These are great questions that I'm struggling with at the moment. Certainly, my chance of taking vaccines in future has gone down a lot. However, mostly I've already taken all the ones I'd ever need including vaccines against the diseases you name, so the question is somewhat moot. In the end there's no real substitute for just weighing up the risks in each case the best you can.

"If you believe data integrity issues are extreme, there's no way to calculate risk of vaccine vs no action. Your decision would depend on whether you trust your own research over the official policy."

Correct. I do actually trust my own research over official policy at this point, but, the difficulty of mounting an alternative data based argument is definitely there. That's why I didn't try but explained my policy via social explanations. However, we can make some assumptions that let us use at least a small amount of data. We can assume that whatever official statistics do exist are manipulated or exaggerated to increase the apparent attractiveness of being vaccinated. There's enormous amounts of evidence that this sort of manipulation is happening, so it means those statistics put an upper bound on things. The truth may be that they're less attractive, but it's unlikely that they're moreso. Thus if even the official statistics, when examined closely, aren't convincing, it seems reasonable to conclude the argument must be very weak indeed.

"But given that most of us have no formal education on the subject, no resources to conduct more accurate studies, no access to primary data sources, nor an educated peer review group to critically examine our analysis, the chances of major flaws and biases seems quite high."

I think this is the source of the disagreement. As far as I can tell, public health researchers and officials are characterized by:

1. No formal education in anything biological or medical. Tedros is of course a former African communist official put in his position by China but even academics can turn out to be untrained. Prof Ferguson, whose bogus predictions created lockdowns, was originally a theoretical physicist and has no qualifications in anything biological or medical. In fact nothing in his team's work has any biology in it. That's totally normal: the people who predict disease and suggest policy frequently have no training in it, they're just data analysts ("mathematicians" to the press, to most corporates they'd be junior business analysts). I touch on this in my presentations to the British government ministers: you can read all the relevant papers without once encountering any actual biology or even any theory of disease. Even when they have training it's irrelevant, because they don't use it.

2. No resources to conduct accurate studies. Most existing studies are done by academics in their living rooms at the moment, so they don't actually have more resources than I do. Again, public health is not medicine. Public health consists primarily of academics and bureaucrats, especially in the current environment, they are mostly just working-from-home Office jockeys. Plus if existing studies are mostly useless then that's still useful to know, as it informs what to do next (i.e. nothing). A basic principle is that if there isn't clear evidence that it's useful to do something, the right response is not to look desperately for something to do (that's the so-called "politician's fallacy") but rather leave things alone.

3. The same access to data sources as everyone else. The primary data is all available and when you read in the press or government announcements about COVID studies, almost always those are simply analyses of publicly available data sets.

4. Peer groups of people who are just as poorly educated as them, with the added problem of groupthink. A big part of why the research is so corrupt is the academic need to please their in-group without looking un-educated or confrontational, so the absence of such groups is an advantage rather than a disadvantage. And at any rate, there are plenty of people out there debating these things in forums that are freer and more open than the average scientific peer group.

Overall I think the chance of flaws and biases in self-done research is lower than amongst the professionals assuming you're willing to sit down and wade through a lot of data and reports, and to stick to the scientific method. The quality of the "professional" stuff is so unbelievably low that as long as you're not actively lying to yourself all the time, and as long as you know how to use Excel, you stand a good chance of doing a better job. Not because the world is filled with high quality amateur scientists but because the world is filled with low quality professionals.