Professor Norman Fenton and Martin Neil, Queen Mary, University of London have a very interesting analysis:
These jabs are truely magical if they not only lower covid mortality (which is claimed), but even non-covid mortality (which is harder to explain)
“By looking at non-covid mortality we are removing the Covid death signal from the data and looking at changing patterns of mortality caused by other causes of death such as cancer, heart diseases, accidents and so forth. When we do this, we notice incomprehensible differences in non-Covid mortality rates (i.e., all-cause minus Covid-19 mortality)”
“The risk/benefit of Covid vaccines is arguably most accurately measured by an all-cause mortality rate comparison of vaccinated against unvaccinated, since it not only avoids most confounders relating to case definition but also fulfils the WHO/CDC definition of “vaccine effectiveness” for mortality.”
“Despite this apparent evidence to support vaccine effectiveness - at least for the older age groups - on closer inspection of this data, this conclusion is cast into doubt because of a range of fundamental inconsistencies and anomalies in the data.”
“By Occam’s razor we believe the most likely explanations are systemic miscategorisation of deaths between the different categories of unvaccinated and vaccinated; delayed or non-reporting of vaccinations; systemic underestimation of the proportion of unvaccinated; and/or incorrect population selection for Covid deaths.”
“Any systemic errors or biases can lead to conclusions that are inversions of the real situation. For example, simply reporting deaths one week late when a vaccine programme is rolled out will (with statistical certainty) lead to any vaccine, even a placebo, seemingly reducing mortality. The same statistical illusion….will happen if any death of a person occurring in the same week as the person is vaccinated is treated as an unvaccinated, rather than vaccinated, death”
“NIMS were double counting some vaccinated people, and hence the NIMS population estimates for the number of people vaccinated were therefore too high. How accurate is the estimate of the proportion of the population that is unvaccinated? In [1] we argued that the ONS data was underestimating the proportion unvaccinated; hence, ONS reported mortality rates (and by implication also effectiveness rates) were too high for the unvaccinated and too low for the vaccinated.”
“An examination of these older age groups reveals a different fundamental problem with the data, which becomes evident when we look at causes of death other than Covid. “
“Setting aside age group 10-59 because of probable age confounding, the data appear to show (in each of the older age groups) a significantly lower non-Covid mortality rate for the vaccinated, compared to the unvaccinated."
“we compare the non-Covid mortality rate of those who are unvaccinated with those who are vaccinated (all vaccination categories combined) along with the timing of the first and second dose rollout.”
“we see peaks in mortality risk for the unvaccinated across the three age groups that occur almost immediately as if they had received the first vaccine and peak at consecutively later times in line with when vaccine was administered for that age group. The fact that the peaks in mortality are not temporally aligned strongly suggests that this is not caused by natural events. As reported previously [16], such a phenomenon would be inevitable if the deaths of people who die shortly after vaccination are miscategorised as unvaccinated.” (emphasis mine)
“So unlike previous years, where the different age cohorts have mortality peaks at the same time during the year (including 2020 when all suffered the April Covid peak at the same time)” ..In 2021 the non-Covid mortality peaks are staggered and map the peaks of the vaccination rollout for those age cohorts.
https://www.researchgate.net/publication/357778435_Official_mortality_data_for_England_suggest_systematic_miscategorisation_of_vaccine_status_and_uncertain_effectiveness_of_Covid-19_vaccination