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:
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#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.
#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.”
#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 mask
#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
“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”
#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”
#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 periods
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.
📈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 #RapidTest
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).
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.
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/
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.
🔹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
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🔹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.
PMC COVID-19 Dashboard, Dec 16, 2024
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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.
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 Forecasting Model, Oct 21, 2024
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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.
PMC COVID-19 Forecasting Model, Oct 21, 2024
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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.
PMC COVID-19 Forecasting Model, Oct 21, 2024
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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.