OVERVIEW OF THE EVIDENCE THERE IS INTENTIONAL COVID-INJECTION BATCH VARIABILITY (TWEET 1/10) Here's an overview of some of the evidence that the COVID injections vary in toxicity from batch to batch, with a small percentage of batches representing outsized harm. In this first clip from an October 2022 interview... with the Corona Investigative Committee(1), former pharma industry R&D executive and entrepreneur Sasha Latypova describes how she arrived at the conclusion there is significant variability in toxicity amongst the novel jabs, first looking at the variability in serious adverse events (SAEs) and deaths amongst flu vaccine batches, and then comparing that to the variability of the COVID injection batches. Lo and behold, while Latypova found that the flu vaccines are "very consistent products," the picture was "dramatically different" for the COVID injections. She notes there was a "huge variation [in SAEs and deaths] between lot to lot for all [the] COVID-19 injections" and that they were hundreds or thousands of times more variable than the flu vaccines. Latypova notes the lots she analyzed were verified by the CDC and she worked off of "a complete list of lots that were issued in the United States with correct lot numbers, manufacture dates, and expiration dates..." 1. Full video:show more

"EVEN AFTER ADJUSTMENT FOR SHIPPED LOT SIZE, ENORMOUS VARIABILITY LOT-TO-LOT REMAINS UNEXPLAINED." Latypova adds in the same interview that the variation in SAEs and deaths caused by different lots cannot be explained by variation in lot size. She notes the sizes of the lots "are not that different," and that a FOIA request(1) provided information on "all the shipments of... Pfizer product in the U.S. by lot number and the number of doses." After adjusting for the lot size, looking at only deaths, Latypova highlights the fact that there was "a huge variability" in lots—up to a 12-fold difference. She notes that variability and toxicity both declined as time went on in 2021, although continued to remain at an "unacceptable" level. Critically, Latypova notes there was a "definite statistical relationship" for Pfizer's injection lots between both an individual lot's date of manufacture and even the alphanumeric codes. For Moderna, as well as Pfizer, in the latter case. "We know which letters and numbers stand for what level of toxicity today and we can tell it to people, and, in fact, we have been," Latypova says. She adds that this "points to [an] intentional act." 1. FOIA data:

"WHAT WE'RE LOOKING AT... IS A PERFECTLY MATHEMATICALLY SEQUENTIAL SERIES OF BATCH CODES WHICH CODE FOR [VARYING LEVELS] OF TOXICITY." In this clip from a video on his BitChute channel(1), Craig Paardekooper, a pharmaceutical sciences student at Kingston University in England(2) and colleague of Latypova's, asks the question: "Did Pfizer use the batch codes to label the different... different dosage levels, so that they could monitor the effects of those levels on the general public?" He comes to conclude that has indeed been the case. Paardekooper shows this by graphing the alphanumeric codes of Pfizer's injection batches in relationship to their number of adverse reactions. The pharmaceutical sciences student notes that "the batches cluster alphanumerically," meaning that adverse events "cluster" around batches that have similar batch codes. The fact that adverse events can be considered a proxy for toxicity, Paardekooper says, means that "batches cluster into different ranges of toxicity according to batch codes." Furthermore, he notes that "the distribution of the batch codes is not random" and that "the toxicity as indexed by adverse reactions is different for each cluster..." For one particular group of batches with similar codes, which all produced outsized adverse reactions, Paardekooper says "What we're looking at... is a perfectly mathematically sequential series of batch codes which code for this high level of toxicity." 1. I can't link to Paardekooper's BitChute because of Twitter blocking the website... It's easy to search, however. 2. Source:

"THESE BATCHES ARE NOT APPEARING RANDOMLY OR CAUSING ADVERSE REACTIONS RANDOMLY. THIS SUGGESTS THE ADVERSE REACTIONS ARE NOT A PRODUCT OF THE RECIPIENTS' HEALTH STATUS, BUT RATHER A PROPERTY OF THE BATCHES THEMSELVES..." In this second part of Paardekooper's video, he further outlines how especially toxic batches belong to a "perfect mathematical sequence" with regard to their alphanumeric codes. For example, Paardekooper shows that batches beginning with the ER designation (e.g. ER8728, ER8729, ER8730, etc.) were all particularly dangerous. Consequently, Paardekooper notes that "These batches are not appearing randomly or causing adverse reactions randomly... [suggesting] the adverse reactions are not a product of the recipients' health status, but rather a property of the batches themselves, which were labeled for their toxicity." "What seems to be the case here is that the level of the adverse reactions is coinciding with batches that all have batch codes... [that] belong to a continuous mathematical series," Paardekooper says. Critically, this observation even holds true for batches that were administered in child populations, meaning the lot-to-lot variation in adverse events cannot simply be attributed to particularly old people getting particular batches.

"WHAT IS CONCERNING IS THAT THIS WOULD BE EXACTLY WHAT SCIENTISTS WOULD DO IF THEY WERE TESTING DIFFERENT DOSAGES OF DRUGS AND MONITORING THEIR EFFECTS." In this third part of his video, Paardekooper notes that "as the alphabet [of the alphanumeric batch codes] ascends [goes from A to Z]... the actual toxicity of the batches decreases." Paardekooper adds, "What is concerning is that this would be exactly what scientists would do if they were testing different dosages of drugs and monitoring their effects. Scientists always label their test tubes [and] they always label each experimental condition so that they can see what medications were applied to which people and then all the effects." "Being as the vaccines are still in an experimental phase, we would expect them to do this and this is what we are actually seeing—different dosages applied to different populations," the pharmaceutical sciences student says. "And each different dosage seems to be labeled alphabetically and numerically so that the different batches for the different toxicity levels all belong to the same mathematical series."

"A CIVIL WAR HAS BEEN DECLARED AGAINST THE RED STATES." In another video Paardekooper has on his BitChute channel, he notes that the VAERS data (which is a stand-in for how toxic each batch is), shows that "red states" in the U.S. (that is, states that skew toward having more Republican voters) have been receiving deadlier batches than "blue states" (states with more Democrat voters). Paardekooper shows that he arrived at the deadliness of the batches by counting the number of deaths associated with each one and controlling for batch size by deriving the deaths per 100,000 doses figure. Most states that received relatively deadly batches, Paardekooper's data analysis shows, were red states. Most states that received relatively less deadly batches, were blue states. Paardekooper goes on to speculate that "what we have here is literally civil war going on." He adds, "a civil war has been declared against the red states."

"THREE PREDOMINANT TRENDLINES WERE DISCERNED, WITH [NOTICEABLY] LOWER SAE RATES IN LARGER VACCINE BATCHES AND ADDITIONAL BATCH-DEPENDENT HETEROGENEITY IN THE DISTRIBUTION OF SAE SERIOUSNESS BETWEEN THE BATCHES REPRESENTING THE THREE TRENDLINES." Supporting Latypova and Paardekooper's findings is a research letter that was published in the peer-reviewed European Journal of Clinical Investigation(1) in March 2023, which found a "batch-dependent" safety signal for Pfizer/BioNTech's COVID injections. In their research letter, Max Schmeling et al. describe how they collected the data related to adverse events and their corresponding vaccine batch labels from the Danish Medical Agency (DKMA). Upon analyzing the data the authors found, "unexpectedly," that "rates of SAEs per 1,000 doses varied considerably between vaccine batches..." The authors add that "three predominant trendlines [sic] were discerned, with [noticeably] lower SAE rates in larger vaccine batches and additional batch-dependent heterogeneity in the distribution of SAE seriousness between the batches representing the three trendlines [sic]." "Compared to the rates of all [AEs], [SAEs] and SAE-related deaths per 1,000 doses were much less frequent and numbers of these SAEs per 1,000 doses displayed considerably greater variability between batches, with lesser separation between the three trendlines [sic]." Indeed, it is easy to see these three trend lines as clear and distinct on the graph from Schmelling et al.'s research letter. The authors note in summary that "the results [of their investigation] suggest the existence of a batch-dependent safety signal for the BNT162b2 [Pfizer-BioNTech's] vaccine..." 1. Research letter:

"A HIGHER-THAN-USUAL NUMBER OF POSSIBLE ALLERGIC REACTIONS WERE REPORTED WITH A SPECIFIC LOT OF MODERNA VACCINE ADMINISTERED AT ONE COMMUNITY VACCINATION CLINIC." As mentioned by Latypova in her presentation to the Corona Investigative Committee, public health officials in California were even aware of one particularly harmful batch of the COVID injections back in January 2021. On January 17, 2021 California State Epidemiologist Dr. Erica Pan issued a statement(1) that providers "pause the administration of lot [i.e. batch] 41L20A of the Moderna COVID-19 vaccine due to possible allergic reactions that are under investigation." Pan noted that "a higher-than-usual number of possible allergic reactions were reported with [the] specific lot of Moderna vaccine administered at one community vaccination clinic." At the time of Pan's statement, 10 recipients of injections from the lot had adverse events that "required medical attention" in just a 24-hour time span. Note that Pan and the California Department of Health identify the lot as the issue, not a particular subset of recipients. Nor even a subset of recipients who received injections from that specific lot. The lot itself is identified as the problem. 1. Department of Health statement:

"THESE ARE CAREFULLY COMPARTMENTALIZED DEPLOYMENTS [OF INJECTION BATCHES]... IT LOOKS LIKE ALL [THE INJECTION MANUFACTURERS] ARE BEING ORGANIZED FROM ABOVE SO THAT NO ONE INTRUDES ON THE OTHER'S OPERATIONS OR TIME SLOT. Going back to Craig Paardekooper, in another video he posted to his BitChute channel, the pharmaceutical sciences student puts a final nail in the coffin holding the idea that there is distinct, significant variability in toxicity between batches of the COVID injections by showing that there are "carefully compartmentalized deployments" of batches. As Paardekooper shows using VAERS data, "each company appears to be working along with the others so that no one intrudes on the other's [deployment] slot." For example, Johnson & Johnson's injections were launched first, relatively briefly, then pulled in favor of Moderna's. Moderna batches were made available for some time, then pulled for another brief period of Johnson & Johnson. Then, those Johnson & Johnson batches were pulled in favor of Pfizer's injections. "[This] result's quite unexpected, because I would have rather expected that the deployments from each company would've been intermingled and spread out," Paardekooper says. "Instead [however,] what we have is carefully compartmentalized deployments from each company."

Finally, I myself performed a cursory search of all the VAERS reports related to one of the batches that Paardekooper and Latypova's website, identified as one of the more toxic: EH9899. I looked specifically at SAEs that were tagged by OpenVAERS as either a death, a permanent disability, or a life-threatening condition. As expected, these SAEs were not reserved for the elderly. (Many critics of the "hot lots" hypothesis say that the SAE anomalies are due to the elderly receiving particular batches.) On the contrary, based on the cursory look, it seems as if recipients in their 20s, 30s, and 40s were just as likely to report an SAE as people in their 60s, 70s, and 80s. Here are some of the SAE reports I found for younger people. I include in this tweet several images of the reports from recipients' in their 20s as well. Reports: Life-threatening SAE for male in his 50s: Life-threatening SAE for male in his 20s: Life-threatening SAE for female in her 20s: Life-threatening SAE for male in his 40s: Permanent disability for female in her 40s: Permanent disability for female in her 40s: Permanent disability for male in his 30s: Permanent disability for female in her 20s: Permanent disability for female in her 40s:

You’d benefit from therapy and meds.