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 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
🧵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.
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.