One the key problems with how the entire âlockdownâ concept was conceived in the first place was the US and UK governmentsâ over-reliance on computer-modeled projections and pandemic simulations.
Itâs now known that almost all of these models turned out to be completely wrong and yet, the government still doubled-down on its policies based on these same false assumptions and corrupted data.
Regarding the COVID crisis going forward, rather than casting their typical one-size-fits-all approach to public health policy, perhaps it would behoove governments to place the majority of weight on one single variable. Maybe then the models might actually become useful. Not surprisingly, that crucial variable happens to be the one at-risk demographic which the government completely failed to protect since the beginning of the so-called âpandemic.â
To be even more accurate, the real risk emerges when you combine old age with corresponding chronic long-term health conditions, also known as comorbidities.
Why are governments still refusing to admit this is the only real variable we should be concerned with?
It has been very clear for some time that very few people younger than 50 years old die from Covid19.
In fact the average of people dying with Covid19 have been around 80 years in most countries and men are more likely to die than women.
These simple facts made me think â how much of this can explain the different mortality rates we observe across countries?
Why has so many people died in Italy and Spain, while mortality rates have been much lower in for example Scandinavia? Similarly why are mortality rates so low in most developing countries?
Can the age composition explain this? The graph below give us the answer.
In the graph I have plotted the number of deads with Covid19 per 1 million population versus the share of the male population older than 80 years (%).
The data was collected on Friday April 17 2020 and I have only looked at countries with at least 100 deaths from Covid19 and excluded very small countries like Andorra.
As we see there is a very strong correlation between the two and it is certainly strong enough for me to argue that the absolut most important variable determining whether or not a country will be hard hit or not by the Covid19 crisis is the the age structure in the country.
Countries with a lot of old men will simply suffer a lot bigger blow than countries with younger populations.
It should of course be noted that I here compare countries, which are in different phases of the Covid19 crisis.
Correcting for that might make the âmodelâ more (or less?) precise and we could of course also add more variables â for example air pollution, which think also is an important factor, but what is notable is that age alone is such an important factor.
From that perspective it also seem amazing to me that countries have introduced more or less draconian curfews and lockdowns around the world basically for everybody rather than focusing on protecting the most fragile parts of the population â the elderly.
In fact, if we look at Sweden which have likely has the most liberal approach to combating the Covid19 we see that Swedenâs mortality rate overall is not much different from other countries and if we put a regression line in the graph then Sweden would be more or less smack on that regression line.
Two nations to worry about â Greece and Japan
When looking at the graph it is very clear that two countries are clear outlier â Greece and Japan. Both countries have a quite high share of males older than 80 years (both above 6% â and higher than in Italy).
However, unlike Italy or Spain both Greece and Japan so far have avoided a large number of deaths. The question is why?
I donât have a clear cut answer, but the Greek government early on put the entire nation on a very strict curfew â essentially locking up the Greek population in their own home.
From ONE factor explains most of the differences in Covid19 deaths across countries