1. Introduction

2. Methods and Results

2.1. 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 statistics involving large sample sizes and provides precise results. As medical authorities are hiding the vaccination status of most dead persons$A^{*}$, this is not feasible at this time. We can, however, obtain official data in England about the infected dead group $B^{*1}$ and 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 allowing public access to information on vaccination status of dead persons.

Taking in account that vaccines do not impact on mortality, the subgroup $A^{*1}$ and subgroup $B^{*1}$ have the same rate of mortality. When both groups would be persons of different ages, let’s say in the subgroup $A^{*1}$ most persons would be under 40 years and in the subgroup $B^{*1}$ most persons would be above 40 years, the Simpson effect could occur. This is not the case in both groups the age distribution is very similar and Simpson’s effect is excluded.

Taking into account that vaccines do not impact on mortality, the subgroup $A^{*2}$ and subgroup $B^{*2}$ have the same rate of mortality. Producers of the vaccines are declaring that effectiveness of vaccines is around 95% which means that the groups $A^{*1}$, $A^{*2}$, $B^{*1}$, and $B^{*2}$ have very similar mortality rates, that is within the value of 5%, so we 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 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)

The impact of the Covid-19 virus on the death rate in group $A^{*1}$ and in group $B^{*1}$ is the same. The proportional numbers $A^{*1}$ obtained in all five of the 28-day time periods are always smaller than the statistical numbers. This provides strong proof that vaccines are increasing the death rate. The statistics pertain to a short time span (four weeks, 28 days); therefore the time variable cannot significantly influence the results. In group $A^{*1}$ and in group $B^{*1}$, people could die because of some unknown reasons. Both groups were living under the same living conditions, so some other cause of death would have the same impact on both groups.

In population statistics for England, we obtained data for the number of infected vaccinated dead and data of infected dead$B^{*1}$. Using equation (9), we calculated the proportional number of infected vaccinated dead $A^{*1}$ and compared it with the statistical number of actual infected vaccinated dead. Thus, we obtained the decreased or increased mortality rate (percentage) associated with or likely attributed to vaccination. The proportional number $A^{*1}$ is the number indicating no impact of 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 that case, vaccines would be saving people’s lives. We can then calculate how many SARS-CoV-2 infected persons have been saved from death with vaccination for a given 4-week period, using the following equation:

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

(10)

In this case, the statistical number of SARS-CoV-2 infected vaccinated dead is bigger than the proportional number $A^{*1}$, and therefore vaccination has a negative impact on mortality rate. In other words, the vaccination is stealing more lives than it saves, i.e., more people have died prematurely because of getting vaccinated than would have occurred had they chosen not to get vaccinated:

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

(11)

Figure 1. Comparing proportional number with statistical number

Figure 1. Comparing proportional number with statistical number

2.2. The calculation for weeks 35-38 in year 2021

Homogeneous distribution of all age groups can be seen in data source. Below is the table from the UK data source [13]. We can see that most of the vaccinated is elderly population. We calculate covid infected vaccinated deaths $A^{*1}=2447$ by summing colons “Received one dose” and “Second dose”. We calculate $B^{*1}=3165$ by summing colon “Total”.

Table 1. Covid infected vaccinated deaths between weeks 35 and 38

Table 1. Covid infected vaccinated deaths between weeks 35 and 38

A “vaccinated” person in this calculation is the person that was vaccinated with the first dose or more. Let’s calculate the proportional number of dead vaccinated in England between weeks 35 and 38. In this time frame, there were 3165 Covid-19 deaths in the United Kingdom; 2448 of those persons had been vaccinated [13]. We see that the percentage of vaccinated UK people with one dose in this period is 65.1%. In 2021 the population of the United Kingdom was 56,191,000 people. 65.1% of the entire population is 36,580,300 people.

$$\mathrm{proportional} \mathrm{number}=\frac{\mathrm{36.580.300}\ast 3165}{\mathrm{56.191.000}}$$

$$\mathrm{proportional} \mathrm{number}=2060.$$

Officially declared vaccinated Covid dead persons between 35 and 38 weeks are 2447.

$$\mathrm{covid} \mathrm{infected} \mathrm{vaccinated} \mathrm{deaths} \mathrm{declared}=2447.$$

This means that 2448 - 2060 = 387 persons had prematurely passed away due to the vaccination in the period of week 35 - 38.

$$\mathrm{lost} \mathrm{lives}=2447-2060=387$$

2.3. The calculation for weeks 39 - 42, 2021

Table 2. Covid infected vaccinated deaths between week 39 in week 41

Table 2. Covid infected vaccinated deaths between week 39 in week 41

Let’s calculate the proportional number of dead vaccinated in England between weeks 39 and 42. In this period there were 2772 covid deaths in the UK. 2270 of them have been vaccinated [13]. We see that the percentage of vaccinated people in the UK with one dose in this period is 66.1% [13]. The population of the UK was 56.191.000 people in 2021. 66.1% of the entire population is 37.142.200 people.

$$\mathrm{proportional} \mathrm{number}=\frac{\mathrm{37.142.200}\ast 2772}{\mathrm{56.191.000}}$$

$$\mathrm{proportional} \mathrm{number}=1832.$$

Officially declared vaccinated covid dead persons between 39 and 42 weeks are 2270.

$$\mathrm{covid} \mathrm{infected} \mathrm{vaccinated} \mathrm{dead} \mathrm{declared}=2270.$$

This means that 2270 - 1832 = 438 persons had prematurely passed away due to the vaccination in the period weeks 39 - 42:

$$\mathrm{lost} \mathrm{lives}=2270-1832=438$$

2.4. The calculation for weeks 43-46, 2021

Table 3. Covid infected vaccinated deaths between week 43 in week 46

Table 3. Covid infected vaccinated deaths between week 43 in week 46

Let’s calculate the proportional number of dead vaccinated in England between weeks 43 and 46. In this four-week period, there were 3726 covid deaths in the UK. 2992 of them have been vaccinated [13]. We see that the number of vaccinated people in England in this period with the first dose is 67.4% [13]. The population of the UK was 56.191.000 people in 2021. 67.4% of the entire population is 37.872.700 people. We use equation (7) and we get:

$$\mathrm{proportional} \mathrm{number}=\frac{\mathrm{37.872.700}\ast 3726}{\mathrm{56.191.000}}$$

$$\mathrm{proportional} \mathrm{number}=2511.$$

Officially declared vaccinated covid dead persons between 43 and 46 weeks are 2992.

$$\mathrm{covid} \mathrm{infected} \mathrm{vaccinated} \mathrm{deaths} \mathrm{declared}=2992.$$

This means that 2992 - 2511 = 481 persons had prematurely passed away due to the vaccination in the period weeks 43 - 46:

$$\mathrm{lost} \mathrm{lives}=2992-2511=481$$

2.5. The calculation for weeks 47-50, 2021

Table 4. Covid infected vaccinated deaths between week 47 in week 50

Table 4. Covid infected vaccinated deaths between week 47 in week 50

Let’s calculate the proportional number of dead vaccinated in England between weeks 47 and 50. In this period there were 2956 covid deaths in the UK. 2140 of them have been vaccinated [13]. By 19 December 2021, the overall vaccine uptake in the UK for dose 1 was 68.2%, see page 3 COVID-19 vaccine surveillance report – week 51 [13]. The population of the UK was 56.191.000 people in 2021. 68.2.% of the entire population is 38.322.200 people. We use equation (7) and we get:

$$\mathrm{proportional} \mathrm{number}=\frac{\mathrm{38.322.200}\ast 2956}{\mathrm{56.191.000}}$$

$$\mathrm{proportional} \mathrm{number}=2016.$$

Officially declared vaccinated covid dead persons (one dose or more) between 47 and 50 weeks are 2140.

$$\mathrm{covid} \mathrm{infected} \mathrm{vaccinated} \mathrm{deaths} \mathrm{declared}=2140$$

This means that 2140 - 2016 = 124 persons had prematurely passed away due to the vaccination in the period weeks 47 - 50:

$$\mathrm{lost} \mathrm{lives}=2140-2016=124$$

2.6. The calculation for weeks 51, 2021 - 1, 2022

Table 5. Covid infected vaccinated deaths between week 51 (2021 and week 1 (2022)

Table 5. Covid infected vaccinated deaths between week 51 (2021 and week 1 (2022)

Let’s calculate the proportional number of dead vaccinated in England between week 51, 2021 and week 1, 2022. In this period there were 3893 covid deaths in the UK. 2878 of them have been vaccinated. By 16 January 2022, the overall vaccine uptake in England for dose 1 was 68.9%, see page 3 [13]. The population of the UK was 56.191.000 people in 2021. 68.9.% of the entire population is 38.322.200 people. We use equation (4) and we get:

$$\mathrm{proportional} \mathrm{number}=\frac{\mathrm{38.715.500}\ast 3893}{\mathrm{56.191.000}}$$

$$\mathrm{proportional} \mathrm{number}=2682.$$

Officially declared vaccinated covid dead persons (one dose or more) between week 52, 2021 and week 2, 2022 are 2878.

$$\mathrm{coronavirus}-\mathrm{infected} \left(\mathrm{test}-\mathrm{positive}\right) \mathrm{vaccinated} \mathrm{deaths} \mathrm{declared}=2878$$

This means that 2878 - 2682 = 196 persons had prematurely passed away due to the vaccination in the period weeks 47 - 50:

$$\mathrm{lost} \mathrm{lives}=2878-2682=196$$

Below we have the results of all calculated periods:

weeks 35-38: total coronavirus-infected deaths are 3165, number of covid infected vaccinated deaths is 2448, number of dead because of heavy adverse effects caused by vaccination is 388 which is 15% of coronavirus-infected vaccinated deaths

weeks 39-42: total coronavirus-infected deaths are 2772, number of covid infected vaccinated deaths is 2270, number of dead because of heavy adverse effects caused by vaccination is 438 which is 19% of coronavirus-infected vaccinated deaths

weeks 43-46: total covid infected deaths are 3726, number of covid infected vaccinated deaths is 2992, number of dead because of heavy adverse effects caused by vaccination is 481 which is 16% of coronavirus-infected vaccinated deaths

weeks 47-50: total coronavirus-infected deaths are 2956, number of covid infected vaccinated deaths is 2140, number of dead because of heavy adverse effects caused by vaccination is 124 which is 6% of coronavirus-infected vaccinated deaths

weeks 51(2021)-2(2022): total coronavirus-infected deaths are 3893, number of covid infected vaccinated deaths is 2878, the number of dead because of heavy adverse effects caused by vaccination is 196 which is 7% of coronavirus-infected vaccinated deaths.

In 20 weeks, the total number of deaths among persons who had tested positive for SARS-CoV-2 infection was 16.505. The total number of the Covid-19 test-positive vaccinated deaths is 12.728. The total number of deaths because of heavy adverse effects caused by vaccination is 1627 persons. This means in the group of Covid-test positive vaccinated deaths which is 12.728 persons, 12.8% have died because of heavy adverse effects. By including all time periods in the calculation, we will have a more comprehensive estimate.

The total number of deaths of the Covid-19 test positive people that died in 20 weeks was 12.728. The total proportional number of vaccinated infected people that died was 11.101. Thus, in the group of test-positive vaccinated deaths, there was a 14.5% higher rate of mortality than in the group of covid positive unvaccinated considering vaccines would not have any influence on the death rate. Our data indicate that infected vaccinated persons have a 14.5% higher probability of dying (ostensibly from prior or concurrent Covid-19 infection, or vaccination, or both) than infected unvaccinated persons.

According to the official narrative, vaccines are saving lives, which means the number of coronavirus-infected vaccinated deaths statistically recorded should be significantly lower than the proportional calculated number of the coronavirus-infected vaccinated deaths. As shown in Table 1, our results indicate that the opposite is true. The statistical number of the coronavirus-infected vaccinated deaths is significantly higher than the calculated proportional number of coronavirus-infected vaccinated deaths, which means that infected vaccinated people are dying at a higher rate than their infected unvaccinated counterparts, presumably because of adverse effects of the vaccines themselves.

Figure 2. Obtained results

Figure 2. Obtained results

2.7. Evaluation of obtained results

In principle, the gene-based Covid-19 vaccines (mRNA vaccines and adenovirus vector vaccines) were designed to significantly decrease the number of deaths associated with SARS-CoV-2 infection when compared to the number of deaths among infected unvaccinated persons. However, the present analysis points to a net negative benefit in terms of mortality reduction. Based on UK population data at five 28-day intervals in 2021-2022, we found that infected vaccinated persons have a 14.5% higher probability of dying than infected unvaccinated persons.

Our findings are limited in scope but of major statistical relevance. The proposed statistical approach offers a highly reliable estimate of how the Covid-19 vaccination campaign has been impacting the mortality rate for entire populations, apparently adding in a major way to deaths attributed to Covid-19. The relation between the “vaccinated coronavirus-infected deaths” and “non-vaccinated coronavirus-infected deaths” in a short four-week period is a statistically viable measure of the unfavourable impacts of these immunizations on Covid-19 mortality. Based on the rules of statistics, if we were to calculate the relationship between the proportional and real number of vaccinated Covid-19 deaths for all other time periods, we would not expect to see results that contradict the present findings. We are therefore inclined to propose that Covid-19 vaccines are causing lethal adverse effects. It seems reasonable to surmise that such impacts on mortality are not only relevant to England but also to other countries where the vaccines have been adopted on a massive scale.

To widen the scope of this research, we could calculate the mortality impacts on the entire population in England and worldwide. This would require data on how many people who died in a given four-week period have been at least once vaccinated (or ever vaccinated). This would allow calculating the proportional number of “dead vaccinated” and comparing it with the actual statistical number of deaths. Because the proposed calculation might be difficult to understand for medical professionals, here is an example: Let’s imagine that in a given country, in January 2024, we will place a red bracelet on the hands of 30% of the entire population. In every age group, exactly 30% of people will have red bracelet. We follow a number of deaths in the ensuing months and see that exactly 30% dead people in each age group will have a red bracelet. This is how statistics work out when applied to large population sizes. We can imagine that Covid-19 vaccine is a red bracelet and has no impact on the health of the vaccinated person. On this plausible supposition, we calculate a proportional number of deaths. Comparing the proportional number of deaths with the real statistical number of deaths shows us the real impact of vaccination on the population death rate.

Calculation of the impact of Covid-19 vaccination on increased mortality is so straightforward that it could be done by anyone with middle-school mathematics ability who has an interest in assessing and monitoring the mortality impact. Most of the published statistics pertaining to Covid-19 vaccine effectiveness are avoiding this calculation because of immense pressures on the medical profession to hide the disastrous results of the vaccination program; however, it is only a matter of time before the truth is revealed. Human society is evolving rapidly and will not support the unbearable falsehoods concerning how Covid-19 vaccines are impacting human lives.

In this simple effective calculation, the entire population of a given country is divided into five 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 Covid-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 within a certain age group. Avoiding these calculations is avoiding the fact that Covid-19 vaccination has done major harm to public health worldwide. Carrying out these calculations on a monthly basis and informing the medical community and general public about them is the main obligation of every medical journal. A simple calculation at the end of each monthly report would provide a concise updated analysis of the Covid-19 vaccination impact on the mortality rate for that particular month. Such calculations would reveal the true impact of Covid-19 vaccinations. This must be done immediately in order to preserve the first principle of medicine: “Primum non nocere”.

The results obtained by the present analysis would seem to reinforce the findings of Tojersen and colleagues, who reported that the Covid-19 vaccinations have led to increased death rates among the elderly population [14,15]. A report from the insurance company OneAmerica is similarly discouraging, with actual data from the latter half of 2021 indicating an unprecedented 40 percent increase in death rates for individuals aged 18 to 64 when compared to the pre-pandemic period [16]. According to the company’s CEO, this represented the highest mortality rate in the history of insurance records, which entail extensive death data collection annually. Previous largescale catastrophes had increased death rates by no more than 10 percent [16]. It seems increasingly clear that Covid-19 vaccination programs are not living up to the “safe and effective” terms they had promised to the general public.

Other concerning data come from German public health authorities showing that “sudden death of unknown cause” increased dramatically in the past two years. In 2021 and 2022, according to official German statistics, approximately 14,800 people died, compared to an annual average of only 1,600 people in the previous five years [17]. According to analyses from the Paul Ehrlich Institute, these “sudden death of unknown cause” increased by about 560% in 2021 and 2022 over previous years [18]. These data are sounding off alarms that something went terribly wrong with the public health response to Covid-19.

Figure 3. Increase of sudden death cause unknown in Germany in 2021 and 2022

Figure 3. Increase of sudden death cause unknown in Germany in 2021 and 2022

Data from Slovenia’s National Institute of Public Health (NIJZ) are also ringing alarm bell. Pulmonary embolism increased by about 36% from 2021 to 2022. In that same two-year period, chronic myocarditis increased by about 65%, while viral pneumonia increased by about 149% [18].

Figure 4. Increase of pulmonary embolism in 2021

Figure 4. Increase of pulmonary embolism in 2021

Figure 5. Increase of chronic myocarditis in 2021

Figure 5. Increase of chronic myocarditis in 2021

Figure 6. Increase of viral pneumonia in 2021

Figure 6. 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-19 vaccination on the increase of these diseases. Despite several calls of researchers from different fields, NIJZ is keeping these data confidential. It is unprecedented that a scientific organization of public health is hiding 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-19 vaccination, so the vaccines represent the most logical candidate for the increased morbidity and mortality. Only when the data become publicly available will we be able to carry out calculations of exact percent of patients that were vaccinated.

3. Numbers of vaccination are coinciding with the numbers of death rate

Figure 7. Excess mortality in EU in November 2022

Figure 7. Excess mortality in EU in November 2022

Table 6. Mortality rate in some European countries in October 2022

Figure 8. Excess mortality and number of daily vaccinations in Japan

Figure 8. Excess mortality and number of daily vaccinations in Japan

Figure 9. Excess mortality and number of daily vaccinations in Australia

Figure 9. Excess mortality and number of daily vaccinations in Australia

Figure 10. Excess mortality and number of daily vaccinations in Guatemala

Figure 10. Excess mortality and number of daily vaccinations in Guatemala

Figure 11. Excess mortality and number of daily vaccinations in Albania

Figure 11. Excess mortality and number of daily vaccinations in Albania

Figure 12. Excess mortality and number of daily vaccinations in Slovenia

Figure 12. Excess mortality and number of daily vaccinations in Slovenia

Figure 13. Excess mortality and number of daily vaccinations in USA

Figure 13. Excess mortality and number of daily vaccinations in USA

Figure 14. Excess mortality and number of daily vaccinations in UK

Figure 14. Excess mortality and number of daily vaccinations in UK

Figure 15. Excess mortality and number of daily vaccinations in Colombia

Figure 15. Excess mortality and number of daily vaccinations in Colombia

Figure 16. Excess mortality and number of daily vaccinations in Israel

Figure 16. Excess mortality and number of daily vaccinations in Israel

Figure 17. Graphs of vaccination and excess mortality in Germany

Figure 17. Graphs of vaccination and excess mortality in Germany

Figure 18. Graphs of vaccination and excess mortality in Austria

Figure 18. Graphs of vaccination and excess mortality in Austria

Figure 19. Graphs of vaccination and excess mortality in Croatia

Figure 19. Graphs of vaccination and excess mortality in Croatia

4. Conclusion

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