Data Not Distress is a data project started in March 2020, when it was clear that
China was handling
Covid-19 well-within the numbers of their usual cold season,
much like SARS
just a few years ago, and yet, Italy had become a disaster.
How do you explain the same common cold acting like any other in some locations,
but seemingly becoming more deadly in others?
After all, this is just a coronavirus -
15% of all common colds,
and with a pattern of interaction with animals
established over millions of years.
History shows that despite deadly forms appearing, we have
almost always had normal cold seasons because of it.
As the data came in, this pattern was very much the same -
the majority of countries in the world were
seeing ordinary cold seasons due to Covid-19. And yet,
Italy was heading upward of three times their ordinary cold season and counting.
How could it be?
Looking at the demographic age data of deaths as it came in,
including from Italy,
it was clear that the numbers were largely
identical to ordinary cold seasons - universally, over 90% of deaths were those ages 55 and up, just like any other year.
However, this pointed out one big difference across countries - the percentage of elderly is very different in different countries.
It is true across the world - more wealthy countries have larger percentages of elderly - after all, what do we do with wealth,
if not use it to try to live longer?
Japan has the largest elderly population in the world at 41%.
Italy has 36% and the
United States has 30%,
but China has 24%, and Iran and
South Africa have 13%.
And across Africa, it is as low as 5%.
The countries with lower elderly populations, and thus fewer vulnerable people, tend to have better results than those with
larger elderly populations. But, Japan has still seen only a tiny fraction of their usual cold season due to Covid-19,
despite their largest-in-the-world elderly population. There had to be something more to explain it.
The answer began to come in looking at
patterns of our usual cold season deaths,
with data from the CDC Wonder mortality database.
Every year, you can see deadliness rise and fall with the onset and end of Winter, and breaking down that data by location shows
that it is not temperature, but our behavior during those times that causes that rise in deadliness.
The answer suddenly started to become obvious - the countries doing the worst in the world were enacting policies that had their
populations acting just like the United States during Winter - staying indoors with the windows shut,
and not interacting with others, and the result was exactly the same - a surge in deadliness that would dissipate after reopening.
This was borne out in data from around the world -
you can literally see the exact dates that lockdown
orders were given and lifted
in the patterns of deadliness of Covid-19, with restrictions on businesses seemingly being the biggest correlating factor
in causing more deaths. This makes sense because it has magnified impact, both on people not getting out of their homes
to go to work, but also in giving their customers less reason to venture out as well.
And so began the mission of Data Not Distress - how do you make this data more accessible to people so they
can see the answer for themselves?
Only populations that behave normally will ever have normal cold-and-flu seasons again,
and the only way to actually save lives will be to get back there.
