The problem arose because, in the first year of the rollout, almost all the reports coming into VAERS—more than 90% of 1.1 million—were for the mRNA covid shots, dwarfing vaccines for all other diseases.4 This meant that analysing the safety of one vaccine, for example Pfizer’s product, involved comparing it to other vaccines, which were overwhelmingly limited to Moderna’s product. But if both mRNA vaccines elevated the risk of an adverse event like myocarditis in roughly equal amounts, the “observed” frequency and “expected” frequency would be similar, resulting in no automated alert.5 The statistical phenomenon is known as “masking.” (This is from the article). The article posted however is missing important context. The PRR used for comparison is a method that the whistleblower Szarfman et al. themselves describe in their own paper as being vulnerable to false positives, while the method she proposed as the primary one is RGPS. link.springer.com/article/10… The same paper explicitly states that VAERS analyses, including both PRR and the improved methods, are for exploratory hypothesis generation. link.springer.com/article/10… The article states that the VSD, which authorities trust, did not detect a signal as of August 2021 (using the official threshold for all ages), but in the 12–39 age group within 0–7 days post-vaccination, there was a highly significant difference with P<0.001, of this signal however determinant effects were seen to be negligible in all but the 12-39 bracket in 2021. In my other responses I was careful to avoid using papers hinged upon US collected data exclusively, hence only two CDC links appear in my prior responses. I have checked against my prior sources, they did not use the mined data discussed in this article. jamanetwork.com/journals/jam… This in TLDR format: Paper is essentially saying the overuse of the VAERS system lead to a deluge of reports on Pfizer and Moderna vaccines, both of which being mRNA vaccines. These were then compared to ALL other vaccines on VAERS (of which none are mRNA) or to each other (similar vaccines) resulting in the mathematical challenge of balancing our abnormal results from a large, unvetted and not-causal database of incidents. For example, the icy road death and gunshot wound were invariably used in statistics and analytical methodologies were applied to the data to disseminate these types of reports en masse (since it was impossible to go through and vet each individual self submitted report). This in theory could have led to a genuine signal of actual side effects being cast aside in the name of statistical purification. It is also important to note other countries did NOT utilize this approach for data collection, and hence other cohort studies (including US studies post 2022) hence remain unaffected by this. It was a big oversight issue for sure, but the phenomena itself is not a new thing and it was possible to annotate even that flawed data for hidden signals, the main regulatory agencies in the US didn't. That doesn't mean study others did not though. Most of the things attached prior in the thread I have checked and they did not utilize this data. Other countries’ active surveillance systems and later U.S. cohort studies (VSD after mid-2021, Nordic registries, England’s 40-million-person analyses, etc.) did not rely on that early VAERS mining algorithm and still found a myocarditis signal after mRNA vaccination that was smaller than the signal after infection itself. The BMJ article documents a genuine process failure in one U.S. signaling tool; it does not by itself invalidate the later, independent evidence.