66% of adults had at least 1 symptom during the acute phase (first 2 months) of diagnosis of #COVID-19.
I’ve highlighted the symptoms experienced by at least 10%. Note that some of the less common symptoms are quite debilitating though (e.g., 9% w/lung pain).
2/12
If you had a #COVID symptom initially, what are the chances it persists beyond 2 months? See 2nd column, green highlights emphasize those enduring among >10%.
Many of the initial symptoms endure in about 20% of ppl. Russian-roulette like odds.
3/12
If you know someone with a new #COVID infection/reinfection who is experiencing symptoms, dive deep into that particular row.
For example, while memory loss is rare (4.3%), it’s the most enduring symptom beyond 2 months (40% persisting).
4/12
If you had an acute #COVID symptom, what were the chances it would resolve within 1 year?
See authors’ BLACK text.
I’ve also added a column with the chances a symptom persists (ORANGE text). Balanced framing. 🙂
5/12
Now, let’s manually combine the acute (<2 month), near-term (>2 month), and long-term (>1yr) #COVID data into one figure. Silly JAMA. 😊
Some symptoms present at 2 months largely fall off. Others persist in >25% (palp, art pain, att/conc, memory, sleep).
6/12
Overall, the number of #COVID-19 symptoms each person experiences diminishes over time.
Caveats: Initial infections were all pre-vax (call for hope), but also pre-omicron and before many reinfections (call for caution). Note, %s are among those who had an acute symptom.
7/12
Older adults, women, and ppl w/>5 acute symptoms were more likely to have persistent #COVID symptoms at 1 year.
Higher BMI = more persistent symptoms. Bad for the U.S.
8/12
An Appendix figure models the typical time to resolution of a #COVID symptom (crude estimate, varies by symptom & individual).
I added the blue line, which suggest about 5% would experience symptoms at 3 yrs. That's >16 million Americans. Very rough estimate. #recession
9/12
Model of time to COVID-19 symptom resolution by subgroup.
#COVID has persistent effects for those with a history of cancer or who had a bad acute case. Either we have a critical gender health disparity or men are trying to walk off heart palpitations. 🤔
An average of 10% of adults were experiencing long-term symptoms from #COVID-19.
The authors note that this is a critical public health problem b/c of the high incidence of infection. They are perhaps too optimistic. We have a high incidence of REinfections.
11/12
Limitations: The COVID-19 initial infections were all before the vaccine era, mostly before reinfections, and pre-omicron.
You cannot have long-term data AND up-to-date world events. Stay cautious until the long-term data are optimistic.
12/12
By the way, feel free to share any of this on other platforms (Mastodon, Discord, TikTok, Myspace, or even Facebook) and with family/friends. I tried to annotate the figures in a way that it would be relatable to a general audience. Where I failed, ask questions.
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1. They compare same-day PCR against self-administered/interpreted rapid tests.
For most ppl, that's not reality. It's RAT today or PCR result in 1-3 days (or do both).
A fairer comparison would be a RAT today versus a PCR yesterday (since you'd have to wait for results).
2. They excluded 13% of the sample who were "confirmatory testers" (weird term) -- basically, people who had just tested RAT+ and were coming in for a PCR.
Basically, they excluded the people for whom the test easily worked. Drug trialists pull this stuff all the time.
YES. I ordered a 6” x 6” sheet with >50 monotone #cancer ribbons from @stickermule. Cost about $20. Price goes waaaaay down the more you order. Comes with free hot sauce for some reason.
I made a new graphic representing my current gist-level representation of the #SwissCheese Model of #COVID mitigation.
In your mind, how do you organize the categories differently? Is there something else you prioritize? 1/5
My mental model of COVID mitigation differs from others in that it gives more weight to secondary and tertiary prevention.
The less the Western world focuses on the first 8 slices of cheese, the more we will need to focus on the final 2-3 slices. 2/5
In my #SwissCheese model, I debated how many slices to devote to masking & clean indoor air. Huge weapons. Masking is simple but w/plenty of nuance (mask selection, distribution, fit, duration). Clean air includes ventilation, filtration (CR boxes, HEPA), UVC, fluid dynamics 3/5
Our new pre-print shows that people are excited to use N95s during COVID surges when given them for free w/helpful information on their evidence & how to use them. 1/ psyarxiv.com/f76vw
You might remember when we posted about the study back in December!
I hope you find the results useful. We tried to make the figures relatable, even if you're not reading science articles every day. Please let me know if you have questions! 2/
We gave out 2,500 #N95 masks in 5 packs to our racially & socioeconomically diverse community. Many used N95s for the 1st time. People treated us like we were giving them kidneys. So grateful!
97% used at least 1 N95 & 40% used all 5 within 1-mo!
Know someone having a baby soon? CONGRATULATIONS! 🍼🍼🍼
As hospitals drop universal COVID protections, these are my top 7 tips for protecting unmaskable un-vaxable newborns from #nosocomial (hospital-acquired) COVID.
What did I miss?
THREAD of Top 7 Tips 🧵
Tip #1 – Determine your #mask rules. Some parents require staff to #N95. Compliance would vary by region/hospital. Prep for what you’ll say if staff don’t comply.
With our newborn twins, we supplied medical staff w/free N95s & tests. Nobody wanted N95s; 1 took a #RAT. 🤣
Tip #2 – U.S. hospitals SHOULD have excellent ventilation (air cleaning) by reg. But HVAC repair doesn’t have a CPT code. Many of my best & worst air quality readings are from hospitals.
Consider buying a #CO2monitor, read on that hashtag, & follow @joeyfox85 for basic tips.
The study gave people nasal irrigation and compared it to CDC data on hospitalization and death rates.
Not everything must be an RCT, but the purpose of an RCT is to compare two equivalent groups so that the observed differences can be attributed to the treatment.
Since this is not an RCT, the people in the nasal irrigation could have easily differed from people in the CDC normative sample.
Specifically, people who sign up for studies are often less ill. If they are less ill, they see better outcomes regardless of the "treatment"