BOMBSHELL STUDY: 3 MILLION EXCESS DEATHS IN 47 COUNTRIES-What about the other 188 countries? Part 2

Deeper extrapolation: This is what happens when you do the ol "Dump & Pump"...

Part 1: HERE

I want to use this study and this meme to demonstrate what happens when you apply the ol’ pump & dump method of analyzing statistics especially from VAERS & EudraVigilance.

Again, this is the study that is getting all the buzz:

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This is a very well referenced study. I don’t read many peer reviewed medical journals, but I read this one and dove into most of the references cited and especially the one that Sonia Elijah cited from author Diego Montano - Department of Population-Based Medicine, Institute of Health Sciences, University of Tübingen, Tübingen, Germany:

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Diego definitely did the ol dump & pump. To be clear, the D&P means downloading or extracting data without modeling the data or cleaning it up before analyzing (the pump) or pumping it out to the world in terms of graphs, manuscripts, or other visualization means. Modeling data is the core of analysis. Where and how it’s done is super important. When getting your final concept into the simplest graph possible one might normalize the data to “per 100K” when working with huge numbers with lots of zeros. However, the step before the step is trying get to the most accurate and complete data possible out of the dump before you move on to phase two. It seems like all these PhD’s and computational biologists have mastered the art on analyzing, but are lacking at filling in the holes? No surprise, they are PhD’s and they are good at the pump or analyzing if they are given good variables or NOT.

I apologize to Diego in advance for using him as an example, but Diego like many other brainiac PhD’s and MD’s are building their models from curated dog shit variables especially coming from VAERS & EudraVigilance when trying to make a sound, valid, and cogent argument. At least it’s bitter sweet that the carnage is so bad the collateral damage can’t be completely hidden. I will never accept when one star PhD told me, the data is bad enough when I pointed out all the missing ages.

1st Issue: Age Cohort Analysis:

Did you see up in my meme that 492K Covid-19 reports are missing the age field? That’s 30% of ALL C19 reports are missing the age field.:

30% (492,371) for dump & pumpers, but around 9% (~147,000) unknown ages when accounting for ages that are properly documented in the summary narrative. This is why I have a hard time with Diego’s results section here when comparing flu vax and people 65yrs or older and their severe adverse events.

I co-authored a little paper on ResearchGate with Herve Seligman who was also referenced in this buzzy study. Herve from Luxembourg was a reference of a reference to be precise, anyhow we show based on my diligent work of ethically populating missing age fields, that the younger population is actually “hidden” the most! HERE. Yo Diego did you catch any of the ~300 “hidden” dead kids after the C19 depop shot? Hidden only because their age was NOT populated in the age field, see HERE. Who else jumps on international stages and says there are only 200 dead kids in VAERS for C19? Hmmm…

There’s ~500 dead kids in VAERS and C19 de-pop shots.

2nd Issue: Down-coding of Serious Adverse Events (SAE)

Yo Diego, what did you do about these 986 myocardial infarctions or cardiac arrests VAERS is saying are not serious, aka None of Above?

Also, to me there might be as many as 500 cardiac arrests that actually died because there is no mention of spontaneous resuscitation (ROSC). Oh well I guess some these not dead M.I. or arrest victims went down but woke-up in a office visit and went home.

I doubt if Diego accounted for any of the examples I’m showing here and I’m not letting EudraVigilance slide either. I’ve been showing all kinds of obfuscation in EudraV but here is a new one just for Diego to demonstrate the under-coding of SAEs even in EudraV, especially in EudraV…:

Here’s the thing that bugs me, when these hot shot PhD’s do their p-values and carry out their confidence intervals to the tenth or hundredths decimal, the average Joe is led to believe these highly educated doctorates must have superior command over the data and analysis they put forward? When in actuality their breadth of knowledge is very narrow but deep. Oh btw these VAERS & Eudra examples are just the tip, there is over 100K SAEs in VAERS not classified as SAEs.

3rd Issue: C19 injuries attributed to Unknown vax type, Other vax type, or concomitant medication.

Did you know there was this many reports of Unknown Vax Type that appeared on the scene during the Covid de-pop shot era?

What rhymes with Moderna?

Nothing rhymes with Moderna. Yo Diego did you know there was this many reports under Unknown Vax Type, with the word “Moderna” in the summary narrative? I would say my CI 95% is they are Moderna.

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Conclusion:

I’m sorry I made Diego my punching bag in this article, because otherwise his study is fabulous! I wish I could whip out PhD style work like Diego, but like Diego my knowledge and experience is narrow and deep as well. I may not be smart, but I think I’m pretty wise. Being smart and being wise are two distinct conditions and one does not imply the other. God Bless

You should ask yourself how many other PhD’s are out here running around making all the same oversights Diego made?

I’ve been working on a manuscript with Dr. James Thorp about infertility disorders and he’s making me a co-author. Jim gets what I’m throwing down and expanding the manuscript for most of the things I’m discussing here. This paper will hopefully blow people’s hair back with the revelations we are coming out with. I think this paper will even light Naomi Wolf’s hair on fire! God Bless

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