Nenad Bakic: Why Has the Virus Become So Deadly in the New EU Countries?

By 20 December 2020
Nenad Bakic Analysis
Nenad Bakic Analysis Source:

December 20, 2020 – The European Union has so far recorded over 300,000 deaths caused by the coronavirus pandemic, with the second wave being 50 percent more deadly than the first one. It is easily possible that the total number will exceed half a million by the time the pandemic is brought under control. Mathematician, investor, and analyst Nenad Bakic explains why for

In terms of the number of deaths per million inhabitants, the new members of the European Union, the countries of the "new European Union", namely the former socialist countries – including, unfortunately, Croatia – are in the lead. Some of them have several tens of times more deaths in the second wave than in the first.

Covid deaths EU.png

Confirmed cases of death due to coronavirus in the European Union / Source:

What is happening? Why did the virus in the second wave become so deadly in the new European Union members? By studying this example, we can learn a lot about the pandemic in general.

  1. The countries of the New European Union (NE), 11 ex-socialist countries, did very well in the first wave, with only one of them among the 13 most-affected. All the governments of these countries attributed the success to themselves. In some countries like Croatia, it was done by gurus who considered themselves ideologues of barbaric imprisonment or, as they ignorantly called it, "quarantine".

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Graph 1. Coronavirus deaths per million, until June 30, 2020. Source: / JHU CSSE

They are marked in red on the first graph. A lighter shade highlights the small Baltic countries because something strange is happening there, but it doesn't matter. It is the same when we look at it without this separation.

What is the probability that the NE countries were so much more successful in their will than the older, smarter, and more experienced brothers? Maybe it's something else.

  1. In the second wave, NE countries were significantly more affected, as we can see in the second graph.

Graph 2. Coronavirus deaths per million, from July 1, 2020 until December 18, 2020. Source: / JHU CSSE

Out of the top 8 countries, they occupy seven positions. What is the probability that they are so much more unsuccessful than other countries by their own will? Very small.

Of course, it's easy to recognize a "return to the core value" here – as the virus does what it wants, most countries end up converging to a similar number of deaths. Graph 3 shows the coefficient of variation, which is the standard measure of a set's scatter.

Graph 3. Coefficient of variation, deaths from coronavirus in EU countries per million. Source:

Here we can already conclude that the performance of the NE countries as a group has nothing to do with their governments' competencies. The probability that a group with its ability is far above average and then that same group is far below average, especially in a situation like this where the virus spreads across the continent without knowing the boundaries, is zero. Of course, some individual countries are better or worse, both in epidemic management and in treatment.

  1. But things are only now becoming very interesting. The number of deaths in the second wave not only offset the one from the first wave but also shifted it. The NE countries as a group are now considerably worse than the rest, as we can see in Graph 4.

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Graph 4. Total coronavirus deaths per million. Source: / JHU CSSE

They occupy eight of the first 13 places. If we exclude the small Baltic countries, only Slovakia remains in the lower half, but the situation deteriorates quickly, and it could easily get to the upper half.

As we can see, there is something special about the small Baltic countries and Finland. We still don't know what, and it doesn't matter for this analysis either. If we single out those countries, things become clearer, but the analysis works without them.

  1. What is the explanation? It can be the following:
  • A. It has been shown that COVID-19 is highly seasonal. In NE countries, the epidemic came later in late winter 2020 and therefore could have done much less damage by the time spring came. This is undoubtedly the case with Croatia, as you can see in Graph 5: the reproductive factor R fell below 1 already before the end of March, before the measures were introduced on March 23 in Croatia and could take effect.

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Graph 5. Source:

The introduction of a movement prohibition and a drop in R below 1 are marked with a red and green line. An international group of the London School of Health and Tropical Medicine made this calculation, in which a member of the Croatian Scientific Council also participated. Somehow they later forgot to let us know that R had already fallen below 1 even then. However, at the beginning of the epidemic, everything was explained with its help, which advanced countries are doing now. From a time perspective, all of this is now obvious, and that first wave seems completely benign compared to this one now.

But let's remember the psychosis in which we lived then when the concept of "Camp Croatia" with GPS tracking and leaving the house every third or fifth day was already announced when the epidemic was already falling. Inexperienced and impressed by the violent measures, we thought they helped.

But why did the epidemic come later? Here I think the key is in international connectivity. I used an imperfect DHL connectivity index and got a great explanation of the difference, which can be seen in the following chart.

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Graph 6. Source:

Interestingly, even such an imperfect measure of connectivity explains so much of the variation. As we know, the most affected countries are also the most connected: Italy – densely populated Lombardy and workers from China; Italy, France, Spain – tourism; Belgium – the center of the European Union and others; Sweden – far more connected than its neighbors; and a million Swedes went on school holidays abroad in the last week of February.

  • B. The first wave was actually far stronger than it seems now because we tested and hunted cases much less. Many countries found that their dark number (undiscovered cases) was several tens of times higher than those found. In our country, depending on the interpretation of the data, 50 to 80 times, in Denmark 80 (at some point). Now the dark number is probably 5 to 10 in most countries, and the current maybe even just 3 because as more and more people are being tested, and more and more people have been exposed to the virus, the significant dark number has nowhere to hide.

Therefore, most of the countries of old Europe became infected in the spring, a part of the population gained immunity, and significantly more than in the NE, which we cannot see well if we look only at the cases.

  • C. It is now quite clear that strongly seasonal is not only an epidemic of SARS-CoV-2 virus but also COVID-19 disease. Clinical pictures are, on average, far more difficult now than a month or two ago. Mortality rates in most EU countries have doubled in just a month or two, meaning twice as many people die among those confirmed infected. It is also the insight of an international group of scientists in which Croatians Gordan Lauc, Alemka Markotić, Dragan Primorac, and others also participated. At first, it was controversial, but now it is generally accepted. Those infected in spring (more in the old than in the NE) had a much better chance of surviving.
  • D. One explanation indeed lies in the quality of hospital systems. I believe richer countries have more resources. For example, expensive HFOT devices save lives better than respirators (Croatia has now procured a larger quantity).
  • E. Other variables could be considered, such as previous flu seasons, the percentage in the population over 80, or the people in nursing homes. Still, I believe they would indicate a lower expected number of deaths in the NE (but I did not check the data).

In general, the NE countries, including Croatia, were not particularly unprepared for the supposedly expected strong second wave. Let's look at how strength and early outbreak surprised even the most advanced countries, with entirely different strategies: from Germany through Denmark and the Netherlands to Sweden. Remember that in almost all countries, politicians said "let's just wear masks, and we won't need any special measures," then "let's introduce some measures, and we certainly won't need lockdown," and so on. Now we have reached a solid lockdown in almost the entire Union.

Even Germany, the first wave model, is experiencing a real drama after a failed soft lockdown that was supposed to ensure a peaceful Christmas. Denmark and some other countries are already overtaking us in terms of the number of infected. It is not impossible for Germany to overtake us, even in terms of deaths.

In some countries, a third or "second B" wave is already being born, under the influence of winter COVID-19. R is contextual, and even if it falls below 1, under the influence of various circumstances, it can return over 1. It seems that our second wave peak was delayed by merging with that (surprising to all) the third wave.


  • The development of the epidemic is mostly beyond the reach of the authorities.
  • Countries with stronger measures do not fare better than those with weaker ones. For example, Slovenia is the worst in this group, despite introducing extreme measures before the epidemic escalated.
  • The introduced travel ban is not useful. The inspiration for it was the spring ban, which was considered our most important measure, and obviously did not affect the epidemic.
  • On the whole, we are not somewhat more unsuccessful than others. Indeed, although some have had significantly stronger measures for longer (this is one group we can compare ourselves to, and the other is our neighborhood shown in Graph 7, and only Serbia is better than us), we should consider any success or failure relatively. It is known that some measures work, such as banning gathering, maintaining physical distance, washing hands, ventilation, etc. The introduction of measures should be proportionate to the goal because the disproportionate introduction of measures has severe negative consequences for society. Countries that introduce brutal and unnecessary measures (there are arguments that some brutal measures even encourage an epidemic) can also cause significant collateral damage to their populations' lives and health.


Graph 7. Showing data from October 6, 2020 to December 19, 2020. Source:

Let's not forget, the goal in epidemic control is to bring the reproductive factor R below 1, and "zero-covid" strategies have long since been abandoned. Fortunately, in Croatia, R is currently significantly below 1. Let's hope that the data on the epidemic we have are credible and that such a situation will persist.

Of course, the main goal is to save as many lives as possible, although we are often helpless with the virus. Therefore, it is necessary to adhere to epidemiological measures with enhanced protection of vulnerable groups.

To read more about coronavirus in Croatia, read TCN's dedicated page.