This Russian article received half a million views just in few days — Worth reading.

Media irresponsibly continues to fill our space with news about victims of coronavirus, although neither data from doctors nor WHO supports this information. Journalists de facto independently name the causes of death while scientific community silently let them. This manipulation with data takes a toll on society. Today, it is extremely important not to confuse all-cause mortality (with cnfirmed coronavirus) with mortality caused by coronavirus.

While the true mortality of COVID-19 will take some time to fully understand, the data we have so far indicate that the crude mortality ratio (the number of reported deaths divided by the reported cases) is between 3–4%, the infection mortality rate (the number of reported deaths divided by the number of infections) will be lower — World Health Organization.

We have all seen frightening numbers of deaths among those who tested positive for COVID-19. But the high percentage of mortality that we observe is an illusion — for the most part, we look at background mortality, which would have happened without infection, because something else was the cause. That is, the death rate from infection is multiplied by the natural one, and we see the result of this multiplication, although we need to look at the quotient.

Roughly speaking, death is a natural event in every person, and many people with coronavirus who had gone to another world would have died sooner or later. We don’t know how many, but we can calculate the risks based on probability theory. To do this, we need to compare the overall mortality with mortality in the presence of infection. And it has already been done by David Spiegelhalter (one of the world’s foremost statisticians).

Comparing annual mortality rate and mortality rate among people tested positive for COVID-19, we clearly see that the curve shapes are identical. And the ratio between the absolute values varies from 0.5 to 2, and in the age group under 50 it is on average less than 1. Consequently, the background or natural mortality of people is often even greater than the one with coronavirus.

How can we compare the annual value and data for a new virus, which is only a few months old?! — There were many such comments on my last article. Some even suggested that mortality caused by coronavirus should be multiplied by a quotient between 12 months and a certain time period for infection. Many misunderstand the meaning of the interval and confuse sweets with sugar. Probabilities work differently.

Equality between mortality rates doesn’t mean that coronavirus kills as many people during an epidemic as all other diseases in a year. These are different probabilities. By the way, extensive myocardial infarction mortality will be significantly greater than COVID-19 mortality.

Equality between the coefficients means that the probability of dying from coronavirus equals to the probability of not living another year. In other words, the risk of dying from a new infection is equal to the risk of daily life throughout the year. Those who are convinced of the opposite forget that firstly you have to get infected with the virus and only then to die from it.

It’s important to note that all the risks quoted are the average (mean) risks for people of the relevant age, but aren’t the risks of an average person! This is because, both for COVID-19 and in normal circumstances, much of the risk is held by people who are already chronically ill. So for the large majority of apparently healthy people, their risks of either dying from COVID-19, or dying of something else, are much lower than those quoted here.

That is why David Spiegelhalter in his article speaks about the importance of spreading the infection in order to avoid overloading the national healthcare system, which could lead to an increase in background mortality. And here an extremely difficult dilemma arises. Many people call to flatten the curve in order to evenly distribute the burden on the health system. However, tough suppression measures and vigilant surveillance directed on every person who coughed once also overload this system.

But what if it is much more difficult to predict reality than it seems and all the models showing scary exhibitors are lying shamelessly?

Chthonic abyss in Italy

I think many of you have heard stories about crowded morgues and that utter horror happening on the land of Michelangelo. But let’s think in defined categories, and not give away to the panic in social networks. Coronavirus didn’t arrive in Europe yesterday and we have a chart with the number of deaths that includes the first 12 weeks of 2020.

Does anyone observe new extreme points? Now let’s look at a similar chart specifically for Italy, which was also prepared by researchers from EuroMOMO.

Looking at the image above, we clearly see that the new peak value is at the same level as the flu epidemic in winter 2016. Yes, the data may come with a delay, but keep in mind that fear-mongers claim that the real distribution of coronavirus is much wider. And this is indeed so — the official statistics are objectively unable to take into account all cases of infection.

Therefore, some people can quote as much as they want the words of the mayor of Bergamo about the deaths toll of unknown causes in his small town, but the fact remains that the number of people died in Italy in early 2020 doesn’t exceed the numbers in the beginning of 2017. A retrospective analysis of that dangerous winter demonstrated 25,000 excess deaths. And here arises the question: how come in 2017 Italian healthcare system worked stably and didn’t require the emergency measures that are being taken today?

According to WHO data from March 31, more than 100,000 coronavirus infected were detected in Italy and 11,000 deaths were recorded among them. At the same time, the hospital bed fund exceeds 200,000 beds. China’s experience shows that hospitalization is required for 13.8% of infected people, and intensive care is required for 4.7%. Let’s round the first value to 15%. That is about 15,000 people needed hospitalization.

How could 7.5% of the non-simultaneous burden on the health system cause such a critical destabilization of this system?

Don’t forget that I provided the numbers for the last day of March, and problems in medical institutions in Italy began much earlier. Therefore, I unequivocally claim that the overload is caused not by the number of people who need treatment, but by an excessive amount of effort to establish a diagnosis. If doctors in 2017 began to put everyone in the hospital with suspected flu, then the collapse would be even larger.

The measures that are being taken limit the resources of the national healthcare system which is more like using a sledgehammer to crack a nut. In California, for example, there was an acute shortage of nurses because quarantine forbids students from practicing in hospitals. In Germany, doctors with a positive COVID-19 test result have to self-isolate even if they don’t have any symptoms. I am sure that such contradictions can be witnessed everywhere.

Furthermore, there is also the risk of the so-called hospital-acquired infection or nosocomial spread. According to NNIS estimates, nearly 2 million cases occur in the USA each year, resulting in 99,000 deaths, a third of which are associated with pneumonia! Just think about the potential degree of the absurdity of what’s happening.

Countries rushed to save the population from the pseudo-bubonic plague of our time which is threatening the entire health care system. However, today there is no clear evidence that a new disease is more dangerous than flu. Mankind allowed itself to think that it is able to predict the future and came up with computer models and frightening exhibitors which gave grounds for full-blown nosophobia.

With all the current technologies and a centuries-old dataset of climate information, our weather forecast doesn’t always coincide with reality. The quality, completeness, and volume of data is fundamental, and in the case of pandemic none of the above is available to us. By the way, there is a very good article that shows how from a supposedly simple and obvious model with the multiplication of three easily measurable digits, the task turns into a difficult cohort analysis with dozens of factors and a high uncertainty coefficient.

Millions of people believed in the dubious result of computing, while the scientific community didn’t reach consensus so far. Yet researchers themselves speak of nonidentifiability in model calibrations and too high level of variability. Therefore, the main problem is not scientists, but the thoughtless interpretation of their works by journalists and pseudo-experts from social networks.

Cumulative cognitive bias

It is known that it all started with China. Statistics on coronavirus in China became the basis for making first decisions in many countries. On March 31, the head of the Disease Control Department of the State Health Committee of the PRC, Chiang Jile, told The Wall Street Journal that starting April 1 they will begin to publish data on asymptomatic infected people.

My surprise with this news cannot be expressed in standard language. So, before we observed statistics only for those Chinese who had symptoms? Can you imagine what asymmetry in the data this caused? In this case, our idea of mortality is overstated by multiple! However, I admit the possibility of understatement or taking words out of context on journalists’ part. Therefore, let’s talk a little about something else.

Is it possible that the Italians 10 times more susceptible to the virus than the Germans? In pursuit of confirmation of this hypothesis, many stories have already appeared on the web with discussions about national immunity and vaccination. But I challenge this way of thinking, for the main difference must be sought in the source data.

If we study the statistics of the two countries on inhabitants with a positive test, we will see that in Italy, 55% of infected are over 60, in Germany, they are only 24%. According to the latest data of the Italian National Health Institute ISS, the average age of the positively-tested deceased in Italy is currently about 81 years. 90% of deaths correspond to the age group over 70 years. How much do you think one is related to another?

For some, the explanation for this situation will probably be the statement that the elderly age group is at risk. This thesis came to us from China. But I’ve already told you about background mortality and its interpretation. The older the person, the greater the likelihood of their death. For example, at the age of 85, the chance of not attaining the age of 86 is about 10%, without any viruses.

Equally important, 80% of the deceased had suffered from two or more chronic diseases and less than 1% of the deceased were apparently healthy persons, i.e. persons without pre-existing chronic conditions. However, let’s still look at the dynamics of the number of deaths among the Italians aged 65 years and older from the local Ministry of Health.

Does it turn out, that all the media tell us that pensioners drop like flies from coronavirus, but the absolute number of deaths in this age group during the period of influenza epidemic 2016–2017 was much greater? The false opinion is so widespread that I won’t be surprised if the objective reality raises doubts and the question “why are we being deceived?”.

Throughout the story, I operated only on dry facts, but now I will allow myself one assumption. Society independently misleads itself and does so unconsciously. One case seemed specifically remarkable to me when in Los Angeles, a 33-year-old woman was refused a COVID-19 test because she was not elderly or otherwise a high-risk patient.

It is obvious that any disease is better tolerated by a young. Believing that coronavirus poses a greater danger for the elderly and testing them first, all we do is contributing to confirmation of this thesis. This is like confirmation bias on a macro scale. And there is no better illustration of this than the one you are now seeing on the screen.

The Netherlands only looks into severe cases, and Iceland tests everyone, even asymptomatic ones. Who do you think will have more mortality among older people with confirmed COVID-19? I also remind you that coronavirus may not be the only cause for complications among those who tested positive in the Netherlands. Thus, the general picture of the world can be distorted beyond recognition.

If I test only the Lombardi grandfathers with a cough brought to me by ambulance, then the mortality rate in this group would at its highest. It’s known, the initial probability of death for a person who has visited a medical facility independently is much greater than that of someone who arrived in an ambulance. Such flexibility of statistics is surprising.

Most people, looking at the increasing number of infected people, associate it primarily with ongoing epidemic. But the latest data from the German Robert Koch Institute show that the increase in test-positive persons is proportional to the increase in the number of tests, i.e. in percentage terms it remains roughly the same.

Apotheosis

There is no methodological integrity in the data. It is not certain whether journalists are right about the changes in Chinese calculations, but the fact that this has become news for WSJ, Financial Times, Bloomberg, The Hill, and others is a huge problem in itself. There should be a common standard and unified approach in statistics, but we face the ambiguity of terms. Nevertheless, the world believed in apocalyptic models built from this mess of a data provided by WHO.

Note that up to this point I have discussed the feasibility of measures to control coronavirus without taking into account the cost of these measures. Now it’s time to talk about the damage to economy. In connection with global quarantine, Goldman Sachs forecast a decline in US GDP in the second quarter to 24%. Morgan Stanley predicts a 30% reduction in GDP with an increase in unemployment rate to 12.8% from the current 3.5%.

The number of jobless claims in the United States has reached an absolute peak for the entire existence of the labor exchange. This had happened a week ago, and yesterday that peak doubled. For those who see just a curve in the image, I’ll say that I see great sorrow, alcohol abuse, crimes, death, decline of birth and many more. Forgive me such a risky comparison, but for me, this curve isn’t less scary than some footage of September 11.

I understand that all of the above clashes with today’s news agenda. But I am trying to carefully talk about what has already happened so far, while everyone who has watched an introductory course on computer modeling or just knows how to multiply three parameters, confidently talks about what will be in the future. I also understand that for many people credentials are often more important than common sense. Therefore, I share a summary of professional opinions.

German immunologist and toxicologist, Professor Stefan Hockertz, explains in a radio interview that COVID-19 is no more dangerous than influenza (the flu), but the former is simply observed much more closely. More dangerous than the virus is the fear and panic created by the media and the “authoritarian reaction” of many governments.

The Argentinean virologist and biochemist Pablo Goldschmidt explains that COVID-19 is no more dangerous than a bad cold or the flu. It is even possible that the virus circulated already in earlier years, but wasn’t discovered because no one was looking for it. Dr. Goldschmidt speaks of a “global terror” created by the media and politics.

Professor Martin Haditsch, a specialist in microbiology, virology and infection epidemiology, sharply criticizes the COVID-19 measures. These are “completely unfounded” and would “trample on sound judgment and ethical principles”.

The renowned Italian virologist Giulio Tarro argues that the mortality rate for COVID-19 is below 1% even in Italy and is therefore comparable to influenza. The higher values only arise because no distinction is made between deaths with and by COVID-19 and because the number of (symptom-free) infected persons is greatly underestimated.

Sweden has so far pursued the most liberal strategy in dealing with COVID-19, which is based on two principles: Risk groups are protected and people with flu symptoms are kept at home. “If you follow these two rules, there is no need for further measures, the effect of which is only marginal anyway,” said chief epidemiologist Anders Tegnell.

John Lee, Professor Emeritus of Pathology, argues that the particular way in which coronavirus cases are registered leads to an overestimation of the risk posed by COVID-19 compared to normal flu and cold cases.

The German Network for Evidence-Based Medicine (EbM) criticizes the media reporting on COVID-19: “The media coverage does not in any way take into account the criteria of evidence-based risk communication that we have demanded. The presentation of raw data without reference to other causes of death leads to an overestimation of the risk”.

German researcher Dr. Richard Capek argues that the “Corona epidemic” is in fact an “epidemic of tests” based on the results of a quantitative analysis. Capek shows that while the number of tests has increased exponentially, the proportion of infections has remained stable and mortality has decreased, which speaks against an exponential spread of the virus itself.

German Virology professor Dr. Carsten Scheller from the University of Würzburg explains in a podcast that COVID-19 is definitely comparable with influenza and has so far even led to fewer deaths. Professor Scheller suspects that the exponential curves often presented in the media have more to do with the increasing number of tests rather than with an unusual spread of the virus itself.

The two Stanford professors of medicine, Dr. Eran Bendavid and Dr. Jay Bhattacharya, explain in an article that the lethality of COVID-19 is overestimated by several orders of magnitude and is probably only at 0.01% to 0.06% even in Italy, and thus below that of influenza.

According to Stanford Professor John Ioannidis, the new coronavirus may be no more dangerous than some of the common coronaviruses, even in older people. Ioannidis argues that there is no reliable medical data backing the measures currently decided upon.

Professor Sucharit Bhakdi has called lockdown measures “useless”, “self-destructive” and a “collective suicide”. Thus, the extremely troubling question arises as to what extent the increased mortality of these elderly, isolated, highly stressed people with multiple pre-existing health conditions may in fact be caused by the weeks-long lockdown measures still in force.

It just great luck that I met all the statements on the website of Swiss Propaganda Research.

Thank you for reading to the end. The only purpose of my article is to call for discussion. If you agree with the logic of the story, then do not be too lazy to share this article with your friends.

Best regards, Ilya Pestov.