Post #1390: COVID-19 trend to 1/7/2022

Cases continues to rise at 77% per week.  Which is, believe it or not, a slower rate of increase than we had one week ago.

The U.S. now stands at 206 new COVID-19 cases / 100K /day.  No area has been spared.  Just three states remain below 100 new cases / 100K / day (of all states reporting data today):   Maine, Montana, and Idaho.

At the other end of the scale, if the data are to be believed, Rhode Island now has nearly 500 cases / 100K / day (seven-day moving average basis).  At that point, it almost doesn’t that Omicron is less virulent than Delta.  With that many cases, give it a few days and you will fill your available hospital beds.

Continue reading Post #1390: COVID-19 trend to 1/7/2022

Post #1389: COVID-19 trend to 1/6/2022: A bit more of a slowdown.

 

Looks like were getting closer to a peak in daily new COVID-19 cases.

The rate of increase is slowing, and that’s occurring across all regions.  Cases only (only?) increased 77% in the past seven days, to 187 new cases per 100K per day.  Just two days ago, we were still seeing new cases double every week.

DC appears to have peaked, but no other states have so far.

Data source for this and other graphs of new case counts:  Calculated from The New York Times. (2021). Coronavirus (Covid-19) Data in the United States. Retrieved 1/7/2022, from https://github.com/nytimes/covid-19-data.”  The NY Times U.S. tracking page may be found at https://www.nytimes.com/interactive/2020/us/coronavirus-us-cases.html.

On the bright side, there’s typically a two-week lag between new COVID-19 cases and new COVID-19 deaths.  We’re now almost three weeks into our Omicron wave (U.S. cases started to increases rapidly beginning 12/17/2021), and, so far, there’s been no uptick in COVID-19 deaths at all. 

Below, you can look back at the far-more-virulent Delta wave and see that almost-perfect two-week lag.  You can see the ramp-up in deaths followed the ramp-up in cases.  And then you can see that’s not happening with Omicron.  If there had been, you surely would have read about it by now.

Source:  CDC COVID data tracker.  Notes are mine.

That was the story in South Africa — a lot of cases, few deaths.  And that’s also how it’s unfolding in Great Britain.


The United Kingdom Omicron wave in three charts, via Google Search.

Huge volume of new cases.  Three weeks from the upward kink in the curve (December 14 2021) to the apparent top of the curve (January 4 2022).

Big increase in hospitalizations, but not such a big increase in ICU use.

Slight uptick in deaths:

 Now here’s the crazy thing.  If the U.S. a) follows the United Kingdom’s time table for the wave, and b) I correctly dated the 1/14 (U.K.) and 1/17 (U.S.) starts of the Omicron waves, then …. tomorrow should be the peak of the U.S. Omicron wave.  That is, the day when that seven-day moving average of new cases finally levels off.

Well, we know Omicron can move fast.  It was upon us before we were really ready for it.  And it’ll be receding before we can get ourselves out of crisis mindset.

What am I going to do with my time once I can no longer blog about COVID?

Post #1388: COVID-19 trend to 1/5/2022, maybe a bit of a slowdown.

 

As of 1/5/2022, the U.S. stands at 179 new COVID-19 cases per 100K population per day.  Washington, DC is now the only area that appears to have topped out.

That said, with this last batch of data, there was a slight — but widespread — slowing of the growth in U.S. new case counts. Cases less-than-doubled in the last seven days.

Although it probably feels like it’s been longer, today is just the the 12th day after Christmas.  That’s just about the right timing to suggest that we’re seeing the results of a slowdown in the rate of new infections over the Christmas holidays.   Continue reading Post #1388: COVID-19 trend to 1/5/2022, maybe a bit of a slowdown.

Post #1387: Admissions for COVID versus admissions with COVID

The issue

I first flagged this issue three weeks ago, in Post #1349, with a little more explanation in Post #1351.

In many data systems, a “COVID hospitalization” is a hospitalization of a person who has tested positive for COVID.  Period.  This includes:

  • people who are being treated for COVID
  • people who are being treated for something else entirely:
    • for whom the finding of a COVID infection is completely irrelevant or
    • for whom COVID might have exacerbated the underlying condition that got them hospitalized.

My guess is that the final category involves relatively few people.  So, crudely, this breaks down into two groups:

1:  People admitted for COVID, who wouldn’t be in the hospital if COVID hadn’t been around, and who represent a true additional burden on the hospital system caused by the pandemic.  And then,

2:  People admitted with-but-not-for-COVID, who would be in the hospital in any case, and who don’t represent any additional burden on the hospital system caused by COVID.  For the simple reason that they are sick with something else.

Any additional cost burden from that second group is truly incidental.  They have to be kept isolated, and they are capable of infecting hospital staff with COVID.  So the cost of their hospital stay may be higher than it would normally have been.  But they would have been hospitalized COVID or not.


This is now greatly affecting U.S. COVID hospitalization counts.

In prior waves of COVID, this distinction didn’t matter much.  The overwhelming majority of patients admitted with COVID were being admitted for treatment of COVID.

In the Omicron wave, that’s no longer true.

This was first noted in South Africa, where one large hospital system there found that 76% of their patients “with COVID” were in the hospital for treatment of something else.  This was particularly true of their pediatric patients in South Africa, most of whom had an asymptomatic COVID infection that was only found after they were admitted to the hospital for the treatment of some completely unrelated condition.

Now I’m seeing reports of the same thing happening in U.S. hospitals (emphasis mine):

Roughly two-thirds of patients who have tested positive at hospitals run by the L.A. County Department of Health Services were admitted for something other than the coronavirus, according to Health Services Director Dr. Christina Ghaly.

This time around, many “may have not known they were COVID-positive ... but they’re in the hospital for something else,” Ghaly said.

Source:  LA Times, 1/4/2022.

Dr. Fritz François, chief of hospital operations at NYU Langone Health in New York City, said about 65% of patients admitted to that system with COVID-19 recently were primarily hospitalized for something else and were incidentally found to have the virus.

Source:  AP News, 1/5/2022

Compared with earlier waves, a smaller percentage need intensive care. At Hackensack Meridian Health's hospitals, 140 of 1,100 COVID patients on Tuesday, or 13%, were in ICUs, and 75 were on ventilators. That's down from about 20% requiring ICU care at the pandemic's start. 

Some patients are admitted for other illnesses, only to discover after admission testing that they have COVID. Over the last month, that portion has increased to “45% who were admitted for something else but were found to have COVID, too,” Bennett said.

Source:  NorthJersey.com, 1/5/2022

Gov. Ron DeSantis said 50% of COVID hospitalizations at Orlando Health are not being treated for the virus.

“We have found that a great majority of our hospital in-patients who have been diagnosed with COVID-19, were admitted for medical conditions not related to the virus,” Orlando Health spokeswoman Alayna Curry said.

Source:  ClickOrlando, 1/4/2022

I am pretty sure I could find more if I looked.


Why does this matter?

Pediatric admission trend.  First, I will point out that numerous sources — including Dr. Fauci — suggest that this is particularly important issue for pediatric admissions.  I.e., that the number of children admitted for COVID in prior waves is far less than the number that has been counted (per this research).

And so, currently, pediatric admissions are increasing as a fraction of all COVID admissions.  Does that mean that Omicron differentially attacks children? Or does this just mean that these “incident” cases matter more in this group, where the number of admissions for COVID-19 is quite small?  Nobody can give you an answer to that.

True comparisons of illness severity.  One of the main ways everyone compares Omicron to Delta is by the likelihood that it will put you in the hospital, if you catch it.  But if a larger share of Omicron hospitalizations are persons for whom COVID-19 is an incidental finding, it makes Omicron appear to have higher severity than it actually does.

True estimates of hospital stress.  If half of the Omicron cases in the hospital are people who would have been hospitalized anyway, regardless of Omicron, then the raw hospitalization count overstates the true degree of hospital stress because caused by Omicron.

Finally, it’s not even clear what hospitals are reporting to the Federal government.  For the stock of patients in the hospital, it’s clear that the definition includes anyone with a positive COVID-19 test.  For “new admissions”, the guidance says to count patients ” … who had confirmed COVID-19 at the time of admission … ” .  If the hospital gives every incoming patient a rapid test for COVID-19, then, aside from the high false-negative rate of those tests, presumably, they are going to count every patient with detectable COVID at time of admission.  (I went through all of this in Post #1394).

My contention is that everybody talks about that new admissions number, but it’s not crystal clear what it actually represents.  Plausibly, it does include most of the “incidental” COVID-19 cases, if they are found by antigen testing during the hospital admission process.


A big problem with the math.

Here’s my main problem with this.  There’s no plausible set of circumstances that I can come up with that would generate that many incidental COVID-19 cases.  I.e., that many people who were hospitalized for something else, and just happened to have COVID discovered once admitted to the hospital.

It’s easy enough to understand how these incidental COVID-19 cases get into the hospital.  In the U.S., in 2018, per the AHRQ HCUP hospital database, 55% of hospital admissions occurred via the emergency room.  (And so were presumed to be emergency admissions).  Those patients are going to have to be admitted no matter what. Another chunk would be “urgent” admissions that cannot be postponed indefinitely.  Those people would likely be admitted regardless of COVID-19 status.  (And somewhere around 20% are “elective” or “scheduled” admission where, presumably, anybody testing positive for COVID would not be admitted.)

And so, presumably, these “incidental” COVID cases are just randomly distributed across all emergency (and urgent) hospitalizations, based on the prevalence of COVID in the community.  For emergency and urgent care, those persons end up hospitalized.  And they would carry any existing COVID infection to the hospital with them.

In other words, if 1 percent of the people in your community are walking around with an active COVID-19 infection, then, to a first approximation, about 1 percent of those showing up to be admitted to the hospital for any random condition will have a COVID-19 infection.

The problem is that a) yeah, somewhere around 1 percent of the population probably is walking around with an active COVID infection right now, but b) 1 percent of ongoing hospital admissions wouldn’t come close to explaining the high number of cases admitted to the hospital with COVID as an incidental finding.

Here’s the math.

There’s nothing tricky here.

  • First, the U.S. has about 30 hospitalizations per 100K population per day (in a normal year).
  • Second, based on the number of daily new COVID-19 cases, I estimate that just over 1% of the U.S. population is currently walking around with COVID.  (I’ve gone through my factor-of-six rule of thumb in prior posts).
  • Multiply those two together, and you get an estimated 0.4 “incidental” COVID-19 admissions per 100K per day.
  • But right now, we’re getting 5.5 COVID admissions per 100K per day.
  • So … those incidental admission would only amount to 7% of the total.  Nothing close to the 50% to 66% being reported anecdotally.

This has been puzzling me for weeks, ever since the South African finding came out.  And it boils down to “something most be wrong with the assumptions behind that calculation”.  But I have yet to figure out what.

One possibility is that there are vastly more asymptomatic Omicron cases than anyone has estimated.  There is a tiny amount of evidence to suggest that this might be plausible.   (I.e., this one research study).  But you would need so many cases that I don’t think you could account for this with asymptomatic infections alone.

That is, to bring that 7% figure up to 50%, you’d need to have seven times as many infections present in the population.  I think that, at that rate, the entire population would have been infected with Omicron within a couple of weeks.  It just requires too many people to have an active infection.

A second possibility is that persons who need hospitalization for some other condition have a vastly higher rate of COVID-19 infections.  But recall that most of these individuals are entering the hospital with asymptomatic COVID.  So it’s not like the finding that certain comorbodities increase risk of hospitalization for COVID-19.  Here, you’d have to believe that comorbidities likely to get you hospitalized also vastly increase your likelihood of asymptomatic COVID infection.  I can’t quite get my mind around that.

A third possibility is that maybe tests are turning up a lot of false positives on old COVID-19 infections.  So that, as these persons enter the hospital for some other reason, and get tested for COVID, we’re picking up not just those currently infected, but a significant fraction of those who have been infected sometime in (say) the past 90 days.

But, while such false positives do occur with PCR tests, I don’t think anybody says that they are common.  (The possibility of false-positives in that timeframe is why you are not supposed to get routinely re-tested for COVID within 90 days of a positive test.)  And nobody, so far, suggests that such false positives are more common with Omicron than with prior variants.

None of these explanations seems plausible to me, given the number of persons that would have to be involved.

Let me just spin the numbers the other way, and you can see what I’m talking about, in terms of not being able to get the math to work out.

On any given day, per 100,000 population, these days the U.S. would see

  • about 30 hospitalizations unrelated to COVID-19
  • about 6 COVID-19 hospitalizations.

If half of those COVID hospitalizations are incidental ones (where the person is admitted for something else, but has an asymptomatic case of COVID), that means you need to see 3 “incidental” COVID admissions coming out of the 30 individuals who were admitted for other causes.

In other words, if half the COVID admissions are “incidental”, that requires that 10 percent of all regular hospital admissions have an asymptomatic COVID infection upon entering the hospital.  (Or manage to trigger a positive on a COVID-19 test for some other reason.)

Which, to a first approximation, requires that, at any given time, 10 percent of the population would have to have an asymptomatic COVID infection?

Which I think is not even remotely plausible.

And that’s where I give up.  I cannot gin up any plausible scenario under which half the current set of COVID-19 admissions are “incidental” COVID cases.  That would require something like 10% of all regular hospital admissions have asymptomatic COVID.  Or somehow, certain diseases and conditions attract asymptomatic COVID infections.  Or Omicron results in a huge number of false positives, based on having had a prior (not active) infection.

None of those seems plausible.  But without something along those lines, the numbers just don’t make sense.  At current rates, if half of COVID-19 admissions are “incidental”, that equates to 10% of all admissions for treatment of anything but COVID walking in the door with an active asymptomatic COVID infection.

 

Post #1386: COVID-19 trend to 1/4/2021, new infections still doubling every seven days.

 

New York and Washington, DC still appear to have plateaued.  Otherwise, for the U.S. as a whole, new infections are still doubling every seven days.  With the exception of NY, DC, and Maine, new cases are rising rapidly everywhere.  The U.S. now stands just shy of 170 new COVID-19 infections / 100K / day. Continue reading Post #1386: COVID-19 trend to 1/4/2021, new infections still doubling every seven days.

Post #1385: Revised CDC estimate of Omicron incidence, and the Omicron case hospitalization rate.

The CDC issued another weeks’ worth of estimates of Omicron as a fraction of all cases. 

For the week ending 1/1/2022, they estimate that 95% of cases were Omicron. Estimates for prior weeks were revised as well.  Below, the current estimates are in the first column.  And you can see how those numbers have bounced around from week to week by reading across the additional columns.

Source:  CDC COVID data tracker, accessed on various dates ending 4/1/2022.

Assuming this latest estimate is more-or-less correct, this has implications for a lot of things.  Some good, some not so good, some neither/nor.

The worst of which is that the U.S. case hospitalization rate for Omicron is nowhere near as low as one-third that of Delta.  It’s now looking like it’s half, or more. Continue reading Post #1385: Revised CDC estimate of Omicron incidence, and the Omicron case hospitalization rate.

Post #1384: Just the worst possible sort of news reporting on COVID

 

Today, this headline caught my eye, from this source.

It caught my eye because it’s that’s not even remotely close to being true.  I just did the numbers this morning.

If you read far enough down into the story, you can see this:

These guys can’t possibly be so stupid as to fail to understand this.  Or, if they are, they shouldn’t be reporting on it.

If a state doesn’t report data for (e.g.) three days, what you see when they finally do report a new case number is four days’ worth of cases.

Just taking a simple average across the states, today’s raw count reflects nearly three days’ worth of cases, on average.

So they just took today’s raw total.  Fully realizing that it reflects cases accumulated over several days.  Then misleadingly added the word “daily” to their headline.  Just to make sure you misunderstood what you were being shown.  And ran with that as their headline.  As if the U.S. had seen a million new COVID-19 cases today.

Isn’t the actual Omicron outbreak scary enough as-is?  Exaggeration would seem to be unnecessary.  But if fear is your main product, rather than information, then any amount of exaggeration you can plausibly justify appears fair game.

It boils down to this:  They aren’t so stupid as to misunderstand what that raw number is.  But they’re hoping that you are.  Hey, they got me to click on it.  I guess that’s all that counts.

Post #1383: COVID-19 update to 1/3/2021

 

The U.S. is now up to at least 151 new COVID-19 cases per 100K population per day. 

About a half-dozen states did not report new data today, including, most critically, Florida.  If I gap-fill all of those with my projections from yesterday, I would estimate 160 new cases / 100K / day for today’s true count.  So there’s a bit more bad news that will come out later in the week as those states finally get around to reporting new data.

Omicron is now putting more people into the hospital than Delta did.  I’m still figuring that, at best, Omicron has one-third the case hospitalization rate of Delta.  And we’re now more than three times the new case rate at the peak of the Delta wave.  So it’s no surprise that Omicron’s hospitalizations are now above the peak of Delta’s.

Evidence still suggests a lower ICU use, when hospitalized, so we may or may not overrun hospital ICU capacity in many places.  And the jury is still out on case mortality rate, but the lower ICU use pretty strongly suggests that we’ll see a lower case mortality rate as well.

Are there any rays of light?  Maybe.  New York and DC led the way up.  Both appear to be topping out.  It’s a bit too early to say for sure.  But both had a few days with no net growth in new cases.  Maybe they’ve topped out, maybe they’ve just run out of testing capacity.  I should also note that, nationally, even after non-reporting adjustment, we came in below my constant-growth projection of 180 new cases (Post #1382).  So something slowed down, at least a bit, between a few days ago, and today.

Now for the pictures.

Continue reading Post #1383: COVID-19 update to 1/3/2021

Post #1382: Gap-fill using second-order extrapolation.

 

If you read this blog, you’re aware the most states don’t bother to release new COVID-19 case counts on holidays or weekends.  Also, you know that we have to wait a day to get the full set of U.S. data.  Together, those two things mean that tomorrow (Tuesday) will be the first time in several days that we’ll have been able to get an accurate fix on the level of new COVID-19 cases in the country.

One of the few benefits of this is that nobody knows what the rate actually is, right now.  So newspapers have to be quiet on that subject, for a couple of days, waiting for the new data to come in.  Same as I do.  Which is something of a relief, in the current situation.

Up to now, my solution to the missing data has been to assume that states carry on at their current level of daily new cases, until such time as they report new data.  If their seven-day average stood at 100 on Friday, I assumed it would be 100 on Saturday and Sunday as well.  Until the state finally reported new data on Monday.

In effect, my old gap-fill method assumed that every curve remains level until new data show otherwise.

In normal times, that’s a pretty good gap fill.

These aren’t normal times.

For today’s estimate, I ginned up a “second order” gap fill.  Instead of assuming the level of cases remains constant, this one assumes that a state’s most recent trend remains constant, over the period where data are missing.  If cases were increasing (e.g.) 10 percent per day just prior to Friday, I’ll now assume they continue to increase 10 percent per day over the weekend.

In effect, the new gap-fill method assumed that every curve remains at its prior slope until new data show otherwise.

Really, this is just the nerd’s way of extending the curve along the existing slope.  It’s a bit nicer than that, as it uses current data where available.  But that’s the gist of it.

So, take this for what it’s worth.  Here’s my best guess as to where the U.S. actually stands on Sunday 1/2/2022:

Based on the same rate of growth, we can plausibly expect the data for Monday 1/3/2022 — the data that will show up tomorrow — to show about 180 new cases / 100K / day, for the U.S. as a whole.

I like to put a prediction down on paper to keep things honest.  But this one serves two more purposes.

First, it’s a good test of whether or not U.S. new case growth is slowing.  If new case growth actually is slowing down — and in South Africa, that happened abruptly — then tomorrow’s number will come in well under 180.

And if it hasn’t, and tomorrow’s number, based on actual data, comes in around 180, then we’re definitely into the territory where we’ll start to see as many daily hospitalizations from Omicron as we saw at the peak of the Delta wave.  (That was, recall, where two states — AK and ID — declared crisis standards of care because they’d run out of ICU beds).

Second, this is just to get people ready for the shock.  Because if new case growth didn’t slow down, it’s a good bet that the new cases numbers will be all over the media tomorrow.

One caveat is that, even assuming I did the arithmetic right, there’s no way to know how good this new extrapolation is.  It’s the first time I’ve tried it.  But the bottom line is that simple extrapolation-of-trend puts us well into the hospital-admissions territory that caused trouble last time.  If we actually end up where my prediction suggests, then only hopeful thing we can point to is the lower ICU use per case, so far, for Omicron compared to Delta..  So maybe even if we fill all the acute-care beds, maybe we won’t fill the ICUs.  Just yet.

I never thought the U.S. would get anywhere close to this number of cases.

But I never thought we’d still be sleepwalking through the pandemic, either.  I see where the U.S. House of Representatives is finally going to require not just a mask, but a good mask, when in the Capitol complex.  Plausibly a NIOSH-certified N95.  All I can say is, what took you so long.  And how about suggesting that for the rest of us.

Post #1380: Omicron, I sure got it wrong.

 

I expected the U.S. Omicron wave to be short, sharp, and with very low average case severity.  That’s what occurred in South Africa, and that’s what I expected to see here.

If we’d repeated the South African experience, we’d have peaked by now. 

Instead, the Omicron wave in America is continuing longer, and moving  higher, than it did in South Africa.  And average case severity for new cases, relative to Delta, is higher here than it was in South Africa.  As a result, what I thought was going to be a fairly benign wave of COVID in the U.S. is starting to show some potential for turning into a true disaster.

In short, the South African experience was not a good model for what’s happening in the U.S., and the U.K., and some other European countries.

What are some possible reasons for that?  Turning that around, what are some major differences between South Africa and the U.S. that might have caused the Omicron wave to have differed?


Delta never left us.

Let me start with the most obvious contrast between South Africa and the U.S./U.K./Europe.

South Africa had a “pure” Omicron wave, in the sense that there were almost no pre-existing Delta cases circulating in the country.  All you ever saw there, for their short, sharp wave, was Omicron.  As you can see, the daily new case count was practically zero prior to the start of their Omicron wave.

In the U.S., by contrast, we never really finished our Delta wave.  You can see a significant case count of Delta already occurring by the start of the U.S. Omicron wave.  The U.S. — and most of Europe — was already in the middle of a mild (U.S.) to quite severe winter (U.K.) wave of Delta, when Omicron came along.

 

We know that Omicron is displacing Delta as a fraction of all cases Here’s the most recent CDC estimate:

Source:  CDC COVID data tracker accessed 1/20/2022.

(This is something that I’ve puzzled over before.   Somehow, each new strain manages to kill off the prior strains.  Alpha displaced the native (Wuhan) strain, Delta displaced Alpha, and in each case, more or less 100% of new cases end up being the new strain.  The older strain disappears.  But the mechanism behind that has never been clear to me.)

So, Omicron has been displacing Delta.  Or has it?  Delta has been falling as percent of cases.  But what has it been doing in terms of the actual number of cases?

Let’s convert the CDC’s Omicron-as-a-percent-of-new-cases numbers above to actual counts of Omicron and Delta cases.  That’s easy enough to do — just multiply the total new case count by those variant percentages. (There are a few fine points of method here — I filled in the daily percentages using the week-to-week growth rates above, I slid the whole assembly of daily percentages back by three days prior to the listed end-of-week dates, and and so on.  Those were all obvious things to do if you’d thought about it for five minutes.)

And despite how obvious it was to do this, I got a pretty big surprise.  Through Christmas 2021, Omicron did not displace Delta, it mostly added on top of Delta.

Source:  Calculated from case counts as variant estimates from the CDC COVID data tracker.

Above, the orange line is my estimate for the count of new Delta cases.  As you can see, that hadn’t really budged, as of Christmas 2021.  Omicron accounted for more than half of new U.S. cases by Christmas.  But it did that by growing on top of a fairly stable population of daily new Delta cases.

As simple and obvious as this now appears, I haven’t seen this point made elsewhere yet.  So I wonder if this is a new phenomenon.  Maybe this is some unique consequence of Omicron being so vastly more contagious than Delta.  As some point, if I can dig up the data, I may want to go back and see what happened at the Wuhan/Alpha and Alpha/Delta transitions.

The upshot is that one major difference between South Africa and the U.S. is the Delta wave.  South Africa didn’t have one.  All they had to deal with was Omicron.  But as of Christmas 2021, in the U.S., that winter Delta wave has not gone away.  It’s still here, hiding beneath the Omicron wave.  If anything, it appears to be fading slowly.


Difference sources of COVID-19 immunity

Another glaring difference between South Africa and the U.S./European experience is the mix of sources of COVID-19 immunity within the population.  Roughly speaking, most of our immunity comes from vaccination, most of theirs comes from prior infection.  Approximately like this:

Sources of information:

U.S. percent with prior infection is the count of positive cases as of 12/15/2021, times 1.9 (based on the most recent seroprevalence data from CDC, to account for cases not formally diagnosed), divided by total U.S. population.  All the COVID data are from the CDC COVID data tracker.

U.S. percent fully immunized and boostered is from the CDC COVID data tracker as of 2/1/2022.

South African percent fully immunized is from Our World in Data, rounded down to 25%. 

South African percent with prior infection is from this analysis from this  undated PowerPoint from the South African National Institute for Communicable Diseases.

To be clear, Omicron appears to be able to infect both the fully-vaccinated and prior-infection populations easily.  That is, based on the South African experience, there were a lot of breakthrough infections (among fully-vaccinated) and reinfections (among those recovered from prior infection).

If there were some difference in protective ability, then that might influence the course of the Omicron pandemic in these countries.  But the bottom line is that there is no hard evidence one way or the other, on this point.  Near as I can tell, all the evidence says that neither prior infection nor full (two-shot) vaccination provides significant protection against Omicron.  Which one is the lesser of two zeroes cannot be determined from existing data.

In theory, this ought to be roughly knowable from population-based administrative data available in the U.S.  In U.S. states, on a person-by-person basis, state health departments know who has tested positive for COVID-19 in the past, and who has been vaccinated (partially, fully, or boostered).  From that, they can (and some do) flag cases that are breakthrough (in a fully-vaccinated person) and reinfection (in a person with prior positive test for COVID-19).  If there is some new, significant different in immunity across those populations, then the ratio of identified reinfections to identified breakthrough infections should change as the Omicron fraction of all infections rises.

There is no doubt that a state health department could do this analysis.  That said, as an outside, I have yet to find a state health department that has published the relevant, current data, let alone done the analysis.

Instead, I have to rely on various scholarly studies.  Near as I can tell, these boil down to:

  • Neither prior infection nor standard (two-dose) vaccination provides much protection against Omicron, if any.
  • Studies disagree whether or not prior infection or vaccination provides better immunity.
  • There’s enough uncertainty around the estimates that it’s probably not possible to answer this question from existing research data.

The first study comparing natural immunity and vaccine immunity against Omicron is a study of infection rates of persons in Great Britain, using data from the end of November into early December.  Based on their sample sizes, they are unable to rule out zero protection from Omicron, from either source of immunity.  Omicron.  As reported at this link, based on the original research as reported at this link:

The reinfection risk estimated in the current study suggests this protection has fallen to 19% (95%CI: 0-27%) against an Omicron infection.
vaccine effectiveness estimates against symptomatic Omicron infection of between 0% and 20% after two doses, and between 55% and 80% after a booster dose.

A different study, using in vitro assays of immune response, again found little response from either prior infection or full vaccination, but suggested that the prior infection response was, if anything less than that of antibodies from fully-immunized individuals.  That’s reported at this link, with the original research at this link.

Antibodies from people double-vaccinated with any of the four most widely used vaccines—Moderna, Pfizer, AstraZeneca, Johnson & Johnson—were significantly less effective at neutralizing the omicron variant compared to the ancestral virus. Antibodies from previously infected individuals were even less likely to neutralize omicron.

I’m going to give up on finding anything more definitive for now.  Near as I can tell, neither prior infection or full vaccination provides much protection against Omicron, if any.  It seems unlikely that any small difference in effectiveness between these two sources of immunity would be able create such a large difference between the U.S. and South African experience.


COVID hygiene.

The research above suggests that neither full vaccination nor prior infection provides any significant protection against Omicron.  The logical implication is that for the roughly 70 percent of the U.S. population that has not received a booster dose, the only thing that slows spread of Omicron is COVID-19 hygiene:  Wearing a high-quality mask, staying out of high-transmission-risk situations, and the like.

Restated:  If most of the population has virtually no immunity to Omicron, then differences in COVID hygiene can play a significant role in determining variations in Omicron spread across nations.

For the U.S., as I have shown repeatedly here, mask use has hardly changed over the past month, based on data from Carnegie-Mellon University.

Source:  Carnegie-Mellon COVIDcast.

It’s tough to find hard data on the extent to which South Africans increased use of masks.

News reporting makes it clear that they take mask mandates seriously.  (Thousands arrested for not wearing masks, dated Feb 2021).  I don’t believe I’ve ever heard of an American arrested or even fined for failing to wear a mask.  And, while South Africa is now lifting other restrictions, failure to wear a mask in public remains a criminal offense.

Historically, rates of mask use in South Africa appear to have been comparable to those in the U.S., based on self-reported survey data from the end of 2020.  That’s reported at this link.

I can’t seem to find objective data.  But the presence of a national law that makes it a criminal act to be outside the home without a mask — actually enforced with arrests and penalties — suggests a far more serious attitude in South Africa than in the U.S.

So this remains a guess, but I’m guessing that South Africans take mask wearing more seriously.  Certainly compared to a country with no national mask mandate, where state mandates seem to be completely unenforced by law officers, and where many states have chosen to prevent localities from passing their own mask mandates.


Summary.

There’s no simple answer as to why South Africa’s experience with Omicron has been so vastly better than our own.

In part, we were already burdened with Delta, and we continue to be burdened with that.  But that, by itself, wouldn’t explain prolonged growth of Omicron here, compared to South Africa.  More total cases, perhaps, but not more growth.

In part, prior pandemic waves seem to have been somewhat shorter, consistent with the U.S. being a geographically sprawling country compared to South Africa.

In part, for both countries, out existing immunity defenses have largely failed.  Near as I can tell, neither prior infection (the main South African source of immunity to COVID) nor full vaccination (the main U.S. source of immunity to COVID) does much of anything against Omicron.  There, only the boostered population has significant resistance to symptomatic infection.  And that would argue for a smaller wave in the U.S. than in South Africa, as about 30% of our population has been boostered (against what I believe to be a negligible fraction of the South African population.)

Finally, in that case, if our main defenses against COVID-19 fail against Omicron, we’re down to our backups.  That’s mask wearing, distancing, and avoiding high-risk situations.  More-or-less, it’s as if we’re back to the start of the pandemic, and the only real barrier to transmission is COVID hygiene.

South Africa never took down its backup systems.  It had kept restrictions on some forms of social activity in place since the start of the pandemic.  It made mask-wearing outside the home a legal requirement, and enforced that.  And it kept that legal requirement in place, even after the end of the Delta wave.

In the U.S. by contrast, we dismantled the backups.  And that seems to be permanent.  The issue of mask-wearing has been so poisoned by the Republican party that few governors have the stomach for putting any sort of mask mandates back in place. (Or, alternatively, the U.S. population is so full of snowflakes on this issue that few governors dare to do that.)

And so, as a country, we’ve gone into the Omicron wave with no effective vaccine (without a booster shot), no effective protection based on prior infections, and a Republican-driven culture that prevents mere re-imposition of a mask mandate, let alone enforcement of it.

In effect, we have made ourselves purposefully defenseless.  No immunity, no mask.  Nothing except the booster shots, and the common sense of the people.

Once I boil it down that way, I guess it all starts to make sense.  We’ve already had far more cases that I would have remotely believed possible.  And it’s not clear that there’s a light at the end of the tunnel yet.

I keep asking “are we done being stupid yet”?  And the answer keeps coming back, “No”.  I got my prediction wrong.  But as a country, I think we’re fundamentally getting Omicron wave wrong.  If we have no effective immunity, and hospitals are starting to fill, we’re right back where we were in the winter of 2020.  And out COVID-19 hygiene ought to reflect that. But it doesn’t.

To sum up the U.S. situation:  We have

  • no immunity from prior infection,
  • no immunity from two-shot vaccination,
  • no mask use or other COVID hygiene policies,
  • no way to reimpose any such hygiene, and
  • a new variant that is off-the-charts contagious. 

In that context, an overwhelming U.S. Omicron wave starts to make sense.

Maybe things will turn out OK anyway.  Maybe we won’t generate enough cases to overwhelm the hospital system.  Maybe there will be a huge number of hospitalizations, but not so many ICU cases that hospitals run out of ICU beds.

Maybe we’re due for a break any day now.  But in the middle of what I’ve termed the “don’t give a damn” wave, we sure aren’t doing one whole heck of a lot to make that happen.