THREAD: 19 Tips for a DIY mask fit test to reduce your risk of #COVID19.
H/t @amandalhu & @__philipn__
What did I miss?
Fit-testing Tip #1: Keep it Simple.
Get a nebulizer (usually $30-40) & some 3M FT-32 Bitrex solution ($24).
Fit-testing Tip #2: Taste the Failure.
Use the nebulizer to spray the bitrex solution (barely visible). Breathe through your mouth. If you taste it, there’s a mask leak.
"It’s not rocket science," as @CorsIAQ likes to say.
Fit-testing Tip #3: Spray at Problem Areas.
I use the nebulizer to spray bitrex fit-testing solution all around the nose bridge, by both cheeks, and under the chin.
You’ll quickly taste a leak.
Fit-testing Tip #4: Go Hoodless.
Do what ya wanna, but for DIY fit testing, the method above works fine w/o the hood.
I bought a hood – overpriced! Plus, the goal is to get as many people as possible fit testing. Many would find them off-putting or feel claustrophobic.
Fit-testing Tip #5: Don’t Test around Maskless People/Animals.
After reinstalling a new filter on my Flo Mask, I did a fit test while my son was having a bath. He started coughing. For a moment, I worried he had COVID.
Put 2&2 together, cranked up the HEPA & gave him juice.
Fit-testing Tip #6: Have a Beverage Handy.
You’re testing for leaks. You will find some. The bitrex tastes horrible, like licking a rubber band. Have some OJ or a soda ready for after you’re done.
Fit-testing Tip #7: Share the Wealth.
Supplies cost $60 total. It takes hardly any fit-testing solution to test, so offer the opportunity to friends, family, or co-workers. You’ll help protect their health & better cocoon yourself from illness too.
I tested all 3 of my favorite N95s: the Aegle flat-fold, 3M Aura, and 3M VFlex. I could pass a fit test with each, some caveats noted later.
Fit-testing Tip #9: Select the Best N95 for YOUR Face.
If you have several masks, test and compare. Go with the winner.
For me, the 3M VFlex held up most robustly. The 3M Aura needs to be readjusted if I talk to much. The Aegle is harder to seal at the nose.
Fit-testing Tip #10: Get your best N95 to fit better.
Although the 3M VFlex most easily & robustly passed fit-testing, I realized I hadn’t been pulling it back far enough under the chin (@jasmith_yorku). I also learned how best to adjust the nose piece to get the best fit.
Fit-testing Tip #11: Elastomeric Masks beat N95s.
I tested 6 elastomeric masks. I hate the word “elastomeric.” It’s alienating.
They’re just non-disposable, reusable masks. Great seal. All outperformed my disposable N95s when testing the limits.
Fit-testing Tip #12: Get your Elastomeric to Fit Better.
Straps can wear out or loosen over time! Filters also need to be reinstalled properly. Use fit testing periodically and when installing new filters to confirm no leaks.
Fit-testing Tip #13: Procedure Masks are a Joke.
Fit tested, fails in <0.5 sec. Air flows to the path of least resistance. Gaps poorly guard against inhaling/exhaling viral-laden aerosols.
Everybody should be using #BetterMasks, paid w/public funds.
Many KN95/KF94 masks are counterfeits, especially on Amazon. Even the city of New Orleans distributed fakes “N95s” last winter. Use fit-testing to check whether a mask is legitimate. thelensnola.org/2022/01/14/cit…
Fit-testing Tip #17: Facial Hair is a COVID Risk.
My disposable N95s start to fail fit-testing after about 2.5 days w/o shaving. My elastos make it about 3.5 days. If you’re clean-shavin, keep it clean.
If you prefer facial hair, use a mask-safe cut, or know the risk.
Fit-testing Tip #18: DBAA.
No, fit-testing is not REQUIRED for masks to “work.”
It’s about improving safety on the margins (5-10%) and especially for the most dangerous prolonged contexts. osha.gov/laws-regs/stan….
FYI, I have no conflicts of interest, such as investing in one of the companies mentioned.
I’m a psychologist just trying to help people understand COVID mitigation tips I didn’t know a year ago so maybe you can reduce your lifetime number of cumulative SARS-CoV-2 infections.
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You probably saw this week's NEJM article on #LongCOVID. We did a special section on it in this week's PMC COVID-19 Forecasting Report (pgs 6-8).
THREAD of tables. 🧵🔢
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Details:
Our model continues to provide estimates of Long COVID cases that will ultimately result from each day’s infections.
We provide a credible interval that 5-20% of infections will result in Long COVID.
This week, Al-Aly and colleagues reported in the New England Journal that in the more recent era of the pandemic, vaccinated individuals have a 3.5% chance of developing Long COVID from a particular infection.
They focused on medically documented new serious health conditions. We continue to view 5% as a useful lower bound for two reasons.
Long COVID chances were higher in unvaccinated individuals in their study, and there were no analyses based on time since last vaccination.
With many Americans still unvaccinated and many not vaccinated in the past year, the true estimate for a 2024 infection could well surpass 5% for a medically documented new serious health condition.
Moreover, Long COVID is a heterogeneous condition, and many cases are likely not medically documented, especially at the less debilitating end of the spectrum.
The following tables show the risk of ever developing Long COVID from an infection assuming 3.5%, 5.0%, and 20.0% rates.
These statistics document the seriousness of Long COVID with Americans getting infected nearly once a year (average of 12.5 months by our estimates).
However, it is also important to know that some effects are enduring, and others more likely to improve, so many with Long COVID will improve.
Many will also have repeated bouts of Long COVID, likely with different phenotypes.pmc19.com/data/
If you assume 3.5% of people get Long COVID per infection, the risk grows sizably with reinfections, which are happening nearly once per year. Avg of 9 infections/American the next decade.
In the previous Tweet, we note how 3.5% is an obvious underestimate.
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Based on that 3.5% estimate, a more realistic low-ball estimate of serious long COVID is 5-7%, given that not all serious new health conditions are documented in medical records & rates are higher among those unvaxxed or not recently vaxxed.
Transmission continues to decline. About 1 in 161 people in the U.S. are infectious, the lowest levels since July 1. Transmission levels are higher than during 27% of the pandemic, but a good time to catch up on delayed care. 1/4
I have some concerns about Biobot's real-time data quality at the moment. Their real-time data have over-reported levels the past 8 weeks (11% last week, previously 6%, 10%, 7%, 5%, 9%, 4%, 5%) relative to later corrections. Huge bias!
2/4
Qualitatively, the over-reporting in real-time data lead me to believe there's a 50-50 chance we see a May "wavelet" versus continued decline for a couple months. Some of the county-level Biobot data seem implausible (e.g., levels of "3" in Mason County, WA, but others too). 3/4
31 Reasons Why the New 1-Day COVID Isolation Policy is Wrong
#1
Experts in modeling and testing know that people are infectious with COVID for an average of 7 days, with substantial variability around that average.
#2
People use defense mechanisms to temporarily avoid the death anxiety evoked by thinking of COVID. The too-short 5-day iso was an example of this (see final example).
Such defenses provide temporary relief and are almost always harmful long-term.
PMC COVID-19 Forecast, Week of Feb 26, 2024
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Forecast for the next month
Over the next month, we should see transmission fall from 790,000 infections/day toward more like a range of 200,000-450,000 infections per day, depending on better or worse scenarios.
That's "good" news in the relative sense for those putting off medical appointments the past 6 months, though still extremely high transmission in any objective sense.
See the online report for details on the models.
Surge in Context
At this point in the surge, it is clear that the peak transmission day was around December 27 (1.92 million/day), and the midpoint of “surging” infections (>1 million/day) was around January 9.
We are estimated to have had 85 total days with >1 million infections per day (November 28 through February 20) during the surge, though these numbers may still fluctuate with corrections the next few weeks.
The low-point leading into the surge was October 18 at 547,000 infections/day. Infections have been at “wave” levels (>500,000 infections/day or higher) since the onset of the late summer wave surpassed that milestone on July 27. We are estimated to dip below 500,000 infections/day around March 6.
This is very unfortunate timing because the medical facilities that enacted universal masking may end policies on March 1. Many were hoping for a period of lower transmission before such policies ended. As of today, the estimated low point for transmission is March 27 (348,000 infections/day), but the level and date are subject to much uncertainty.
PMC COVID-19 Forecast, Week of Feb 26, 2024
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Current State of the Pandemic
🔹73 million infections in the U.S. in 2024 (so far)
🔹790,000 daily infections
🔹1.66% (1 in 60) actively infectious
🔹40,000+ resulting #LongCOVID cases/day
Deeper Dive
Transmission is finally starting to decline again, and expect major declines the next four week.
U.S. wastewater levels indicate that COVID transmission is higher than during 58.4% of the days of the pandemic (down from 85.9% a week ago). Transmission is lower than 41.6% of the pandemic.
As we noted the past two weeks, we believed the post-peak hill was itself peaking on around February 7th and that last week’s slightly higher values might get retroactively corrected downward. That was, in fact, the case (the peak was the 7th), and transmission has fallen further since.
We are still at very high “wave” levels, but no longer “surging” at over a million infections/day. The big picture remains very bad, but this is good news for people putting off medical appointments for months.
PMC COVID-19 Forecast, Week of Feb 26, 2024
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Risks in Group Settings
Although transmission is falling, it's easy to get distracted by the relative changes and ignore that the absolute risk remains high, especially in large groups with limited or no mitigation.
In a group of 10, there's a 15% at least one person is actively infectious. In a group of 30, it's a 40% chance, and so forth. Almost nobody would take those chances of a serious illness if informed and capable of grappling with the seriousness of that risk without becoming defensive. Unfortunately, a lot of institutions are pushing minimizer narratives if not directly forcing students and workers into more dangerous settings.
Dr. Moriarty & other modelers know people are infectious for an average of about 7 days, per high-quality studies. Many for much longer.
Dr. Mina's pinned Tweet lays out a sample timeline.
Sending kids to school on Day 2 positive will essentially maximize infections. 2/4
The consequence of the California 1-day isolation policy is that many parents and grandparents will develop serious health conditions and too often die prematurely.
Bad for families. Good for inspiring the next generation of bereavement workers.