One cannot claim to be on team “science and data” when their data is a garbage heap. Being able to tell between “hospitalized because of Covid” and “died because of Covid” vs “hospitalized and tested positive” and “died and tested positive” is an incredibly important thing.
I have no idea why people continue to dismiss this other than fears of people “not taking Covid serious” because… well it might not be as serious as the trash data suggests. It’s completely manipulative, a common theme from “the experts”
You cannot in good faith claim to be “following the data” and accept commingling “from” and “with”.
https://sanjosespotlight.com/santa-clara-county-revises-tota...
Whether such classification errors were deliberate is a separate issue. In most cases I suspect it was more due to lack of resources and/or incompetence rather than a deliberate attempt to mislead.
Medicare did pay hospitals more to care for COVID-19 patients. That is also a fact not open to dispute. Whether doctors or hospitals deliberately inflated numbers to make money is unknown.
https://www.usatoday.com/story/news/factcheck/2020/04/24/fac...
About half of the COVID-19 positive hospital patients were admitted for unrelated reasons, and only tested positive as part of admission screening.
https://gothamist.com/news/new-preliminary-state-data-shows-...
Please find me a single topic which impacts more than a roomful of people where someone isn't engaging in this type of discourse.
This sounds like you justifying your former false beliefs (or at least lack of willingness to investigate alternative beliefs) by blaming it on other people who were also wrong.
"Died with" was not a meaningful distinction at the time and falls under the "bad faith" category for me.