Respiratory Virus burden due to lack of herd immunity developed in summer (part Policy-induced, part novel Virus) 
  4. Experimental Vaccines and Vaccine-Associated Virus Interference (policy-induced)

🤷🏻‍♂️ How big each fo the above effect will be is hard to speculate, but it is certain that they will ALL contribute in some degree to a more-than-necessary death toll.

As a theme for the year, the UK and all member states of the WHO seem to be royally missing the wood for the trees.

🤕 They continue their myopic and obsessional focus on one diseased state while dropping the ball on broader Public Health due to poor Policy Decisions and an utter lack of Wellness encouragement/support.




ONS Monthly Mortality dataset (Dec 2020 release)


The Original Facebook Post

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