Share this page!

Marc Lipsitch Profile picture
Twitter logo
15 Mar, 4 tweets, 3 min read
CONGRATULATIONS DR. @AccorsiEmma defending her PhD with flying colors today. Thanks especially to @chuttenh who supervised much of the work linking microbiome and #epidemiology #EpiTwitter and to committee members @SHaneuse and @BillHanage @HarvardEpi @CCDD_HSPH @HarvardChanSPH
Two of her thesis papers have been published. genomebiology.biomedcentral.com/articles/10.11…
and link.springer.com/article/10.100…
Another baking to emerge soon.

• • •

Missing some Tweet in this thread? You can try to force a refresh
　

Keep Current with Marc Lipsitch

Marc Lipsitch Profile picture

Stay in touch and get notified when new unrolls are available from this author!

Read all threads

This Thread may be Removed Anytime!

PDF

Twitter may remove this content at anytime! Save it as PDF for later use!

Try unrolling a thread yourself!

how to unroll video
  1. Follow @ThreadReaderApp to mention us!

  2. From a Twitter thread mention us with a keyword "unroll"
@threadreaderapp unroll

Practice here first or read more on our help page!

More from @mlipsitch

Marc Lipsitch Profile picture
28 Feb
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
Read 18 tweets
Marc Lipsitch Profile picture
25 Feb
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.
including @XuetingQ @EvaRumpler @LeeKShaffer @rebeccajk13 Ed Goldstein @NeneRiehus from @CCDD_HSPH with special guests @mats_julius and @mugecevik .
We consider the challenges of several kinds of studies: 1. Seroprevalence studies to estimate cumulative incidence
where a key challenge is representativeness of participants
Read 17 tweets
Marc Lipsitch Profile picture
25 Feb
@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
Read 6 tweets
Marc Lipsitch Profile picture
31 Jan
@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).
Read 4 tweets
Marc Lipsitch Profile picture
31 Jan
Reupping this. Existing vaccines may well have been unable to get us to the herd immunity threshold before the variants made things harder. Now more unlikely. But if we can identify (hard) and vaccinate (harder) the most vulnerable it will make continued spread less destructive.
ccdd.hsph.harvard.edu/2020/12/17/cov…
I haven't double-checked @roby_bhatt 's numbers but there is evidence so far that the vaccines are highly effective against the most severe forms of COVID, even in South Africa where most cases were the local variant.
Read 4 tweets
Marc Lipsitch Profile picture
20 Dec 20
The @CDCgov ACIP move toward priortizing frontline workers is premised on "only slightly" more deaths compared to prioritizing by age &/or comorbidity. But that finding depends on the vaccine blocking transmission very efficiently, which we don't know.
In my opinion prioritizing by risk of death is the most robust strategy in the sense of being optimal or near-optimal whatever we find out about transmission blocking and the like. #ACIP
Notwithstanding misinterpretations and deliberate trolling from many the last few days, I have been saying for some time that in my view the most lifesaving strategy, and likely the one that will return us to functioning fastest, would be
Read 5 tweets

Did Thread Reader help you today?

Support us! We are indie developers!

This site is made by just two indie developers on a laptop doing marketing, support and development! Read more about the story.

Become a Premium Member ($3/month or $30/year) and get exclusive features!

Become Premium

Too expensive? Make a small donation by buying us coffee ($5) or help with server cost ($10)

Donate via Paypal Become our Patreon

Thank you for your support!

Follow Us on Twitter!

Like this author's thread?

Get emails when @mlipsitch has new unrolls!

Check out other threads from @mlipsitch!

Read all threads by @mlipsitch