Some Interesting Facts About Covid in Sweden.

By: Jan Kjetil Andersen – Re-Blogged From WUWT`

Sweden has some good stuff. One of them is SCB, Statistics Central Bureau, a jewel for statistic geeks.

Sweden has also made headlines because of their alternative non-lockdown policy during the pandemic, so let’s take a look on some numbers.

A table of special interest in these pandemic times is the weekly mortality rate, and even more interesting is it when we compare that with the Worldometer Covid statistics.

I base the statistics on reports from December 5th but make a cutoff on November 15th to avoid errors because of late reported deaths. According to the information from SCB, no significant changes occur on data more two to three weeks old. We can therefore trust the data up to November 15 as accurate.

Figure 1 Worldometer from December 5th, with a cutoff November 15th
Figure 2. Total deaths per day in Sweden up to November 15. 2020 figures in purple, the green line average numbers from 2015 to 2019 and the red line shows 2020 numbers when the reported Covid fatalities are subtracted.


According to Worldometer, seen in figure 1, Sweden had 6405 Corona deaths up to November 15. That is about 600 deaths per million citizens, which place Sweden among the hard-hit countries such as UK, France, and US.

As we see in figure 2, the excess deaths from Covid is clearly visible from mid-March to June, and we also see a start of a second wave from mid-October.

However, here comes the interesting part, the excess death rate for 2020 compared to the average for 2015 -2019, is only 3570. That is only 56% of the Covid deaths reported by Worldometer over the same period.

The reason for this is that the death rate for 2020 is lower than average both before the first wave and in the time between the two Covid waves. The actual numbers from SCB before, under and after the first Covid wave is shown in the table below

Total reported Deaths in Sweden 2020 Anomaly compared 2015 -2019 average Covid Deaths Death Anomaly Covid extracted
Jan 1st – March 14th 19063 -1411 4 -1415
March 15- June 30th 31110 5521 5479 42
July 1st – November 15th 30956 -540 518 -1171
Table based on numbers from SCB.  We see that 2020 has lower death rate than average for 2015 -2019 both before and after the first Covid wave. 


Parts of this anomaly may be purely coincidental. For instance, was the 2019 –2020 influenza season especially mild in Sweden.

One can speculate whether the disturbing pandemic reports early this year may have influenced enough people to be extra cautious about infections and therefore also caused less influenza spread, but that may be a stretch.

Sweden’s chief epidemiologist, Ander Tegnell, as suggested that the mild influenza season is partly to blame for the relatively high Covid death rate early in the pandemic. More of the most vulnerable survived the weak influenza season which means that Sweden entered the Covid pandemic with a higher number of vulnerable people than normal.

He may have a point, but still, the excess deaths in 2020 is projected to be large enough to bring down the life expectancy by 0.3 years in the whole country.  In Stockholm County, life expectancy is estimated to decline by 1.2 years, from 83.7 years to 82.5 years.

Misleading Worldometer statistics

Another interesting aspect here is that the Worldometer statistics always shows a dip for the most recent days for Sweden. The reason for this is that there is a delay in the reporting so the reported numbers for the most recent days are far to low. This is illustrated in the two figures below.

The Worldometer graphs from November 21st show a decline after November 9th. This decline is artificial and caused by the late reporting.


The Worldometer from December 5 shows that the death rate continued to increase after November 9th.

It is too early to tell whether the rate has continued upwards after November 24th.

These two graphs illustrate how easy we can be fooled by statistics and that can be dangerous because we depend on good statistics to make the right decisions.

For example, the authorities use the figures for the number of new infected as a tool to either tighten or ease the restrictions that will reduce the reproduction rate R. The goal is to keep R below 1.0. I am quite sure the decision makers in the government knows about this lag, but the public may not, and that influences how serious we take the situation.

Worldometer is a universally used site, and many laymen look it up for their countries. When the statistics shows a dip for the most recent days many will think, “Thank God, it is over, we can ease up now.”

That may not be the case.


Leave a Reply

Fill in your details below or click an icon to log in: Logo

You are commenting using your account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s