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HomeCOVID-19Yet more evidence to disprove claims that vaccines are safe and effective

Yet more evidence to disprove claims that vaccines are safe and effective


NEW population-level data on the vaccination programme from the Czech Republic, collected from 2.2million individual health records, have been analysed by Fürst et al and their analysis has been accepted for publication in the International Journal of Infectious Diseases (the pre-publication date on the article is May 2024).

They analysed the all-cause mortality (ACM) of people vaccinated and unvaccinated against Covid-19 and found that ACM was consistently much lower in freshly vaccinated groups. Now in case you are thinking that this surely means the vaccines saved lives, it turns out that they found this pattern even outside ‘pandemic’ waves (cold & flu season) and they concluded that this was explainable by the Healthy Vaccinee Effect (HVE). And the effect of this bias was sufficiently large, that they further concluded that it leads to an overestimate of Covid-19 vaccine efficiency in observational studies.

We have been repeatedly asking the authorities for population data to be released here in the UK and worldwide to determine vaccination efficacy and safety. Most recently MP David Davis offered to approach the UK Office for National Statistics (ONS) to request this data. As far as we know he never did submit the request. However, Andrew Bridgen and six other MPs did submit the request and it was rejected in this response by Professor Diamond of the UK Statistics Authority, essentially on the basis that the vaccines were ‘safe and effective’.

It is therefore very positive news that Fürst et al have managed to obtain vaccination data from two of the largest health insurers in the Czech Republic.

What did they find? For each of the insurance companies (CPZP and OZP) they found that the ACM (number of deaths per 100k person years) was higher in the unvaccinated than the vaccinated, across numerous age groups.

They say: ‘At first sight, the figure might suggest that vaccination works remarkably well to prevent death. However . . . shows the all-cause mortality, not COVID-related mortality. Since only approx 14 per cent of all deaths over the study period were COVID-related (37,000 out of 269,000 deaths), it was impossible for the vaccine to have had such an effect on all-cause mortality.’

They go on to contrast the ACM during high and low covid seasons:

Concluding: ‘Between June 2021 and September 2021, virtually no COVID-related deaths were recorded in the Czech Republic (only approx 0.3 per cent of deaths were COVID-related). Thus, almost all the deaths . . . were COVID-unrelated, although we can observe huge differences in ACM among groups in this period . . . When comparing the two largest groups in that period, i.e., unvaccinated and those with the completed primary course, the unvaccinated population was more than twice as likely to die as the population with the completed primary course. This apparent “vaccine efficacy” in a period when no COVID was present is likely an artifact of the HVE.’

Given these results are for all-cause mortality, and Covid-19 mortality is a small subset of this, they show that observational data is so biased it cannot be used to support any claim by the authorities that the Covid-19 vaccines were proved effective or safe.

The role of (un)healthy vaccinee effects

Crucial in our request to David Davis MP is that information on comorbidities be made available, as without this we cannot determine whether there is a healthy or an unhealthy vaccine effect in any data released. This is crucial in determining whether a one or the other effect exists within any observational data set, and the extent to which this explains observed mortality outcomes.

Note that Fürst et al have not obtained the necessary data on comorbidities needed to identify and isolate this effect in Czech data. Not that they need to of course. It is a credible hypothesis, where the burden of proof is on the authorities to demonstrate it does not exist rather than on them to prove that it does.

In contrast with Fürst et al we argued in this report, where we analysed the ONS data in 2021, that rather than a HVE it was an Unhealthy Vaccinee Effect (UVE) that partly explained the UK observational data.

Our evidence for arguing for UVE was two-fold:

  • There is very little indication that terminally or critically ill patients in the UK were less likely to be vaccinated. In fact, it was policy that almost everyone should be vaccinated, with the critically ill being prioritised.
  • The ONS released data in the form of the monthly percentage of the population in the very poor health category by vaccine status in the 70-79 age group. This data showed that the percentage of those in very poor health, and who were vaccinated, increased as the vaccination programme progressed but the percentage of those who were unvaccinated and in very poor health decreased.

We said: ‘The unvaccinated cohort contains, always, a lower percentage of very poor health people than all of the vaccinated groups. There is no increase observed in the percentage of very poor health people in the unvaccinated group at the time of dose one rollout, and it is consistently below the percentage in very poor health for the whole population. This suggests that not only were those in very poor health not excluded from the dose one rollout, but that they were prioritised: hence the reduced percentage remaining. The decrease rather than increase in the percentage of unvaccinated in very poor health around the time of dose one rollout offers, therefore, a direct refutation of the hypothesis that the increase in non-Covid mortality observed in the unvaccinated at that time was due to them being moribund.’

We don’t know if the Czech Republic had a policy to actively discourage vaccination in the moribund or not, but it might prove helpful if Fürst et al could investigate this issue further.

As readers will know, we have been arguing strongly and repeatedly that the observational data on vaccination has suffered from the ‘cheap trick’ miscategorisation selection bias effect. To date, there is overwhelming evidence for this, and we have written a systematic review summarising the problem and submitted it for publication (the pre-print can be accessed here).

We believe that there are likely numerous selection biases lurking in observational data – the cheap trick is not the only one. These other biases are perhaps operating at different times, in different cohorts, to different degrees. Some age groups might be biased by HVE whilst other, more vulnerable age groups, might be contain both UVE and miscategorisation biases, interacting together. There is also the known issue with the UK data whereby the proportion of unvaccinated was being underestimated by the authorities, leading to systemic overestimation of mortality in the unvaccinated and underestimation in the vaccinated.

This mechanism of UVE and miscategorisation, operating together, would involve a higher mortality rate in the vaccinated, either because they were naturally moribund or suffered a higher mortality due to an unsafe vaccine, but by the simple act of recategorisation this increased mortality burden could easily be transferred into the unvaccinated cohort, making the vaccinated cohort look relatively healthier and the vaccines look effective and safe.

Therefore, we have two competing mechanisms that might explain the same outcomes, where, in the absence of additional data on comorbidity, each would give rise to the same observed mortality patterns in the population. And what’s more, we could not easily tell from the raw data available, whether the HVE or ‘UVE plus miscategorisation’, or some combination of both, explains mortality outcomes in any particular set of population data. We suspect this is likely why the authorities will not release comorbidity data: the waters must remain muddy.Subscribe

Is there evidence of the cheap trick in Czech data?

Kovařík, Fürst (same first author as the above main paper) and Kremeňová had, in January 2023, reported suspicious changes in the data published by the Institute of Health Information and Statistics (IHIS): ‘We found out that the datasets published by the Institute of Health Information and Statistics (IHIS) are retroactively changed in such a way that the deceased after the first dose of the vaccine and seniors hospitalised in the ICU with covid disappear from them. Given that the first of these modifications may mask the side effects of vaccines, and the latter invalidate one of the fundamental arguments of the 2021 vaccination campaign, we consider these modifications to be an absolutely fundamental problem.’

They speculated that miscategorisation had been employed and found evidence of asymmetrical changes to death but not cohort size data: ‘We wondered if the reason for this revision could have been a retroactive change in the definition of individual vaccination categories. As we know, IHIS considers a person to be fully vaccinated only 14 days after the second dose. Could it be that they would have retrospectively changed their minds at the IHIS that they actually wanted to consider people 14 days after the first dose to be unvaccinated? If the reason for this retrospective revision of the data was some modification of the definition of individual vaccination categories, the sizes of the cohorts in these categories would logically have to change along with the number of deaths in the given category. Therefore, we looked at whether there was any difference in the size of the “average daily number of people in the 1st dose category” cohort in January, February or March in the data downloaded on October 1 and December 16, 2022. Surprisingly, however, we found that there was no data revision at the size of these cohorts! For example, in March 2021, thanks to the revision, a total of 330 deaths mysteriously disappeared from the “after the first dose” category from the original 566 – or almost 60 per cent! However, there was only a change in the size of the “post-first dose” cohort from the original 605,025 to a revised 605,016, which is a negligible difference.’

They report similar issues with ICU data: ‘Mysteriously, people vaccinated with the first dose who died with covid are disappearing retroactively from the official data sets of IHIS. Likewise, seniors hospitalized in intensive care units are mysteriously disappearing.’

Given this we suspect that the Czech data contains HVE, UVE and miscategorisation selection biases rather than HVE alone.


Note that we strongly welcome and recommend the paper by Fürst et al. Whilst we might quibble about mechanisms and proof, as curious scientists and statisticians are apt to do, the policy implications of their analysis are profound and important.

No matter how you cut the data, they have demonstrated that the observed data on vaccination cannot and should not be used to support any claim that the Covid-19 vaccines are or were effective or safe.

This article appeared in Where are the numbers on April 16, 2024 and is republished by kind permission. 

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