See the below research surrounding the Covid-19 virus and the vaccine statistical analysis:
VERY IMPORTANT (Vaccines may be responsible for excess deaths) – Excess mortality across countries in the Western World since the COVID-19 pandemic: ‘Our World in Data’ estimates of January 2020 to December 2022 (https://bmjpublichealth.bmj.com/content/2/1/e000282)
Although COVID-19 vaccines were provided to guard civilians from suffering morbidity and mortality by the COVID-19 virus, suspected adverse events have been documented as well.15 The secondary analysis of the placebo-controlled, phase III randomised clinical trials of mRNA COVID-19 vaccines showed that the Pfizer trial had a 36% higher risk of serious adverse events in the vaccine group. The risk difference was 18.0 per 10 000 vaccinated (95% CI 1.2 to 34.9), and the risk ratio was 1.36 (95% CI 1.02 to 1.83). The Moderna trial had a 6% higher risk of serious adverse events among vaccine recipients. The risk difference was 7.1 per 10 000 vaccinated (95% CI −23.2 to 37.4), and the risk ratio was 1.06 (95% CI 0.84 to 1.33).39 By definition, these serious adverse events lead to either death, are life-threatening, require inpatient (prolongation of) hospitalisation, cause persistent/significant disability/incapacity, concern a congenital anomaly/birth defect or include a medically important event according to medical judgement.39–41 The authors of the secondary analysis point out that most of these serious adverse events concern common clinical conditions, for example, ischaemic stroke, acute coronary syndrome and brain haemorrhage. This commonality hinders clinical suspicion and consequently its detection as adverse vaccine reactions.39 Both medical professionals and citizens have reported serious injuries and deaths following vaccination to various official databases in the Western World, such as VAERS in the USA, EudraVigilance in the European Union and Yellow Card Scheme in the UK.42–48 A study comparing adverse event reports to VAERS and EudraVigilance following mRNA COVID-19 vaccines versus influenza vaccines observed a higher risk of serious adverse reactions for COVID-19 vaccines. These reactions included cardiovascular diseases, coagulation, haemorrhages, gastrointestinal events and thromboses.39 49 Numerous studies reported that COVID-19 vaccination may induce myocarditis, pericarditis and autoimmune diseases.50–57 Postmortem examinations have also ascribed myocarditis, encephalitis, immune thrombotic thrombocytopenia, intracranial haemorrhage and diffuse thrombosis to COVID-19 vaccinations.58–67 The Food and Drug Administration noted in July 2021 that the following potentially serious adverse events of Pfizer vaccines deserve further monitoring and investigation: pulmonary embolism, acute myocardial infarction, immune thrombocytopenia and disseminated intravascular coagulation.39 68
This study explored the excess all-cause mortality in 47 countries of the Western World from 2020 until 2022. The overall number of excess deaths was 3 098 456. Excess mortality was registered in 87% of countries in 2020, in 89% of countries in 2021 and in 91% of countries in 2022. During 2020, which was marked by the COVID-19 pandemic and the onset of mitigation measures, 1 033 122 excess deaths (P-score 11.4%) were to be regretted.17 18 A recent analysis of seroprevalence studies in this prevaccination era illustrates that the Infection Fatality Rate estimates in non-elderly populations were even lower than prior calculations suggested.37 At a global level, the prevaccination Infection Fatality Rate was 0.03% for people aged <60 years and 0.07% for people aged <70 years.38 For children aged 0–19 years, the Infection Fatality Rate was set at 0.0003%.38 This implies that children are rarely harmed by the COVID-19 virus.19 38 During 2021, when not only containment measures but also COVID-19 vaccines were used to tackle virus spread and infection, the highest number of excess deaths was recorded: 1 256 942 excess deaths (P-score 13.8%).26 37 Scientific consensus regarding the effectiveness of non-pharmaceutical interventions in reducing viral transmission is currently lacking.75 76 During 2022, when most mitigation measures were negated and COVID-19 vaccines were sustained, preliminary available data count 808 392 excess deaths (P-score 8.8%).39 The percentage difference between the documented and projected number of deaths was highest in 28% of countries during 2020, in 46% of countries during 2021, and in 26% of countries during 2022.
VERY IMPORTANT (UK ONS excess deaths analysis) – Excess mortality in England post COVID-19 pandemic: implications for secondary prevention https://www.thelancet.com/journals/lanepe/article/PIIS2666-7762(23)00221-1/fulltext
This model finds that in the period from week ending 3rd June 2022 to 30th June 2023, excess deaths for all causes were relatively greatest for 50–64 year olds (15% higher than expected), compared with 11% higher for 25–49 and < 25 year olds, and about 9% higher for over 65 year old groups. While the median age of these groups has changed since 2020, age-standardised mortality analysis breaking down death rates by sex find clearer age differences still. The age-standardised CMI found similar patterns with the largest relative excess deaths for 2022 observed in young (20–44 years) and middle-aged (45–64 years) adults.7 These findings should be interpreted carefully because of greater than usual delay in registration of deaths in the latter part of 2022.8
Several causes, including cardiovascular diseases, show a relative excess greater than that seen in deaths from all-causes (9%) over the same period (week ending 3rd June 2022–30th June 2023), namely: all cardiovascular diseases (12%), heart failure (20%), ischaemic heart diseases (15%), liver diseases (19%), acute respiratory infections (14%), and diabetes (13%).6
For middle-aged adults (50–64) in this 13-month period, the relative excess for almost all causes of death examined was higher than that seen for all ages. Deaths involving cardiovascular diseases were 33% higher than expected, while for specific cardiovascular diseases, deaths involving ischaemic heart diseases were 44% higher, cerebrovascular diseases 40% higher and heart failure 39% higher. Deaths involving acute respiratory infections were 43% higher than expected and for diabetes, deaths were 35% higher. Deaths involving liver diseases were 19% higher than expected for those aged 50–64, the same as for deaths at all ages.9
Looking at place of death, from 3rd June 2022 to 30th June 2023 there were 22% more deaths in private homes than expected compared with 10% more in hospitals, but there was no excess in deaths in care homes and 12% fewer deaths than expected in hospices. For deaths involving cardiovascular diseases the relative excess in private homes was higher than all causes at 27%. Deaths in hospital were 8% higher and deaths in care homes only 3% higher.9
The greatest numbers of excess deaths in the acute phase of the pandemic were in older adults. The pattern now is one of persisting excess deaths which are most prominent in relative terms in middle-aged and younger adults, with deaths from CVD causes and deaths in private homes being most affected. Timely and granular analyses are needed to describe such trends and so to inform prevention and disease management efforts. Leveraging such granular insights has the potential to mitigate what seems to be a continued and unequal impact on mortality, and likely corresponding impacts on morbidity, across the population.
IMPORTANT (Modelling analysis that suggests Government response to Covid was unfounded) – Epidemic outcomes following government responses to COVID-19: Insights from nearly 100,000 models https://www.science.org/doi/10.1126/sciadv.adn0671
Government responses to COVID-19 are among the most globally impactful events of the 21st century. The extent to which responses—such as school closures—were associated with changes in COVID-19 outcomes remains unsettled. Multiverse analyses offer a systematic approach to testing a large range of models. We used daily data on 16 government responses in 181 countries in 2020–2021, and 4 outcomes—cases, infections, COVID-19 deaths, and all-cause excess deaths—to construct 99,736 analytic models. Among those, 42% suggest outcomes improved following more stringent responses (“helpful”). No subanalysis (e.g. limited to cases as outcome) demonstrated a preponderance of helpful or unhelpful associations. Among the 14 associations with P values < 1 × 10−30, 5 were helpful and 9 unhelpful. In summary, we find no patterns in the overall set of models that suggests a clear relationship between COVID-19 government responses and outcomes. Strong claims about government responses’ impacts on COVID-19 may lack empirical support.
VERY IMPORTANT (Vaccine associated mortality) Rancourt – COVID-19 vaccine-associated mortality in the Southern Hemisphere https://correlation-canada.org/covid-19-vaccine-associated-mortality-in-the-Southern-Hemisphere/
All 17 countries have transitions to regimes of high ACM, which occur when the COVID‑19 vaccines are deployed and administered. Nine of the 17 countries have no detectable excess ACM in the period of approximately one year after a pandemic was declared on 11 March 2020 by the World Health Organization (WHO), until the vaccines are rolled out (Australia, Malaysia, New Zealand, Paraguay, Philippines, Singapore, Suriname, Thailand, Uruguay).
Unprecedented peaks in ACM occur in the summer (January-February) of 2022 in the Southern Hemisphere, and in equatorial-latitude countries, which are synchronous with or immediately preceded by rapid COVID-19-vaccine-booster-dose rollouts (3rd or 4th doses). This phenomenon is present in every case with sufficient mortality data (15 countries). Two of the countries studied have insufficient mortality data in January-February 2022 (Argentina and Suriname).
Detailed mortality and vaccination data for Chile and Peru allow resolution by age and by dose number. It is unlikely that the observed peaks in all-cause mortality in January-February 2022 (and additionally in: July-August 2021, Chile; July-August 2022, Peru), in each of both countries and in each elderly age group, could be due to any cause other than the temporally associated rapid COVID-19-vaccine-booster-dose rollouts. Likewise, it is unlikely that the transitions to regimes of high ACM, coincident with the rollout and sustained administration of COVID‑19 vaccines, in all 17 Southern-Hemisphere and equatorial-latitude countries, could be due to any cause other than the vaccines.
Synchronicity between the many peaks in ACM (in 17 countries, on 4 continents, in all elderly age groups, at different times) and associated rapid booster rollouts allows this firm conclusion regarding causality, and accurate quantification of COVID-19-vaccine toxicity.
The all-ages vaccine-dose fatality rate (vDFR), which is the ratio of inferred vaccine-induced deaths to vaccine doses delivered in a population, is quantified for the January-February 2022 ACM peak to fall in the range 0.02 % (New Zealand) to 0.20 % (Uruguay). In Chile and Peru, the vDFR increases exponentially with age (doubling approximately every 4 years of age), and is largest for the latest booster doses, reaching approximately 5 % in the 90+ years age groups (1 death per 20 injections of dose 4). Comparable results occur for the Northern Hemisphere, as found in previous articles (India, Israel, USA).
We quantify the overall all-ages vDFR for the 17 countries to be (0.126 ± 0.004) %, which would imply 17.0 ± 0.5 million COVID-19 vaccine deaths worldwide, from 13.50 billion injections up to 2 September 2023. This would correspond to a mass iatrogenic event that killed (0.213 ± 0.006) % of the world population (1 death per 470 living persons, in less than 3 years), and did not measurably prevent any deaths.
The overall risk of death induced by injection with the COVID-19 vaccines in actual populations, inferred from excess all‑cause mortality and its synchronicity with rollouts, is globally pervasive and much larger than reported in clinical trials, adverse effect monitoring, and cause-of-death statistics from death certificates, by 3 orders of magnitude (1,000‑fold greater).
VERY IMPORTANT (Not Covid associated mortality) Rancourt – Spatiotemporal variation of excess all-cause
mortality in the world (125 countries) during the Covid period 2020-2023 regarding socio-economic factors and public-health and medical interventions https://correlation-canada.org/wp-content/uploads/2024/07/2024-07-19-Correlation-ACM-World-125-countries-Rancourt-Hickey-Linard.pdf
Inconsistencies that disprove the hypothesis of a viral respiratory pandemic to explain
excess all-cause mortality during the Covid period are seen on a global scale and
include the following.
- Near-synchronicity of onset, across several continents, of surges in excess
mortality occurring immediately when a pandemic is declared by the WHO
(11 March 2020), and never prior to pandemic announcement in any country - Excessively large country-to-country heterogeneity of the age-and-health-status-
adjusted (P-score) mortality during the Covid period, including across shared
borders between adjacent countries, and including in all time periods down to
half years - Highly time variable age-and-health-status-adjusted (P-score) mortality in
individual countries during and after the Covid period, including more-than-year-
long periods of zero excess mortality, long-duration plateaus or regimes of high
excess mortality, single peaks versus many recurring peaks, and persistent high
excess mortality after a pandemic is declared to have ended (5 May 2023) - Strong correlations (all-country scatter plots) between excess all-cause mortality
rates and socio-economic factors (esp. measures of poverty) change with time
(by year and half year) during the Covid period, between diametrically opposite
values (near-zero, large and positive, large and negative) of the Pearson
correlation coefficient (e.g., Figure 29, first half of 2020 to first half of 2023)
One might tentatively add:
- No evidence of the large vaccine rollouts ever being associated with reductions
in excess all-cause mortality, in any country (and see Rancourt and Hickey,
2023) - Exponential increases with age in excess all-cause mortality rate (by population),
consistent with age-dominant frailty rather than infection in the limit of high
virulence
We describe plausible mechanisms and argue that the three primary causes of death
associated with the excess all-cause mortality during (and after) the Covid period are:
(1) Biological (including psychological) stress from mandates such as lockdowns and
associated socio-economic structural changes
(2) Non-COVID-19-vaccine medical interventions such as mechanical ventilators
and drugs (including denial of treatment with antibiotics)
(3) COVID-19 vaccine injection rollouts, including repeated rollouts on the same
populations
In all cases ― for all three identified primary causes of death ― a proximal or clinical
cause of death associated (such as on death certificates) with the quantified excess
all-cause mortality is respiratory condition or infection. Therefore, we distinguish (and
define) true primary causes of death from the pervasive and accompanying proximal or
clinical cause of death as respiratory.
VERY IMPORTANT (UK stats on Midazolam application leading to deaths) – Excess Deaths in the United Kingdom: Midazolam and Euthanasia in the COVID-19 Pandemic https://www.researchgate.net/publication/377266988_Excess_Deaths_in_the_United_Kingdom_Midazolam_and_Euthanasia_in_the_COVID-19_Pandemic
Macro-data during the COVID-19 pandemic in the United Kingdom (UK) are shown to have significant data anomalies and inconsistencies with existing explanations. This paper shows that the UK spike in deaths, wrongly attributed to COVID-19 in April 2020, was not due to SARS-CoV-2 virus, which was largely absent, but was due to the widespread use of Midazolam injections which were statistically very highly correlated (coefficient over 90 percent) with excess deaths in all regions of England during 2020. Importantly, excess deaths remained elevated following mass vaccination in 2021, but were statistically uncorrelated to COVID injections, while remaining significantly correlated to Midazolam injections. The widespread and persistent use of Midazolam in UK suggests a possible policy of systemic euthanasia. Unlike Australia, where assessing the statistical impact of COVID injections on excess deaths is relatively straightforward, UK excess deaths were closely associated with the use of Midazolam and other medical intervention. The iatrogenic pandemic in the UK was caused by euthanasia deaths from Midazolam and also, likely caused by COVID injections, but their relative impacts are difficult to measure from the data, due to causal proximity of euthanasia. Global investigations of COVID-19 epidemiology, based only on the relative impacts of COVID disease and vaccination, may be inaccurate, due to the neglect of significant confounding factors in some countries.
VERY IMPORTANT (Excess cardio deaths increase) – Excess Cardiopulmonary Arrest and Mortality after COVID-19 Vaccination in King County, Washington https://www.preprints.org/manuscript/202405.1665/v1
We found that both the total number of cardiopulmonary arrests and fatal events increased
more than expected coinciding with the rollout of the COVID-19 mass vaccination program in King
County, WA. Our study estimated a 1,236% rise in excess cardiopulmonary arrest deaths following
the introduction of COVID-19 vaccines, which have regulatory warnings for myocarditis and
thromboembolism [17,18]. Both of these conditions have been proven to likely be fatal in autopsy
studies of death after COVID-19 vaccination [19,20]. A very strong correlation between higher
vaccination rates and excess cardiopulmonary arrest mortality was observed in the quadratic model.
Additionally, the population of King County decreased by 0.94% in 2021, which coincided with the
sharp rise in cardiopulmonary arrest fatalities and onset of vaccination campaigns. Applying our
model to the entire United States yielded 49,240 excess cardiopulmonary arrest deaths from 2021-
2023.
These findings are consistent with existing literature that report an increase in cardiopulmonary
arrests and cardiovascular-related deaths since 2020 and 2021 [11,12,21–23]. Sun et al found a 25%
increase in the number of cardiac arrest and acute coronary syndrome EMS calls among the 16–39
age group during the COVID-19 vaccination campaign in Israel compared with the same time period
in prior years, corroborating the 25.7% increase in cardiopulmonary arrests estimated in our study
[22]. Moreover, they used Negative Binomial regression models and found the weekly emergency
call counts were significantly associated with COVID-19 vaccination rates in the 16-39 age group, and
not with COVID-19 infection rates [22]. The authors concluded that surveillance of COVID-19 vaccine
adverse events should incorporate EMS data, as we did in our study. Woodruff et al found that from
2020 to 2022, 228,524 excess cardiovascular-related deaths occurred in the United States, which was
9% more deaths than expected based on trends from 2010 to 2019, supporting our national estimate
of 49,240 excess cardiopulmonary deaths possibly due to COVID-19 vaccination [23]. The largest
COVID-19 vaccine safety study, conducted by the Global Vaccine Data Network (GVDN) and
included around 99 million vaccinated individuals across multiple countries, found that the risk of
myocarditis was significantly elevated after mRNA COVID-19 vaccinations, with the risk being 510%
and 186% higher than baseline rates following the second doses of the mRNA-1273 and BNT162b2
vaccines, respectively [24]. Moreover, the large study found that the risk of pulmonary embolism was
33% higher than baseline rates after the first dose of mRNA-1273 and 29% higher than baseline rates
after the first dose of BNT162b2, respectively [24]. Rose et al analyzed the Vaccine Adverse Event
Reporting System (VAERS) and found that myocarditis reports following COVID-19 vaccination in
2021 were 223 times higher than the average incidence for all vaccines combined over the past 30
years, with a 2.9% fatality rate. They concluded that COVID-19 vaccines are strongly associated with
a significant adverse safety signal for myocarditis, leading to hospitalization and death [4]. Since 98%
of the population in King County was vaccinated against COVID-19, it can be inferred that an excess
number of individuals may have suffered from COVID-19 vaccine-induced myocarditis or
thromboembolism.
VERY IMPORTANT (Number of doses to mortality) – Reaffirming a Positive Correlation Between Number of Vaccine Doses and Infant Mortality Rates: A Response to Critics https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9897596/
VERY IMPORTANT (Risk to benefit assessment) – Is the Harm-to-Benefit Ratio a Key Criterion in Vaccine Approval? https://www.frontiersin.org/articles/10.3389/fmed.2022.879120/full
IMPORTANT (Steve Kirsch study on efficacy using data sets) – A Novel Practical Approach for Directly Assessing COVID-19 Vaccine Efficacy against Hospitalization https://www.preprints.org/manuscript/202408.0338/v1
We revisit a 2023 JAMA-published analysis of data from patients admitted for either COVID-19 or influenza to U.S. Veterans Administration (VA) hospitals in the fall/winter of 2022-2023. We note that baseline characteristics between the cohorts were similar, and the difference in vaccination rates was minimal, even after propensity score weighting. Had the vaccines been even minimally effective, significant differences in vaccination percentages would be expected. These findings call into question any efficacy claims associated with either the COVID-19 or influenza vaccines. Furthermore, the lack of efficacy of the influenza vaccines in reducing hospitalization is consistent with an earlier detailed study that found the same lack of efficacy, further validating the current result. This suggests that comparing vaccination rates between those hospitalized for different vaccine-preventable diseases can serve as a practical method for validating the vaccine efficacy claims of different vaccines.
IMPORTANT 2022 WHO STUDY (Risks of Adverse Events from the vaccine greater than any benefits) – Serious Adverse Events of Special Interest Following mRNA Vaccination in Randomized Trials https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4125239
IMPORTANT (Serious Adverse Events for younger age groups) – A comparative analysis on serious adverse events reported for COVID-19 vaccines in adolescents and young adults https://pubmed.ncbi.nlm.nih.gov/37377545/
IMPORTANT (Temporal association of vaccines to adverse avents) – Temporal Analysis of Vaccine Adverse Effects for Causation Inference https://europepmc.org/article/PPR/PPR776637
We measure a vaccine fatality rate of order 0.01 for all vaccine manufacturers and identify a strong heterogeneity in the vaccine toxicity across vaccine lots, spanning up to four orders of magnitude. We compute the correlation between vaccination dates and death dates, and produce an estimate of the time lag that maximises the correlation, finding that the onset of adverse effects happened statistically (i.e. 32-41 percentiles) within one day after the vaccine administration and that death happened statistically (i.e. 22-50 percentiles) within about two weeks after the vaccine administration.
IMPORTANT (Debunking the computational “saved millions” studies) – Analysis of COVID-19 Vaccination Effectiveness https://www.walshmedicalmedia.com/open-access/analysis-of-covid19-vaccination-effectiveness-120520.html
IMPORTANT (ACM not showing the jabs effective) – Does the healthy vaccinee bias rule them all? Association of COVID-19 vaccination status and all-cause mortality from an analysis of data from 2.2 million individual health records https://www.sciencedirect.com/science/article/pii/S1201971224000468
Highlights
- •Analysis based on two independent datasets, total population of approx. 2.2 million.
- •All-cause mortality (ACM) of vaccinated and unvaccinated against COVID-19.
- •ACM consistently much lower in freshly vaccinated groups even outside COVID waves.
- •Healthy vaccinee bias demonstrated on visualizations of the data.
- •This bias overestimates COVID-19 vaccine efficiency in observational studies
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% 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.
Between June 2021 and September 2021, virtually no COVID-related deaths were recorded in the Czech Republic (only approx. 0.3% 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.
NARRATIVE BIASED CORRUPT MODELLING (Moderna funded trial, carried out by Moderna employees, find Moderna jab better at protecting citizens than Pfizer) – Clinical impact and cost-effectiveness of the updated COVID-19 mRNA Autumn 2023 vaccines in Germany https://www.medrxiv.org/content/10.1101/2023.10.09.23296505v1
Results Compared to no Autumn vaccination, the mRNA-1273.815 campaign is predicted to prevent approximately 1,697,900 symptomatic infections, 85,400 hospitalisations, and 4,100 deaths. Compared to an XBB.1.5 BNT162b2 campaign, the mRNA-1273.815 campaign is also predicted to prevent approximately 90,100 symptomatic infections, 3,500 hospitalisations, and 160 deaths. Across both analyses we found the mRNA-1273.815 campaign to be dominant.
Conclusions The mRNA-1273.815 vaccine can be considered cost-effective relative to the XBB.1.5 BNT162b2 vaccine and highly likely to provide more benefits and save costs compared to no vaccine in Germany, and to offer high societal return on investment.
IMPORTANT (Computational models not reproducable) – Reproducibility of COVID-era infectious disease models https://www.medrxiv.org/content/10.1101/2023.10.11.23296911v1.full-text Published https://www.sciencedirect.com/science/article/pii/S1755436524000045?via%3Dihub
We found that only four out of 100 randomly sampled studies released between January 2020 and August 2022 could be computationally reproduced using the resources provided (e.g., code, data, instructions). For the 100 most highly cited articles from the same period we found that only 11 were reproducible. Reflecting on our experience, we discuss common issues affecting computational reproducibility and how these might be addressed.
IMPORTANT (Debunking the “doesn’t prevent infection but prevents severe hospitalisation and death”) – Comparison of hospitalizations and deaths from COVID-19 2021 versus 2020 in Italy: surprises and implications https://f1000research.com/articles/10-964
The combination of non-alternative hypotheses may help explain the discrepancy between the results in the entire population and the vaccination’s success claimed by the ISS in reducing infections, serious cases and deaths:
- a bias: counting as unvaccinated also “those vaccinated with 1 dose in the two weeks following the inoculation”, and as incompletely vaccinated also “those vaccinated with 2 doses within two weeks of the 2nd inoculation”.
- a systematic error: counting as unvaccinated also “vaccinated with 1 dose in the two weeks following the inoculation”, and as incompletely vaccinated also “vaccinated with 2 doses within two weeks of the 2nd inoculation”.
Many reports show an increase in COVID-19 cases in these time-windows, and related data should be separated
- levels of protective effectiveness in vaccinated people, often considered stable, actually show signs of progressive reduction over time, which could contribute to reducing the overall population result
- unvaccinated people show more severe disease than in 2020, supporting also in humans the theory of imperfect vaccines, which offer less resistance to the entry of germs than the resistance later encountered inside the human body. This favors the selection of more resistant and virulent mutants, that can be spread by vaccinated people. This damages first the unvaccinated people, but ultimately the whole community.
IMPORTANT (All cause mortality did not rise during Covid 2020, logical explanation is government response) – All-cause mortality during COVID-19: No plague and a likely signature of mass homicide by government response https://www.researchgate.net/publication/341832637_All-cause_mortality_during_COVID-19_No_plague_and_a_likely_signature_of_mass_homicide_by_government_response PDF https://ia803202.us.archive.org/27/items/all-cause-mortality-during-covid-19-no-plague-and-a-likely-signature-of-mass-hom/All-cause%20mortality%20during%20COVID-19%20-%20%20No%20plague%20and%20a%20likely%20signature%20of%20mass%20homicide%20by%20government%20response%20Denis%20G.%20Rancourt,%20PhD.pdf
IMPORTANT (Iatragenic deaths not Covid) – Excess Deaths in the United Kingdom: Midazolam and Euthanasia in the COVID-19 Pandemic https://www.researchgate.net/publication/377266988_Excess_Deaths_in_the_United_Kingdom_Midazolam_and_Euthanasia_in_the_COVID-19_Pandemic
Macro-data during the COVID-19 pandemic in the United Kingdom (UK) are shown to have significant data anomalies and inconsistencies with existing explanations. This paper shows that the UK spike in deaths, wrongly attributed to COVID-19 in April 2020, was not due to SARS-CoV-2 virus, which was largely absent, but was due to the widespread use of Midazolam injections which were statistically very highly correlated (coefficient over 90 percent) with excess deaths in all regions of England during 2020. Importantly, excess deaths remained elevated following mass vaccination in 2021, but were statistically uncorrelated to COVID injections, while remaining significantly correlated to Midazolam injections. The widespread and persistent use of Midazolam in UK suggests a possible policy of systemic euthanasia. Unlike Australia, where assessing the statistical impact of COVID injections on excess deaths is relatively straightforward, UK excess deaths were closely associated with the use of Midazolam and other medical intervention. The iatrogenic pandemic in the UK was caused by euthanasia deaths from Midazolam and also, likely caused by COVID injections, but their relative impacts are difficult to measure from the data, due to causal proximity of euthanasia. Global investigations of COVID-19 epidemiology, based only on the relative impacts of COVID disease and vaccination, may be inaccurate, due to the neglect of significant confounding factors in some countries.
IMPORTANT (Reinfection rate increases post vaccination) – Rate of SARS-CoV-2 Reinfection During an Omicron Wave in Iceland https://pubmed.ncbi.nlm.nih.gov/35921113/
IMPORTANT (Increased mortality) – Forgotten “Primum Non Nocere” and Increased Mortality after
COVID-19 Vaccination https://www.primescholars.com/articles/forgotten-primum-non-nocere-and-increased-mortality-after–covid19-vaccination.pdf
VERY IMPORTANT (Overall mortality increases post vaccination) – Randomized clinical trials of COVID-19 vaccines: Do adenovirus-vector vaccines have beneficial non-specific effects? https://www.cell.com/iscience/fulltext/S2589-0042(23)00810-6
IMPORTANT (Comparison for children, jabbed and unjabbed, during Delta and Omicron, showed ARR much more effective being unjabbed) – Real-world Effectiveness of BNT162b2 Against Infection and Severe Diseases in Children and Adolescents https://www.medrxiv.org/content/10.1101/2023.06.16.23291515v3.full-text
VERY IMPORTANT (Messaging and survey showed a liklihood that between 229,319 – 344,319 have lost their lives to the injections, further fuelling hesitency) – COVID-19 Illness and Vaccination Experiences in Social Circles Affect COVID-19 Vaccination Decisions https://www.publichealthpolicyjournal.com/_files/ugd/adf864_4c3afc4436234a96aa1f60bb6e677719.pdf
An online survey of COVID-19 health experiences was conducted to collect information regarding reasons for and against COVID-19 inoculations, including experiences with COVID-19 illness and COVID-19 inoculations by survey respondents and their social circles. The survey was completed by 2,840 participants between December 18 and 23, 2021. Logit regression analyses were carried out to identify factors influencing the likelihood of being vaccinated. Those who knew someone who experienced a health problem from COVID-19 were more likely to be vaccinated (OR: 1.309, 95% CI: 1.094-1.566), while those who knew someone who experienced a health problem following vaccination were less likely to be vaccinated (OR: 0.567, 95% CI: 0.461-0.698). Thirty-four percent (959 of 2,840) reported that they knew at least one person who experienced a significant health problem due to the COVID-19 illness. Similarly,
22% (612 of 2,840) indicated that they knew at least one person who experienced a health problem following COVID-19 vaccination. With these survey data, the total number of fatalities due to COVID-19 inoculation may be as high as 289,789 (95% CI: 229,319 – 344,319). The large difference in the possible number of fatalities due to COVID-19 vaccination that emerges from this survey and the available governmental data should be further investigated.
VERY IMPORTANT (Observational study bias) – Sources of bias in observational studies of covid-19 vaccine effectiveness https://onlinelibrary.wiley.com/doi/10.1111/jep.13839
VERY IMPORTANT (Bias in test negative control designed studies) – Potential Biases in Test-Negative Design Studies of COVID-19 Vaccine Effectiveness Arising from the Inclusion of Asymptomatic Individuals https://www.medrxiv.org/content/10.1101/2023.11.16.23298633v1 Published https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwae288/7736089?login=false
VERY IMPORTANT (Critique of vaccine effectiveness studies) – SEIR models in the light of Critical Realism – A critique of exaggerated claims about the effectiveness of Covid 19 vaccinations https://www.researchgate.net/publication/368463364_SEIR_models_in_the_light_of_Critical_Realism_-_a_critique_of_exaggerated_claims_about_the_effectiveness_of_Covid_19_vaccinations
VERY IMPORTANT (Statement from Office for Statistics Regulation on ONS being inaccurate for basing vaccine efficacy data) – Ed Humpherson to Norman Fenton, Martin Neil, Clare Craig and Scott McLachlan: ONS Deaths by Vaccination Status statistics https://osr.statisticsauthority.gov.uk/correspondence/ed-humpherson-to-norman-fenton-martin-neil-clare-craig-and-scott-mclachlan-ons-deaths-by-vaccination-status-statistics/
Your paper on this topic recognised that the sample analysed in the Deaths by Vaccination Status publication is not a whole-population sample. We agree and think this is an important point. To summarise, the publication uses data from the Public Health Data Asset (PHDA), which combines data from the 2011 census and the General Practice Extraction Service (GPES). For an individual to be included in the PHDA, they must have responded to the 2011 census and be presently registered with a GP. Approximately 79% of the population fall into this category. Those missing from the PHDA dataset are therefore not missing at random, and they are more likely to fall under one or more of the following categories:
- Younger in age
- Born outside of the UK
- Unvaccinated (as it is more difficult to obtain a COVID-19 vaccination without being registered with a GP)
We consider that it is therefore likely that the sample used in the Deaths by Vaccination Status publication is not representative of the general population. Those who are missing are, we think, more likely to be younger and unvaccinated. This is also acknowledged by ONS in its Deaths by Vaccination Status publications.
ONS is working to address some of the sampling issues present in the first six iterations of the publication. As stated in the notice at the top of the most recent publication, there is a delay in publishing the next edition. This is because ONS requires further data on subsequent booster vaccinations, and also because it is waiting for data from the 2021 Census. These data will substantially increase the sample size, meaning that the sampling frame will be much more representative of the general population. We will monitor how ONS delivers and communicates these changes as part of our ongoing review work.
IMPORTANT (Open letter to MHRA) – “From Watchdog to Enabler?” Undertake an urgent review into the MHRA’s approval of the Covid vaccines https://togetherdeclaration.org/MHRA/ Download the presentation with citations
IMPORTANT (CDC errors made to analysis) – Statistical and Numerical Errors Made by the US Centers for Disease Control and Prevention During the COVID-19 Pandemic https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4381627
Results: We documented 25 instances when the CDC reported statistical or numerical errors. Twenty (80%) of these instances exaggerated the severity of the COVID-19 situation, 3 (12%) instances simultaneously exaggerated and downplayed the severity of the situation, one error was neutral, and one error exaggerated COVID-19 vaccine risks. The CDC was notified about the errors in 16 (64%) instances, and later corrected the errors, at least partially, in 13 (52%) instances.
Conclusion: A basic prerequisite for making informed policy decisions is accurate and reliable statistics, even during times of uncertainty. Our investigation revealed 25 instances of numerical or statistical errors made by the CDC. Our investigation suggests 1) the need for greater diligence in data collection and reporting, and 2) that the federal entity responsible for reporting health statistics should be firewalled from the entity setting policy due to concerns of real or perceived systematic bias in errors.
VERY IMPORTANT (Ioannidis Covid-19 IFR) – The infection fatality rate of COVID-19 inferred from seroprevalence data https://www.medrxiv.org/content/10.1101/2020.05.13.20101253v3 Published https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7947934/pdf/BLT.20.265892.pdf/
The authors provide age-stratified risks:
Ages 0-19: fatality rate 0.0003%; survival rate 99.9997%
Ages 20-29: fatality rate 0.003%; survival rate 99.997%
Ages 30-39: fatality rate 0.011%; survival rate 99.989%
Ages 40-49: fatality rate 0.035%; survival rate 99.965%
VERY IMPORTANT (NNT and ARR / RRR) – Curing the pandemic of misinformation on COVID-19 mRNA vaccines through real evidence-based medicine; Part 1 – https://insulinresistance.org/index.php/jir/article/view/71/224 – Part 2 – https://insulinresistance.org/index.php/jir/article/view/72/228
IMPORTANT (IFR – Ioannidis et al 2022) – Age-stratified infection fatality rate of COVID-19 in the non-elderly informed from pre-vaccination national seroprevalence studies https://www.medrxiv.org/content/10.1101/2022.10.11.22280963v1
IMPORTANT (Excess deaths – John P.A. Ioannidis) – Excess death estimates from multiverse analysis in 2009-2021 https://www.medrxiv.org/content/10.1101/2022.09.21.22280219v1
IMPORTANT (IFR Rate) – Infection fatality rate of COVID-19 in community-dwelling populations with an emphasis on the elderly: An overview https://www.medrxiv.org/content/10.1101/2021.07.08.21260210v1.full Published in European Journal of Epidemiology volume 37 https://link.springer.com/article/10.1007/s10654-022-00853-w
IMPORTANT (IFR OMICRON) – Published Aug 05 2022 – Seroprevalence and infection fatality rate of the SARS-CoV-2 Omicron variant in Denmark: A nationwide serosurveillance study https://www.thelancet.com/journals/lanepe/article/PIIS2666-7762(22)00175-2/fulltext
IMPORTANT (IFR Rate) – Predicted COVID-19 fatality rates based on age, sex, comorbidities and health system capacity https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7482102/
Accounting for differences in the distribution of age, sex and relevant comorbidities yields substantial differences in the predicted IFR across 21 world regions, ranging from 0.11% in Western Sub-Saharan Africa to 1.07% for high-income Asia Pacific. However, these predictions must be treated as lower bounds in low- and middle-income countries as they are grounded in fatality rates from countries with advanced health systems. To adjust for health system capacity, we incorporate regional differences in the relative odds of infection fatality from childhood respiratory syncytial virus. This adjustment greatly diminishes but does not entirely erase the demography-based advantage predicted in the lowest income settings, with regional estimates of the predicted COVID-19 IFR ranging from 0.37% in Western Sub-Saharan Africa to 1.45% for Eastern Europe.
VERY IMPORTANT (Causal link to vaccine fatality rate) – Causal effect of covid vaccination on mortality in Europe https://www.researchgate.net/publication/368777703_Causal_effect_of_covid_vaccination_on_mortality_in_Europe
IMPORTANT (Mortality in Qatar post Omicron) – A turning point in COVID-19 severity and fatality during the pandemic: A national cohort study in Qatar https://www.medrxiv.org/content/10.1101/2023.05.28.23290641v1.full-text
IMPORTANT (Over and under counting of deaths and the impact – John P.A. Ioannidis) – Over- and under-estimation of COVID-19 deaths https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8318048/
A nomogram is offered to assess the potential extent of over- and under-counting in different situations. COVID-19 deaths were apparently under-counted early in the pandemic and continue to be under-counted in several countries, especially in Africa, while over-counting probably currently exists for several other countries, especially those with intensive testing and high sensitization and/or incentives for COVID-19 diagnoses. Death attribution in a syndemic like COVID-19 needs great caution. Finally, excess death estimates are subject to substantial annual variability and include also indirect effects of the pandemic and the effects of measures taken.
IMPORTANT (Case biases and death misattribution) – Biases in COVID-19 Case and Death Definitions: Potential Causes and Consequences https://www.cambridge.org/core/journals/disaster-medicine-and-public-health-preparedness/article/biases-in-covid19-case-and-death-definitions-potential-causes-and-consequences/0CD0A1C5ACE38DBB24ECCA2427B917EF#
First, evidence suggests China’s surveillance data were biased and misinterpreted by the World Health Organization (WHO), prompting the WHO to advise nations to copy China’s lockdowns. China appeared to use narrow diagnostic definitions that undercounted cases and deaths. Second, novel genomic data disseminated during the pandemic without adequate guidance from rigorous epidemiologic studies biased infection control policies in many countries. A novel genomic sequence of a virus is insufficient to declare new cases of a novel disease. Third, media reports of COVID-19 surveillance data in many nations appeared to be biased. Broadened surveillance definitions captured additional information, but unadjusted surveillance data disseminated to the public are not true cases and deaths.
IMPORTANT (Miscategorisation / misattribution of vaccine status) Prof Fenton – The extent and impact of vaccine status miscategorisation on covid-19 vaccine efficacy studies https://www.researchgate.net/publication/378831039_The_extent_and_impact_of_vaccine_status_miscategorisation_on_covid-19_vaccine_efficacy_studies
It is recognised that many studies reporting high efficacy for Covid-19 vaccines suffer from various selection biases. Systematic review identified thirty-nine studies that suffered from one particular and serious form of bias called miscategorisation bias,wherebystudy participants who have beenvaccinatedare categorised as unvaccinated up to and until some arbitrarily defined time after vaccination occurred. Simulation demonstrates that this miscategorisation bias artificially boosts vaccine efficacy and infection rates even when a vaccine has zero or negativeefficacy.Furthermore, simulation demonstrates that repeatedboosters, givenevery few months, are needed to maintain this misleading impression of efficacy. Given this, any claims of Covid-19 vaccine efficacy based on these studies are likely to be a statistical illusion
VERY IMPORTANT (Younger age groups not near 0 risk from the virus) – Deaths in children and young people in England after SARS-CoV-2 infection during the first pandemic year https://www.nature.com/articles/s41591-021-01578-1
Authors found:
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is rarely fatal in children and young people (CYP, <18 years old), but quantifying the risk of death is challenging because CYP are often infected with SARS-CoV-2 exhibiting no or minimal symptoms. To distinguish between CYP who died as a result of SARS-CoV-2 infection and those who died of another cause but were coincidentally infected with the virus, we undertook a clinical review of all CYP deaths with a positive SARS-CoV-2 test from March 2020 to February 2021. The predominant SARS-CoV-2 variants were wild-type and Alpha. Here we show that, of 12,023,568 CYP living in England, 3,105 died, including 61 who were positive for SARS-CoV-2. Of these deaths, 25 were due to SARS-CoV-2 infection (mortality rate, two per million), including 22 due to coronavirus disease 2019—the clinical disease associated with SARS-CoV-2 infection—and 3 were due to pediatric inflammatory multisystem syndrome temporally associated with SARS-CoV-2. In total, 99.995% of CYP with a positive SARS-CoV-2 test survived. CYP older than 10 years, Asian and Black ethnic backgrounds and comorbidities were over-represented in SARS-CoV-2-related deaths compared with other CYP deaths. These results are important for guiding decisions on shielding and vaccinating children. New variants might have different mortality risks and should be evaluated in a similar way.
VERY IMPORTANT (Link between shots and ACM (All Cause Mortality) – Is there a Link between the 2021 COVID-19 Vaccination Uptake in Europe and 2022 Excess All-Cause Mortality? https://www.preprints.org/manuscript/202302.0350/v1
Authors found:
We primarily study a possible link between 2021 COVID-19 vaccination uptake in Europe and monthly 2022 excess all-cause mortality, i.e., mortality higher than before the pandemic. Analyses of 31 countries weighted by population size show that all-cause mortality during the first nine months of 2022 increased more the higher the 2021 vaccination uptake; a one percentage point increase in 2021 vaccination uptake was associated with a monthly mortality increase in 2022 by 0.105 percent (95% CI, 0.075-0.134). When controlling for alternative explanations, the association remained robust, and we discuss the result emphasizing causality as well as potential ecological fallacy. Also, the study shows that 2021 all-cause mortality was lower the higher the vaccination uptake, but this association became non-significant when controlling for alternative explanations.
VERY IMPORTANT – (All cause mortality linked to vaccination) – A Critical Analysis of All-Cause Deaths during COVID-19 Vaccination in an Italian Province https://www.mdpi.com/2076-2607/12/7/1343
We used data from an Italian study on COVID-19 vaccine effectiveness, with a large cohort, long follow-up, and adjustment for confounding factors, affected by ITB, with the aim to verify the real impact of the vaccination campaign by comparing the risk of all-cause death between the vaccinated population and the unvaccinated population. We aligned all subjects on a single index date and considered the “all-cause deaths” outcome to compare the survival distributions of the unvaccinated group versus various vaccination statuses. The all-cause-death hazard ratios in univariate analysis for vaccinated people with 1, 2, and 3/4 doses versus unvaccinated people were 0.88, 1.23, and 1.21, respectively. The multivariate values were 2.40, 1.98, and 0.99. Possible explanations of this trend of the hazard ratios as vaccinations increase could be a harvesting effect; a calendar-time bias, accounting for seasonality and pandemic waves; a case-counting window bias; a healthy-vaccinee bias; or some combination of these factors. With 2 and even with 3/4 doses, the calculated Restricted Mean Survival Time and Restricted Mean Time Lost have shown a small but significant downside for the vaccinated populations.
IMPORTANT (Calculates FORTY FIVE times more people were killed than in 32 years of flu vaccines) – Safety of mRNA Vaccines Administered During the First Twenty-Four Months of the International COVID-19 Vaccination Program https://ijvtpr.com/index.php/IJVTPR/article/view/70
IMPORTANT (Lower infection fatality rates) Published Jan 2023 – Significantly lower infection fatality rates associated with SARS-CoV-2 Omicron (B.1.1.529) infection in children and young people: active, prospective national surveillance, January-March 2022, England https://www.journalofinfection.com/article/S0163-4453(23)00037-3/fulltext
VERY IMPORTANT (Data reporting flaw in statistics Australia) – Data reporting flaw in plain sight distorting COVID-19 mortality statistics https://www.academia.edu/85597731/Data_reporting_flaw_in_plain_sight_distorting_COVID_19_mortality_statistics
In Figure 3, the official claims of “reduced severe illnesses and deaths” can be seen clearly to be broadly contradicted by the COVID mortality data of new deaths since 4 September 2021. The five million doses injected through boosters since early 2022 have seen total COVID deaths (including those before the dataset) increased from 663 to 3,610 by 2 July 2022, and to 4,446 on 11 August – a 5.7 times increase.
It is clear that even the altered official claims are false because COVID injections have been associated with manifold increases in severe illnesses and deaths. Somehow, an absurd blame has been put [6] on the “unvaccinated”, despite the fact that both their population and deaths (black bars in Figures 2 and 3) were quite constant in 2022, suggesting a steady death rate for the “unvaccinated”. In contrast, Figure 3 (blue and red bars) shows the rapid increase in deaths in 2022 came from the steady “vaccinated” population (see Figure 2). We need to address the puzzle: despite over a thousand published research papers [7] providing evidence of severe disease and death closely associated with COVID-19 injections, how could official statistics failed to report the rapid increase in deaths from the “vaccinated” population, particularly from the boosters? Given the overall picture, in all seriousness, how could the false official claims be maintained? How could the same official data above, be used by the health authorities to justify those false claims?
IMPORTANT (Bradford Hill criteria on Australia excess deaths) – Australian COVID-19 pandemic: A Bradford Hill analysis of iatrogenic excess mortality https://www.academia.edu/99252694/Australian_COVID_19_pandemic_A_Bradford_Hill_analysis_of_iatrogenic_excess_mortality
Author found:
Australian official mortality data show no clear evidence of significant excess deaths in 2020, implying from an older WHO definition that there was no COVID-19 pandemic. A seasonality analysis suggests that COVID-19 deaths in 2020 were likely misclassifications of influenza and pneumonia deaths. Australian excess mortality became significant only since 2021 when the level was high enough to justify calling a pandemic. Significant excess mortality was strongly correlated (+74%) with COVID-19 mass injections five months earlier. Strength of correlation, consistency, specificity, temporality, and dose-response relationship are foremost Bradford Hill criteria which are satisfied by the data to suggest the iatrogenesis of the Australian pandemic, where excess deaths were largely caused by COVID-19 injections.
Therefore, a strong case has been presented for the iatrogenic origins of the Australian COVID-19 pandemic and therefore, the associated mortality risk/benefit ratio for COVID injections is very high.
IMPORTANT (Vaccine associated excess deaths) – Differential Increases in Excess Mortality in the German Federal States During the COVID-19 Pandemic https://www.researchgate.net/publication/378124684_Differential_Increases_in_Excess_Mortality_in_the_German_Federal_States_During_the_COVID-19_Pandemic
Results: Excess Mortality varied substantially across federal states in each of the pandemic years. In nearly all states, excess mortality was small in the first pandemic year, increased in the second and even more in the third pandemic years. The increase varied substantially across the federal states as well. Regarding the covariations with the explored state-specific quantities, two correlation patterns are noticeable. In the first two years of the pandemic, but not in the third, there was a strong correlation between excess mortality and the number of reported COVID deaths, suggesting that the differences in excess mortality observed earlier in the pandemic are due to differences in the levels of exposure to COVID-19. However, this cannot explain the increase of excess mortality in the second and third pandemic years because the number of COVID-19 deaths decreased instead of increased in almost all federal states. Regarding the increase in excess mortality, an increasingly strong positive correlation with the vaccination rate of a federal state is observed, which reaches a value of r = 0.85 in the third pandemic year, indicating that excess mortality increased the stronger the higher the vaccination rate in a federal state was. An analysis of stillbirths showed exactly the same pattern. No other systematic correlation pattern was observed.
Conclusions: Excess mortality during the pandemic varied substantially between federal states, a finding that requires explanation. While the positive correlation of excess mortality with COVID-19 infections and deaths in the the phase of the pandemic without vaccinations suggests an explanation through different levels of exposure to COVID-19, COVID-19 cannot explain the increase in excess mortality after vaccinations began. For the second and third pandemic year a significant positive correlation between the increase of excess mortality and COVID-19 vaccinations is observed, a fact that strongly calls for further investigations on possible negative effects of COVID-19 vaccinations.
IMPORTANT (General vaccination worse outcomes than unvaccinated) – Revisiting Excess Diagnoses of Illnesses and Conditions in Children Whose Parents Provided Informed Permission to Vaccinate Them https://ijvtpr.com/index.php/IJVTPR/article/view/59
VERY IMPORTANT (Vaccine induced injury worse than Covid) – COVID-19 and All-Cause Mortality Data by Age Group Reveals Risk of COVID Vaccine-Induced Fatality is Equal to or Greater than the Risk of a COVID death for all Age Groups Under 80 Years Old as of 6 February 2022 https://www.vixra.org/abs/2202.0084
IMPORTANT (Ananlysis on reinfections and variants causing same strain reinfections) – High number of SARS-CoV-2 persistent infections uncovered through genetic analysis of samples from a large community-based surveillance study https://www.medrxiv.org/content/10.1101/2023.01.29.23285160v1.full-text
IMPORTANT (Confounding factors in mortality) – Effect of Age, Sex, and COVID-19 Vaccination History on All-Cause Mortality: Unexpected Outcomes in a Complex Biological and Social System https://www.preprints.org/manuscript/202304.0248/v1
All vaccines exhibit both specific and non-specific effects. The specific effects are measured by the efficacy against the target pathogen, while the non-specific effects can be detected by the change in all-cause mortality . All-cause mortality data (gender, age band, vaccination history, month of death) between January 2021 and May 2022 was compiled by the Office for National Statistics. COVID–19 vaccination gave good protection on many occasions but less so for younger ages. Each gender and age group shows its own unique vaccination benefit/disbenefit time profile. Individuals are free to make vaccination decisions. For example, women aged 18-39 show a cohort who do not progress beyond the first or second dose. The all-cause mortality outcomes for the Omicron variant showed a very poor response to vaccination with 70% of sex/age/vaccination stage/month combinations increasing all-cause mortality, probably due to unfavorable antigenic distance between the first-generation vaccines and this variant, and additional non-specific effects. The all-cause mortality outcomes of COVID–19 vaccination is far more nuanced than have been widely appreciated, and virus vector appear better than the mRNA vaccines in this specific respect. The latter are seemingly more likely to increase all-cause mortality especially in younger age groups. An extensive discussion/literature review is included to provide potential explanations for the observed unexpected vaccine effects.
VERY IMPORTANT (VAERS analysis 2023) – Extended: Analysis of COVID-19 Vaccine Death Reports from the Vaccine Adverse Events Reporting System (VAERS) Database https://www.researchgate.net/publication/367030584_Extended_Analysis_of_COVID-19_Vaccine_Death_Reports_from_the_Vaccine_Adverse_Events_Reporting_System_VAERS_Database?channel=doi&linkId=63beadaf56d41566df59a661&showFulltext=true
Authors found:
In 2021 we presented an interim analysis of reported deaths associated with Covid-19 using data from the Vaccine Adverse Events Reporting System (VAERS). This work applies the same analytical approach used on the original 250 reports from the December 2020 to March 2021 VAERS dataset, to a larger collection containing 1012 reports from the December 2021 to March 2022 VAERS dataset. Crucial differences between both data sets are that in the original data set the vaccination regime was targeted primarily to the elderly and front-line healthcare workers, while in this more recent dataset the vaccines were broadly available to most of the community. Our analysis indicates that: (i) as the vaccines were rolled out to each younger age group, VAERS reports for that age group also grew; (ii) that the identified disparity between male and female VAERS death reports in the 2021 cohort became less pronounced in the 2022 cohort; (iii) that cardiac and diabetic comorbidities continue to be significantly correlated with a VAERS death report; and (iv) that almost half of all death reports in the 2022 cohort include evidence of the individual having been diagnosed with a breakthrough Covid-19 infection. While there are concerns regarding the accuracy and quality of the data recorded on the VAERS system, there is a precedent for using this database. Even taking these concerns into account, the present analysis is consistent with many of the insights and key determinants of mortality identified in the previous analysis. Compared to adverse events associated with all other vaccines in the VAERS database, there is a significant increase in deaths associated with covid-19 vaccines.
IMPORTANT – Increasing SARS-CoV2 cases, hospitalizations and deaths among the vaccinated elderly populations during the Omicron (B.1.1.529) variant surge in UK https://www.medrxiv.org/content/10.1101/2022.06.28.22276926v3
Authors found:
The vaccine effectiveness (VE) for the third dose was in negative since December 20, 2021, with a significantly increased proportion of SARS-CoV2 cases hospitalizations and deaths among the vaccinated; and a decreased proportion of cases, hospitalizations, and deaths among the unvaccinated. The pre-existing conditions were present in 95.6% of all COVID-19 deaths and we also observed various ethnic, deprivation score and vaccination rate disparities that can adversely affect hospitalization and deaths among the compared groups based on the vaccination status.
CONCLUSIONS There is no discernable optimal vaccine effectiveness among ≥18 years of age, vaccinated third dose population since December 20, 2021 during the beginning of the Omicron variant surge. Pre-existing conditions, ethnicity, deprivation score, and vaccination rate disparities data need to be adjusted by the development of validated models for evaluating VE for hospitalizations and deaths. The increased proportion of cases with significantly increased risk of hospitalizations and deaths among the elderly population during the Omicron variant surge underscores the need to prevent infections in the elderly irrespective of vaccination status with uniform screening protocols and protective measures.
IMPORTANT (Vaccinated as source of transmission and persistence of virus) – The epidemiological relevance of the COVID-19-vaccinated population is increasing https://www.sciencedirect.com/science/article/pii/S2666776221002581
Article author notes:
High COVID-19 vaccination rates were expected to reduce transmission of SARS-CoV-2 in populations by reducing the number of possible sources for transmission and thereby to reduce the burden of COVID-19 disease.
Recent data, however, indicate that the epidemiological relevance of COVID-19 vaccinated individuals is increasing. In the UK it was described that secondary attack rates among household contacts exposed to fully vaccinated index cases was similar to household contacts exposed to unvaccinated index cases (25% for vaccinated vs 23% for unvaccinated). 12 of 31 infections in fully vaccinated household contacts (39%) arose from fully vaccinated epidemiologically linked index cases. Peak viral load did not differ by vaccination status or variant type [1].
In Germany, the rate of symptomatic COVID-19 cases among the fully vaccinated (“breakthrough infections”) is reported weekly since 21. July 2021 and was 16.9% at that time among patients of 60 years and older [2]. This proportion is increasing week by week and was 58.9% on 27. October 2021 (Figure 1) providing clear evidence of the increasing relevance of the fully vaccinated as a possible source of transmission.
A similar situation was described for the UK. Between week 39 and 42, a total of 100.160 COVID-19 cases were reported among citizens of 60 years or older. 89.821 occurred among the fully vaccinated (89.7%), 3.395 among the unvaccinated (3.4%) [3]. One week before, the COVID-19 case rate per 100.000 was higher among the subgroup of the vaccinated compared to the subgroup of the unvaccinated in all age groups of 30 years or more.
In Israel a nosocomial outbreak was reported involving 16 healthcare workers, 23 exposed patients and two family members. The source was a fully vaccinated COVID-19 patient. The vaccination rate was 96.2% among all exposed individuals (151 healthcare workers and 97 patients). Fourteen fully vaccinated patients became severely ill or died, the two unvaccinated patients developed mild disease [4].
The US Centres for Disease Control and Prevention (CDC) identifies four of the top five counties with the highest percentage of fully vaccinated population (99.9–84.3%) as “high” transmission counties [5].
Many decisionmakers assume that the vaccinated can be excluded as a source of transmission. It appears to be grossly negligent to ignore the vaccinated population as a possible and relevant source of transmission when deciding about public health control measures.
VERY IMPORTANT (Connection between vaccination rates and child mortality) – Reaffirming a Positive Correlation Between Number of Vaccine Doses and Infant Mortality Rates: A Response to Critics https://www.cureus.com/articles/134233-reaffirming-a-positive-correlation-between-number-of-vaccine-doses-and-infant-mortality-rates-a-response-to-critics#!/
Results
The critics’ reanalysis combines 185 developed and Third World nations that have varying rates of vaccination and socioeconomic disparities. Despite the presence of inherent confounding variables, a small, statistically significant positive correlation of r = 0.16 (p < .03) is reported that corroborates the positive trend in our study. Multiple linear regression analyses report high correlations between IMR and HDI, but the number of vaccine doses as an additional predictor is not statistically significant. This finding is a likely consequence of known misclassification errors in HDI. Linear regression of IMR as a function of percentage vaccination rates reports statistically significant inverse correlations for 7 of 8 vaccines. However, several anomalies in the scatter plots of the data suggest that the chosen linear model is problematic.
Our odds ratio analysis conducted on the original dataset controlled for several variables. None of these variables lowered the correlation below 0.62, thus robustly confirming our findings. Our sensitivity analysis reported statistically significant positive correlations between the number of vaccine doses and IMR when we expanded our original analysis from the top 30 to the 46 nations with the best IMRs. Additionally, a replication of our original study using updated 2019 data corroborated the trend we found in our first paper (r = 0.45, p = .002).
Conclusions
A positive correlation between the number of vaccine doses and IMRs is detectable in the most highly developed nations but attenuated in the background noise of nations with heterogeneous socioeconomic variables that contribute to high rates of infant mortality, such as malnutrition, poverty, and substandard health care.
VERY IMPORTANT (Ivermectin reducing instances in Peru) – COVID-19 Excess Deaths in Peru’s 25 States in 2020: Nationwide Trends, Confounding Factors, and Correlations With the Extent of Ivermectin Treatment by State https://www.cureus.com/articles/172991-covid-19-excess-deaths-in-perus-25-states-in-2020-nationwide-trends-confounding-factors-and-correlations-with-the-extent-of-ivermectin-treatment-by-state?score_article=true#!/
Results
Reductions in excess deaths over a period of 30 days after peak deaths averaged 74% in the 10 states with the most intensive IVM use. As determined across all 25 states, these reductions in excess deaths correlated closely with the extent of IVM use (p<0.002). During four months of IVM use in 2020, before a new president of Peru restricted its use, there was a 14-fold reduction in nationwide excess deaths and then a 13-fold increase in the two months following the restriction of IVM use. Notably, these trends in nationwide excess deaths align with WHO summary data for the same period in Peru.
Conclusions
The natural experiment that was put into motion with the authorization of IVM use for COVID-19 in Peru in May 2020, as analyzed using data on excess deaths by locality and by state from Peruvian national health sources, resulted in strong evidence for the drug’s effectiveness. Several potential confounding factors, including effects of a social isolation mandate imposed in May 2020, variations in the genetic makeup of the SARS-CoV-2 virus, and differences in seropositivity rates and population densities across the 25 states, were considered but did not appear to have significantly influenced these outcomes.
IMPORTANT (Risk benefit for young adults boosters) – Covid-19 vaccine boosters for young adults: A risk-benefit assessment and five ethical arguments against mandates at universities https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4206070
IMPORTANT (Risk benefit for young adults boosters) –Pros and Cons for COVID-19 Vaccination and Boost of Young Adults in Light of Recent Literature https://esmed.org/MRA/mra/article/view/2943/193546242
IMPORTANT (Infection rate rises with vacination – Iceland study) Published 03 August 2022 – Rate of SARS-CoV-2 Reinfection During an Omicron Wave in Iceland https://jamanetwork.com/journals/jamanetworkopen/article-abstract/2794886
IMPORTANT Adverse All Cause – US COVID-19 Vaccines Proven to Cause More Harm than Good Based on Pivotal Clinical Trial Data Analyzed Using the Proper Scientific Endpoint, “All Cause Severe Morbidity” https://www.scivisionpub.com/pdfs/us-covid19-vaccines-proven-to-cause-more-harm-than-good-based-on-pivotal-clinical-trial-data-analyzed-using-the-proper-scientific–1811.pdf
IMPORTANT (All cause) – COVID vaccination and age-stratified all-cause mortality risk https://www.researchgate.net/publication/355581860_COVID_vaccination_and_age-stratified_all-cause_mortality_risk
IMPORTANT (All cause mortality) – Published July 2022 – Covid-19 vaccinations and all-cause mortality -a long-term differential analysis among municipalities https://www.researchgate.net/publication/361818561_Covid-19_vaccinations_and_all-cause_mortality_-a_long-term_differential_analysis_among_municipalities
IMPORTANT (All cause mortality – exploratory analysis Prof Fenton) – The Devil’s Advocate: An Exploratory Analysis of 2022 Excess Mortality https://wherearethenumbers.substack.com/p/the-devils-advocate-an-exploratory
IMPORTANT (ACM showing evidence of stopping condition) – COVID-Period Mass Vaccination Campaign and Public Health Disaster in the USA From age/state-resolved all-cause mortality by time, age-resolved vaccine delivery by time, and socio-geo-economic data https://www.researchgate.net/publication/362427136_COVID-Period_Mass_Vaccination_Campaign_and_Public_Health_Disaster_in_the_USA_From_agestate-resolved_all-cause_mortality_by_time_age-resolved_vaccine_delivery_by_time_and_socio-geo-economic_data
Authors found:
We also quantify total excess all-cause mortality (relative to historic trends) for the entire covid period (WHO 11 March 2020 announcement of a pandemic through week-5 of 2022, corresponding to a total of 100 weeks), for the covid period prior to the bulk of vaccine delivery (first 50 weeks of the defined 100-week covid period), and for the covid period when the bulk of vaccine delivery is accomplished (last 50 weeks of the defined 100-week covid period); by age group and by state. We find that the COVID-19 vaccination campaign did not reduce all-cause mortality during the covid period. No deaths, within the resolution of all-cause mortality, can be said to have been averted due to vaccination in the USA. The mass vaccination campaign was not justified in terms of reducing excess all-cause mortality. The large excess mortality of the covid period, far above the historic trend, was maintained throughout the entire covid period irrespective of the unprecedented vaccination campaign, and is very strongly correlated (r = +0.86) to poverty, by state; in fact, proportional to poverty.
IMPORTANT (Risks) – Trends and associated factors for Covid-19 hospitalisation and fatality risk in 2.3 million adults in England https://www.nature.com/articles/s41467-022-29880-7
IMPORTANT (Increased vaccinated risk) – Elevated risk of infection with SARS-CoV-2 Beta, Gamma, and Delta variant compared to Alpha variant in vaccinated individuals https://www.science.org/doi/10.1126/scitranslmed.abn4338
IMPORTANT (Levels of vaccination unrelated not connected to instances of Covid) – Increases in COVID-19 are unrelated to levels of vaccination across 68 countries and 2947 counties in the United States https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8481107/
Authors note:
At the country-level, there appears to be no discernable relationship between percentage of population fully vaccinated and new COVID-19 cases in the last 7 days (Fig. 1). In fact, the trend line suggests a marginally positive association such that countries with higher percentage of population fully vaccinated have higher COVID-19 cases per 1 million people. Notably, Israel with over 60% of their population fully vaccinated had the highest COVID-19 cases per 1 million people in the last 7 days. The lack of a meaningful association between percentage population fully vaccinated and new COVID-19 cases is further exemplified, for instance, by comparison of Iceland and Portugal. Both countries have over 75% of their population fully vaccinated and have more COVID-19 cases per 1 million people than countries such as Vietnam and South Africa that have around 10% of their population fully vaccinated.
Across the US counties too, the median new COVID-19 cases per 100,000 people in the last 7 days is largely similar across the categories of percent population fully vaccinated (Fig. 2). Notably there is also substantial county variation in new COVID-19 cases within categories of percentage population fully vaccinated. There also appears to be no significant signaling of COVID-19 cases decreasing with higher percentages of population fully vaccinated (Fig. 3).
Of the top 5 counties that have the highest percentage of population fully vaccinated (99.9–84.3%), the US Centers for Disease Control and Prevention (CDC) identifies 4 of them as “High” Transmission counties. Chattahoochee (Georgia), McKinley (New Mexico), and Arecibo (Puerto Rico) counties have above 90% of their population fully vaccinated with all three being classified as “High” transmission. Conversely, of the 57 counties that have been classified as “low” transmission counties by the CDC, 26.3% (15) have percentage of population fully vaccinated below 20%.
Since full immunity from the vaccine is believed to take about 2 weeks after the second dose, we conducted sensitivity analyses by using a 1-month lag on the percentage population fully vaccinated for countries and US counties. The above findings of no discernable association between COVID-19 cases and levels of fully vaccinated was also observed when we considered a 1-month lag on the levels of fully vaccinated (Supplementary Figure 1, Supplementary Figure 2).
NOTE TO ABOVE STUDY – Comment on Subramanian and Kumar, “Increases in COVID-19 are unrelated to levels of vaccination” https://pdmj.org/papers/Comment_on_Subramanian_and_Kumar?utm_source=substack&utm_medium=email
In Switkay [2], it is argued that a linear model should not be employed unless the predictor and response variables are supported on the whole real number line (-∞,∞). If they are not, one should employ appropriate transformations of the variables before starting a linear analysis.
Subramanian and Kumar studied the relationship between new case rates and vaccination rates in 68 countries. Since vaccination rates vary between 0% and 100%, they were treated with the logit function. Since case rates are positive but rarely approach anything near 100%, they were treated with the log function. The transformed variables now have doubly infinite support, so one may explore the strength of a linear association between the transformed variables.
The scatterplot of the transformed variables is shown in figure 1. This corresponds to figure 1 in [1]. However, the points in the lower left corner of figure 1 in [1] are now nicely separated.
Figure 2 zooms in on the most densely populated portion of figure 1.
The positive association is now clear, and the coefficient of determination, R-squared, is a remarkable 0.2409. The p-value is about 0.00002. Even by the standards of [2], that is highly significant.
One may deduce that not only is it not true that there is no relation between the two variables in [1], as their title states, or that the association is “marginal”; indeed, there is a very strong positive association.
VERY IMPORTANT (Baysian causal impact of vaccination) – Worldwide Bayesian Causal Impact Analysis of Vaccine Administration on Deaths and Cases Associated with COVID-19: A BigData Analysis of 145 Countries https://www.researchgate.net/publication/356248984_Worldwide_Bayesian_Causal_Impact_Analysis_of_Vaccine_Administration_on_Deaths_and_Cases_Associated_with_COVID-19_A_BigData_Analysis_of_145_Countries
Author noted:
Results indicate that the treatment (vaccine administration) has a strong and statistically significant propensity to causally increase the values in either y1 or y2 over and above what would have been expected with no treatment.
IMPORTANT (Comorbidities associated with severe Covid-19 infection) – Comorbidities and the risk of severe or fatal outcomes associated with coronavirus disease 2019: A systematic review and meta-analysis https://pubmed.ncbi.nlm.nih.gov/32721533/
Authors found:
Results: A total of 34 eligible studies were identified. In patients with severe/fatal COVID-19, the most prevalent chronic comorbidities were obesity (42%, 95% CI 34-49%) and hypertension (40%, 95% CI 35-45%), followed by diabetes (17%, 95% CI 15-20%), cardiovascular disease (13%, 95% CI 11-15%), respiratory disease (8%, 95% CI 6-10%), cerebrovascular disease (6%, 95% CI 4-8%), malignancy (4%, 95% CI 3-6%), kidney disease (3%, 95% CI 2-4%), and liver disease (2%, 95% CI 1-3%). In order of the prediction, the pooled ORs of the comorbidities in patients with severe or fatal COVID-19 when compared to patients with non-severe/fatal COVID-19 were as follows: chronic respiratory disease, OR 3.56 (95% CI 2.87-4.41); hypertension, OR 3.17 (95% CI 2.46-4.08); cardiovascular disease, OR 3.13 (95% CI 2.65-3.70); kidney disease, OR 3.02 (95% CI 2.23-4.08); cerebrovascular disease, OR 2.74 (95% CI 1.59-4.74); malignancy, OR 2.73 (95% CI 1.73-4.21); diabetes, OR 2.63 (95% CI 2.08-3.33); and obesity, OR 1.72 (95% CI 1.04-2.85). No correlation was observed between liver disease and COVID-19 aggravation (OR 1.54, 95% CI 0.95-2.49).
Conclusions: Chronic comorbidities, including obesity, hypertension, diabetes, cardiovascular disease, cerebrovascular disease, respiratory disease, kidney disease, and malignancy are clinical risk factors for a severe or fatal outcome associated with COVID-19, with obesity being the most prevalent and respiratory disease being the most strongly predictive. Knowledge of these risk factors could help clinicians better identify and manage the high-risk populations.
IMPORTANT (Vaccination no different to natural immunity) – Rates of COVID-19 Among Unvaccinated Adults With Prior COVID-19 https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2791312
IMPORTANT (Vaccination no impact on Long Covid) – Effect of COVID-19 vaccine on long-COVID: A 2-year follow-up observational study from hospitals in north India https://www.medrxiv.org/content/10.1101/2022.07.18.22277740v1
IMPORTANT Published July 2022 – Incidence, risk factors, natural history, and hypothesised mechanisms of myocarditis and pericarditis following covid-19 vaccination: living evidence syntheses and review https://pubmed.ncbi.nlm.nih.gov/35830976/
IMPORTANT (Israeli study) – Comparing SARS-CoV-2 natural immunity to vaccine-induced immunity: reinfections versus breakthrough infections https://www.medrxiv.org/content/10.1101/2021.08.24.21262415v1.full-text
IMPORTANT – Official mortality data for England suggest systematic miscategorisation of vaccine status and uncertain effectiveness of Covid-19 vaccination https://www.researchgate.net/publication/357778435_Official_mortality_data_for_England_suggest_systematic_miscategorisation_of_vaccine_status_and_uncertain_effectiveness_of_Covid-19_vaccination
IMPORTANT – Official mortality data for England reveal systematic undercounting of deaths occurring within first two weeks of Covid-19 vaccination https://www.researchgate.net/publication/358979921_Official_mortality_data_for_England_reveal_systematic_undercounting_of_deaths_occurring_within_first_two_weeks_of_Covid-19_vaccination
IMPORTANT – Discrepancies and inconsistencies in UK Government datasets compromise accuracy of mortality rate comparisons between vaccinated and unvaccinated https://www.researchgate.net/publication/355437113_Discrepancies_and_inconsistencies_in_UK_Government_datasets_compromise_accuracy_of_mortality_rate_comparisons_between_vaccinated_and_unvaccinated
IMPORTANT – Paradoxes in the reporting of Covid19 vaccine effectiveness: Why current studies (for or against vaccination) cannot be trusted and what we can do about it https://www.researchgate.net/publication/354601308_Paradoxes_in_the_reporting_of_Covid19_vaccine_effectiveness_Why_current_studies_for_or_against_vaccination_cannot_be_trusted_and_what_we_can_do_about_it?channel=doi&linkId=6141e3dd60f0fe3442618e98&showFulltext=true
IMPORTANT (CDC Fraud overcounting deaths by Covid) – Published 2020 – COVID-19 Data Collection, Comorbidity & Federal Law: A Historical Retrospective https://www.ratical.org/PandemicParallaxView/C19dataCollection-C+FL-HistPerspec.pdf
IMPORTANT – Increasing SARS-CoV2 cases, hospitalizations and deaths among the vaccinated elderly populations during the Omicron (B.1.1.529) variant surge in UK https://www.medrxiv.org/content/10.1101/2022.06.28.22276926v3
IMPORTANT– Covid-19: Fact check—how many patients in hospital are unvaccinated? https://www.bmj.com/content/376/bmj.o5
IMPORTANT – Understanding Definitions and Reporting of Deaths Attributed to COVID-19 in the UK – Evidence from FOI Requests https://www.medrxiv.org/content/10.1101/2022.04.28.22274344v1
IMPORTANT (Long Covid) – Long COVID after breakthrough SARS-CoV-2 infection https://www.nature.com/articles/s41591-022-01840-0
IMPORTANT (Article from Dr McCullough) – Rational harm-benefit assessments by age group are
required for continued COVID-19 vaccination https://enromiosini.gr/newsite16/wp-content/files/2023/01/Scand-J-Immunol-2022-Polykretis-Rational-harm%E2%80%90benefit-assessments-by-age-group-are-required-for-continued-COVID%E2%80%90191.pdf