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Mike Hoerger, PhD MSCR MBA Profile picture
@michael_hoerger
Jul 19, 2022 • 12 tweets • 9 min read • Read on X
Top 10 tips everyone should know about wearing #N95 & #elastomeric masks.

What did I miss?

THREAD! Image
Tip #1: Masks buy time. Context matters too: Ventilation (HVAC/outdoor air), filtration (HEPA), & ⬇️ people buy more time.

The longer you’ll be someplace or the worse the context, the better the mask you’ll need.

In a “typical” setting, you might expect this (per @akm5376): Image
Tip #2: If you’re going to be someplace a long time (home, office, hospital, wedding), open windows, add #HEPA, turn HVAC from ‘auto’ to ‘on' & do testing.

BOOM, you just improved your mask. Better context = less work for the mask.

Tip #3: These are my three fav N95s. The Aegle & 3M Aura are good for most adult size faces. The Vflex is good for larger faces. I think 80-90% would be happy with the Aura.

What’s your fav #N95 and why?

Tip #4: Have a unique concern? There’s an N95 for you. Just ask.

For example, a lot of people like the Airgami if they have COPD or other breathing challenges.

The Readimask is good for MRIs, haircuts, or dental visits.
Image
Tip #5: Do a quick #N95 seal check each time. Fit the nose piece using both hands. Exhale a deep breath to check for obvious leaks.

Read the instructions that came w/them, e.g., the 3M Aura or Vflex should be pulled back taut under the chin, not loose.

cleanaircrew.org/masks/#How_to_…
Tip #6: At low cost, you can fit-test an N95.

Buy a nebulizer & sweet (called FT-31) or bitter (FT-32) fit testing solution. The nebulizer vaporizes the solution. If you can taste it, your mask has gaps.



Tip #7: N95s are great, but for a better fit, try an “#elastomeric.”

That’s just a reusable elastic-band type mask.

Twitter search “elastomeric” for recs & sizing. Good ones: GVS models ($), @DentecSafety ComfortAir ($), @flo_mask ($$, adult & kid’s size), & Envo mask ($$) Image
Tip #8: Always buy directly from the manufacturer, a nonprofit like @projectn95, or a verified sourced. For example, Amazon sells a ton of fakes, but GVS is verified to sell authentically via Amazon. Do your homework.

Any questions on where to buy?

projectn95.org
Tip #9: Share the wealth. You can give away N95s to your family, friends, co-workers, patients, clinicians, & community.

Share these tips too. RT 🔁or post these tips on legacy platforms like Facebook Image
Tip #10: Follow for more N95 and elastomeric tips…
@LazarusLong13 @amandalhu @Amal4Solutions @sri_srikrishna @akm5376 @projectn95 @NgoTheWorld @ghhughes @denise_dewald @crosscutanne @masknerd

Who else?
FYI, I have no COIs, including no investment in any company listed. I’m a multidisciplinary scientist. My goal is to pass along advice from experts in a way that’s more relatable to communities.

• • •

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More from @michael_hoerger

Mike Hoerger, PhD MSCR MBA Profile picture
Jan 28
1) PMC COVID Dashboard for the Week of Jan 27, 2025 (U.S.)

🔹1 in 108 actively infectious
🔹3.1 million weekly infections
🔹>150,000 weekly resulting Long Covid conditions Current Levels for Jan 27, 2025 % of the Population Infectious 0.9% (1 in 108) New Daily Infections 443,000 New Weekly Infections 3,101,000 Resulting Weekly Long COVID Cases 155,000 to 620,000 Monthly Forecast Average % of the Population Infectious 0.9% (1 in 106) Average New Daily Infections 452,933 New Infections During the Next Month 13,588,000 Resulting Monthly Long COVID Cases 679,000 to 2,718,000 Running Totals Infections Nationwide in 2025 18,779,000 Average Number of Infections Per Person All-Time, U.S. 3.60 There is more COVID-19 transmission today than during 41.9% of the pan...
2) We predicted the wave peak would be 0.8 to 1.3 million across various forecasts. We presently have it at 0.9-1.0 million, though retroactive corrections can change that. The WHN also runs an excellent model, with a peak estimated at 1.3 million.
whn.global/estimation-of-…
3) Approx 1 million daily infections is quite serious. This is a far cry from the various #nothingburger predictions, and the Monday morning quarterbacks who in hindsight minimize U.S. infections, Long Covid, & disability.

Perhaps they have social media revenue COIs. I don't.
Read 9 tweets
Mike Hoerger, PhD MSCR MBA Profile picture
Jan 20
1) PMC COVID-19 Forecast for Jan 20, 2025 (U.S.)

If we are lucky, the 10th wave has peaked, likely in the 0.9-1.1 million daily infections range, barring significant retroactive corrections.

Over the next month, we should still see about 14 million infections, resulting in 700K to 2.8 million new conditions and enduring symptoms under the umbrella of #LongCOVID. This is simply your reminder than transmission remains high on the back on of a wave.

Regarding the peak, there were huge retroactive downward corrections, especially in Oregon. The CDC data originally showed one of the largest waves there all-time, and then corrected it to say a complete lull the whole time. Once the Biobot data get updated, we may see the peak date change by a week, or jump a bit higher than what you see in the main figure.

What you see in the far end of the forecast is unlikely to be a "high lull," but rather an average between a low lull versus a sustained post-peak haunch of lingering transmission. So, keep an eye on the data. If you're putting off a non-urgent medical appointment, we could get into relatively lower transmission in the next 4-8 weeks. What has me concerned is a sneak-peek of @jlerollblues's long-term forecast indicating a clear possibility of an earlier "mid-year" wave than usual, perhaps even in April. We're still getting pretty lucky on the viral evolution front, but the longer that persists, in absent of major policy change, the bigger the wave we could get. It's a very important time to stay tuned.

Caveats: No data from Biobot in weeks (20% model weight). The California wildfires and pending severe storms in the Deep South are wildcards for transmission. School-based transmission could pick up, but to get a higher peak, transmission would need to pick up much faster in the South and West than in the Midwest and North (unlikely).

In the report, I note that PMC will persist even if the CDC drops or scales back their surveillance program. Also, the most two recent "odd" waves have helped clarify how to handle historical data, and a minor update to the model should help with future atypical waves. If time permits, we will fine-tune those changes further, but there are always more battles on the Covid front than we're able to fight. We also provide a link and light commentary on our recent pre-print showing what our current case estimation model for estimating present/prior daily infections has performed well, and why a lot of other models (BNO, JP, CDC) are underestimates.

Info for new readers:

For those unfamiliar with the PMC model, find full weekly reports for the past 1.5 years at pmc19.com/data

The models combine data from IHME, Biobot, and CDC to use wastewater to estimate case levels (r = .93 to .96) and forecast levels the next month based on typical levels for that date and recent patterns of changes in transmission the past 4 weeks.

Our work has been cited in top scientific journals and media outlets, which are fully sourced in a detailed technical appendix at pmc19.com/data/PMC_COVID…

Examples include JAMA Onc, JAMA-NO, BMC Public Health, Time, People, TODAY, the Washington Post, the Institute for New Economic Thinking, Salon, Forbes, the New Republic, Fox, CBS, NBC, and CNN. See pgs 11-13 at the above link.

#MaskUp #VaxUp #CleanTheAir #RapidTestCurrent Levels for Jan 20, 2025 % of the Population Infectious 1.1% (1 in 87) New Daily Infections 547,000 New Weekly Infections 3,829,000 Resulting Weekly Long COVID Cases 191,000 to 766,000 Monthly Forecast Average % of the Population Infectious 1.0% (1 in 102) Average New Daily Infections 466,700 New Infections During the Next Month 14,001,000 Resulting Monthly Long COVID Cases 700,000 to 2,800,000 Running Totals Infections Nationwide in 2025 15,281,000 Average Number of Infections Per Person All-Time, U.S. 3.59 How Does Risk Increase with More Social Contacts? Number of People | Ch...
2) Here is the issue of Oregon I noted, with the "disappearing surge" in the CDC data. By that, I don't mean a surge that declined quickly. I mean, the CDC saying there was a huge surge in OR and then saying it was a lull the whole time. Baffling.

3) It's an important time to reflect that we have never had a federal Covid response commensurate with the magnitude of this $14-billion problem in the U.S.

3/11/20-1/19/21 = 290K infections/day (91 million total)

1/20/21-1/19/25 = 759K infections/day (1.1 billion total)

10 waves and >1 billion estimated infections in 5 years.

We have never had a well-conceived multi-layered mitigation strategy, and the strategy we have had has often underachieved due to insufficient operational management.

This places society at greater systemic risk from repeat-infection Long COVID. The approach is unreasonable to people with primary immunodeficiencies, cancer, organ transplants, kidney disease, type 1 and 2 diabetes, Long COVID, pregnancy, and many other conditions. Upwards of 2 million older adults in the U.S. are in early retirement, with the labor participation rate still well below pre-pandemic levels, and older adults almost wholly accounting for that presently. The children that were pretended to be magically shielded from Covid are not doing well on the cumulative infection front either.

I do not see that changing. I hope the many scientists and public health officials biting their tongues the past 4 years now feel liberated to speak up on Covid. Note that state and regional organizations and individuals were a big reason why transmission was better under control in year 1 of the pandemic.

Note that our statistics are estimated "true" cases based on the PMC model, not reported cases, which are vast undercounts (ascertainment bias). See the first Tweet for info on our model, including our website, which contains hundreds of pages of reports (pmc19.com/data), or read our recent pre-print showing the high accuracy of our case estimation model, to the extent that is ascertainable (researchsquare.com/article/rs-578…). To believe the true infection estimates are lower than these figures, one would have to suspend cognitive reasoning and merely assume transmission happens at vastly lower rates in the U.S. than those documented through the most-rigorous testing-based program in Europe.figure showing the 10 Covid waves (U.S.)
Read 5 tweets
Mike Hoerger, PhD MSCR MBA Profile picture
Jan 6
1) PMC COVID-19 Dashboard, Jan 6, 2025 (U.S.)

📈1 in 49 people actively infectious
🔥Nearly 1 million daily infections
🎲About a 50-50 chance someone has COVID in a large class if typical risk and no testing/isolating
🏥300,000+ new Long Covid conditions per week

The infections are likely minor underestimates. AZ and OR did not report this week. They were surging, so the lack of data brings down the average. As well, the model gives 80% weight to CDC wastewater data and 20% weight to Biobot, but Biobot took the week off, so this is dependent on observed changes in the CDC data.

It would be wise to add multiple imputation into the model to account for all the non-random missingness during surges, but I won't likely get to that anytime soon.

The peak is looking more and more like 1.4 million daily infections, but I wouldn't be surprised if it's earlier than shown and more like 1.3 million, based on the pattern of retroactive data corrections last winter. If the real-time data really stink, it could come in closer to 1.0-1.1 million. To top 1.6 million, we would probably need some serious immune escape that at present I just don't see happening. However, in past winters, transmission was declining nationally in early/mid January, and back-to-school is a wild card.

Info for new readers:

For those unfamiliar with the PMC model, find full weekly reports for the past 1.5 years at pmc19.com/data

The models combine data from IHME, Biobot, and CDC to use wastewater to estimate case levels (r = .93 to .96) and forecast levels the next month based on typical levels for that date and recent patterns of changes in transmission the past 4 weeks. Our work has been cited in top scientific journals and media outlets, which are fully sourced in a detailed technical appendix at pmc19.com/data/PMC_COVID…

Examples include JAMA Onc, JAMA-NO, BMC Public Health, Time, People, TODAY, the Washington Post, the Institute for New Economic Thinking, Salon, Forbes, the New Republic, Fox, CBS, NBC, and CNN. See pgs 11-13 at the above link.

We will have a pre-print out in the next week or so documenting very compelling evidence for the validity of using wastewater to estimate case rates. Forecasting is challenging in the context of the current viral evolution, but the real-time estimates of cases are impressively accurate to the best we can evaluate it.

#MaskUp #VaxUp #CleanTheAir #RapidTestCurrent Levels for Jan 6, 2025 % of the Population Infectious 2.1% (1 in 49) New Daily Infections 980,000 New Weekly Infections 6,860,000 Resulting Weekly Long COVID Cases 343,000 to 1,372,000 Monthly Forecast Average % of the Population Infectious 2.7% (1 in 38) Average New Daily Infections 1,272,833 New Infections During the Next Month 38,185,000 Resulting Monthly Long COVID Cases 1,909,000 to 7,637,000 Running Totals Infections Nationwide in 2025 5,468,000 Average Number of Infections Per Person All-Time, U.S. 3.55 How Does Risk Increase with More Social Contacts? Number of people |...
2) PMC COVID-19 Dashboard, Jan 6, 2025 (U.S.)

We're in the 10th wave of the pandemic (1st graph), and transmission this year has picked up atypically late, while coming on strong (2nd graph).Two graphs, summarized in tweet
3) PMC COVID-19 Dashboard, Jan 6, 2025 (U.S.)

Note that sputtering in the West's rise is likely an aberration, as surging OR and AZ did not provide data this week.

Read 5 tweets
Mike Hoerger, PhD MSCR MBA Profile picture
Jan 3
📢Clean Air Advocates📢

I recently learned of a new strategy to get more clean indoor air to people's homes. I don't believe I've heard anyone mention this on here, but please add if you have made inroads.
1/
Last August, I was surprised to learn that Entergy, our regional energy company, was giving away free HEPA filters to customers.

This was surprising to me. Why would an energy company do this?
2/
Apparently, most jurisdictions in the U.S. have regulations that require a portion of consumers' energy payments to go toward an energy efficiency fund.

These are often used for discounts on thermostats but occasionally for Energy Star appliances.
3/
Read 4 tweets
Mike Hoerger, PhD MSCR MBA Profile picture
Dec 20, 2024
x.com/i/article/1870…
2) This is one of the better scenarios I noted, with national levels coming in at about 3.33. Unfortunately, the rise was a little lower than anticipated only because transmission slowed in the west. Not uniform, so lots of uncertainty.

3) Transmission remains much higher than people realize. Many will get caught off guard by a seemingly #SilentSurge. This is in part because the CDC spent the past month downplaying numbers in misleading graphs.

Read 8 tweets
Mike Hoerger, PhD MSCR MBA Profile picture
Dec 16, 2024
PMC COVID-19 Dashboard, Dec 16, 2024
🧵1 of 8

🔹1 in 64 (1.6%) actively infectious in the U.S.
🔹750,000 new daily infections and rising
🔹Highest % increase in transmission in nearly 3 years
🔹10th wave is the "silent surge," coming on late out of nowhere

The video will walk you through each of the graphs on the dashboard and covered in this thread.

Info for new readers:

For those unfamiliar with the PMC model, find full weekly reports for the past 14+ months at pmc19.com/data

The models combine data from IHME, Biobot, and CDC to use wastewater to estimate case levels (r = .93 to .96) and forecast levels the next month based on typical levels for that date and recent patterns of changes in transmission the past 4 weeks.

Our work has been cited in top scientific journals and media outlets, which are fully sourced in a detailed technical appendix at pmc19.com/data/PMC_COVID…

Examples include JAMA Onc, JAMA-NO, BMC Public Health, Time, People, TODAY, the Washington Post, the Institute for New Economic Thinking, Salon, Forbes, the New Republic, Fox, CBS, and NBC. See pgs 11-13 at the above link.

We will have a pre-print out in the next month documenting very compelling evidence for the validity of using wastewater to estimate case rates. Forecasting is challenging in the context of the current viral evolution, but the real-time estimates of cases are impressively accurate to the best we can evaluate it.
PMC COVID-19 Dashboard, Dec 16, 2024
🧵2 of 8

🔹10th wave taking off (U.S.)
🔹5 million infections expected this week
🔹>250,000 post-infection conditions (#LongCovid) expected to develop from this week's infections
🔹Higher transmission than 73% of the pandemic

Info for new readers (as noted in Tweet 1):

For those unfamiliar with the PMC model, find full weekly reports for the past 14+ months at pmc19.com/data

The models combine data from IHME, Biobot, and CDC to use wastewater to estimate case levels (r = .93 to .96) and forecast levels the next month based on typical levels for that date and recent patterns of changes in transmission the past 4 weeks.

Our work has been cited in top scientific journals and media outlets, which are fully sourced in a detailed technical appendix at pmc19.com/data/PMC_COVID…

Examples include JAMA Onc, JAMA-NO, BMC Public Health, Time, People, TODAY, the Washington Post, the Institute for New Economic Thinking, Salon, Forbes, the New Republic, Fox, CBS, and NBC. See pgs 11-13 at the above link.

We will have a pre-print out in the next month documenting very compelling evidence for the validity of using wastewater to estimate case rates. Forecasting is challenging in the context of the current viral evolution, but the real-time estimates of cases are impressively accurate to the best we can evaluate it.Current Levels for Dec 16, 2024 % of the Population Infectious 1.6% (1 in 64) New Daily Infections 748,000 New Weekly Infections 5,236,000 Resulting Weekly Long COVID Cases 262,000 to 1,047,000 Monthly Forecast Average % of the Population Infectious 2.5% (1 in 41) Average New Daily Infections 1,178,167 New Infections During the Next Month 35,345,000 Resulting Monthly Long COVID Cases 1,767,000 to 7,069,000 Running Totals Infections Nationwide in 2024 242,424,000 Average Number of Infections Per Person All-Time, U.S. 3.50 There is more COVID-19 transmission today than during 73.3% of th...
PMC COVID-19 Dashboard, Dec 16, 2024
🧵3 of 8

Areas of the U.S. depicted in darker red have higher transmission, as of 9 days ago. The map uses CDC data and is simply the CDC "cool blue" map recolored in more traditional red, which is best practices.

The line graph shows transmission increasing by region.

CDC map:
cdc.gov/nwss/rv/COVID1…

CDC regional graph:
cdc.gov/nwss/rv/COVID1…

Info for new readers (as noted in Tweet 1):

For those unfamiliar with the PMC model, find full weekly reports for the past 14+ months at pmc19.com/data

The models combine data from IHME, Biobot, and CDC to use wastewater to estimate case levels (r = .93 to .96) and forecast levels the next month based on typical levels for that date and recent patterns of changes in transmission the past 4 weeks.

Our work has been cited in top scientific journals and media outlets, which are fully sourced in a detailed technical appendix at pmc19.com/data/PMC_COVID…

Examples include JAMA Onc, JAMA-NO, BMC Public Health, Time, People, TODAY, the Washington Post, the Institute for New Economic Thinking, Salon, Forbes, the New Republic, Fox, CBS, and NBC. See pgs 11-13 at the above link.

We will have a pre-print out in the next month documenting very compelling evidence for the validity of using wastewater to estimate case rates. Forecasting is challenging in the context of the current viral evolution, but the real-time estimates of cases are impressively accurate to the best we can evaluate it.Map shows highest transmission in Arizona, New Mexico, Minnesota, and Massachusetts. Estimated Percentage Actively Infectious PMC Model Raw CDC Data (9 days old) National 1.6% (1 in 64) 0.9% (1 in 113) Northeast 0.8% (1 in 132) 0.4% (1 in 234) Midwest 2.4% (1 in 41) 1.4% (1 in 73) South 1.3% (1 in 74) 0.8% (1 in 132) West 1.5% (1 in 66) 0.9% (1 in 118)
Read 8 tweets

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