@CT_Bergstrom @jsm2334 Certainly this kind of bias merits consideration. I think the particular figure cited in that table is an example of Simpson's paradox, which is a special type of confounding.
@CT_Bergstrom @jsm2334 For those new to these terms, confounding is just the problem that (in this case) vaccine is not randomly distributed in the population, so the vaccinated have different risks from the unvaccinated for reasons other than their vaccine: in this case, age.
@CT_Bergstrom @jsm2334 Simpson's paradox is an extreme form of confounding in which a combined analysis for two groups of people gives an unusually misleading estimate, relative to the (more) accurate estimate for each group individually.
@CT_Bergstrom @jsm2334 As en.wikipedia.org/wiki/Simpson%2… exemplifies, defining Simpson's paradox precisely is hard, so I'd prefer to just call it confounding, which, again, it is, though it can only happen under certain circumstances
@CT_Bergstrom @jsm2334 For a clear and precise discussion of the relationship see academic.oup.com/ije/article/40… by the ever clear-headed @_MiguelHernan @CAUSALab
@CT_Bergstrom @jsm2334 @_MiguelHernan @CAUSALab I don't think that this is the explanation for the most striking result, on slide 7 of this deck from @IsraelMOH which I shared recently as it is hard to find online gov.il/BlobFolder/rep…
@CT_Bergstrom @jsm2334 @_MiguelHernan @CAUSALab @IsraelMOH that result is that Jan vaccinees, over 65, for severe disease, have a VE of 55% or so, after adjusting for two key confounders: week and 10-year age group (up to 85+), as well as sex (not much of a confounder)
@CT_Bergstrom @jsm2334 @_MiguelHernan @CAUSALab @IsraelMOH So to invoke confounding by age, you'd have to assume that the residual confounding within these age groups is very large. Similar result for Feb (60% point estimate) and higher VE for the March vaccinees in that age group (who are probably quite unusual given the rollout speed
@CT_Bergstrom @jsm2334 @_MiguelHernan @CAUSALab @IsraelMOH This is consistent with what you'd expect if waning of immunity to, combined with Delta, is causing a drop in VE to severe disease.
@CT_Bergstrom @jsm2334 @_MiguelHernan @CAUSALab @IsraelMOH This drop was not seen as far as I know in the data on infections pre-Delta (up to mid-June), certainly not up to early April in a very similar analysis by the same group of people at MOH thelancet.com/journals/lance…
@CT_Bergstrom @jsm2334 @_MiguelHernan @CAUSALab @IsraelMOH If indeed this is a new finding (ie only in the late June and after data) it also doesn't make much sense to me to think this is due to depletion of susceptibles bias (which is one of my favorite candidates and one I've written a lot about) ....
@CT_Bergstrom @jsm2334 @_MiguelHernan @CAUSALab @IsraelMOH because the drop came during a lull in incidence, while depletion of susceptibles requires incidence medrxiv.org/content/10.110…
@CT_Bergstrom @jsm2334 @_MiguelHernan @CAUSALab @IsraelMOH So I'm all in favor of discussing potential biases that could create the observations we've seen, but I would say in this case I don't think that confounding or depletion of susceptibles bias is a full explanation for the observed decline which is concentrated in the
@CT_Bergstrom @jsm2334 @_MiguelHernan @CAUSALab @IsraelMOH earliest-vaccinated, oldest group in the Delta era
@CT_Bergstrom @jsm2334 @_MiguelHernan @CAUSALab @IsraelMOH I'll also mention that along with many in Israel I was uncertain about the early indications of waning immunity to infection because of possible differential testing, but I don't think that could explain observed reduced VE for severe disease, a well-ascertained outcome
@CT_Bergstrom @jsm2334 @_MiguelHernan @CAUSALab @IsraelMOH Key thing is for the analyses to be public so we can discuss possible explanations for the observed data and ways to distinguish among them. Hopefully will have a robust discussion and pressure-test these findings; current views, could change in light of new evidence or analysis

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More from @mlipsitch

13 Aug
As often happens, the headline is too simple for the more subtle message of the article washingtonpost.com/outlook/corona…
The article's main point is unarguable: "we cannot control the delta variant by maximizing the immunity of only a segment of the population."
But some (incl me) have thought the main goal of vaccination all along should be to defang (make less harmful) not defeat (eliminate) the virus.
Read 7 tweets
20 Jul
At the risk of boiling down too much and certainly losing some detail, one way to summarize this wonderful thread is that when we think about vaccine effectiveness, we should think of 4 key variables: 1 which vaccine, 2 age of the person, 3 how long after vax, 4 vs what outcome.
We've been using the simple view that the major vaccines in use in the US/Europe are possibly less effective against infection/symptoms when a variant is involved, but remain highly effective against severe outcomes. Published data so far support this view.
To be more precise, we would say "so far in the general population, up to about 6 months after vaccination, the vaccines have held up against severe outcomes even from Delta, though there is some evidence from Israel, UK, and Canada of declines in effectiveness vs infection."
Read 14 tweets
7 Jul
Different approach from many other VE studies, following HCW vaccinated vs unvaccinated, tested when exposed to a case, to assess VE against infection given exposure, consistent with our recommendations in sciencedirect.com/science/articl…
Also looked at infectiousness (proxied by Ct). Take home messages: fully vaccinated 65% (45-79) protected against infection given exposure. This is lower than other estimates of symptomatic or arbitrary mix of symptomatic and other cases, as expected.
Read 8 tweets
13 Jun
Now out with @rebeccajk13 Interpreting vaccine efficacy trial results for infection and transmission authors.elsevier.com/sd/article/S02…
funded in part by #SeroNet
In which we show that earlier work by Rinta-Kokko et al on interpreting prevalence measures for vaccine efficacy generalizes to the COVID-19 case pubmed.ncbi.nlm.nih.gov/19490983/ and that the odds ratio for PCR+ in vax vs unvax persons swabbed at random
is under reasonable assumptions a lower bound on the vaccine's effect against transmission, the critical quantity for herd immunity that combines reduced risk of acquiring and shorter duration.
Read 11 tweets
25 May
washingtonpost.com/politics/2021/…. A key point: lab leak does not imply manipulation and manipulation does not imply ill intent.
I disagree with @SenTomCotton on many many things but this set of tweets quoted in the article lays it out correctly
In contrast this statement is illogical “However, since we observed all notable SARS-CoV-2 features, including the optimized RBD and polybasic cleavage site, in related coronaviruses in nature, we do not believe that any type of laboratory-based scenario is plausible.”
Read 4 tweets
13 May
This tweet got me thinking again about a topic that's been on my mind for the last several weeks and throughout the pandemic. In principle I fully agree with @flodebarre that people should evaluate arguments for logical soundness and consistency with facts, not who makes them.
But many people have asked me (most recently @AmyDMarcus) how thoughtful people should know whom to trust in getting information (science) and advice (for personal actions) and opinions (about policy) on a topic like COVID
Consistent with @flodebarre's tweet, my first response was you shouldn't trust anyone intrinsically, but should trust good arguments. As a scientist, that is how we are (or should be, there is still too much hero worship in our field) trained.
Read 28 tweets

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