The U.S. as a whole is now 10% below the 9/1/2021 peak of the Delta wave. We stand at 46.1 new cases / 100K / day, down from 46.6 yesterday.
A month ago, when I first tried to predict the peak of the Delta wave, and came up with “early September”, an astute reader suggested that the wave for the U.S. as a whole ought to be much “broader” than the waves for the individual states. In hindsight, I’m going to say, that seems to be correct.
Overall, for the past week, the number of new cases is essentially unchanged. But that’s due to that big “divot” in the curve, depressing the case counts last week. I’ve found no clear explanation for that “divot”. At this point, I’m going to attribute it to an inexplicably large impact of the Labor Day holiday on testing and reporting of testing. In the past, major national holidays produced impact of that size. We’d just never seen anything like that before for (e.g.) Memorial Day, July 4th, or Labor Day.
If I airbrush that out, and bridge the gap, I get a plausible, if somewhat broad, shape to the peak.
In short, despite all my panicky posts of the past week, it appears that the U.S. merely continues to grind through the Delta wave. Which, as of now, peaked on 9/1/2021.
As with prior waves, we’re seeing groups of state move into the U.S. peak position and then have their new case counts decline.
Florida, for example, has now fallen more than 50% since its 8/28/2021 peak of 112 new cases / 100K/ day, on the last day of August. They are currently (9/17/2021 data) at 54.
The initial group of states that led the wave — FL, LA, MA — are all on the down-side of it. We’ve had an intermediate group show up. And now the three states with more than 100 new COVID-19 cases / 100K / day are SC, TN, WV. It’s pretty clear that Alaska is on track to hit that.
The pandemic continues to show considerable geographic clustering. If I separate out the states that had high rates, but appear to have peaked, I get the Gulf states, less Texas, pus Georgia:
Beyond that, it’s difficult to generalize about the next set of states — the states with high and rising case rates. It looks like the southern Appalachians are represented, as is Alaska. Not visible, Montana would also make the cut based on the current high rate of growth there.
So that’s how it looks today. The Gulf states (ex TX) seem to have peaked. Fl, LA, MS are now at about half the rate of daily new cases that they were three weeks ago. A couple of neighboring states (GA, AL) seemed to have peaked maybe a week later.
Now we just have to wait for this to work through the rest of the states. And then, at some point, it will probably converge with a winter wave.
Updating the herd immunity table
I should update my “herd immunity” table. This is my best guess at to the fraction of each state’s population that is immune to COVID-19.
This never did have much accuracy, owing to the need to make a couple of fairly critical (but nearly data-free) assumptions. As time passes, it gets even less accurate, for two key reasons.
First, immunity fades. That’s true of natural immunity (following infection) or immunity acquired via vaccine. As the pandemic stretches on, it becomes increasingly dubious to count people who were infected a year ago, or vaccinated 7 months ago, as immune to COVID-19.
Second, widespread home testing with antigen (quick) tests likely reduces the fraction of the population of truly infected individuals that are formally diagnosed with COVID-19 and counted in the state data. (Restated, increases the ratio of actual, total cases to diagnosed cases counted by state health departments.)
Those antigen tests don’t need to be sent to a lab, so they are not reported to state health departments. And, near as I can tell, they appear to have a low false-positive rate. All of that means that if you give yourself an antigen test, you don’t really need to do anything else, testing-wise. Unless you did something to trigger a false positive (such as drinking an acidic beverage before testing), you can be fairly sure that you’ve got COVID-19 if you get a positive reading. (By contrast, they have a fairly high false negative rate, so if you get a negative reading, there’s still a good chance that you do have COVID).
I think the magnitudes of both of those effects are unknown. And I’m ignoring them for now.
So, FWIW, here are my “standard” assumptions, and the results I get (data is as of about a week ago).
- Two un-diagnosed cases for every formally diagnosed-and-counted case.
- Full vaccination is 84% effective against Delta, on average.
- Partial vaccination is 54% effective against Delta.
- Immunity from prior infection is 84% effective against Delta.
- People get vaccinations at random, regardless of whether they have had a prior infection. (I need this last one to net out the assumed overlap of the prior-infection and vaccination populations).
The table shows the estimated fraction of the population that is totally immune. E.g., if there were 100 people fully vaccinated, I’d count 84 as being totally immune, based on the assumed 84% effectiveness of the vaccines.
Source: Calculated from data on the CDC COVID data tracker, using the assumptions listed above.
I should point out a few things.
First, the high-immunity states are a motley crew. It’s a mix of high-vaccination states, and high-cumulative-infection-rate states.
Second, the high-immunity states are not very well correlated with who is doing well and poorly right now. In part, that’s because you might start to reach high immunity during the Delta wave. In other words, if infection is rampant in your state now (as in Tennessee), that’s pushing you up this list.
Third, in this calculation, 80% is the magic number. (Not 90+%, because I’ve already adjusted for the effectiveness of the vaccines.) If the “R-nought” of the Delta variant is 5.0 (which seems to be somewhere around the consensus), then you need to have 80% fully immune to reach herd immunity (in the sense that the pandemic would die off even if you took no other precautions such as wearing masks, limiting social interaction, and so on.)
(Explanation: If each infected person would infect five others absent an intervention, you need to block at least four of those new infections to get the pool of infected individuals to shrink. Hence, R-nought of 5.0 requires 80% full immunity to achieve herd immunity.)
I’m just pointing out that, with all the shortcomings and assumptions and so on, this is the first time that any state has every reached what would be, in theory, the herd immunity number. (Using my current (more refined) set of assumptions).
This is, in part, why my guess remains that we’re going to have a fairly bad winter wave this year, and then we’ll be done with this. COVID-19 will always be lurking in the background, but it won’t be epidemic in the U.S.
Why? Project this table forward, using last year’s winter wave. The U.S. had about 20 million diagnosed cases in last year’s winter wave. That’s an estimated 60 million actual cases, under my assumptions, or about 18% of the U.S. population. Start tacking 18%s to the numbers above, and everybody from Virginia on up would have hit the magic 80%.
In round numbers, best guess, one more awful winter wave should put the majority of the country at or near the herd immunity level for Delta. Add in a few other factors that also interrupt infections (masking, limits on social activity) and we should at least be in the ballpark. I hope.
