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What is it?

The primary purpose of the VAERS reporting system is to provide the ability for the collection, monitoring, and evaluating of Adverse Events (AEs) and Severe Adverse Events (SAEs) for safety signals to reduce harm to the public, in the context of pharmaceutical and biological agents. In simpler terms, it is a database that is used as a way of tracking health related issues that may be caused by medicines, vaccines, and etc.. It is a passive system, so not all incidences may be reported. VAERS is designed to reveal potential early-warning risk signals from the data that is collected. VAERS is a historical system, already accepted by the medical community, and having been fully documented and various analysis techniques peer reviewed to ensure data validity (to within acceptable ranges of error). In other words, it is not a new system that was designed for the COVID-19 pandemic that nobody understood and had never used – all that was required to be able to record COVID-19 information was the creation of new codes and guidance as to how to record the information per each new code.

How it works

Each type of adverse reaction that a medicine, vaccine, or etc., can have is classified into groups (ID’s) that are associated with that medicine, vaccine, or etc.. Any reactions should be recorded, for each patient treated and per each treatment, in the VAERS database and used for trending and analysis by the scientific community and general public. The codes that are used are also used by the Hospitals and treatment centers for reimbursement by the Government for the type of care that was provided.

As this data can be used for the trending and monitoring of health problems, only trained contractor staff should enter each VAERS report (medical incident) into the database. Therefore, if it is deemed necessary to delete a VAERS ID from the database once it has been entered, then it must be documented with a valid reason. As well it should be documented if a VAERS ID number is changed to a new number. Of course, since VAERS was designed to reveal potential early-warning risk signals from the collected data, if the information is not properly recorded or recorded at all then the system fails its purpose.

I understand the CDC to have said that you can’t ascribe causality to data in VAERS – but I’m not sure that this is true. As I understand it, the Bradford-Hill criteria are accepted principles for assessing causality of an association. In this article, an association between the CHADOX1 NCOV-19 vaccine and prothrombotic immune thrombocytopenia was found. The European Medicine Agency concluded that there is a signal for disseminated intravascular coagulation, cerebral venous sinus thrombosis and haemorrhagic stroke following CHADOX1 NCOV-19 vaccine.

Considering the relevance of safety concerns in the face of the large numbers of SAEs and AEs being reported into the VAERS system in the context of COVID-19 products, it is essential that the VAERS system be carefully and meticulously maintained.

Issues with the presented VAERS data?

While researching this with the consideration of how COVID-19 information is/was being recorded in VAERS, I stumbled across websites and information pertaining to suspected issues with the recording of, and analysis of, the information in the VAERS database. The name Steve Kirsch came up in a search, pointing me to an analysis that he had performed on the validity of the information in the VAERS database. I understand him to have compared each of the 28 published updates. In this appraisal he addresses three issues: 1) deleted reports, 2) delayed entry of reports, and 3) the recoding of Medical Dictionary for Regulatory Activities (MedDRA) terms from severe to mild. As an example, he points out that as of August 6, 2021 there were 1,516 VAERS IDs missing from the most recently updated publicly available VAERS database – which represents 0.4% of the total VAERS IDs.

• Of this missing data, 13% represented death, 11% represented COVID-19 and 63% represented Severe Adverse Events (SAEs). Of this missing death data, only 59% represented redundancies – re-assigned new VAERS IDs – the remainder were unaccounted for.
• Of the total missing VAERS ID data set, 41% of the missing IDs involved hospitalizations and 37% involved emergency room visits.
• It is very strange to report that 70% of the age data contains an “NA” entry in the “AGE_YRS” field – rendering age-grouped data analysis impossible.
• Although the absolute number of missing VAERS IDs may not be high, of this small subset of deleted data, 13% of total missing AEs are deaths. The total number of deaths is 199 and in each sequential iteration of the anti-joining of the datasets, death remained at the highest or near highest frequency for missing AEs in each “SYMPTOM” list for the extracted missing data set, save for SYMPTOM column 5, which rarely contains the primary or most prevalent AE reported per individual.
• A lag time between onset of AEs and entry of AEs into the VAERS public database was discovered, and it appears to depend on the AE type. For example, in the case of COVID-19 breakthrough cases, approximately mid-May, 4100 (38% of total) reports were retroactively added approximately 8.5 weeks following the original onset date.
• SAEs were not found to be downgraded to mild AEs (MAEs) for a tested cohort within 10 selected updates.

As of the time of this information being presented, there were 28 sets of data, and discrepancies can be found between the files from update to update. The descrepancies would not have been noticed by a data analyst if they were only looking at the presented data – it was only noticed because each data set was compared with one another.

He further reports that:

• The absolute number of AEs reported in the context of the COVID-19 products is approximately 11 times higher than for all the reported AEs for 2020 combined.
• The absolute number of deaths reported is approximately 42 times higher than for all deaths reported for 2020.
• The number of deaths is 266 times higher in the context of the COVID-19 products when compared to INFLUENZA products.

Are SAEs and SAs being under-reported?

A decade before COVID-19, a Harvard research study called, “Lazarus”, estimated that VAERS accounted for only 1% of vaccine-induced injuries. Considering this Stever Kirsche, the executive director of the Vaccine Safety Research Foundation, and others conducted an analysis that compared anaphylaxis rates published in a study to rates found in VAERS. Based on their under-reporting factor (URF) they estimated the true death toll from COVID-19 vaccines at 41 times higher than those reported. Another organization, “VAERS Analysis”, analyzes and maintains a historic database of all reported VAERS updates, and used whistleblower data from the Centers for Medicare and Medicaid Services (CMS), to calculate their own under-reporting factor of 44.64 times. As I read, if you were to use their URF for all VAERS-classified SAEs, they had estimated: 205,809 dead, 818,462 hospitalizations, 1,830,891 ER visits, 230,113 life-threatening events, 212,691 disabled and 7,998 birth defects thus far. And here is the results of yet another research team that has suggested that VAERS deaths have been under-reported by a factor of 20 times. I offer this WND News article reporting the Columbia University has also estimated that the death rate reported by the CDC is under-reported by a factor of 20 times (which is consistent with known VAERS under-ascertainment bias) – raising the death rate closer to 400,000 people and suggesting that “the risks of COVID vaccines and boosters outweigh the benefits in children, young adults and older adults with low occupational risk or previous coronavirus exposure.”. The research team emphasized “the urgent need to identify, develop and disseminate diagnostics and treatments for life-altering vaccine injuries.”.

The U.S. Department of Health and Human Services (HHS) has pointed out that a VAERS report is not documentation that a link has been established between a vaccine and an adverse event. The HHS has also noted that VAERS is a “passive” system of reporting, which “receives reports for only a small fraction of actual adverse events”. I have read that some health care workers have disclosed that they had been instructed to not report any harm caused by COVID-19 vaccines to VAERS.

Across articles posted on the Internet, I am also to understand it possible that vaccine-induced deaths have been classified as COVID-19 deaths. Of course, the improper recording of information would increase the COVID-19 death count while reducing the vaccinated death count.

Is all of the information being published?

Considering the criticality of the information, one would think that any information gathered would be made public as quickly and as clearly as possible. So I was extremely disturbed to read an article from the New York Times which advised that the US CDC has not been publishing all of the information that it has received. As I read in the article, early into the release of significant data on the effectiveness of booster shots they withheld information for those aged between 18 and 49 years of age. It is interesting to read that this is the group the data showed was least likely to benefit from the booster shots. They report that with the booster data for this age range not being available, those recommending how to approach the control of COVID-19 had to rely on numbers from Israel when making recommendations as to whether or not to get the booster shots.

As well, as I read the article I became confused and concerned as to the reasoning behind their withholding this vital and critical information that is continuously being referenced and reported on. I read that the US CDC had been slow to release the data “because basically, at the end of the day, it’s not yet ready for prime time.”. I also understood from the article that another reason was that they were fearful that the information might be misinterpreted. Further, the US CDC’s deputy director for public health science and surveillance said the pandemic exposed that data systems at both the US CDC and at the US State levels are outmoded and not up to handling large volumes of data. Here is link to another article, having even more information on this.

Observations: Where to start?

• I’m confused as to how data published from individuals authorized to do so could be so confusing and un-prepared? I outlined at top as to how the system works, so I am confused as to the implication that an additional level of information mangement is required when we are working with what is supposed to be ‘raw data’?
• How you handle the misinterpretation of data is to ensure that the information is provided in a clear to understand manner, and provide a break-out as to the meaning behind that data and what it truely represents. For example, if it could be intrepreted in two different ways, then clarify why it must be interpreted in the way as you suggest. And, during this, you must be ready to defend your position and be ready to retract your position if it cannot be defended.
  • So I find it truely incredible and amazing that those individuals responsible for providing this information to us, the general public, are completely unable to do this. They cannot publish clear information, nor are they able to guide us as to how it needs to be interpreted, which suggests that they would be unable to defend their position – which means their guidance is questionable. Or it means that those who have been charged in provisioning this information are incompetent to the requirement.
• Lastly, I find interesting the suggestion that the data systems are outmoded and not up to handling large volumes of data. If this is true, then why was this critical information not made avaiable to us from the very moment it was identified. One would think that this would have been exposed extremely close to the start of the pandemic, when one would think information would start to come pouring in to it – not years after when discussing booster shots. How is this not viewed as information negligence? Now we have to ask questions like: What data anomolies have stemmed from this lack of ability to gather, process, and provision this ‘raw data’? How did this laking of capability affect the ‘guidance’ that we have been receiving – and how has that affected our economy / heath? I’d like to have a better understanding as to how it was ascertained that the system designed to capture and process this ‘raw data’ being submitted is unable to handle this ‘large amount of data’ – in what way is it unable to do this I wonder? And if it failed then how will this data be reconstructed and validated as accurate?

Read the next section, “PCR Test“.