VAERS New Data Drop 3/25/2023 Pitch Count Summary
What carnival tricks this week (2,786) supposedly "new reports"
Let me come fast with one of my weekly Twitter meme staples:
Lots of info to digest, but what I’ll be analyzing today is the 2,786 “new” Covid & Mokeypox reports published yesterday March 24 which you can see along the pink row. So that’s 94 deaths let’s start there. Unfortunately there are no easy and quick answers in VAERS and these 94 deaths are a great example, but at least we can pin down the overall difference from the week before. 71 domestic & 23 foreign, but how many deaths were deleted this week? Seven deaths were deleted this week, here. So technically there was actually 101 “new” deaths or should I say new ID#’s with the box checked off as death.
Here is why you come get info from me, so I can tell you about the stuff the other analysts do not, and it’s about what gets up-coded or down-coded each week as well. I try to be precise in my terminology because there are jab victims (reports) where the clearly died or “expired” per the summary narrative write-up and/or the symptom code, like these here. This week was super unusual in that there were an additional 7 deaths the experts and VAERS found and they finally decided to correct the tick box, here and the link to MedAlerts Wayback Machine to generate these reports yourself here. Thank you Steven Rubin creator of MedAlerts, otherwise the world would have never known what exactly gets edited or changed every week. I had lunch and a beer with him once in Palo Alto, and he’s a pretty cool dude. Not much of a conspiracy theorist as me, but he dose his job well and that’s all I can ask for.
So on paper, it’s a good thing that VAERS corrected these 7 reports that I had found within the first few days the error was allowed to pass through the vigorous authentication process and ultimately published. However upon close examination, you’ll realize that VAERS took their sweet old time to make the correction? They could have corrected all these long ago, but let’s look a one example so you see what I’m talking about…
Do you see what I’m talking about now? My latest calculations show they have about ~50 more to find and when depending when they do, could be just as old as this example. Ok, if you’re following along you will have seen they made 8 changes to death reports and I said 7, so lets see what happened to that other report which in this case was a down-code.
So many philosophical debates raging in this down-code example. First, this 40yr old frontline nurse became prego shortly before even her 1st dose, but 7 week old baby dies right after the 2nd dose. First trimester are technically called a miscarriage I believe, but can be called a fetal death at any time in the pregnancy, here. I can almost guarantee you if this was some other nurse not related to this baby and following her clinic marching orders, this report would have been reported as a “spontaneous abortion” and a Office Visit or None of Above event level, if at all. So be it, why does VAERS find the need to correct this “error” report? For all the missing ages, missing vax dates, death dates and dates of all sorts, why was this report prioritized over the mountains of backlog they must have? I rage on about some of this philosophy down the road, but just to say this report just dropped down to the next highest level which was Emergency. She probably would not even be at that level had she not been an ER nurse herself? So much for VAERS being a passive system and people can submit whatever they want. Never mind VAERS dragging ass and slow playing everything to help the greatest con in history. Let move on.
Pop Quiz! What do you see? Can you start to see the throttling? There is so much more we are going to dive into, but I’ll just leave you a little homework assignment to jump into the dashboard here and click on every button and picture you see below.
God Bless
Albert, I’m very pleased to have your updates coming direct to my inbox. Thank you and keep it coming. You’re right that you’re the only one (the ONLY one) looking at this data the way you do, and presenting it in a way that’s quick and easy to digest. 😸