Is there some bizarre legal notion of causality at play here that the force used would have had to be such that it would have killed anyone, not just the actual person it did kill?
I'm willing to believe that the law traditionally has such a notion (or not -- hope some lawyers will help me understand) but if so it seems truly indefensible. We all have the preexisting condition of being mortal. We each have a different breakpoint for how much...
of a certain kind of abuse we can survive. It seems incoherent to have a standard that it's not murder if a different person would not have died under the same horrific abuse -- and I'm not saying that is true, only that this seems to be the defense's standard.
Seems from the replies like the defense holds no legal water. Would be nice if the journalists covering it emphasized that point.
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.@alisonannyoung has been one among the most active, persistent, and fair-minded reporters covering lab accidents in the US @USATODAY. This long piece makes the serious case for investigating poss lab origin for #SARSCoV2. usatoday.com/in-depth/opini….
This is not about conspiracy theories or China-bashing. This is about the basic principle, at least as old as Rev. Bayes and Sherlock Holmes, that when something unusual happens, you have to consider explanations that are also individually unlikely.
To be explicit, the @WHO mission's conclusion that a lab accident was unlikely was unjustified (as @alisonannyoung notes they are frequent) but even if true, global pandemics are also uncommon, so by definition the sequence of events leading to one do not happen all the time.
New preprint on estimating and Interpreting vaccine efficacy trial results for infection and transmission | medRxiv. With @rebeccajk13. Long discussion on applications to observational VE studies medrxiv.org/content/10.110…
tl;dr: Analyze separately cases ascertained for different reasons. Don't combine those found because symptomatic with those found by screening a cross section or by testing contacts.
In an RCT there are typically one of these (symptomatic cases, the primary endpoint in most COVID trials) or two (symptomatics and cross-sections). Symptomatics are incident cases and VE is properly measured by 1- incidence rate ratio. The VE measured is vs symptomatic infxn
Our paper on identifying and mitigating biases in epidemiologic studies of #COVID-19 is now out and is #OA . doi.org/10.1007/s10654…. Skillfully led by @AccorsiEmma
this project involved much of our group and many discussions arising from papers we were reading.
We consider the challenges of several kinds of studies: 1. Seroprevalence studies to estimate cumulative incidence
where a key challenge is representativeness of participants
@ZoeMcLaren Thanks for tweeting about this article. I'm going to leave the matching issue for another day, but I want to add a note of caution as one of the authors. We did not claim, and the data do not directly address, the reduction in total infections.
@ZoeMcLaren We used the word "documented infection" to highlight the fact that many infections may have gone undocumented, especially those not symptomatic. The documented infections is a mixture of symptomatic (probably most of them) and asymptomatic (probably a smaller fraction)
@ZoeMcLaren As a consequence, it is mathematically possible to have a big effect on documented infections but a smaller effect on total infections. As an extreme case (likely more extreme than the truth) suppose that symptomatic infections are detected with probability 90% and
@profshanecrotty Thanks @profshanecrotty for another super informative thread (ht @HelenBranswell for tweeting). My 2 cents is just to remember that the comparison between sero+ and sero- in the control arm in Novavax was not randomized and involved ~40 cases in each group.
@profshanecrotty@HelenBranswell Study was of course not designed to assess natural immunity, so kudos to the scientists for reporting these important data, but caution in interpretation. Several reasons to expect bias in observational seroprotection studies like this dash.harvard.edu/handle/1/37366…
@profshanecrotty@HelenBranswell In particular, those who got infected before (sero+) are likely still at high risk for subsequent infection(due to job, housing, use of transport, other persistent factors), leading to noncausal positive association betwn prior and future infection (confounding).