Switzerland is not running out of ICU beds. It’s a fake news scare peddled by mainstream media and politicians. The proof is in the data from the Swiss Federal Office of Public Health (FOPH) which records the number of ICU beds available and occupied. The data clearly shows that hospitals are adjusting the number of ICU beds on an as needed basis to keep occupancy as high as possible while still having a number of beds available for emergencies.
Here’s the data from Feb. 15 2021 to Dec. 10 2021:
I am not going to belabor this point any longer, and conclude the topic here with presenting more evidence that the “Swiss hospital are running out of ICU beds” story in the news media is completely false (fake news!). Hospital are running at a high occupancy, yes, but the ICU-bed capacity is adapted as needed and changes from day to day. This can can be seen directly from the data provided by the Federal Office of Public Health (FOPH) by everyone who cares to actually look at the daily numbers and compare them for several days. Here are the numbers from December 1 and December 2, 2021:
It’s easy to see that for Switzerland, numbers are actually slightly down from Dec. 1 to Dec. 2:
Total ICU beds have gone up by +1 (but that’s still 4 less than on Nov. 30);
The total occupancy has gone down by -7 beds;
COVID-19 patients has gone up by +9, while Non-COVID-19 patients has gone down by -14 beds;
Free ICU has gone up by +8 beds
Occupancy is at 81.2% on December 2, which is -0.9% compared to December 1. On November 30, it was 81.1%, but there were 863 ICU beds that day. So, it’s again obvious, that giving the number “ICU beds are x% occupied” is highly misleading, as the total number, the “100%” changes from day to day.
It’s also easy to see that the situation in Zurich has improved from Dec. 1 to Dec. 2:
Total number of beds has stayed the same, at 183 beds;
Total occupancy has gone down by -9 beds;
COVID-19 patients occupancy has gone down by -1 beds;
Non-COVID-19 patients occupancy has gone down by -8 beds;
Free ICU beds has gone up +9 beds
So in conclusion, we can see from the numbers, that hospital ICU-beds, are managed on an “as-needed” basis. They are activated and deactivated as the situation requires, and hospitals are not interested in running a high-number of unoccupied ICU-beds, just to keep the statistics nice. Of course, there is a maximum number to which ICU-beds can be increased, but has that been reached yet? We don’t know and are not told in any statistics. The real limiting factor is staff-availability, not number of physical beds, by the way. But curiously, for that, we don’t see any statistics, and we also are not told, what is done to alleviate the pressure on the medical staff.
Let’s look at the official numbers from the Swiss Federal Office of Public Health again. Here, I have compared the numbers from November 28 with those of November 30:
For Switzerland we make some observations:
First, note the Total number of ICU beds for Switzerland. Nov. 28: 854, Nov. 30: 863. The total number of ICU-beds is not constant over time, it is GROWING (+9). So the “beds are x% occupied” news are grossly misleading;
Second, note the number of non-COVID-19 patients in ICU beds has grown quicker (+25) than the number of COVID-19 patients (+16). This is evidence, that COVID-19 is not the only driver for increased demand for ICU beds;
Let’s look at the numbers for Canton of Zurich:
First, note the Total number of ICU beds for Zurich. Nov. 28: 179, Nov. 30: 183. Number of beds were increased in two days (+4)
Second, note the number of non-COVID-19 patients has grown quicker (+5) than the number of COVID-19 patients (+4). This is evidence, that COVID-19 is not the only driver for increased demand for ICU beds;
Third, the number of available ICU beds has dropped by -5 and is now at 12 (6.6% of Total for that day)
So, the key observations are:
The total “capacity” of ICU-beds differs from day to day, as, presumably, hospitals create new capacity as needed. Meaning: News like the above, that “hospitals are to x% occupied” are nonsense in this form, because they do not take into account that the capacity can be and is increased as needed (up to a certain maximum, of course, but we and they don’t know where that is);
Contrary to what these press statements would make you believe, ICU beds are not only filling up because of COVID-19 patients, In fact, non-COVID-19 patients fill up ICU-beds in Switzerland quicker than COVID-19 patients do. So, the obvious question: What’s up with that? But nobody in this shitty news outlets actually asks these “obvious” questions – I wonder why…
This is posted for future reference. The data covers the period from 2001 to 2019 (inclusive) – thus it is pre-pandemic data. As we can see from the data, the number of beds in this period have been reduced by 12%, despite the fact that the population grew by 19%, a rise in hospitalizations by 25% during the same period.
Here is another view on the number of ICU beds in the Canton of Zurich for 2018 – which is also pre-pandemic. The article raises he same points as the above (reduction of number of beds, despite growing population):
The Swiss Federal Statistical Office (SFSO) has some nice data with which you can play around. To hone my R programming skills, I grabbed a recently updated dataset for Swiss female and male surnames for babies in 2019. You can find the datasets here.
The first challenge is to find out how to work with px-files. Thankfully, this is easy, the pxR package takes care of that. It imports a file in px-format and produces a data-frame that you can use like any other data-frame.
The second challenge was with one of the original column names “Sprachregion / Kanton”. This did not want to filter and kept me giving either a column name not found or an empty data-set. So I change this column name in the original file to read “Kanton” and it worked.
I thought I start with a density plot to see if this tells me anything about the names:
The names to the left are the ones that are not chosen by many, but there are an awful lot of these, lets call them rare, names. The names to the right are the ones that are chosen by many, but there are not a lot of these, lets call them common, names.
A first look would seem to suggest that 2019 was a year in which the diversity of baby names chosen was the highest in this period (2000-2019) for both male and female baby names.
Some number crunching: Total number of (unique) names in dataset are (for 2019) 2765 (female) and 2702 (male). You can read the SFSO press release (no English version) to find out more on the most common names in 2019 and more.
If you want to have a look at the code I wrote, you can find it on github.