There’s more than meets the eye with the latest “vaccine efficacy” study published by the New England Journal of Medicine (NEJM). The study in question, “Effectiveness of covid-19 vaccines in ambulatory and in patient care settings,” was immediately featured by the Centers for Disease Control (CDC) to advertise covid-19 vaccines.
Upon further investigation of the data, it seems this study and its interpretation were designed to deceive the public. After configuring the true rate of sickness post vaccination, the vaccine efficacy could be interpreted as negative 13 percent! It seems that taking covid vaccines increases the risk of hospitalization.
Study omits hospitalization data for recently vaccinated to boost “vaccine efficacy”
The study measured the efficacy of covid-19 vaccines in a test-negative design that included 41,552 participants. The study looked for diagnoses of “covid-like illness,” symptomatic illness, and test positivity by vaccination status in 50+ age group. The study looked at emergency department and urgent care hospitalization data across nine states from January to August 2021.
The study identified 41,552 hospitalizations for “covid-like illness” (CLI). This broad diagnostic term could describe numerous respiratory infections of various origins. The term could embody different types of allergies, asthma, inhalation poisoning, or underlying respiratory conditions. The term could describe an adverse event to a drug or vaccination. The term could represent a severe case of illness following vaccination.
From the onset, the study recorded a total of 103,199 hospitalizations across nine states. The study used specific criteria (ages 50 and above and CLI) to narrow the data down. The hospitalization data used in the study was only a fraction of the hospitalizations observed in the general population, and represented an even smaller fraction of the hospitalizations recorded for people over 50 years old. By simply excluding all-cause hospitalization by vaccination status, this study design could have easily removed tens of thousands of hospitalizations in the vaccinated cohort.
Of the 61,647 hospitalizations excluded in the study, many were medical issues for people under 50 years old. Could the covid vaccines be unnecessarily causing medical emergencies and health issues in young people who could easily overcome the infection? That data is omitted, so it’s hard to say. The study also omitted data for repeat admissions and for instances where there were no records for vaccination or covid-19 testing.
The most shocking omission of data included hospitalizations for the recently vaccinated. The majority of adverse events and hospitalizations occur in the first week after vaccination, yet the study omits all of these hospitalizations if they are after the first dose. There were 1,872 hospitalizations in this recently vaccinated category, a category intentionally left out to deceive the public.
Diagnostic fraud and data distortion being used to deceive the public
The fraud doesn’t end there. The study configured “vaccine efficacy” by artificially reducing the total number of CLI in the vaccinated cohort. This was done using disparate cycle counts during PCR “confirmation” of covid-19. The study depended on the fraudulently-calibrated PCR test, which are used to inflate official covid cases in the unvaccinated, to artificially reduce the number of covid cases in the vaccinated, and to ultimately promote a high vaccine efficacy percentage.
A lower cycle count for the vaccinated removed all the false positives, reducing the official covid case count only for the vaccinated. In fact, when the PCR test is taken out of the equation,, cases of CLI remain steady across all three groups, the unvaccinated, the partially vaccinated, and the fully vaccinated.
Even though the CLI diagnosis remains steady among all three groups, the reported “covid cases” for the fully vaccinated is significantly lower (due to lower cycle thresholds being used for the fully vaccinated). This is diagnostic fraud and data manipulation to make a product (the covid-19 vaccines) appear as though it is stopping a specific illness.
That illness is not properly defined, PCR cycles are not absolute or definitive in their diagnosis, and the ensuing distortion of data is used to fool the public about the “effectiveness” of an experimental gene altering product.
If the study calculated vaccine efficacy by taking into account all the CLI admissions(including the omitted 1,872 hospitalizations for recently vaccinated individuals), then the vaccine efficacy falls to a net negative value of -13 percent! This means that taking these experimental vaccines actually INCREASES a person’s risk of hospitalization.