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England population by age category and vaccination status for week 26 (Estimated from NIMS versus PHE/ONS actual)
Source publication
UPDATE: A significantly revised version of this report is here:http://www.eecs.qmul.ac.uk/~norman/papers/inconsistencies_vaccine.pdf To determine the overall risk-benefit of Covid-19 vaccines it is crucial to be able to compare the all-cause mortality rates between the vaccinated and unvaccinated in each different age category. However, current pub...
Contexts in source publication
Context 1
... for our reverse engineering of the figures, we are reliant on the PHE/ONS mortality report for total deaths by vaccination status, all our population sizes by age category must therefore be 'prorated' down to the population figure used therein, which is 39,245,327. If we apply these percentages to the ONS population size of 39,245,327 we get the distribution and totals shown in Table 3. ...Context 2
... that in Table 3 the estimated totals are significantly different, but dramatically so for the unvaccinated category. Nearly 3 million of those we estimate to be classified as unvaccinated, using NIMS, are classified as two-dose vaccinated compared with the PHE/ONS survey. ...Context 3
... can do this again for deaths in each age category and then use the ONS 2020 population survey to calculate the UMR for each age category. When we apply this UMR to the estimated populations in Table 3, we get the results shown in Table 4. Notice that the Expected Total all-cause deaths (summing the totals of the three columns) is 5,945 whilst the PHE/ONS Total sums to 6,956. This is a significant difference. ...Similar publications
There are many pros and cons to the government's policy regarding the Covid-19 Vaccine for students in schools. Low knowledge and understanding of the Covid-19 vaccine are one of the causes. Socialization and education related to the Covid-19 Vaccine are one of the efforts to support this vaccination program. The purpose of this study is to determi...
Citations
... 34 Under-and over-reporting of vaccination may potentially occur in several ways, like failure in digital record, not correctly identified individuals and errors in data entry. 35 Moreover, a not fully effective vaccine may convey an overall perception of low protection in the population. ...
The success of mass vaccination campaigns may be jeopardized by human risky behaviors. For example, high level of vaccination coverage may induce early relaxation of social distancing. In this paper, we focus on the mutual influence between the decline in prevalence, due to the rise in the overall immunization coverage, and the consequent decrease in the compliance to social distancing measures. We consider an epidemic model where both the vaccination rate and the disease transmission rate are influenced by human behavior, which in turn depends on the current and past information about the spread of the disease. We highlight the impact of the information-related parameters on the transient and asymptotic behavior of the system that is on the early stage of the epidemic and its final outcome. Among the main results, we evidence that sustained oscillations may be triggered by the behavioral memory in the prevalence-dependent vaccination rate. However, the relaxation of social distancing may induce a switch from a cyclic regime to damped oscillations.
... Our recent articles [1,2] have argued that the simplest and most objective way to assess the overall risk/benefit of Covid-19 vaccines is to compare all-cause mortality rates of the unvaccinated against the vaccinated in each separate age-group. For such an assessment we need accurate periodic data on both age-categorized deaths and the number of vaccinated/unvaccinated people in each age group for that period. ...
... The UK Government has been better than most countries in providing detailed data on Covid cases and deaths indexed by vaccine status. However, in [1] we highlighted the absence of relevant agecategorized mortality data for England, and major inconsistencies in the data provided by different agencies. Of most concern are the very different estimates provided by UKHSA (United Kingdom Health Security Agency) and the ONS (Office for National Statistics) of the number of vaccinated and unvaccinated people. ...
... They claimed that the ONS data 'fixed' this bias and hence properly adjusted the results. However, as we pointed out in [1], while the NIMS data may indeed overestimate the number of vaccinated, it is likely that it also underestimates the number of unvaccinated (a much more difficult number to estimate than those vaccinated). ...
The risk/benefit of Covid vaccines is arguably most accurately measured by comparing the all-cause mortality rate 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. We examine two of the most recent UK ONS vaccine mortality surveillance reports, which provide the necessary information to monitor this crucial comparison over time. At first glance the ONS data suggest that, in each of the older age groups, all-cause mortality is lower in the vaccinated than the unvaccinated. This conclusion is cast into doubt upon closer inspection of the data due to a range of fundamental inconsistencies and anomalies in the data. Whatever the explanations for these are, it is clear that the data is both unreliable and misleading. It has been suggested that the anomalies are the result of healthy vaccinee selection bias and population differences. However, we show why the most likely explanations for the observed anomalies are a combination of 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. We also find no evidence that socio-demographic or behavioural differences between vaccinated and unvaccinated can explain these anomalies.
... Our recent articles [1,2] have argued that the simplest and most objective way to assess the overall risk/benefit of Covid-19 vaccines is to compare all-cause mortality rates of the unvaccinated against the vaccinated in each separate age-group. For such an assessment we need accurate periodic data on both age-categorized deaths and the number of vaccinated/unvaccinated people in each age group for that period. ...
... The UK Government (through its various relevant agencies) has been better than most countries in providing detailed data on Covid cases and deaths indexed by vaccine status. However, in [1] we highlighted the absence of relevant age-categorized mortality data for England, and major inconsistencies in the data provided by different agencies. Of most concern are the very different estimates provided by UKHSA (United Kingdom Health Security Agency) and the ONS (Office for National Statistics) of the number of vaccinated and unvaccinated people. ...
... They claimed that the ONS data 'fixed' this bias and hence properly adjusted the results. However, as we pointed out in [1], while the NIMS data may indeed overestimate the number of vaccinated, it is likely that it also underestimates the number of unvaccinated (a much more difficult number to estimate than those vaccinated). ...
This paper has been updated and the new version can be found here:
Official mortality data for England suggest systematic miscategorisation of vaccine status and uncertain effectiveness of Covid-19 vaccination
UPDATED WITH ONS DECEMBER DATA RELEASE & HEALTHY VACCINEE/MORIBUND ANALYSIS
http://dx.doi.org/10.13140/RG.2.2.28055.09124
https://www.researchgate.net/publication/357778435_Official_mortality_data_for_England_suggest_systematic_miscategorisation_of_vaccine_status_and_uncertain_effectiveness_of_Covid-19_vaccination
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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. We examine the latest UK ONS vaccine mortality surveillance report which provides the necessary information to monitor this crucial comparison over time. At first glance the ONS data suggest that, in each of the older age groups, all-cause mortality is lower in the vaccinated than the unvaccinated. 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. Whatever the explanations for the observed data, it is clear that it is both unreliable and misleading. While socio-demographical and behavioural differences between vaccinated and unvaccinated have been proposed as possible explanations, there is no evidence to support any of these. 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.
U hrvatskim je medijima sve više govora o cijepljenju djece protiv covid-19, unatoč maloj ulozi djece u prijenosu novog koronavirusa i njihovom malom riziku od teških simptoma, postojanju drugih oblika prevencije, činjenici da klinička ispitivanja nisu dovršena, raznih problema u provedenim ispitivanjima i rastućoj zabrinutosti oko sigurnosti cjepiva i mogućih štetnih učinaka. Cilj je ovog kratkog pregleda odabrane znanstvene literature potaknuti kvalitetnu javnu raspravu prije donošenja potencijalno ishitrenih odluka.
