Very detailed and helpful paper. Upshot:
- found a small (non-significant) *decrease* in full vax rates in Ohio post lottery
- found a small (non-significant) increase over all lottery states
Agree: "unlikely there are hugely positive or hugely negative effects"
As a non-expert, I like the preregistration & use of synthetic control. Some remaining questions
- is theirs the right counterfactual? (see thread)
- is the proper outcome to measure full vax, as they did, or 1 dose (I'd actually think 1 dose is the more lottery-relevant outcome)
Disappointingly, the quote tweets of the paper mostly seem to read "lol, vaccine lotteries didn't work"
People should read the whole thread & embrace the acknowledgement of substantial uncertainty that the authors recognize! (I know this runs contrary to twitter norms.)
My guess is we'll soon see many papers assessing vaccine lotteries, using different counterfactuals (which is good!).
Some will find + effects, some fail to reject a null hypothesis, some may even find - effects.
Similar to challenge of assessing if min wage affects employment
Also, as with the min. wage debate, the way people--especially lay popularizers--interpret evidence will probably end up being driven heavily by their prior hunches, and/or their normative beliefs about vaccine lotteries' acceptability or lack thereof
Something else that would be really interesting: comparing the vaccine lotteries that at first glance appear to work well vs. not work:
"77% of white adults who want a shot have gotten one, compared with 60% of Black adults and 55% of Hispanics who want one."
Not everyone who WANTS a vaccine has been able to get one. "The survey suggests that vaccine access is at least as big of a problem as vaccine hesitancy."
"The racial gap persists across income levels, but is widest among people making less than $50,000 annually: 72 percent of white adults in that group who want a shot have gotten one, compared with 57 percent of Black adults and 47 percent of Hispanic adults in that income range."
"Otis Rolley...of The Rockefeller Fdn's U.S. equity and economic opportunity initiative, said the emphasis on vaccine hesitancy puts the burden on individual people rather than on institutions that should be providing information about the shots and making it easy for people."
COVID-19 remains a pandemic that causes serious, widespread, not fully understood harms
Universally stopping an efficacious COVID-19 vaccine should only be done after seriously weighing the harms of stopped access against side effects of the vaccine
ACIP didn’t do this
2/12
ACIP justified not rigorously weighing harms/benefits b/c other vaccines “are available”
Not just MDs but:
- health econ (@healthecon_dan)
- behavioral health (@abuttenheim)
- literally wrote the book on "nonmaleficence" (Jim Childress)
- tribal health (@echohawkd3)
et al
2/6
In contrast, every #ACIP voting member (exc 1 community member) is a MD/DO/RN. Couple w/a MPH. But no health econ. No ethicists. No behavioral sci. No tribal health experts.
Great group for indiv patient care & virology expertise
We have enough supply that we could send MI more vaccines. Only Jeff Zients’ bizarre burden-insensitive conception of “fairness” prevents this
Or we could let MI extend dosing intervals by 2 weeks to get first doses to more people
But apparently sticking w/an ethically ungrounded Trump Admin holdover policy of giving vaccines only proportional to population (which many states aren’t doing intra-state), & an arbitrarily selected dosing interval, is more important than letting people in MI protect themselves
For those following #ACIP vaccine prioritization debate - proposal to have 75+ alongside frontline workers in phase 1B is interesting, and different from prior discussion. But there are still pitfalls with any age cutoff, whether 75 or 65, as I explained in a comment to ACIP /1
Down Syndrome deaths are disparately high and happen before 75. 54%, 61%, and 69% of Black, Hispanic, and AI/AN deaths (respectively) happen before 75. I haven't seen US data on income x age at death, but a similar gradient is plausible, and may help explain the race data. /2
So I continue to think #ACIP should encourage states & localities to look at overlapping risk factors like housing+age as LTCF priority did and @CDCDirector suggested, rather than using age cutoffs that sweep in ppl at very different risk & exclude some