[shadowgovt]

1) not at all. What I'm saying is that if a doctor has a 40-year-old patient with a deep vein thrombosis who hasn't had a vaccine since they were in their mid-20s, that case doesn't go into VAERS. But if they have a patient with deep vein thrombosis that had a COVID vaccination last month, it does. And since the pandemic has caused a national vaccination push, we're now seeing a lot more of the latter.

The people who call in a bunch of unrelated leads during a murder investigation also aren't uneducated; it's perfectly reasonable, expected human behavior that when people are looking for trouble they find it more than if they aren't expecting any connection. Whether or not the connection is actually causal.

2) insufficient data to know if it should be alarming, because outside of a pandemic circumstance, the 20 to 60 demographic doesn't get very many vaccinations. So you're comparing on other years a population with possibly very different behavior to the general population (for example, one explanation could be that there's correlation between people being healthier and people getting vaccinated on years that aren't pandemic years... Possibly because the kind of person who goes out of their way to get vaccinated when it isn't required for school attendance is the kind of person that cares about their health more than average, is more prompt on upkeeping preventative medicine, has access to the kinds of doctors that catch early signs of heart disease before they evolve into full-blown conditions, etc.).

[BoHerfVJrEsq]

I'm sorry in advance if I'm not understanding again, but is the suggestion that we normally get however many cases of e.g. aphasia, but we just didn't know in 2019 because there was no vaccine push? What then is VAERS for? If there was an alarming situation that VAERS would help us see, what would it look like?

Edit: this has been unjustly flagged.

[shadowgovt]

VAERS is for gross data aggregation. But it is the absolute zeroth step in finding a causal link between vaccines and negative effects in the population. It's raw data without scientific controls for confounding factors (or even independent checks against self-reporting error), and misleading to the point of actively harmful without rigorous analysis and (more importantly) follow up study with proper scientific controls.

To give an absolutely terrible, but perhaps useful, analogy... You're an old sea captain on a sailing vessel without modern weather technology. VAERS is the crewman whose knee acts up about half the time before a bad storm. At best, if he tells you his knee's acting funny, you put your weather eye out... You don't turn around and go back to port.

[BoHerfVJrEsq]

OK. VAERS just sounds the alarm, at which point we have to investigate further. Peter Schirmacher apparently did autopsies and established a lower bound that about 30% of the victims died due to the vaccines. D-dimer tests have apparently shown clotting. Troponin levels are apparently indicating heart damage. Is the system not working exactly as intended, except that the inconvenient results are being suppressed?

[shadowgovt]

No; the system is working as intended, but you're naming outliers that haven't been replicated or confirmed. It's not "suppression;" it's "This result was weird, and other people aren't seeing it." Which is far more often study error or misinterpretation or confounding factor than an actual issue.

... and that's the problem. The general populace doesn't know how rigorous medical testing works. And when they get their hands on something that sounds serious (but isn't actually at a scale that causation can be confirmed), or someone with an axe to grind decides to push a counter-narrative that doesn't stand up to scrutiny (but who cares whether it does if the general populace doesn't know how "scrutiny" works and is weighing the evidence of the medical community and the CDC vs. one pathologist in Germany as if their words have equal weight), it becomes a general problem for public health.

One that, apparently, Google has decided it doesn't want to be part of.