Forgotten “Primum Non Nocere” and Increased Mortality after Covid-19 Vaccination

1. Introduction

Alive people in a given country are set “alive”. In this set, we have a subset of “vaccinated”. As people are dying in a given time period, we have a set of dead persons. In this set, we have a subset of vaccinated persons. In case vaccines have no impact on the death rate following equation is valid:

$$\frac{\mathrm{vaccinated}\left(\mathrm{A}\right)}{\mathrm{alive}\left(\mathrm{B}\right)}=\frac{\mathrm{dead}\mathrm{vaccinated}\left(A^{*}\right)}{\mathrm{total}\mathrm{deaths}\left(B^{*}\right)}.$$

(1)

We calculate the proportional number of dead vaccinated as follows:

$$\mathrm{dead}\mathrm{vaccinated}\mathrm{proportional}\mathrm{number}{A}^{*}= \frac{\mathrm{vaccinated}\left(\mathrm{A}\right)\ast \mathrm{total}\mathrm{deaths}\left(B^{*}\right)}{\mathrm{alive}\left(\mathrm{B}\right)}.$$

(2)

The proportional number for a given time period should be always bigger than the statistical number of dead vaccinated. In this case, vaccines are saving lives. If the proportional number will be smaller than the statistical number, vaccines are increasing the death rate. This calculation should be done for each month of the year 2021 for 5 age groups: up to 20 years, from 20 to 40, from 40 to 60, from 60 to 80, and above 80. In this way, the so-called Yule-Simpson effect in statistics is excluded. These precise statistical analyses would give us a highly precise result of how massive vaccination decreases the rate of deaths of the entire population, preventing people from dying because of covid. Or eventually, the opposite result is how massive vaccination increases the death rate of the entire population. Results of insurance company OneAmerica are not encouraging: “The head of the insurance company OneAmerica stated that their data indicated that the death rate for individuals aged 18 to 64 had increased 40% over the pre-pandemic period. Scott Davidson, the company’s CEO, stated that this represented the highest death rate in the history of insurance records, which does extensive data collection on death rates each year. Davidson also noted that this high death rate increase has never been seen in the history of death data collection. Previous catastrophes of monumental extent increased death rates by no more than 10 percent, 40% is unprecedented [1]. It is becoming clear that the Covid-19 vaccination analysis might not get the expected results.

There are no “hidden variables'' that could influence the result of the calculation proposed in this article. Vaccinated and non-vaccinated people in a given country are eating the same food, drinking the same water, breathing the same air, and watching the same TV programs. The only reason that could impact their health status is the Covid-19 vaccination.

At this point, the crucial question is arising: is the Covid-19 vaccine saving more lives or causing excess deaths because of numerous heavy adverse reactions? Research published in NATURE states that the difference in the spread of the virus between those who have been vaccinated and those who have not been vaccinated is negligible [2]. A recent article in LANCET is confirming that Covid-19 is spreading at a similar rate between unvaccinated and vaccinated: “This study showed that the impact of vaccination on community transmission of circulating variants of SARS-Cov-2 appeared not to be significantly different from the impact among unvaccinated people” [3].

Preliminary research on the effectiveness of Covid-19 vaccination is not encouraging. Research done by Ingrid Tojersen has shown that the Covid-19 vaccination has been causing the deaths of the elder population [4,5]. Research done by Sivan Gazid and co-authors is confirming that the natural immunity of unvaccinated people is far better protection than Covid-19 vaccines [6]. At this point, it is clear that it is necessary to calculate the effectiveness of Covid-19 as we are proposing. BMJ editorial is suggesting, that for the rigorous mathematical evaluation of covid vaccine efficacy we need row data [7]. We could calculate the exact impact on the entire population in a given country and worldwide if we would have data on how many people who died in a given time period of one month have been at least once vaccinated. This would allow calculating the proportional number of “dead vaccinated” and comparing it with the actual statistical number of dead vaccinated people.

In each company or governmental agency, we can calculate the effectiveness of the Covid-19 vaccination by comparing the days of work with the sick status days in percentage in a given month or year:

Working days of vaccinated workers in one month…………. 100%

Sick days of vaccinated workers in one month…………… X%

$$X{\%}_{ }=\frac{N_{sick days of vaccinated workers}\ast 100}{N_{working days of vaccinated workers}}$$

(3)

Working days of nonvaccinated workers in one month…………. 100%

Sick days of nonvaccinated workers in one month…………… Y%

$$Y{\%}_{ }=\frac{N_{sick days of nonvaccinated workers}\ast 100}{N_{working days of nonvaccinated workers}}.$$

(4)

In a given company, we can easily see which percentage of sick days is higher. Let’s imagine we have a company with 100 employees. 50% of them are vaccinated, and 50% of them are not vaccinated. Vaccinated workers are protected from Covid-19, and should have a much smaller percentage of sick days than nonvaccinated workers. According to the Covid-19 vaccination doctrine percentage of sick days should be much smaller in the vaccinated group of people than in the non-vaccinated group of people.

In Slovenia and worldwide, we observe a highly increased number of dead-born babies in 2022 respect to the previous years. The first check that should be done is the possible influence of Covid-19 vaccination. The number of death-born babies $X_D$ is the sum of the following numbers:

$$X_D= X_6+ X_5+ X_4+ X_3+ X_1 + X_0,$$

(5)

where $X_6$ is the number of dead-born babies where both parents are each three times vaccinated, where $X_5$ is the number of dead-born babies where one parent is three times vaccinated, and another parent is two times vaccinated (and so on), where $X_0$ is the number of dead-born babies where both parents have not been vaccinated. Using this model, we could see possible relations with the Covid-19 vaccination. EMA, VAERS, and the Yellow card reports on high numbers of vaccines’ side effects [8,9,10] are alarming bells for detailed analysis proposed in this article.

A recent article in Vaccine (Elsevier) is confirming the excess risk of serious adverse effects: “Pfizer and Moderna mRNA COVID-19 vaccines were associated with an excess risk of serious adverse events of special interest of 10.1 and 15.1 per 10,000 vaccinated over placebo baselines of 17.6 and 42.2 (95 % CI −0.4 to 20.6 and −3.6 to 33.8), respectively. Combined, the mRNA vaccines were associated with an excess risk of serious adverse events of special interest of 12.5 per 10,000 vaccinated (95 % CI 2.1 to 22.9); risk ratio 1.43 (95 % CI 1.07 to 1.92)” [11]. The article reported that the excess risk of Adverse Effects of Special Interest (AEIs) was higher than the risk reduction for covid-19 hospitalization: “In the Moderna trial, the excess risk of serious AESIs (15.1 per 10,000 participants) was higher than the risk reduction for COVID-19 hospitalization relative to the placebo group (6.4 per 10,000 participants). In the Pfizer trial, the excess risk of serious AESIs (10.1 per 10,000) was higher than the risk reduction for COVID-19 hospitalization relative to the placebo group (2.3 per 10,000 participants)” [11].

Theoretical research published back in 2021 has estimated that Covid-19 will diminish the death rate [12]. The proposed statistical analysis presented in this article can verify the theoretical study of how many lives were saved by covid vaccines in a particular country not only for ages above 60 but for the entire population.

2. Calculations of the death rate of the infected vaccinated group and infected non-vaccinated group using official data of the UK HEALTH SECURITY AGENCY

In the calculations, we compare the sample $A/B$ of the entire population with the sample $A^{*}/B^{*}$ in the dead group of persons.

$$\frac{vaccinated \left(A\right)}{alive\left(B\right) }=\frac{vaccinated dead\left(A^{*}\right)}{total dead\left(B^{*}\right)}$$

(1)

Formula (1) is valid for big numbers statistics; it gives exact results. As medical authorities are hiding the vaccination status of dead persons $A^{*}$ this cannot be done for now. But we find out official data in England about the infected dead group $B^{*1}$ and we can write following equation:

$$\frac{vaccinated dead\left(A^{*}\right)}{dead\left(B^{*}\right)}= \frac{infected vacinated dead\left(A^{*1}\right)+noninfected vaccinated dead\left(A^{*2}\right)}{ infected dead\left(B^{*1}\right)+ noninfected dead\left(B^{*2}\right)}$$

(6)

The problem is that for non-infected vaccinated dead $A^{*2}$ we have no data because medical authorities are not providing vaccination status of dead persons for public use. Supposing the group of infected vaccinated people $A^{*1}$ is dying with a similar rate as the group of non-infected vaccinated people $A^{*2}$ (vaccines are equally protecting both groups, they are declared 95% effective by the producers), we can write the following equation:

$$\frac{A^{*1}}{B^{*1}} \approx \frac{A^{*2}}{B^{*2}}.$$

(7)

Out of (7) follows:

$$\frac{vaccinated\left(A\right)}{alive\left(B\right)}=\frac{vaccinated dead\left(A^{*}\right)}{dead\left(B^{*}\right)}=\frac{infected vaccinated dead\left(A^{*1}\right) }{infected dead\left(B^{*1}\right)}=\frac{noninfected vaccinated dead\left(A^{*2}\right) }{noninfected dead\left(B^{*2}\right)}.$$

(8)

Out of (8) follows following equation:

$$\frac{vaccinated\left(A\right)}{alive\left(B\right)}=\frac{infected vaccinated dead\left(A^{*1}\right) }{infected dead\left(B^{*1}\right)}.$$

(9)

In statistics of England, we have data of the number of infected vaccinated dead and we have data of infected dead $B^{*1}$. Using equation (10) we calculated proportional number of infected vaccinated dead $A^{*1}$ and we compare it with the real statistical number of infected vaccinated dead. In this way we get percentage of decreased or increased mortality rate caused by vaccination. The proportional number $A^{*1}$ is the number, where there is no impact of the vaccination on the death rate. When 10% of the population is vaccinated in the group of Sars-Cov-2 infected dead persons $B^{*1}$, 10% will be vaccinated. When 20% of the population is vaccinated in the group of Sars-CoV-2 infected dead persons $B^{*2}$, 20% will be vaccinated, and so on. When 100% of the population is vaccinated in the group of Sars-CoV-2 infected dead persons $B^{*2}$, 100% will be vaccinated.

Now we will compare the numbers of Sars-CoV-2 infected vaccinated dead persons in official statistics with the Sars-CoV-2 infected vaccinated deaths proportional number $A^{*1}$. The statistical number of Sars-CoV-2 infected vaccinated dead persons must be lower than the proportional number $A^{*1}$ In this case, vaccines are saving people’s lives. We can calculate how many Sars-CoV-2 infected persons have been saved from death with vaccination in a given 4 weeks by the following equation:

$$\mathrm{saved}\mathrm{lives}=A^{*1}-\text{Sars-CoV-2 infected vaccinated deaths in statistics}$$

(10)

In case, that the statistical number of Sars-CoV-2 infected vaccinated dead is bigger than the proportional number $A^{*1}$, vaccination has a negative impact on mortality rate, it takes lives, some people have died prematurely because of being vaccinated:

$$\mathrm{lost}\mathrm{lives}=\mathrm{Sars}-\mathrm{CoV}-2\mathrm{infected}\mathrm{vaccinated}\mathrm{deaths}\mathrm{in}\mathrm{statistics}-A^{*1}$$

(11)

3. Discussion

Results of insurance company OneAmerica are not encouraging: “The head of the insurance company OneAmerica stated that their data indicated that the death rate for individuals aged 18 to 64 had increased 40% over the pre-pandemic period. Scott Davidson, the company’s CEO, stated that this represented the highest death rate in the history of insurance records, which does extensive data collection on death rates each year. Davidson also noted that this high death rate increase has never been seen in the history of death data collection. Previous catastrophes of monumental extent increased death rates no more than 10 percent, 40% is unprecedented” [1]. It is becoming clear that Covid-19 vaccination did not get positive results.

We could calculate the exact impact on the entire population in England and worldwide if we would have data on how many people who died in a given time period of four weeks have been at least once vaccinated. This would allow calculating the proportional number of “dead vaccinated” and comparing it with the actual statistical number of deaths. The proposed calculation might be difficult to understand for medical experts, so I will give an example: Let’s imagine that in a given country we give in January 2021 a red bracelet on the hands of 30% of entire population. In every age group, exactly 30% of people have red bracelet. We follow number of deaths in the next months, and we will see that exactly 30% dead people in each age group will have a red bracelet. This is how statistics of big numbers work. We can imagine that Covid-10 vaccine is a red bracelet and has no impact on the health of the vaccinated person. On this plausible preposition, we calculate a proportional number of deaths. Comparing the proportional number of deaths with the real statistical number of deaths is showing the real impact of vaccination on the population death rate.

German official data has shown that “sudden death of unknown cause” has increased in 2021 and in 2022 for more than 400 precent. In 2021 and 2022, according to official statistics, around 9,000 people died each year in Germany due to "sudden death of unknown cause", and in the previous five years, an average of 1,600 people died, which means that due to "sudden death of unknown cause" in 2021 and 2022 in Germany around 14,800 people died [14]. These data are alarm bell that with the massive covid vaccination there is something utterly wrong and not hearing this bell would mean that medical ethics is dead.

Data from Paul-Ehrlich-Institute from Germany are also ringing the alarm bell. In year 2021 and year 2022 “sudden death with cause unknown” increased for about 560% in respect with previous years [15].

Figure 2. Increase of sudden death cause unknown in Germany in 2021 and 2022.

Figure 2. Increase of sudden death cause unknown in Germany in 2021 and 2022.

Data from National Institute of Public Health are also ringing alarm bell. Pulmonary embolism raised from 2021 to 2021 for about 36%. Chronic myocarditis has raised from 2021 to 2021 for about 65%. Viral pneumonia has raised from 2020 to 2021 for about 149% [16].

Figure 3. Increase of pulmonary embiolism in 2021.

Figure 3. Increase of pulmonary embiolism in 2021.

Figure 4. Increase of chronic myocarditis in 2021.

Figure 4. Increase of chronic myocarditis in 2021.

Figure 5. Increase of viral pneumonia in 2021.

Figure 5. Increase of viral pneumonia in 2021.

The status of the vaccination of these patients is not publicly known, which makes it impossible to calculate the exact impact of covid vaccination on the increase of these diseases. Despite several calls of researchers from different fields, NIJZ is keeping these data in secret. This is an unprecedented situation in science that scientific organization of public health is hiding essential data that could prove the danger of a given medical treatment. In the lives of people in Slovenia, the only big change of life in 2021 was massive covid vaccination, so the only possible candidate for the increase of these diseases is covid vaccination. When data will be available, we will carry out calculation of exact percent of patients that were vaccinated.

4. Percentage account of increased mortality caused by covid vaccination

Calculation of the covid vaccination on increased mortality can also be done by middle school mathematics if someone would have an attempt to see the real impact of vaccination. Most statistics about covid vaccines effectiveness that are published are avoiding this calculation because there is a huge pressure on medical profession to hide devastating results of covid vaccination. But this is only the question of time. Human society is developed to the stage that will not support the unbearable lie stories of how covid vaccines are saving human lives.

In this simple effective calculation, the entire population of a given country is divided into 5 age groups: 0-20 years, 21 to 40 years, 41 to 60 years, 61 to 80 years, and over 80 years. Each age group (total number – TN) consists of two subgroups: vaccinated subgroup (VA) and unvaccinated subgroup (UN):

TN = VA + UN

(8)

where TN stands for all people in a particular group, VA stands for vaccinated persons and UN stands for unvaccinated persons. A certain number of people die each month in each age group:

D = Dva + Dun

where D means all dead people in a certain age group, Dva means dead vaccinated people and Dun means unvaccinated dead people. Unvaccinated people are not protected from the deadly virus Kovid-19 and therefore should die in greater numbers. The calculation of mortality expressed in percentage in the vaccinated subgroup in a certain age group for each month is calculated as follows:

mortality in percentage of vaccinated subgroup: 100Dva / VA.

The calculation of the mortality in percentage in the unvaccinated subgroup in a certain age group for each month is as follows:

mortality in percentage of unvaccinated subgroup: 100Dun / UN.

For each month, it is possible to accurately calculate the mortality of the vaccinated subgroup in a certain age group and the mortality of the unvaccinated subgroup in a certain age group. Avoiding these calculations is avoiding the fact that covid vaccination has done un unrepairable harm to the public health worldwide. Carrying out these calculations and inform about them scientific medical community is the main task of every medical journal whose editors respect the first principle of medicine: “Primum non nocere”! Today nobody is ready to carry out these calculations that would show the real impact of covid vaccination on public health. The fear that massive covid vaccination could be the biggest mistake of medicine ever is too big.

Despite enormous media pressure all over the world that covid vaccination is the only way to prevent Covid-19 infection, in India ivermectin was used, and it has given excellent results [17]. This shows that Indian doctors keep a high level of medical ethics, which has saved many lives and has maintained the original spirit of medicine. The aim of medicine in the first place is to increase health, not to increase illness so that big pharma could sell more medicals. For the last 20 years, the use of medicals all over the world has increased drastically. This is not a coincidence; this is the business plan of big pharma. A healthy human being is not a customer, and so it has become the main enemy of big pharma. This is where medicine has to fight for its independence back. In the first place, medicine is about increasing health, in the second place, medicine is about preventing disease, and in the third place, medicine is about the cure of disease. In India, this original spirit of medicine is still alive.

5. Conclusions

Covid-19 vaccination should significantly decrease the number of covid infected vaccinated deaths in comparison to the number of covid infection unvaccinated deaths. There are no "hidden variables" that could influence the results because covid-infected vaccinated and covid-infected unvaccinated are living under the same conditions. The results of the presented analysis call for an extensive analysis of UK HEALTH SECURITY AGENCY data for all four weeks periods of the time of covid vaccination for different age groups in England.

Almost every county has accurate data on who has been vaccinated, how many times they have been vaccinated, and who has not been vaccinated. As long as the person is alive, the health authorities know about the vaccination status. After the person has died, the status of the vaccination is lost. Nobody is ready to compare the death rate of vaccinated and non-vaccinated groups, which is the best proof of vaccination's effectiveness or harmfulness. This is where medicine has lost its ethics. The only way to get it back is to carry out a rigorous analysis of massive covid vaccination on the death rate of vaccinated and non-vaccinated groups. In general, the vaccination status of sick people is hidden. This is the worldwide practice of today’s medicine. When a person gets sick and visits a doctor, he will not ask about covid vaccination status. In this way, big pharma would like to hide the disastrous impact of covid vaccination on public health. The medical profession has lost its independence and has become a prolonged hand of pharmaceutical companies, which have their own interest that is far from the public interest.

A simple calculation at the end of the article can give us a detailed analysis of the Covid-19 vaccination impact on the mortality rate in a given month. This should be done urgently in order to preserve the first principle of medicine: “Primum non nocere”. Obtained results are not encouraging. It seems that massive covid vaccination has done un unrepairable harm to public health worldwide. How this has happened still is an unanswered question. One thing is clear: at the end of the year 2020 all security measures of public health has been destroyed, all protocols for early treatment of Covid-19 with tested medicals were banned. Politics has established new rules of medicine that are not scientific, they are pure dogmatism. This is where medical doctors have lost their holy grail of medicine. Medicine has become a tool of globalist politics to reach their goals. The only way for medical doctors to continue their mission with respect and grace is to take medicine back into their hands.