VaersAware take on the Denmark Study

Batch-dependent safety of the BNT162b2 mRNA COVID-19 vaccine by Max Schmeling, Vibeke Manniche, Peter Riis Hansen

1. The money shot of the study:

2. The lots:

   

3. The fancy explanation:

   Debunking the yellow dot lot placebo theory...

   4. The unanswered questions…

   1. How does blue, green, and yellow dots (lot#) look like with other countries?

      

      Answer: Right away Denmark looks to have much more hospitalizations, while Belgium is screaming with Permanent Disabilities. Austria has an anomaly with lot# FD4555 and the “non-severe” events.

      Before we go further let’s get that ugly anomaly lot# FD4555 out of the way now from Austria. Those 10.5K reports from Austria were mostly Breakthrough, drug ineffective reports originally cross-walked over into VAERS and with no even level marked off meaning officially they are sitting at the lowest level “None of Above” adverse event aka “not serious” aka safe & effective. VaersAware up-codes breakthrough or drug ineffective to Office visit level. You can really see Austria by symptoms and up-coding better here:

      

      I know this is about the Denmark study and I’m already diverting to Austria and mostly lot# FD4555 in this case but I wanted you to see the whole onion before I start peeling away the layers and seeing what’s what.

      Here is the same country view again but with the true definition of what CDC/VAERS considers Severe Adverse Events, which is basically everything above Emergency.:

      

      Now we see Denmark jump to the front of the pack! I think it’s impossible to calculate if Denmark was given more toxic vials within lots compared to other countries, or it’s all just a big coincidence. Whatever it is Denmark should be happy they are not Belgium! Belgium I guess is about twice as large as Denmark, so maybe we do need the PhD’s to tell us who is worse off?

      For now I will stick with Denmark and break down only Denmark’s Blue, Green, Yellow lot’s per professor Schmeling and the gang. One small disclaimer is that Jessica Rose included Emergency Level as a severe event, which I am not opposed, but for the purpose of keeping terminology correct I removed ER level reports from my study. I didn’t look super close to how Schmeling and company treated ER level Adverse Events, but gaging by what I see at high level already and by country it’s not going to make a material difference unless we were talking about Japan. The second small disclaimer is there happened to be very little ethical upcoding by vaersaware going on with Denmark and this combination of lot#’s aka the blue, green, yellow dot lots as depicted here:

      

      b. What is the expiration dates on these lots?

      

      

      

      It looks like Jessica Rose’s hunches and bets were safe about the older the Lot# number, the more severe it seems to be. Now whether that’s because of old folks getting sacrificed first or for a combination of other reasons one can only speculate. I will speculate now…. The reason why this Denmark study is getting poo-pooed now is because of the immense amount of throttling (purposeful delay) of publishing reports that has been really going on in mass since Nov 2022. To me Jessica alludes to the throttling but she is calling it the “extended data” in this particular analysis. I call it throttling by sophisticated evil and intelligent design and I draw my conclusions because I can go really deep and I have great visibility with my dashboards. I hope we can stop beating around the bush some day. I am a bit confused why Dr. Rose says she doesn’t have the manufacture date of the lot’s? I don’t either but the expiration date is printed on all the vials and if we work backwards wouldn’t that gives us the clue? Is the manufacture date more important than the expiration date? Me thinks not. I’ve scraped expiration dates from all over, and as a matter of fact “we” meaning Jessica, Sasha Latypova, and myself have exchanged lists of expiration dates. When I say exchange, I mean Sasha had a list of Pfizer lot expiration dates from her secret source and I had/have a list of Moderna and JJ expirations from mine and we exchanged and pass them on to Jessica. I’m a little confused but for shits and giggles let’s look at those blue dot lot# reports by vax date since that’s what Jessica defaulted to and then let’s look at the victim ages of the blue dots:

      

      

      In these age statistics Dr. Rose would quote the stats on the left, I calibrate all my dashboards to the stats on the right. Hmmm this is strange, I would expect to see more old folks than younger, according to what any layman can see without ethical data extraction from the summary narrative to help populate age fields, on the left side. The dump and pump crowd would have to exclude the 295 victims of UNK AGE and roll with 116 reports with a proper age. Quick math says ~38.8% (45 of 116) is 60yrs old or older. On the right side with ages “cleansed” and a more precise view it’s ~48.3% (196 of 406) that are 60 and over. That’s not a super strong case for Rose or Dennis Rancourt's hypothesis that Rose referenced.

      c. So how much of these blue, green, yellow reports were throttled into VAERS or basically since this Denmark study cutoff of Jan 11, 2022.

      Answer: the VAERS drop was Fri Jan 7 & Jan 14 in 2022, so here in 1/14/2022 to current 6/30/2023 for Denmark’s SAE only:

      

      Staring at the self explanatory metrics above, I can see the super grand majority reports were processed by VAERS quickly (7-14 days) once getting them cross-walked from Denmark seen in the “Rec’dDtopub Lag” graph. The vax dates were old however. Did these victims have long onset dates which would be a reasonable indicator for the citizenry of Denmark to delay submitting reports in respects to their vax date?

      

      The answer is no most of victims of delayed reports had very fast onset to symptoms! In fact 78.9% of these throttled victims had an arbitrary onset of 0-14days.

      Conclusions:

      All in all the Demark study was on point when it was done, but has now become antiquated like many other calculations and maybe even like Kirsch’s URF 41?

      Not knowing the doses I would have produced a tabular list of Relative Toxic Lot Values like this:

      

      I’ve spelled out my RVU formulary many times but you can clearly see the formula spelled out in the dashboard. However, now knowing lot size and taking a big assumption that it is how many doses went in arms for the sake of this study my Toxic Lot RVU for Denmark SAE only is as follows:

      

      I think it’s pretty close, however look at some of the very last lots on the list, lot FF0884 with one death has a higher RVU than lot FH8469 with four deaths but with double the doses? My eyeballs are telling me FH8469 looks more toxic? Oh well I think we’ve proven the yellow dots aren’t necessarily placebos or not toxic or not harmful. I think all vaxxes are dog shit, but I wouldn’t doubt the cabal has reserved non-harmful vials for the Gestapos.

      Lastly I created a quick Interactive Scatter plot dashboard you can play with here:

      

      Click to launch Tableau

      I also created a handy filter on my dashboard to quickly get to blue, green, lots so you can do everything I just did! No PhD’s needed this time…

      

      click to launch on laptop (best)

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