Leora Horwitz Profile picture
Sep 29, 2020 10 tweets 4 min read Read on X
My periodic reminder that WE ARE NOT GOING TO SOLVE #COVID19 THROUGH NON-VACCINE HERD IMMUNITY. For those who need more convincing, thread follows.
First, we have NEVER gotten to herd immunity without vaccine for a virus. If you are over 40, you almost certainly had chicken pox as a kid. Until vaccine in 1995, we had >4 million cases/year (& ~125 deaths) - about the same as how many kids are born each year.
In other words, EVERY NON-IMMUNE PERSON (i.e. every kid) STILL GOT IT, even though antibody rates among adults were 90-95%, and immunity is near lifelong. With circulating virus and no vaccine, most without immunity will eventually catch it even if the pop is largely immune.
Vaccines help with herd immunity (non immune people not getting sick) both because they make people immune AND because they do so without them first getting sick and spreading the virus. That helps reduce the amount of virus in circulation.
And even then, the non-immune are still vulnerable - witness big recent outbreaks of measles, mumps from letting up just a little in vaccination. (Yes, measles is more contagious than covid. But we have 10000x fewer infections and way higher immunity.) cdc.gov/measles/cases-…
Second, my guess is that natural #COVID19 immunity won’t be as durable as, say, chicken pox immunity. At least, it isn’t for seasonal cold coronavirus. So the number of non-immune people is likely always to be high even with widespread transmission. nature.com/articles/s4159…
Third, as @CDCgov recently reminded us, even if we thought it would work, we are crazy far away from widespread #COVID19 immunity - probably <10% nationally. cdc.gov/coronavirus/20…
In NYC, with highest rates of immunity in the nation, we are having an outbreak right now in the very communities that were hardest hit in the spring and that have even higher immunity rates than the rest of the city. ny1.com/nyc/all-boroug…
And finally and most importantly, trying to get to natural herd immunity - even if it were feasible - would require a gut-wrenching number of deaths and long term complications. At least 800k deaths at a conservative 0.3% IFR. We can not become a society that welcomes that.
So, if not fatalistic resignation and hope for natural immunity, what options do we have? Care for each other: mask wearing, avoidance of indoor crowds, redesign of work, making every effort to keep schools open. It’s not sexy, but it will save lives as we wait for vaccine.

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More from @leorahorwitzmd

Dec 19
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
Read 18 tweets
May 25, 2023
1st #NIHRECOVER adult cohort results are out today in @JAMA_current, proposing an expanded working definition of #LongCovid (aka post-acute sequelae of SARS-CoV-2 [PASC]). Led by @tthaweethai, this is a dense paper with a ton of results. Buckle up! 🧵
jamanetwork.com/journals/jama/…
#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.
Read 24 tweets
Apr 9, 2022
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
Read 4 tweets
Jan 30, 2022
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.
Read 4 tweets
Jan 4, 2022
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
Read 8 tweets
Dec 22, 2021
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?!).
Read 18 tweets

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