Mike Hoerger, PhD MSCR MBA Profile picture
Dec 20, 2023 10 tweets 8 min read Read on X
As a clinical health psychologist, I notice that many people are using psychological defense mechanisms to downplay the risk of COVID.

These are my Top 7 examples:

🧵 Top 7 Psychological Defense Mechanisms Used to Downplay COVID
#1 – Denial – Pretending a problem does not exist to provide artificial relief from anxiety.

Examples:

“During COVID” or “During the pandemic” (past tense)

“The pandemic is over”

“Covid is mild”

“It’s gotten milder”

“Covid is now like a cold or the flu”

“Masks don’t work anyway”

“Covid is NOT airborne”

“Pandemic of the unvaccinated”

“Schools are safe”

“Children don’t transmit COVID”

“Covid is mild in young people”

“Summer flu”

“I’m sick but it’s not Covid”

Taking a rapid test only once

Using self-reported case estimates (25x underestimate) rather than wastewater-derived case estimation

Using hospitalization capacity estimates to enact public health precautions (lagging indicator)

Citing mortality estimates rather than excess mortality estimates. Citing excess mortality without adjusting for survivorship bias.This is from a psychology book by Nancy McWilliams. I will post a link to a PDF of newer edition of the full book at the end of the thread. If someone has a better "ALT" trick, please educate me on this one.
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#2 – Projection – When someone takes what they are feeling and attempts to put it on someone else to artificially reduce their own anxiety.

Examples:

“Stop living in fear.” (the attacker is living in fear)

“You can take your mask off.” (they are insecure about being unmasked themselves)

“When are you going to stop masking?”

“You can’t live in fear forever.”This is from a psychology book by Nancy McWilliams. I will post a link to a PDF of newer edition of the full book at the end of the thread. If someone has a better "ALT" trick, please educate me on this one.
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#3 – Displacement – When someone takes their pandemic anxiety and redirects their discomfort toward someone or something else.

Examples:

Angry, seemingly inexplicable outbursts by co-workers, strangers, or family

White affluent people caring less about the pandemic after learning that it disproportionately affects lower-socioeconomic status people of color

Scapegoating based on vaccination status, masking behavior, etc.

“Pandemic of the unvaccinated”

Vax and relax

“How many of them were vaccinated?” (troll comment on Covid deaths or long Covid)

Redirecting anxiety about mitigating a highly-contagious airborne virus by encouraging people to do simple ineffective mitigation like handwashing

“You do you” (complainers are the problem, not Covid)

Telling people to get vaccinated or take other precautions against the flu or RSV but not mentioning Covid

Parents artificially reducing their own anxiety by placing children in poorly mitigated environments

Clinicians artificially reducing their own anxiety by placing patients in poorly mitigated environments

Housework to distract from stress

Peer pressure not to maskThis is from a psychology book by Nancy McWilliams. I will post a link to a PDF of newer edition of the full book at the end of the thread. If someone has a better "ALT" trick, please educate me on this one.
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#4 – Compartmentalization – Holding two conflicting ideas or behaviors, such as caution and incaution, rather than dealing with the anxiety evoked by considering the incautious behaviors more deeply (hypocrisy)

Hospitals and clinicians claim to value health/safety but then don’t require universal precautions

Public health officials claim to value evidence but then give non-evidence based advice (handwashing over masking), obscure or use low-value data over high-quality data (self-reported case counts over wastewater), etc.

Getting a flu vaccine but not a Covid vaccine

Interviewing long Covid experts who recommend masking in indoor public spaces but then going to Applebee’s

Masking in one potentially risky setting (grocery store) but not masking in another similar or more-risky setting (classroom)

Infectious disease conference where people are unmasked

Long Covid and other patient-advocacy meetings where only half the people mask

In-person only EDI events

Not testing because it’s just family

Mask breaksThis is from a psychology book by Nancy McWilliams. I will post a link to a PDF of newer edition of the full book at the end of the thread. If someone has a better "ALT" trick, please educate me on this one.
#5 – Reaction formation – expressing artificial positive feelings when actually experiencing anxiety

“It’s good I got my infection out of the way before the holidays”

“I had Covid but it was mild”

Anything quoted in Dr. Jonathan Howard’s book, “We Want Them Infected: How the Failed Quest for Herd Immunity Led Doctors to Embrace Anti-Vaccine Movement”

Herd immunity (infections help)

Hybrid immunity (infections help)

“It’s okay because I was recently vaccinated”

“Omicron is milder”

“Textbook virus”

“Building immunity”This is from a psychology book by Nancy McWilliams. I will post a link to a PDF of newer edition of the full book at the end of the thread. If someone has a better "ALT" trick, please educate me on this one.
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#6 – Rationalization – Artificially reducing Covid anxiety through a weak justification.

Examples:

“I didn’t mask but I used nasal spray”

“I don’t need to mask because I was recently vaccinated”

“It finally got me.”

“You’re going to get Covid again and again and again over your life.”

“It’s not Covid because I don’t have a sore throat.”

“It’s not Covid because I took a rapid test 3 days ago.”

“It’s not Covid because I’m vaccinated.”

“Airplanes have excellent ventilation.”

“I’ve had Covid three times. It’s mild.”

“Verily was cheaper.”

“Nobody else is masking.”

“Nobody else is testing.”

“My roommates don’t take any precautions, so there’s no point in me either.”

“I have a large family, so there’s no point in taking precautions.”

Surgical masks (they are actual “procedure masks,” by the way)

Various pseudo-scientific treatments used by the left and right

Handwashing as the primary Covid public health recommendation

Droplet transmission as a thing

Public health guidance that begins with “data shows” (sic)

Risk maps that never turn deep red

5 expired rapid tests

“Masks recommended” instead of universal precautions

“Seasonal”This is from a psychology book by Nancy McWilliams. I will post a link to a PDF of newer edition of the full book at the end of the thread. If someone has a better "ALT" trick, please educate me on this one.
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#7 – Intellectualization – using extensive cognitive arguments to artificially circumvent Covid anxiety

Examples:

Unending threads to justify indoor dining

Data-rich public health dashboards that use low-quality metrics and/or don’t change public health recommendations as risk increases

The entire justification for “off-ramps”

Oster, Wen, Prasad

Schools denying air cleaners because it “could make children anxious”

Schools not rapid testing this surge because it “could make children anxious”

The mental gymnastics underlying the rationales for who can get vaccinated, how frequently, or with what brand

Service workers told not to mask because it could make clients uncomfortable

“What comorbidities did they have?”

“The vulnerable will fall by the wayside”

Musicians and others holding large indoor events

5-day isolation periodsThis is from a psychology book by Nancy McWilliams. I will post a link to a PDF of newer edition of the full book at the end of the thread. If someone has a better "ALT" trick, please educate me on this one.
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Here's a link to the full book, a newer edition than what I own. The information on defense mechanisms begins on textbook page 100.

Please let me know if there's a more accessible alt-text solution that you would prefer so I can do better next time.
isotis.files.wordpress.com/2016/07/mcwill…

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More from @michael_hoerger

Dec 16
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
Oct 22
PMC COVID-19 Forecasting Model, Oct 21, 2024
🧵1 of 4

Every indication is that the 10th U.S. Covid wave is on the way. Within 2 weeks, expect transmission to be meaningfully higher.

Current estimates from PMC:
🔹1 in 115 actively infectious
🔹Higher transmission than during 43% of the pandemic
🔹Nearly 3 million weekly infections

These estimates are high in the absolute sense, but low relative to the recent summer wave and likely winter surge.

The CDC data show transmission increasing in the Northeast, and a slowing of the decline in transmission elsewhere. Biobot data also show flattening transmission. The raw CDC and Biobot wastewater data are delayed >1 week. Walgreens shows positive cases, testing, and positivity ratios flattening and is delayed only 1 day.

For those unfamiliar with the 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 (median) 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 10-11 at the above link.GRAPH Shows forecasted entry into a 10th Covid wave.  TABLES Current Levels for Oct 21, 2024 % of the Population Infectious 0.9% (1 in 115) New Daily Infections 414,000  New Weekly Infections 2,898,000  Resulting Weekly Long COVID Cases 145,000 to 580,000  Monthly Forecast Average % of the Population Infectious 1.3% (1 in 76) Average New Daily Infections 627,600 New Infections During the Next Month 18,828,000 Resulting Monthly Long COVID Cases 941,000 to 3,766,000  Running Totals Infections Nationwide in 2024 225,097,000 Average Number of Infections Per Person All-Time, U.S. 3.46  How Does ...
PMC COVID-19 Forecasting Model, Oct 21, 2024
🧵2 of 4

These graphs show the forecast for changes in transmission over the next month.

The first graph shows year-over-year transmission. The 2nd focuses on the most recent year. Within a month, expect to see 0.7 to 1.0 million daily infections, if the assumptions of the model hold.

If lucky, we could get a slightly longer "lull" than what the model shows. The model likely underestimates the true value for the recent summer peak because many children were infected while going back to school, in fact, the highest peak at that time period all-time. Wastewater underestimates child infections ("contributions" correlate highly with body weight, so it takes four ill 50 lb kids to show up as one ill 200 lb adult). In underestimating the peak, transmission also fell more rapidly than anticipated post-peak. To the extent we underestimated the magnitude of the peak, there may be fewer than anticipated infections the next two weeks and a longer lull.

If you look at the first graph, however, you will see a clear patterns of escalating transmission in November, so it's more a matter of how quickly the situation will worsen than whether it will worsen.

During this relative "lull," it's an excellent time to stock up on high-quality masks, get vaccinated, upgrade the quality and quantity of air cleaners, re-stock on rapid tests, and encourage others to do the same.Two graphs, described in Tweet.
PMC COVID-19 Forecasting Model, Oct 21, 2024
🧵3 of 4

Regional differences suggest that the NE may already be rebounding in transmission. Transmission declines are slowing elsewhere.

We compare the PMC map in standard red against the CDC map using the same data in cool blue.Estimated Percentage Actively Infectious* National	0.9% (1 in 115) Northeast	1.0% (1 in 101) Midwest	0.9% (1 in 114) South	0.8% (1 in 130) West	0.9% (1 in 106)
Read 4 tweets
Oct 7
PMC COVID-19 Forecasting Model, Oct 7, 2024
🧵 1/4

540,000 daily infections during the "lull" between the 9th & 10th U.S. Covid waves.

🔹1.1% (1 in 88) actively infectious
🔹19 million anticipated infections the next month
🔹Higher transmission than half the pandemicGraph: 10 waves of the pandemic  Tables/stats: Current Levels for Oct 7, 2024 % of the Population Infectious 1.1% (1 in 88) New Daily Infections 541,000  New Weekly Infections 3,787,000  Resulting Weekly Long COVID Cases 189,000 to 757,000  Monthly Forecast Average % of the Population Infectious 1.3% (1 in 74) Average New Daily Infections 643,433 New Infections During the Next Month 19,303,000 Resulting Monthly Long COVID Cases 965,000 to 3,861,000  Running Totals Infections Nationwide in 2024 220,311,000 Average Number of Infections Per Person All-Time, U.S. 3.44  How Does Risk Increase wi...
PMC COVID-19 Forecasting Model, Oct 7, 2024
🧵 2/4

Year-over-year, we have seen the steepest drop in transmission all-time on the back end of a summer/fall wave.

Similar transmission the next month, a very high lull. Expect transmission to accelerate in mid-Nov.Two graphs  Year-over-year transmission. A very high late-summer wave, the highest all-time during Aug/Sep, followed by the steepest decline on the back of a summer wave, all-time.   Forecast. Note similar transmission over the next month, 40-60% of the summer wave's peak. Expect transmission to pick up considerably in mid-Nov in anticipation of a winter surge peaking around New Year's Eve
PMC COVID-19 Forecasting Model, Oct 7, 2024
🧵 3/4

Relative to the Northeast, transmission is 2x higher in the Midwest/South & 2.5x higher in the West region.

However, the CDC regions mask extreme variation within region. The 7 highest-transmission states are far north.Map: Transmission highest in Washington state, Oregon, Montana, Minnesota, Vermont, New Hampshire, and Maine.   Line Graph: Shows the regional statistics summarized in tweet.
Read 4 tweets
Sep 30
PMC COVID-19 Forecasting Model, Sep 30, 2024
🧵 1/5

COVID transmission remains extremely high, but we're entering a "lull" in the U.S. sooner than anticipated.

Among all summer/fall waves, the 22% 1-week drop in transmission is steepest all-time.

Details:

In Friday's data release, the CDC retroactively corrected the prior week's numbers downward 6% (for Sep 14). This is a big correction, bigger than average, but nothing nefarious. The most recent week's numbers show an additional 1-week decline in transmission of 22% (from Sep 14 to Sep 21) on top of that 6% correction (for Sep 14), so the transmission estimates have fallen quickly.

Looking back, we estimate that the 1-week drop of 22% is the largest decline on the back end of any summer/fall wave in the U.S.

*If* these numbers hold against future retroactive corrections, it means people have about 5 weeks of similar transmission from today through Nov 7.

Why might we have seen a record decline in post-peak transmission?

Several hypotheses:

1) Reporting Error: The 22% decline could be driven in part by errors in real-time reporting. These average is 5%, based on our analyses of Biobot wastewater data. We do not have long-term data on the accuracy of Verily/CDC real-time reports versus retrospectively corrected values. In the updated graphic, we have added 95% confidence intervals for the real-time values based on Biobot data, which show that 95% of real-time errors fall within 8.33%. Note that the dotted lines do not show 95% confidence intervals for the forecast, merely how the best estimates would change if a large error in the real-time reports of +/- 8.33%. It’s possible that next week the data will get corrected upward, and the forecast will more resemble the top dashed line. In the next Tweet, we show the forecast for our old (Biobot-based model); it’s still showing a slower decline, but they update their data about 5 days slower than the CDC, so it is unclear whether it’s a big real-time reporting error at the CDC or just that the CDC is ahead of the game.

2) Unprecedented School Transmission: This is the largest wave during the August back-to-school period. It’s possible transmission disproportionately affected school children and their families, and in being more targeted than typical transmission, the wave went down faster that what is normative thus far in the pandemic.

3) Laissez Faire Public Health: Public health guidance has weakened (e.g., 1-day isolation policy, not strongly pushing additional mitigation), which likely pushed the peak of the 9th wave higher, which could have led to a faster-than-usual resolution. The model accounts for these changing dynamics reasonably well, but with the school issue noted in hypothesis #2, it is possible the weakened public health guidance disproportionately hit a subset of the population, which altered the back side of the wave.

4) Missing Data: There are no widespread state-level instances of missing data, as is often the case. It is possible that specific areas did not report this week, and if there is a bias toward higher transmission in those places, the numbers will get retroactively corrected upward. This is one example of the issues that contribute to #1.

5) Politics: There is no evidence to suggest the CDC is modifying transmission data for political reasons. We put deep trust in the fundamental scientists doing the critical work translating wastewater into meaningful downloadable data. The inferences, agency graphs, and guidance can be influenced by politics, but the data are sound, given the limitations noted under #1.

Overall, if the data hold or anything reasonable within the ballpark, which is likely, this means a more prolonged and slightly lower lull than previously anticipated. Those putting off medical appointments and other risky activities may see this as a slightly broader window (today through Nov 7) to get things done. Note that even under the most optimistic forecasting scenarios, transmission remains very high in absolute terms, even if low in relative terms.Graph #3 from the PMC dashboard. Shows a steep decline in transmission based on the most recent CDC numbers.
PMC COVID-19 Forecasting Model, Sep 30, 2024
🧵 2/5

Note that while the CDC data show an unprecedentedly steep decline, Biobot data suggest more gradual changes, along the lines we have been forecasting the past several weeks.

This graph shows a resurrected version of our discontinued model 1 (Biobot-only) forecast.

I would not be surprised if the CDC data get retroactively corrected upward a little bit (this is common, not nefarious), AND the Biobot data go down a bit faster (they lag the CDC data by about 5 extra days). There is regional variation between the data sets, which means that BOTH models could actually be accurate without corrections.

Nonetheless, anything in the ballpark of these two forecasts suggests a "lull" from about now through Nov 7. It's a very high lull, but people find these dates useful for risk-based planning.Biobot-based model suggests a much more gradual decline, with transmission still bottoming out in early November.
PMC COVID-19 Forecasting Model, Sep 30, 2024
🧵 3/5

The United States is coming down from a 9th Covid wave and will soon transition into a 10th.

We are still #DuringCOVID.

The peak will likely be around New Year's Eve, though some models suggest slightly later.

A 3-month forecast is extremely volatile. I mention it now because people are already making travel plans.

Hospitals should formalize their plans for requiring universal masking if they have not already done so. Many have missed the mark during the ongoing summer/fall wave due to reliance an outdated zeitgeist of "respiratory virus season" that treats cold, flu, and Covid at interchangeably equal. Covid peaks twice annually and is more disabling long-term. Nonetheless, even hospitals relying on outdated models will be more likely to take the forthcoming wave more seriously.

As we have published, universal masking during Covid waves is a key indicator of healthcare quality. Yes, this is true based on 2024 data. Unfortunately, it's mostly only the very best-of-the-best health centers. Consider printing and mailing this article to places where you receive care.
jamanetwork.com/journals/jaman…Graph #1 from the PMC dashboard, shows we are coming down from a 9th wave, with a 10th wave about to start.
Read 5 tweets
Sep 24
As an expert in psychological assessment who has testified in court on cognitive assessments I've conducted, people should interpret carefully the new eClinicalMedicine paper on Covid-related cognitive changes.

Quick 25-pt thread⚡️
🧵1/25 Main figure from the paper. It has a lot of information but actually communicates very little that is meaningful. They authors suggest changes in general cognitive skills (A) and curiously mix this with figures showing more viral load among people infected with virus (B). The top half of A is virtually uninterpretable. The bottom half is vastly overstated. I think people see the big findings in B and think a lot is going on cognitively, when it's just about virus.
The field of clinical psychology has developed, implemented, and evaluated normed broadband tests of cognition for the past 119 years.

These are highly specialized instruments with carefully selected tests to cover the breadth of key areas of cognition.

2/25
The study did not use one of the well-established, normed, broadband tests of cognition. Instead, it used a novel app-based hodgepodge of tests with little empirical history.

People should be very cautious in interpreting results. There is no vast literature on the tests.
3/25
Read 25 tweets
Sep 23
PMC COVID-19 Forecasting Model, Sep 23, 2024
🧵 1/8

The U.S. continues to see an estimated 1.1 million daily COVID infections with 2.2% of the population actively infectious as we descend from the peak of a 9th Covid wave.

Transmission will remain very high the rest of 2024.Main PMC figure showing Covid transmission over time. It shows 9 waves. The current wave peaked in August, and we're still seeing >1 million infections/day in the U.S.
PMC COVID-19 Forecasting Model, Sep 23, 2024
🧵 2/8

Looking at the year-over-year graph, note that we're in uncharted territory for this point in the fall. Expect a very high "lull" in early November before the winter surge sets in.

As we have noted previously, our current estimates are likely slight underestimates given elevated school-based transmission and the CDC data standardization process.

Kids: They are smaller, and make smaller "contributions" to wastewater. Basically, it takes more sick kids to produce the average amount of wastewater virus to equate to an average infection (mostly in adults). This issue evens out over time, but it means the model may underestimate during back-to-school periods.

CDC: They describe the details of their process for standardizing data over time. It's very strong, much better than what most localized wastewater orgs or WWS do. It's a bit Dunning-Kruger to question basic wastewater scientists in doing the most fundamental components of their jobs, and the data continue to correlate >.90 with other metrics like Biobot. In comparing with other data, I take their estimates as spot on, but could also see arguments that they may underestimate transmission by 0-5%. It's something we always keep an eye on. Trust, but verify.

Transmission is magnitudes higher than much of the public realizes, so we focus on the big-picture view rather than quibbling over such issues that tend to balance out over time.

I hear @jlerollblues is considering weighting a model based on estimates of the proportion of infections in children. That's actually tougher to estimate than it sounds at first glance. You should key an eye on his models too and the work he and others are doing with the WHN.Estimating a "lull" the 1st week of November, but at an alarming 850k daily infections in the U.S.
PMC COVID-19 Forecasting Model, Sep 23, 2024
🧵 3/8

Zooming in from the big picture, here's the past year of the pandemic.

🔹1.1 million daily infections
🔹Bimodal peak (Aug 10 & 24) of 1.3 million daily infections
🔹50-60% of transmission happens on the back end of waves

Continue to educate family, friends, and co-workers. Look at how the wave descends much more gradually than is arose. Many infections to come, and to try to prevent! Also, most people are not monitoring wastewater. They keep track of the cumulative "anecdata" of people they know sick or diagnosed with Covid recently. In their mind, the peak will feel like late October, when the cumulative count has really built up. You may find people more open to listening during the next month.Annual graph. Shows transmission much higher than a year ago at 1.1 million daily infections today, but nowhere near the 1.9 million daily infections of last winter's peak.   The wave is descending slower than it rose, which is a reminder than much transmission happens on the back end of waves.
Read 8 tweets

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