I posted earlier about the currently known state of the (limited) science on pediatric #COVID19 transmission. Of course, the question is how to apply that knowledge to schools. Many have already posted thoughtfully about this problem. Thread.
Harms of closing schools are enormous: e.g., loss of academic progression, worsening disparities, food insecurity, strain on working parents/impaired economy, delayed social/emotional development, social isolation, increased incidence/reduced reporting of domestic violence, etc.
But, harms of opening schools could also be substantial if they cause significant infections in staff/students, and/or increase community spread. @meganranney has done a great job outlining the stakes.
I largely agree with @AmerAcadPed – decisions must be local, contextual, flexible, but school is so important for child development, disparities, and the economy that we should prioritize SAFELY reopening them in person as fully as possible. aappublications.org/news/2020/06/2…
BUT if not done well, opening in person could be worse than just doing online to start. In person 2 days a week? Ugh. Virtually all the risk (esp to teachers), not much better for learning, and none of the benefit to working parents/economy.
If community prevalence high, I see no viable option but distance learning. So, first priority has to be to keep community prevalence low. Fortuitously, this is also the best long-term strategy for restarting the economy, keeping high risk population safe, etc. A virtuous cycle!
People, if that means that we keep everything else (restaurants, bars, shops, amusement parks, movies, churches, etc) closed or limited for longer, well then that’s what we should do. We have got to prioritize getting our nation’s kids back to school over eating in restaurants.
(not to mention dropping the prevalence of disease would save thousands of lives)
Where prevalence low, we should open all elementary and maybe middle schools fully: all students, 5 days/week. Use high schools, outdoors, school gym/library to maximize distancing. Aggressively cohort kids & stagger starts to minimize cross-exposure.
All learning, lunch, specials etc in one classroom. Teachers in face shields +/- behind Plexiglass so kids can see their face; kids in masks if they can tolerate. Frequent (weekly) pooled saliva testing if FDA approves. Revert to online teaching for 2 weeks if positive case.
Something like that would stand best chance of keeping most kids in physical classrooms for most amount of time. Is it ideal learning? No. But better than being at home and safer than just opening up for business as usual.
High school much tougher. Can’t cohort so easily, too much differentiation. Their risk of disease and spread more approximates adults. They each have more teachers: more staff risk. I am not optimistic about high school being able to fully reopen in person in that many places.
And I say this with great dismay, having 2 high school age kids who HATED online learning. But, at least they can do some independent learning, and working parents can leave them at home if necessary.
Lots of other countries have reopened schools. We can learn strategies from them. But, ultimately this is not about creative ways to distance at school. The way to keep schools open is to minimize spread in community. Isolate. Distance. Mask. Wash. Test. Trace. /End
• • •
Missing some Tweet in this thread? You can try to
force a refresh
Out today in @jama_current, the 2024 update to the #NIHRECOVER 2023 #LongCOVID index. Explainer follows. 🧵 1/njamanetwork.com/journals/jama/…
We use the same methodology as in 2023 to update the index, but now include data on >3,800 more people. See this 2023 explainer for details of the methodology, not repeated here. 2/n
What’s new? Two symptoms newly contribute points: shortness of breath (2 points) and snoring/sleep apnea (1 point). (Sleep disturbance was in the original but rounded to 0 points.) 3/n
#NIHRECOVER Adult is a cohort study of ~15k adults with/without #COVID, followed prospectively. They answer symptom surveys every 3 months and do additional tests yearly. 93% of cohort has been enrolled; this paper includes 9,764 participants. recovercovid.org
Main goal of this paper is to establish an expanded, working symptom-based definition of #LongCOVID for research purposes. Please note we do not propose this as a clinical definition right now pending further validation & refinement.
Have been too busy enjoying seeing people in person and seeing so much great research at #SGIM22 to have been tweeting, but what a great meeting. @nyugrossman was out in force /1
Med student Kyle Smith had a wonderful oral presentation on how we have developed a method of finding people on oral anti psychotics who haven’t had a1c testing (no pics cause I was so busy watching!) with @SaulBlecker /2
T32 trainee Rachel Engelberg had a great poster on incarceration and health outcomes /3
Fascinating article about how research into types and efficacy of traffic stops in multiple CT communities led to changes that both reduced disparities in stops and better targeted actual public safety issues. Some examples follow:
In Newington, 40% (1,608) traffic stops were for defective lights but found only 1 DUI. Dept switched focus to moving violations (defective lights ⬇️67%, moving violations ⬆️60%). Stops with DUI arrest ⬆️250%, from 18 to 63, and disparities substantially reduced: safer & fairer!
Hamden tried increasing stops for admin issues (lights, registration) to reduce crime in Black neighborhood but rarely found contraband (7%), no effect on crime, caused huge disparities. Switched to stops for hazardous driving: crime ⬇️5%, accidents ⬇️10%, found more contraband.
A lot of chatter about hospitalization "with" versus "for" COVID, implying current hospitalization wave isn't "real." NY state is going to start trying to report the distinction; UK already does. Some thoughts, with exemplar data. /1
1st, not so easy to tell. Our health system calls "for" COVID: patients with problem list or clinical impression of respiratory failure with hypoxia (various codes), or x "due to COVID" or COVID positive is the only problem. Specific, but likely not very sensitive. /2
That is, people who meet those criteria are very likely being admitted for COVID, but others will be missed (e.g. diagnosis pneumonia, sepsis, COVID-related stroke/heart attack/PE). So, likely an underestimate. Still, if used consistently, may be useful approximation. /3
Phenomenal preprint from South Africa on #omicron severity. Insanely fast analysis with multiple linked national datasets. Kudos to the authors. Results? You'll see headlines about reduced severity, but full story more complicated. My thoughts. medrxiv.org/content/10.110…
First off, methods. They link lab tests, case data, genome data and hospital data from across all of South Africa. (Wow!) They use a proxy for omicron (SFTF) and require Ct <=30 ("real" infection).
Then they run two comparisons: omicron vs not omicron Oct-Nov, and omicron Oct-Nov vs delta Apr-Nov, and compre frequency of hospitalization and of severe disease (=hospitalised + any of ICU/O2/ventilated/ECMO/ARDS/death). Outcomes assessed on 21 Dec (day preprint posted?!).