everyone just remember that published numbers are state and federal mandated
highly summarized reporting. All of the details for severity, unique conditions, etc are in the EMRs for each individual, and is confidential. So conclusions from analysis with highly summarized numbers is prone to the error called Simpson's paradox,
Simpson's paradox - Wikipedia
is a phenomenon in probability and statistics in which a trend appears in several groups of data but disappears or reverses when the groups are combined.
Also please realize that anecdotal examples are generally not statistically significant, so if you are deducting a conclusion based on your neighbor's experience or story, you are cherry picking with your confirmation bias or anchoring bias. . . example, I had barely any noticeable reactions to all three pfizer shots, but that's my history of virus interactions, shots and genetics. your reaction probably will be unique to your history and genetics. if you did have an uncomfortable reaction, then you realize that there is a huge range of outcomes, just some are more prevalent than others. . . Also realize that if your Myers Briggs personality type has a strong J over P, and S over N, you will be biased towards a black and white, all or nothing, good or bad only interpretation of any data set. And if you believe the first article as truth, then you are using anchoring bias versus any valid research. . .
my point is keep an open mind, and realize the observer effect,
Observer effect (physics - Wikipedia)
where observations (level of testing) can change the data and the interpretations, and that unless you are trained in statistical analysis, you are getting fed interpretations which may or may not be correctly interpreted.
and yes, coachk who looks and reports data to doctors and the states and the independent rating agencies for a medical system of several hospitals, she and I debate the data interpretations for conclusion validity all the time, she has an undergraduate in math, statistics and programming from the 80's and a masters in healthcare informatics. . . we debate interpretations all the time, me from headline data, her from detailed hospital patient records, and there is data in the public domain which isn't being covered but appears to have negative outcomes outside of the study goals, and therefore not studied, but concerning.
her point is that all the data is interesting, changing, incomplete due to summarization, and not black and white, not all or nothing, not all good or bad. Likewise, there is an element of financialization where the incentives affects the decisions / the data story as well as job security, wanting to please your boss's story s/he wants to tell, think govt jobs.
sportsguy and coachk