Monday, October 26, 2020

The Pandemic: Did They Hide the Truth from us?


Have you ever thought of governments as if they were human beings? In that case, you would want them jailed, or even shot by a firing squad. Governments normally engage in murder, genocide, theft, torture, terrorism, and more, but what they are truly specialized in is lying. Truly their second nature, just think of the story of the "weapons of mass destruction" in Iraq. So, there is an interesting question to ask, could it be that they lied to us also about the coronavirus pandemic? 

In the article below, I engaged in an examination of the consistency of the data we have for the pandemic. It turns out that, for Western countries, the data are almost always correct, with just a few possible exceptions, mainly Belarus. It seems that it is easier for governments to use their propaganda machines to terrorize people about the pandemic, rather than actually falsifying the data, with all the risks involved if discovered.


Post published on October 2, 2020, on "Pillole di Ottimismo" (slightly adapted for an international readership)

Note: Since the publication of the original version of this post on Facebook, three weeks ago, the situation in Belarus has not changed substantially, at least in terms of the data reported by the government. We see a modest increase in the virus diffusion and a mortality that remains very low, around 4-5 deaths per day.

By Ugo Bardi, Department of Chemistry of the University of Florence. (1)

💊💊💊There are many legends about the Covid-19 pandemic. Governments are said to have kept quiet about the true extent of the epidemic to avoid panic, or, on the contrary, that the damage caused by it has been exaggerated in order to scare us. However, if we analyze the data, we see that they are on the whole reliable, except in some particular cases. 💊💊💊

It is sometimes said that "if you think ill of someone, you are usually right." It's probably true, but if you follow the rule literally you risk getting lost in the silliest kinds of conspiracy theories, from the story of the moon landings hoax to chemtrails and more. But if we take the sentence as an invitation to verify everything they tell us, then it is a useful invitation to prudence.

In the case of the COVID-19 pandemic, there has been no shortage of speculations and legends. One is that the virus would have claimed many more victims than those indicated by the official data, but that governments hid the truth in order not to cause panic. The other is the exact opposite and it says that the pandemic does not exist, except as an invention concocted by evil governments in order to establish a dictatorship.

Let me tell you right away that the available data show that these are only legends, at least for what concerns Europe and the Western world. But it is still an interesting exercise to go into the details and see how things stand.

We can start by saying that it is never possible to say with absolute certainty whether something is true or false: a classic example is that it is not possible to prove that unicorns do not exist. But it is possible to rely on the idea that if something is true it must be confirmed by more than one independent set of data.

In the case of the COVID-19 pandemic, we are faced with a fairly new event, so that the datasets we can compare are not so many. But we can reason that the pandemic should have caused a significant increase in overall mortality. So, we can verify the consistency of two datasets: the excess mortality must confirm that the epidemic has caused victims.

Perhaps you remember that in Italy, in March, someone who used this method to argue that the epidemic did not exist. Alas, if you want to be a good debunker you need to have a minimum of competence in handling data. As I wrote in a post of mine a few months ago (2), the alleged demonstration of the non-existence of the pandemic was simply a mistake based on incorrect data.

Fortunately, good data are available and we can find them, for example, in a dataset of 24 European countries provided by "Euromomo," European Mortality Monitor, an agency that works in collaboration with the WHO (World Health Organization). In these data for Italy, you see very well the excess mortality that corresponds to the effect of the pandemic. (3).
You see how the mortality peak matches well with the epidemic phase of COVID-19. It is more intense than other seasonal peaks related to respiratory diseases. This tells us that the epidemic has taken place and has hit hard, it was NOT a government invention to cheat us!

There is no need to go into a quantitative comparison between total mortality and the COVID mortality (for a discussion, read this interesting article in Nature (4)). Let's just note that the European countries covered by the Euromomo network have similar social and health structures, so we expect them to give similar results in terms of the ratio between total excess mortality and mortality attributed to COVID.

So, let's put the data all together in a graph. 
On the X-axis I placed the Euromomo mortality data, measured as the height of the peaks. It is an approximation, but sufficient for what we want to see. On the Y-axis, I placed the data for the COVID-19 deaths per million people. Notice how there is a certain proportionality: the majority of the points remain in the vicinity of an average value represented by the line passing through the graph. (note that the line does not indicate the "right" values. It is simply an average obtained by numerical regression). 
Some countries, such as Belgium, seem to have exaggerated in attributing deaths to Covid-19, while others, such as Greece, have been much more cautious in their diagnoses (perhaps too much). In any case, there is a certain agreement between the two datasets, even if not perfect. It is a good indication that the data are reliable within the limits of the uncertainty of this type of measurement.

But what happens outside of Western Europe? There are many cases in global data where it is difficult to trust the data provided simply because certain countries are too poor to afford a reliable monitoring system for the outbreak. There is, however, an interesting case to which I would like to draw your attention: that of Belarus.

Belarus is a European country, although not part of the European Union. Therefore, we would not expect great differences compared to the rest of Europe. But Belarus has the distinction of being one of the few countries in the world, perhaps the only one in Europe, to have taken almost no precautions regarding the epidemic (5). No lockdown, no distancing, no masks, nothing like that. President Lukashenko explicitly stated that in Belarus everything should continue to be done as before, epidemic or not.

Despite the lack of containment measures, the official data indicate that Belarus has been very scarcely affected by the COVID-19 outbreak. The government reports a total mortality of just 89 deaths per million people, which is six times less than the value for Italy. But can we trust the official data?

Returning to the principle that we shouldn't trust anyone, let's say that some doubts about the validity of the data coming from Belarus are legitimate. To try to verify how things stand, I placed the data for Belarus in the same graph for other European countries (see the figure above). Note that Belarus is not among the countries monitored by Euromomo, so I had to make an estimate starting from the excess mortality data reported by Mastitsky (6) (I took a value of 6000 excess deaths), assuming that the proportionality with the Z-score it is the same as for other European countries. The official Covid mortality for Belarus, on the other hand, is found in the most common databases. The result is that the point for Belarus is clearly an outlier on the graph

Is this enough to conclude that the COVID mortality data for Belarus have been altered? No, because the data on excess mortality come from non-validated sources and, as we said, it is good not to trust anyone. Let's say we have an indication that something is wrong. And other data are pointing in the same direction.

Do you remember what I told you in the previous posts? The epidemic diffusion curves are usually "bell-shaped" (not necessarily symmetrical) or sometimes appear as a superposition of bell curves. Now, if you look at the curve for the positive cases in Belarus (see below) you see that it is not exactly "bell-shaped", as in the case of Italy and many other countries. The central part is flattened and the result is something that is shaped like a hat. Also, look at the scale and notice how the curve never surpasses 1000 cases per day, it always stops a little lower. Let's say this is a little suspicious. It looks like someone told to the persons collecting these data, "we must not go above 1,000, or else....."


If we then look at the death curve, in Belarus, it is flat with an almost constant value of 5-6 deaths per day. We can also see this as a little unlikely.
Finally, I can tell you that I performed a validity test using "Benford's Law" which is a statistical method to check if the data has been manipulated. The results are not to be taken as anything conclusive, just an indication, but they do tell us that there may be something wrong in a dataset. So, it turns out that the Belarusian data do not follow Benford's law and therefore are suspect (the data I got from WHO, the Benford test I did by using the website (7)). Incidentally, I can tell you that Italy gives the "right" Benford test result - no indications of cheating.

Taken together, these results tell us something. As I told you before, it can never be proved with absolute certainty that a unicorn does not exist, and it is the same for data manipulation in Belarus. But we can have some legitimate doubts: the data coming from Belarus may well have been doctored a little to play down the extent of the epidemic.
However, note also that there is a limit to how much you can lie with the data. Even the work of Matsitsky (6), who is very critical of the Belarus government, does not come to the conclusion that the epidemic has done catastrophic damage. According to his data, the mortality was about the same as in Italy and other Western European countries.

If then it is true that Belarus has fared no worse than other countries even without containment measures, some might be tempted to conclude that the lockdown is useless but, beware: it is definitely not the case to launch into global generalizations starting from a small country of which we have only uncertain data. Among other things, if we consider the median age of the population, it is 45 in Italy against 40 in Belarus. This means that there is a much smaller number of elderly people in Belarus who, as we know, are the most vulnerable to COVID-19. An assessment of the effectiveness of the lockdown will require a much more complete comparison of data and we can only do it in the future.

I have dwelt on the case of Belarus to show you how even for a national government it is not easy to cheat on data without being discovered or, at least, without arousing suspicion. If other states had done so, someone would have noticed. On this basis, we can say that the data on the pandemic that the various government agencies provide are on the whole reliable, at least in Western Europe.

So, here with us there is no reason to get carried away by the idea that the pandemic is a conspiracy of the powers that be, nor to panic at the suspicion that things are wor
se than they appear. This is not to say that the media can't exaggerate the way they present the data to make it look more catastrophic than it is. Indeed, they almost always do that out of sensationalism. So, to find out how things are really going, you need to be careful and check more than one source of data, if possible. If you are interested in Italy in particular, I suggest reading Paolo Spada's daily "Pills" (8) as an antidote to media exaggeration.


Ugo Bardi is a member of the Club of Rome, faculty member of the University of Florence, and the author of "Extracted" (Chelsea Green 2014), "The Seneca Effect" (Springer 2017), and Before the Collapse (Springer 2019)