Alarming reports are being published in a number of countries of increased ill health and deaths among categories of people normally enjoying robust health. For example:
Unprecedented rise in Indiana death rates
The CEO of OneAmerica life insurance Scott Davison, a $100 billion dollar company, reports that in the third quarter of 2021 deaths were up by 40% over pre pandemic trends.
Davison said the increase in deaths represents “huge, huge numbers,” and that it’s not elderly people who are dying, but “primarily working-age people 18 to 64” who are the employees of companies that have group life insurance plans through OneAmerica. Most of the claims for deaths being filed are not classified as COVID-19 deaths, Davison said.
The insurance industry relies on careful analysis of data. Death rates are historically very stable. The OneAmerica figures represent an unprecedented statistical trend. A 10% increase would have been a 1 in 300 year anomaly. A 40% increase is statistically off any conceivable scale and points to a rise that would never happen during the whole billions year history of earth except during wartime.
Brian Tabor, the president of the Indiana Hospital Association, said that hospitals across the state are being flooded with patients “with many different conditions,” adding “unfortunately, the average Hoosiers’ health has declined during the pandemic.”
Other anecdotal reports of statistics and events include increased incidence of miscarriage and still births, increased incidence of cardiac events including increased incidence among athletes, increased excess death rates as compared to previous years, high incidence of myocarditis among young vaccinated people, and reduced immune efficiency among the vaccinated.
Data Integrity Issues
From a statistical point of view these reports are alarming. They certainly point to a novel cause. The obvious candidate is vaccination but analysing the connection precisely and mathematically is obstructed because of data integrity issues designed to hide the truth:
Inadequate adverse event reporting: Early on governments decided not to require mandatory reporting of adverse events following vaccination. The procedures are too time consuming for busy doctors. Only 5% are reported.
Expectation of vaccine safety: Previously vaccines underwent lengthy testing over many years and were largely safe. Because of this, GPs and hospital staff expect safety and tend to dismiss adverse events as unrelated.
Early mRNA vaccine data was misleading: Reports of 95% efficacy in preventing infection and reports of a near perfect safety record have since been discredited by whistleblowers.
Misleading modelling reports: Based on the Pfizer data and some highly speculative papers on transmission, early modelling greatly overestimated infection and death rates from Covid. This fuelled ideas that there would be a net benefit from vaccination even when the adverse event rate was clearly reaching unprecedented highs. Moreover huge discrepancies between real world data and modelling predictions were ignored. For example modelling reports of 100,000 Covid deaths in NZ and a twenty fold greater rate of Covid transmission among the unvaccinated are patently false and bear no relation to actual data, yet they have helped form government policy and public opinion.
Misrepresentation and concealment of data: Because of the belief that vaccination would provide a net public good, authorities continue to feel it is important to hide information about high adverse effects from the public. In NZ this has happened in government departments and hospitals, particularly with regard to cardiac problems subsequent to vaccination.
Lack of adverse effect data by category: Little data has been provided concerning individual categories of adverse events. This happens because a great many specific adverse effect reports have been dismissed since in the opinion of physicians, based on experience of safety with past vaccines, they could not possibly be related. This happened despite the fact that some unusual categories such as miscarriage have reportedly become common relative to historical data.
Lack of follow up of secondary health issues: The Covid vaccine trials were too short to carry out the standard investigation of incidence of secondary health issues over an extended period of time. As a result the long term effects of vaccination cannot be known unless the health outcomes of vaccinated individuals is followed over time and compared to population norms. This has not happened. The data from OneAmerica insurance highlights the absolute folly of this omission
The net effect is that data documenting the risks of Covid vaccination has been concealed to the extent that insufficient or inaccurate data is made available to researchers. Thereby government policy remains unsupported by real world data, but instead driven by politically biassed or uninformed ideas.
Guy Hatchard PhD was a senior manager at Genetic ID, a food testing and certification company. He has experience in statistical analysis of social indicators.Guy Hatchard PhD
