At peak surge, we will have 2 million U.S. #COVID infections/day.
Nearly 1 in 3 Americans will get infected during the peak 2 months of this winter surge. That’s 105 million infections & >5 million resulting #LongCOVID cases.
2/ Today on Christmas, 3.5% of the U.S. population (1 in 29) is actively infectious with #COVID & rising toward a Jan 10 peak.
COVID transmission is higher than during 94.7% of the pandemic. There's a 50% chance of a COVID exposure if interacting with 20 people today.
3/ We posted our first “Christmas Risk” table on October 30, and as you can see, it performed exceedingly well.
These tables should lend confidence in the PMC dashboard, and raise concern about public health leadership and the news media.
Being able to accurately predict within a few percentage points the probability of infectiousness in a room of 20 people, for example, 8 weeks out is very helpful for planning. Moreover, many would estimate *today* that the risk in a room of 20 people is <1 percentage point. We’re talking about potentially magnitudes of difference in risk estimation, and this was highly predictable long ago. It’s not something unanticipated due to a new oddly-behaving sub-variant (there will always be a new sub-variant this time of year when no mitigation) or high rates of air travel (also unsurprising). It was highly predictable, and public health officials should not be given an out. The media will try to frame this as an unanticipated surge, and it simply was not, according to those who know how to forecast.
The formal PMC forecast keeps to 4 weeks, but sometimes a more speculative long-term estimate can help with planning, especially surrounding booking travel plans. People might want to take a wait-and-see approach to booking, purchase travel insurance, or cancel entirely. We characterized the table with appropriate caution, and hopefully it was helpful.
Putting out these forecasts requires putting one’s professional reputation as a scientist on the line. It’s very easy for anonymous and fake-name accounts to make speculative forecasts. The information we provide tends to be highly conservative within a much broader set of analyses, sensitivity analyses, and scenarios considered. Know that we are very cautious about what information we share, post considerable detail on the underlying methodology and assumptions in the online report, and carefully describe how estimates may be more precise or more speculative at times. A published peer-reviewed article will ultimately account for the strengths and limitations in the accuracy of the model.
4/ Christmas infections will seed New Year’s Eve/Day infections, leading to a peak around the 10th.
Around New Year’s, interacting with 15-20 people means a 50% chance of a COVID exposure. In a restaurant or plane, the risk jumps to >98%.
5/ Zooming out to the full pandemic, we are in the 8th U.S. COVID wave & 2nd biggest all-time.
That assumes no major wastewater corrections.
We've surpassed the 1st wave, winter of 2020-21, Delta, & 2023 summer wave. Claims that “COVID is over” are harmful misinformation.
6/ Hospitals & clinicians should require universal masking. Public health officials should warn of the surge & recommend multi-layered mitigation.
Anything less is grounded in politics, short-term revenue, or defensiveness against COVID anxiety.
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.
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.
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.
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…
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⚡️
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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
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.
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.
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.
Nationally, we appear to have passed the peak of our late-summer wave, and it's not pretty.
At peak:
🔹>1.3 million daily infections
🔹2.8% (1 in 36) actively infectious
🔹Transmission higher than 90.5% of the pandemic
We are showing a peak around Aug 10, but as you look closely at the graph and in later Tweets, you'll see it was bimodal, with near-identical transmission on Aug 10 and Aug 24.
The CDC consistently corrects historical data, so in hindsight, we might expect the official peak date to flip to the 24th, or for the stats on the 10th to jump higher.
We had expected that Friday's data release might show this was the largest summer peak all-time (by the slimmest of margins), but the prior week's data were retroactively corrected downward by about 5%.
This is a common occurrence, which is why it's important to focus on the big-picture forecast (very bad transmission the remainder of 2024) as opposed to minute details.
Let's walk through the details in this Thread....
PMC COVID-19 Forecasting Model, Sept 9, 2024
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The current year-over-year graph on Covid transmission is troubling. We just had the worst August of Covid transmission in the U.S.
We are likely to have our worst September, worst October, and potentially worst November of transmission.
We expect to bottom out around 850,000 daily infections in early November, before the winter surge picks up.
These new monthly records for Covid transmission are the consequence of #LaissezFairePublicHealth, especially the 1-day isolation policy, but more generally that public health officials are not describing transmission frankly and the need for multi-layered mitigation.
PMC COVID-19 Forecasting Model, Sept 9, 2024
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Zooming in, see the forest for the trees: About 74 days in a row with 1 million daily infections.
The peak date is somewhat arbitrary, and either Aug 10 or 24 may be estimated the peak in hindsight.