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What I have learned from COVID19:

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1. Public health is undervalued, underfunded, neglected, mistreated, and it is easy to get away with that for years, decades, but someday that ends up biting you in the ass
2. CDC recommendations/ guidance to restrict early testing was a mistake.

Being able to scale up testing remains a total disaster;

Without testing, fundamental Qs remain unknown,
Sad and honestly embarrassing for such a great nation
3. Doctors love to give unproven, unpromising therapies based on lousy, awful data.

No number of medical reversals and no history book will ever convince many that the harms of just giving things can easily outweigh benefits. Sad!
4. When we do get around to running trials, we do a lousy job:

No controls
No blinding
Awful, bias susceptible endpoints
Too large a sample
Too small a sample
Duplicative and redundant trials
Trials not proportionate to scientific promise

Total disaster
5. Docs love to hype early, uncontrolled, retrospective, missing data, busted time zero, confounding by indication garbage.

We also love to say things like "appears promising"; "a clue"; "may"; "might" "could" ... to absolve us of our faith in these crap papers
6. We are quick to imagine a new disease changes the entire playbook.

Forget everything you know about the vent, blood thinners

We don't realize that such claims are HIGHLY provocative and requires a lot of data
The burden of proof is on those who believe THIS IS DIFFERENT to prove a different strategy is superior

Instead, our experts just change institutional guidelines willy-nilly
7. A few loud mouths can distort and distract all media coverage. Some folks have no shame in saying BS on TV.
8. Even many academics prove to be 'inauthentic' and 'opportunists' tweeting about things they are inexpert in with false confidence.

Craving the same, sad TV fame.

Basically reading the newspaper one day and tweeting about it the next.

Changing their twitter bios. lol.
9. The worse the data supporting the policy,
the louder some shout

"The science says..."
"We must..."
"90 studies show..."

Creating a hostile atmosphere for those who disagree.
BTW, citing the number of weak, tangential, irrelevant studies that support a claim is meaningless.

Go back and look at how many studies support some now debunked claims. It can exceed 5k!
10. If there are serious academics who disagree. My philosophy is hear them out, consider what they say, and then feel free to rule against them;

instead, as @drjohnm and others have observed, I observe there is too much pre-occupation with silencing them.
Asking what their real motivation(s) is/are.

Is it not possible they just disagree?

Do we ask ourselves our motivations simply because we have reached a different conclusion?
11. Preprints. I am not convinced that pre-prints are worse than usual misleading science, but boy do some try to ruin it for their kind
12. There is no private, personal tragedy that someone else cannot make about themselves in an obnoxious, narcissistic tweet.
13. Folks are lying about how good telework and tele-lectures are
14. It is easy to minimize or discount economic damage when you are financially well off with a stable job; and easy to demonize folks who ask us to consider that economic damage actually does crush human health and well being
15. HIPAA is a suggestion
16. When you do something generous, noble or honorable, make sure to let others know about it on twitter
17. Fear-mongering and false certainty drives social media traffic

Nuance can #deleteyouraccount
18. Explaining the need for RCTs to well educated physicians is painful

"Would you be randomized"
yes, of course

"Would you want your loved one randomized"
Yes

"What if it is dire"
All the more

"But it can't hurt"
🤦‍♂️
19. When you get people to make important sacrifices, there is always someone willing to come along and ask for more sacrifices that aren't
20. Some models were wrong. I am sorry to say.

They were.
They made a prediction based on what actually occurred and observed outcomes are outside all uncertainty or confidence intervals. They are not 'wrong' b/c things worked as intended. They failed to predict outcomes
21. There is always someone who will violate professional and ethical norms
statnews.com/2020/04/16/ear…
22. Drug companies won't run the right trials until we make them
reuters.com/article/us-gil…
23. It's important to calculate 95% CI correctly
24. The sensitivity and specificity of the blue check mark is .3 and .5, respectively
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