I do math in a major way, with a long career in software. When pandemic first became a sort of public thing in early 2020, I started graphing data from places like worldometers.org. The statistic that most interested me, considering that we were expecting literal exponential growth, was "Δt to next 100k infections." That is, how long between start and 100k? 100k and 200k? 1M and 1.1M? The 100k interval was chosen because it was a manageable boundary of data being made available. The graph was logarithmic by necessity and showed steadily worsening (dropping, reducing) periods.
Then a funny thing happened: The graph went flat. We started out with thousands of hours from 0 to 100k, and still most of a hundred hours to go 400k → 500k. Eventually we got down to ~24 hrs to go 1M → 1.1M ... and thereafter we never went noticeably below 24 hrs. It even rose some.
The pandemic had stopped being exponential. The graph was flat: It was just another disease percolating around humanity in a constant way, the way flu and strep do. That was early May 2020. We stopped wearing masks, stopped "distancing" (what a stupid word). We took a vacation to Las Vegas in July 2020.
But then the vaxxes started in 2021. And while covid infections and deaths declined, we kept our own counsel about the idea of taking a new medication with little testing and waaaaaaaaaay too much hype. I watched data again. And I didn't, and still don't, like what I see.
My employer, reacting to the administration's demand for "all companies who do business with fed.govt must have all employees vaxxed," published policy for all of us. I reacted to that by demanding exemption. I got it, after pushing on HR a bit, until I gave them a face-saving way to let it go.
I remain unvaxxed. I have a new, horrifyingly bad attitude toward the whole medical profession.
Along comes Mr. Dowd, with a whole career behind him of analyzing data the way I do (in a very different context -- he's from finance, I do engineering simulation these days), and I may have a new hero. He's taken the time to go beyond what someone like me could do, finding all the necessary resources to make the really complete analysis needed, having the "in" to the financial/insurance industry, finding all the all-cause mortality data sources. This book is an excellent summary. The very few who try to discredit Mr. Dowd are, in my opinion, not playing the right game or in the right stadium, and out of season besides.
By now, the data speaks for itself, and Mr. Dowd has given that data a new voice.