Arguably the most important question facing the Centers for Disease Control and Prevention (CDC) is an explanation for the unexpected excess deaths in the United States during 2021 and 2022. These excess deaths are occurring at a time when covid prevalence in the US is very low. The CDC does not seem to be interested in explaining these deaths, so the public is filling the vacuum with their own theories. One theory is that the excess deaths are due to adverse effects of the covid vaccines. The CDC has mortality data stratified by vaccination status, but it refuses to release the data to the public. This refusal only reinforces theories that covid vaccines are the culprit. The United Kingdom, however, has released mortality data stratified by age group and vaccination status for January 2021 through May 2022, though it is unclear whether it will continue to update these data. There are many ways to present these data.
It is my opinion that the best way to test the hypothesis that covid vaccines are responsible for excess deaths is to compare unadjusted mortality rates for unvaccinated people to those of a composite of all partially and completely vaccinated people (people with intent to vaccinate completely). The UK data table organizes mortality for each age group using seven vaccination categories: unvaccinated; first vaccine dose less than twenty‑one days before death; first vaccine dose at least twenty‑one days before death; second vaccine dose less than twenty‑one days before death; second vaccine dose at least twenty‑one days before death; third vaccine dose or booster less than twenty‑one days before death; and third vaccine dose or booster at least twenty‑one days before death. Separation of data for each vaccination status introduces a bias in favor of vaccination, known as the immortal time bias.
For example, someone who dies following the first vaccine dose will not be represented in second or third vaccine dose data. The third vaccine dose data do not represent the general population, but only those people who have survived past the first and second vaccine doses. It is my opinion that this time bias was largely responsible for the mythology that covid is an epidemic of the unvaccinated. This mythology was created when the vaccine became available. Very few people had received the vaccine, and the vast majority of the population was unvaccinated, making true case rates difficult to estimate by counting people rolling into the ICU. This mythology persists among my colleagues and the administration at my institution despite having been thoroughly disproven.
The mortality rates in the data table are “adjusted” for age. I report unadjusted mortality rates, calculated by dividing the number of deaths by the person‑days and then multiplying by 100,000. The differences between unadjusted mortality and “adjusted” mortality are small and do not change any of the conclusions. But it is my opinion that rather than trying to “adjust” for age, we should analyze each age group separately to see how finely the age should be stratified to eliminate different patterns between age groups. I would have preferred the 18–39 age group to be further divided, but I have to work with the data available.
Figure 1: UK unadjusted mortality rates, 18–39 age group
Note: The blue curve represents unvaccinated subjects. The gold curve represents subjects who received any form of covid vaccination (with intent to completely vaccinate), and its values were calculated by summing the deaths and person‑days for each vaccination subgroup.
Figure 1 shatters the myth that the benefits of covid vaccines outweigh the costs for all age groups. The mortality rate for the 18–39 age group was greater in vaccinated subjects than unvaccinated subjects for several months during the period of study. The average difference in mortality from January 2021 to May 2022 showed a net harm from vaccination. But were the differences significant? It would be inappropriate to perform statistical tests such as a t‑test on these data because the statistical weight of each data point could not be equal: the data points represent aggregates of individual test subjects, and we have no information about the variance within each aggregate value.
On average, there was an additional death for roughly every twenty thousand vaccinations in the 18–39 age group. Although the best we can conclude from these data is that vaccination is associated with increased mortality in this age group, we cannot assert that vaccination caused the increase in mortality. It is possible that some unknown factor caused the increased mortality and that this factor was more prevalent in vaccinated subjects than unvaccinated subjects. However, this is the best we can do, given that the Food and Drug Administration (FDA) and CDC stopped the controlled trials after about three months. Thanks to government authorities, we will never have a properly controlled trial of the vaccines. The FDA and CDC should accept the blame for this uncertainty and admit that these vaccines are NOT safe and that they have known for over a year that these vaccines are not safe.
Figure 1 also suggests that any benefits vaccination may grant in terms of reduced deaths from covid decline over time. The trends during the final four months of the data series suggest that either mortality will be equal for the vaccinated and unvaccinated or mortality for the vaccinated will be greater due to adverse events occurring many months after vaccination.
Figure 2: UK unadjusted mortality rates, 60–69 age group
Note: The blue curve represents unvaccinated subjects. The gold curve represents subjects who received any form of covid vaccination (with intent to completely vaccinate), and its values were calculated by summing the deaths and person‑days for each vaccination subgroup.
Figure 2 demonstrates that there was net benefit from vaccination (reduced mortality) in subjects ages 60–69. In this age group, the vaccinated group demonstrated a lower mortality rate each month. Were the benefits significant? Just as with the data for the 18–39 age group, it would be inappropriate to perform statistical tests such as a t-teston these data. The greatest difference between the unvaccinated and vaccinated mortality rates was seen early in the data series, with the two curves converging during the latest months of the data series. It is unclear whether more recent months will continue to demonstrate a benefit from vaccination. Hopefully, the UK will continue to report data to the public.
The average benefit over the period of the study can be used to estimate how many vaccinations will prevent a death. In my opinion, this number represents a better indicator of clinical significance than odds ratios.
Table 1: Vaccinations needed to prevent one death, ages 40 and over
Age group | Vaccinations to prevent one death |
40–49 | 1,832 |
50–59 | 326 |
60–69 | 117 |
70–79 | 34 |
80–89 | 12 |
90 and over | 9 |
Source: Numbers were calculated by dividing 100,000 by the average difference between mortality rates for vaccinated and unvaccinated subjects.
Table 1 illustrates that a recommendation of vaccination for people over ninety would be very reasonable, while such a recommendation for people ages 40–49 would be very questionable, especially since full vaccination seems to be a never-ending proposition. Note that a net benefit of the vaccine does not justify a mandate for vaccination, since death by covid and death by vaccine are not comparable, even though both are deaths. Individuals have different perceptions about these two forms of death.
My direct observation of patients demonstrates that some people are much more concerned about covid than about the vaccine, while others are much more concerned about the vaccine than about covid. The best that healthcare providers can do is to inform our patients about the risks of both choices and to let patients decide for themselves. Browbeating patients into vaccination is inexcusable, as the vaccines are objectively NOT safe.
Space does not permit a detailed discussion of the data for the other age groups, but some observations are of note. For instance, the 40–49 age group demonstrated a net harm from vaccination in March and April 2021 as well as in February, April, and May of 2022. Also, the over-ninety age group demonstrated a net harm from vaccination for March, April, and May 2022. The maximal benefit of vaccination was seen in different months for each age group, which likely reflects the progressive rollout of vaccination beginning with the oldest age group. All of the age groups demonstrated a convergence of mortality rates during the final months of the data series compared to earlier months.
Conclusion
The risks of the covid vaccines are often comparable to the risks of getting the disease itself. This is especially true for younger people. The principle of informed consent requires healthcare providers to inform patients of the objective risks of vaccination. Older patients are more likely to exhibit net benefit from vaccination. Vaccination should be offered but not recommended to patients under the age of forty.
