24h update. They don't know what is going on. On the upside, I have learned the fascinating details of @FedEx corporate structure, that the people at @FedExHelp are helpless if you are trying to deliver to a home. Obviously it is my job to route the problem to the right person.
Since for them to do it is quite challenging. Probably requires computers and stuff, and who would expect them to be good at that?
Their customer service rep wrote: I have advised the management team on the Express side that is responsible for the pick up and the Home Delivery side that is responsible for transporting and delivering the package of the issue so it can be handled as quickly as possible.
From giving advice recently to a friend who was symptomatic, got tested and was told to expect a 3-5d delay, I've come to realize a gap in our prevention approach. The advice on preventing transmission if you are infected is mainly provided through contact tracing.
That's good but it's not enough. Especially with these kinds of delays, it could be almost a week from the time someone feels the need to get tested (symptoms, poss contact, whatever) until they might get a call from contact tracers if positive.
In the interim, if they were truly a SARS-CoV-2 infection, they would likely have passed through their peak period of infectiousness, the 4-6 days or so immediately before and after symptom onset we believe.
The @aier, the Libertarian think tank on an estate in Massachusetts that offered @MartinKulldorff@SunetraGupta and Jay Bhattacharya a comfy country retreat to write the Great Barrington Declaration clearly states the contents of same:
It advocates MAXIMIZING infection among the allegedly low-risk. aier.org/article/lockdo…. They should ask for their money back from Dr. Bhattacharya who argued today that it recommends trying to slow the spread. It advocates trying to speed it, as is clear from GBD's text.
This is just simply saying one thing when trying to influence policy and the opposite when trying to deflect criticism from scientists.
I think @realDonaldTrump and @SWAtlasHoover were committed to a policy with no scientific basis and would have dragged the country there regardless. But GBD provided a veneer of respectability for this deliberate subversion of public health
He takes a commentary I wrote with @ted_h_cohen about Listeria -- a bacterial disease we get typically from food -- that suggested (citing another paper -- this was not original research) that a lack of herd immunity to listeria could be leading to increased case numbers.
(of symptomatic Listeria infection). It also mentioned the idea that rubella vaccines used in the wrong way could increase severe (congenital) rubella through modest amounts of herd immunity that delay but do not prevent infection, increasing its incidence in pregnant women.
This is just crazy. Mainstream experts have been trying to get through with almost no success. But take an out-there position and you get access. Of course take extra precautions for the most vulnerable. But don't relax everything else before evidence these precautions work.
The argument is incoherent if you don't do low-cost low-inconvenience things like universal masking. Surely any rational strategy uses low-downside strategies to reduce transmission in the whole population while shielding the vulnerable.
Two of these scientists, @SunetraGupta and @MartinKulldorff, have long been my friends. But I think they are dead wrong without a demonstrated plan for how such shielding would work. There is no good example in a dense western country.
Don’t quite understand how source thinks “foot on the neck to make them go go go” is ok to say in 2020 or even, insensitivity aside, makes sense.
Also don’t know how @HHSGov Spox Mango can say with certainty what the vax trial results will be when they are still not unblinded. Every time someone corporate or govt says something like that they should be asked how they know.
usually agree with both @StevenSalzberg1 and @nataliexdean. In this case agree with the cautious view. Even if safety were known (which I don’t think it is for this) RCT r really important for efficacy. Alternatives, which both @nataliexdean & I work on, are full of pitfalls.
The uncertainty stated on this site is purely statistical uncertainty assuming data and model are accurate. This _vastly_ understates uncertainty. In many places, case confirmation is delayed dramatically (weeks) & variably, but this assumes 5 days from infection to confirm'n.
Changing testing practices mean changing proportions of cases ascertained and thus changing estimates of cases and R separate for reality. No correction or acknowledgment of uncertainty.
As one colleague emailed me facetiously "Can you please forward this to John Snow?"
Notwithstanding that economists historically favor different techniques for causal inference from observational data, making such inference is the goal of much observational epidemiology (not all -- sometimes we aim for description or prediction) amstat.tandfonline.com/doi/full/10.10…
@DiseaseEcology@US_FDA@rebeccajk13@Steve_Bellan I may not be explaining well, and it's a subtle thing I'm trying to say. I think it is important to know effect on serologic infection. My point is that there may well be a vaccine that 1) makes disease less likely/severe, 2) makes shedding much less and 3) permits seroconversion
@DiseaseEcology@US_FDA@rebeccajk13@Steve_Bellan Such a vax would look good on the disease endpoint (esp if they use our approach or similar to correct for missed infections), but null on the infection endpoint. This vaccine would be very good for herd immunity (and direct protection) but the analysis might miss that fact.
I agree with a lot of this thread. Primarily - in any time, but especially these days, it is inspiring to see a government agency release data, get bad press, and respond by releasing more data and asking for expert input.
Also impressive was the evidently hard-working, experienced, resourceful team of people trying to make this program a success, and the consistent effort to confront unsatisfactory numbers with feasible means for improvement. Given mission to make TTI successful, very impressive
On its face (and maybe even after some careful consideration), this article is concerning. The First Covid Vaccines May Not Prevent Covid Infection a.msn.com/00/en-us/BB15t…
It points out as as been noted before blogs.sciencemag.org/pipeline/archi… that the Oxford vaccine in macaque studies does not prevent (or even visibly reduce) the nasal shedding of virus RNA -- infection and perhaps contagiousness are the same, but vaccinated macaques don't get sick
My conclusion is that we should be trying to work together to fight injustice, reduce transmission, and where possible resume some normal activities, including protests.
Any effort to assign numbers to one activity is full of assumptions, including the assumption that R stays constant over time -- something we can change if we choose by making greater efforts to suppress transmission.
I offer the comparison simply to point out the risk of trying to assign responsibility to one decision in the face of all the dependencies -- consequences of infectious disease cases are dependent on the transmission environment, which is in our control.
First on the math: this is critically dependent on the value chosen for "R~1" because in a branching process with R<1, the ultimate number of cases eventually caused by one case is N=1/(1-R) -- the sum of a geometric series with a=1 and r=R. Thus for R=.95, N=20.
But R near 1 was arbitrarily chosen to be 0.95, and this has a huge influence on results. with R=0.9, N=10, so half as many cases / deaths; with R=0.98, N=50, so 5 times as many. This number is probably the most sensitive -- and least supported -- input into the calculation.
In light of the retractions it's worth remembering: Peer review is one imperfect part of the at-least 4-part safety net that keeps science functioning. Layer 1 is basic ethics among investigators: don't make up or misrepresent data.
Layer 2 is related to but distinct from layer 1. Try your best to be the one who finds the limitations or flaws in your findings and esp interpretations, before anyone else does. Fix flaws / limitations if you can; highlight them in Discussion if you can't bostonreview.net/science-nature…
Layer 3 is transparency -- to the extent practicable, make code, data and other resources for replication available to others. This is costly -- sharing usable code is time consuming, and trades off with other forms of productivity. "Open Science" is a good principle, but costly.
@ID_ethics@AlexJohnLondon Gabriela Gomes is the one who has been exploring this idea theoretically for a decade +, and a combination of a chat with her and a chat with Gael Kurath @USGS at a conference led me to work with both of them, @ecoevo_kel and Andrew Wargo @VIMS_News et al. on this
It's getting increasingly hard to take John Ioannidis's "let's keep to the science" line seriously. My postdoc advisor Bruce Levin said "What distinguishes science from the rest of academia is that in science, you can't predict the conclusion from the name of the author."
I don't actually agree with that as a literal statement (and offered a "proof" of why it's wrong 10y ago at Bruce's 70th birthday. But it gets at a deep truth that serious scientists keep seeking evidence that they are wrong so they can get righter.
This is quite a run of papers saying "see, my priors were right" from Dr. Ioannidis. Punctuated with occasional appearances in front of such truth-seeking bodies as Laura Ingraham's show and the Arizona House of Representatives.
Two preprints recently make an important point: for any infection, including COVID-19, it is possible that herd immunity can be accomplished with more than 1/R0 of the population still susceptible. The first was by Gabriela Gomes et al. @LSTMnewsmedrxiv.org/content/10.110…
They are complementary. Both consider the impact of individual heterogeneity. Gomes et al. consider a well-mixed model with individuals varying in their rates of exposure or probabiity of infection given exposure (susceptibility).