For new VAERS data that is about to drop today Apr 21,2023, bottom line is 56 “new” deaths against 2,858 new total records for C19 & MonkeyPox. You might notice a little math discrepancy between either 48 or 56 new deaths? I will know better when the files actually release, at 6:54am PST this morning this is the few hour window where the WONDER system is updated first but downloadable files have not become available. I know it has to do with death records being deleted. The “house on fire” alert for me and for the last six weeks is the fact CDC’s VAX Tracker System has not been updated. This is typically a look ahead at how many death reports are “in process”. As you can see there are still over 2,000 death reports in inventory waiting to be published? I wonder how many have come in since March 1st?
There has basically been more rumblings around the world that Adverse Events Systems all over have not been updating systems. Norman Fenton from some Royal College or “the” Royal College just cross posted a Substack article from my new friend Stephan Feldman’s article way back on April 5th. A little late by todays standards but superfast considering this was Mr. Feldman’s first Substack article and it made it to Fenton’s attention within a couple weeks is pretty incredible. I did have Fenton’s email but it didn’t dawn on me to push the article to him. Sorry Stephan, I’ll make sure to push your MHRA article through some power channels I have, now that we have some street cred from Norman! Great job Stephan, I’ve been trying to tell people over here in the USA, “VAERS DOES NOT PUBLISH ALL LEGITIMATE REPORTS RECEIVED!”
Here is Stephen Feldman’s excellent article again:
OOOh, the files just dropped now 7:07am PST, you guys are in luck here is a summary view from MedAlerts Wayback Machine:
Those two deleted deaths are from Brazil and a UNK American State, both are peek-a-boo where they were published for the first time the week before, but deleted this week! Isn’t that a kick in the pants? Another carnival trick they pull is deleting reports that have been sitting in the system for a very long time, notice the ID#’s that start with “1”? The numbering system is sequential by increments of one, but comingled with all VAX TYPES. The other point is that although the bulk of the reports say “minor”, MedAlerts is just following the Event Level definition of SAE and NON-SAE. Serious is considered anything above Emergency Visits, however it all comes down to boxes being checked-off on the report. There are very serious reports like death, cardiac arrest, pulmonary embolism, myocarditis, etc in the Minor or “not serious” bucket all because an event level box was not checked off, or it was scrubbed by CDC themselves. It’s not a stretch to make this accusation with these hucksters.
Anyhow, there a couple others that need a shout out that I will be highlighting individually soon as I get some breathing room. The first is my main man the “Hawk”. Gary Hawkins is an old philosophical lion, a Python probabilities pro, and SQL guy, and all around good man. I won’t divulge his work experience here, maybe he’s mentioned it in one of his Substacks, but we are all paying subscriptions to this billionaire now, and Hawk was right in the thick of it back in 2000’. You see Hawk helps me “cleanse” the VAERS lots aka batch numbers using the Python probabilities tools. Basically returning what the lot number should be based on a predefined set of rules. In simpler terms his program changes O to 0, changes Z to 2, etc... There is way more sophistication that goes into his algorithms and it does not stop and just lot numbers. We (he) can pull out patient ages, symptoms, lot expiration dates, etc., from the summary narrative section as well. Do you see where I’m going with this? This all apart of the data cleansing and data modeling that needs to happen before ANY analysis is being done! If you jump to the analyzing straight from what is being regurgitated from VAERS, your just going on a fools errand. I think it might be why NOT to many of the top celebrity analysts respond to me when I ask what kind of data cleansing are you doing on doses, ages, and lot#’s? In the perfect world top analysts and data cleanser/modelers like Hawk could work from a master file where we are all pushing and pulling in the same direction. I’ve offered my master files to anybody who is serious, and anybody humble enough to ask. Crickets. Maybe I’ll just leave my master files available opensource and available for download on my website, so nobody has to ask and the celebrities can save face. I know there are plenty of PhD’s that will snatch someone else’s trophy and jump onstage at all these weekly grab ass seminars and receive all the accolades. Here is Hawk, use him!
Another young gun is Aravind from Vaccine Data Science. He’s doing something similar to Hawk, not quite, but similar.
A super big shout out to Julie Threet aka PrayingHawk144 of Chico California. This lady goes in person to the Board of Supervisor meetings every week and gives them a three minute earful, almost every week! She is actually one of the only people that actively uses my dashboards as intended! I create these dashboards as a tool for the average person to analyze like a grizzled PhD data analyst. She’s the proof.
She some very hot topic in Chico and exposing all the low people in high places there. Follow her video here:
Follow her Twitter HERE.
Here is PrayingHawk and me filling out her mother’s death report on VAERS
Here is me filling my uncle’s Permanent Disability report after a stroke 1mn after his 2nd Moderna shot.
I also have a follow-up video of the response VAERS gave me, where they basically invented symptoms my uncle simply did not have! Particularly psychosis and Parkinson’s like symptoms. They also omitted and changed phrases in my write-up!! VAERS basically submitted a false report on my behalf as far as I’m concerned. This would be a perfect law case, I have all the documents and even video evidence! I originally made these videos hoping they could be a “how to” for the next person that needed to file a report but didn’t know what to do. It’s helped me deeply understanding the entire system.
Another guy I’m excited about the word cloud guy at matchyourbatch.org , he doing the how bad is you batch thing with a word cloud based on symptoms like this:
I like that he gives you an option to read actual reports from medalerts or from openvaers. Ok ya’ll report back soon on the shennaniga’s in this weeks drop.
It was established back in 2010 that less than 1% of all ACTUAL (documented) vaccine injuries are ever reported to VAERS. And since then, VAERS has done thing but implement systems and strategies that would further reduce the % of actual vaccine injuries that would end up being reported. SEE: https://digital.ahrq.gov/ahrq-funded-projects/electronic-support-public-health-vaccine-adverse-event-reporting-system
Even before you begin to cite how many are deleted (of the "less than 1% that are ever reported to VAERS in the first place) one must first begin by multiplying/calibrating the published VAERS numbers by at least 100 times before you're even in the neighborhood of anything close to the truth.
The 2010 study of the VAERS system proved that vaccine injuries are "common" and that "less than 1% of vaccine injuries" are ever reported to VAERS in the 1st place. VAERS exists to launder the dead bodies so that the money made off of them doesn't need to be laundered. Although it is admitted that VAERS is only supposed to serve as a sort of "sample" to provide safety "signals" our "scientists" represent the VAERS numbers as a TOTAL for injuries in order to prop up their "rare" slogan, which is then used to prop up their "safe" slogan.
They have no valid "science" (or numbers) to support their marketing slogans. The evidence proves that vaccine injuries (including deaths) have always been extremely COMMON, not "rare". Even an Oxford study was forced to admit that close to 80% of the deaths occurring after vaccination are within the first 24 hours of being jabbed.
I suspect that the throttling efforts are widespread, but with the primary focus on number of deaths. That's why the method I've used to estimate underreporting focuses on deaths. While the numbers of specific diseases can be argued because of assignment problems, that is not the case with deaths. Someone could classify myocarditis as pericarditis, but that misclassification would not occur with deaths. You either die or you don't!
My method takes the ratio of 1) deaths expected to 2) the fraction of VAERS deaths that fall into the expected category, then multiplies the non-expected segment of VAERS deaths by that ratio. The more throttling by the criminals who "manage" VAERS, the higher the ratio. With my method, they don't escape. The detailed methodology can be found here (https://www.trialsitenews.com/a/underreporting-factors-for-vaers-are-vastly-underreported-e3a21062).