Post #1400, Part 3: When will Omicron pose no more risk than flu?


The genesis of this is a simple question:  At what point in this pandemic does COVID pose no more risk than flu does, at the peak of a typical U.S. flu season?

This turned out to be yet another of my TLDR posts, so let me just give the spoiler right here:  At 30 new Omicron cases / 100K / day.  And at 16 per day, it poses no more risk than the risk that flu poses for the average of the entire flu season (instead of the peak week).  Those are the rates at which, by my calculation, the average American faces no more risk of hospitalization or death from COVID-19 than from normal seasonal flu.

To be clear, my definition of “risk” involves both the likelihood of catching the disease, and then the typical severity of illness once you’ve caught it.  It’s the risk of just walking about minding your own business one day, and ending up in the hospital a week later with COVID or with the flu.

When you think of it that way, there’s always some point — once daily new COVID-19 infections have dropped to a sufficiently low rate — at which the risk of serious harm from COVID is less than the risk of serious harm from flu at peak flu season.  The point of this is to calculate that rate, to serve as one benchmark for a return to normalcy.  Once new cases get to that level, rationally, if you are a risk-neutral individual, you should only take about as much precaution against COVID as you do against flu.

This is, in a nutshell, how we’re going to get by in the shadow of “endemic COVID”.  We hope.  The disease itself isn’t going to become harmless.  It’s just going to become rare enough to pose little day-to-day threat.  We hope.

Think of Ebola, brain-eating amoebas, the plague, and so on.   Those are dread diseases, for sure.  But no rational resident of U.S. spends a lot of time worrying about them, or taking precautions against them, because the odds of contracting them on any given day, in the U.S., are more or less nil.  They are serious diseases, but they are not a significant threat in the U.S. 

That’s where we now hope Omicron is headed.  And this posts answers the question “how will we know when we’ve gotten there?”.

This analysis is a rough cut, for sure.  I’d like to do one more iteration, because the only people I care about, in this analysis, are those who are fully vaccinated and boostered.The people who won’t bother to do that pretty clearly aren’t worried about their risks.  So why should I be?

That vaccinated-only comparison turns out to be difficult to do, for a variety of reasons.  I’ve been trying, without success, to write this up that full calculation, for about the past week.  I may never have the data to do that well.  So let me just grind out the calculation for the average of all persons — vaccinated and not — and be done with it.  I’m quite confident that the results I show here are conservative, in the sense that they overstate the COVID-versus-flu risk for fully-vaccinated individuals.  Think of these results as a lower bound on the levels of COVID that should cause only minimal concern to a fully-vaccinated individual.

Background and recap

In my first post in this series, I made the argument that we lucked out with Omicron.  Evolutionary pressures move successive variants of COVID-19 toward greater infectiousness and toward “immune escape”.  But the virulence of each new dominant variant is really a matter of chance.  Delta was much more virulent, Omicron is much less virulent, compared to the original (Wuhan) strain.  And, just by chance, the variant that has come out on top (for the time being) generates a lower average severity of illness compared to prior variants.

In my second post in this series, I tried and failed to get my mind around what “endemic Omicron” will actually mean.  We’ve got another month or two of very high new case rates, in the current Omicron wave.  And after that, the consensus of scientific opinion seems to be that we’ll probably have COVID-19 circulating in the population, at some low level, permanently.

But Omicron isn’t very much like any of our other endemic infectious diseases.  In particular, that combination of being extremely infectious and airborne, and yet lacking a permanent vaccine or permanent immunity of any sort, just seems to put this in a different league, to me.  I can’t help but think that serious outbreaks will be part of the landscape, to a far greater extent than we see with (e.g.) seasonal flu.

That said, from what I read, the model for “endemic Omicron” that most people seem to be settling on is flu.  In the long run, so the story goes, COVID-19 will be just another disease like influenza.  If you’re worried about it, get vaccinated, stay out of crowds when there’s an outbreak going on, maybe mask up if you are vulnerable.  Wash your hands.  But otherwise, just get on with your life.

In this post, I want to do as thorough a job as I can, to compare the risk of harm from Omicron and typical flu at the peak of flu season. My focus is in estimating the risk of serious illness for someone who is fully vaccinated and boostered against COVID-19. 

It’s not as easy to do this as you might think, because where data are available, they will refer to averages for the entire population.  I’m going to have to “back solve” to break those down for the vaccinated and unvaccinated populations.

But the basic point is simple:  If we can get to the point where your risk of illness from Omicron is essentially the same as your risk from flu, then … if you don’t take extraordinary steps during flu season, you really shouldn’t feel compelled to take extraordinary steps against Omicron season.

Outline of the analysis.

So here’s the exact question.  Let’s say you’re the average American, out and about on a day during typical U.S. peak flu season.  You incur a (small) risk of getting flu, and an even smaller risk of getting a case that’s so severe that you’ll end up either hospitalized or dead.  And you typically think nothing of it.

How rare would new Omicron case have to be, in order for Omicron to pose the same level of risk, compared to a peak week of seasonal flu?

And I want to know that for the fully-vaccinated population, in each case.  Vaccinated against flu, and vaccinated and boostered against Omicron.

There is going to be a lot of imprecision in this analysis.  Rather than bore you with the methodology first, I’ve decided to present the numbers first.  And bore you with methods last, if I have the time to write that up.  Just rest assured that a lot of quantitatively important issues are being swept under the rug at this point.

I’m boiling this down to risk of hospitalization and death, fully acknowledging that there are aspects of illness beyond those two simple measures.  The problems are that a) nobody tracks the numbers on those other aspects of COVID-19 illness, and b) there’s no flu equivalent to things like long COVID, or loss of sense of taste and smell.

In short, the only possible head-to-head comparison between COVID-19 and flu is in terms of risk of hospitalization and death.  Because those are the two things that are routinely tracked, and that are common to both illnesses.

The plan of attack is as follows:

  1. Get the raw (average) case hospitalization rate and case mortality rate data put down in black-and-white.
  2.  Do the crude flu-versus-Omicron comparison based on those raw numbers.
  3. As and if possible, adjust the numbers to account for differences in severity between the vaccinated and un-vaccinated populations.

Given the vast uncertainties involved, at the end of this, I’ll just wave my hands about methodological uncertainties.  I mean, at this point, we don’t even really know whether Omicron is what we’ll be living with in the long run.  So there’s no justification in splitting hairs on the accuracy of the analysis.

Step 1:  The basic numbers on case hospitalization and case mortality rate

One step at a time.

1.1  Flu case hospitalization and mortality rates.

Let me start from the CDC’s estimates of the illness burden of flu, on this CDC web page.  Here, I’ve just ignored the statistical uncertainty (the 95% confidence intervals) and taken the median of values for the past ten US flu seasons.  I’m also ignoring some potentially significant differences between the definition of “a case” as used here, and as used in the Omicron analysis below.

Source:  Calculated from CDC illness burden of flu web page.

In a typical year, calculating from the CDC data, in the U.S., 1.4% of persons with a symptomatic case of the flu end up in the hospital, and 0.13% die.  So those are the benchmarks for something we can routinely live with.

1.2 Omicron case hospitalization and mortality rates.

Source:  Calculated from CDC COVID data tracker files access 1-19-2022. 

As I have noted in numerous prior posts, there’s essentially no lag between new cases as reported, and new hospitalizations as reported.  Therefore we can calculate a true case hospitalization rate right on out to the last available day of data.

Mortality is not so straightforward.  In theory, you only know the ultimate mortality rate months after-the-fact, because you have to wait to see whether or not people diagnosed on a given day ended up dying.

In practice, I’ve had good success with a much cruder approach, which is to divide current deaths by new cases from two weeks earlier.  This accounts for the roughly-two-week median time from diagnosis to death for COVID-19 decedents.  (Whether or not that has remained at roughly two weeks, with Omicron, is not known at this time).

From the look of the graph, the case hospitalization rate has stabilized, and is currently about 2.6 percent.  The case mortality rate appears to be continuing to fall, and I’m not sure what to make of that.  The final value in the series is 0.34%, so I’m sticking with that.

1.3  Final estimates, flu versus Omicron case rates, raw data (no adjustments for impact of vaccination).

And so we get the table above, showing un-adjusted values.  In round numbers, a symptomatic Omicron infection is about twice as likely to land you in the hospital, and about three times as likely to kill you, compared to a symptomatic flu infection.

I want to note that this is vastly better than the way things looked earlier in the pandemic.  The very first wave of the pandemic had a case mortality rate around 8 percent, both here, and in China, and in the U.K.  Later, the Delta wave — which occurred after mass vaccination of the population — had a case mortality rate and case hospitalization rate were more than three times what’s shown above. The point being that the current situation really is different from what has gone on before.

In short, with Omicron, and with a lot of vaccination and prior infection, we’ve finally gotten a COVID-19 variant whose danger is somewhere in the ballpark of that of flu.  That’s a first for the pandemic.

Riskier, for sure.  Twice the hospitalization rate, three times the mortality rate.  But no longer orders-of-magnitude riskier.

Step 2:  The crude calculation, before considering the separate impact of vaccines.

This part is not rocket science.  If COVID’s case rates for hospitalization and death are 2-times and 3-times that of flu, then COVID presents the same risk as flu when your odds of getting infected are one-half (hospitalization) to one-third (death) as high as they are for flu.

2.1 Just how bad is a typical peak week of flu in the U.S.?  How bad is the average week, year-round?

As noted in the prior section, the U.S. sees about 30 million symptomatic flu cases in a typical year, according to the U.S. CDC.  To allocate that to individual weeks, and find the peak rate, I used the 2017-2018 flu season as a model, and assumed that symptomatic flu cases occurred in proportion to the CDC’s estimate of visits for influenza-like-illness at their network of sentinel (reporting) providers.  All of the underlying data come for the CDC web pages on the disease burden of flu.

When I do that, I come up with about 2.1M new U.S. symptomatic flu cases in a typical peak flu week.

Translating that to the language we use for Omicron, that works out to 100,000 x ((2.1M / 330M) / 7)  = 91 new flu cases per 100K population per day at the peak of flu season.

If I crudely define “flu season” as the 18 weeks were new case rates remain at or about 500,000 per week, then the average daily risk of flu, during flu season works out to an average of 100,000 x ((20.6M / 330M) / (18 x 7)) = 49 cases per 100K population per day.

2.2 The crude calculation

In round numbers, Omicron has twice the case hospitalization rate and three times the case mortality rate.  Taking the greater of those two, the “case rate risk” of Omicron is three times that of flu, averaged over all persons.  So we’d need to see one-third the number of new Omicron cases for the overall risks to be equal.

If we take the peak of flu season as our benchmark for risk, the mortality risk from Omicron infection would be no higher than that of flu when Omicron gets down to 30 new cases / 100K / dayIf we take the entire flu season as the benchmark, then the risk from Omicron matches the all-season risk from flu when Omicron gets down to about 16 cases per 100K per day.

Conclusion for now.

I think this has been a good start, and I’m going to stop right there, for the time being.

The clear bottom line is that, at present, Omicron poses a vastly higher risk of hospitalization and death, for the average American, relative to seasonal flu.  Call it ten-fold higher risk.

In part, that’s because it’s two to three times as virulent, per case.  But mostly, that because there’s just so much of it in circulation.

I’m starting to home in on a level of Omicron at which, if I am rational and risk-neutral, I should be no more worried about Omicron than I am about season flu.  Based on this first cut of the calculation, that ought to occur at either 30 new Omicron cases / 100K / day (if peak flu week is your benchmark), or 16 new Omicron cases / 100K / day (if all of flu season is your benchmark).

While that seems like it will be an eternity from now, if cases continue begin to fall at 30 percent per week (typical internationally, slower than what we see in individual states right now, per last post), it would only take about six weeks for case rates to get down to that upper benchmark level.

Mid-March?  Will Omicron in the U.S. reach that first benchmark by mid-March?  If so, and if I’m rational, and risk neutral, and the next analysis (including vaccination) does not materially alter this, then that’s the point at which I resume all prior activities.  (Maybe masked, because why not).

Because, to put it plainly, it would never even occur to me to avoid going to the movies during flu season.  Just would not cross my mind.  And that’s now my benchmark for que sera sera.  It’s the point at which I’m willing to throw in the towel and say I’ll just live with endemic COVID.

The final question is whether these benchmarks are materially incorrect for the fully-vaccinated?  My suspicion is that they are, but they err on the side of caution.  That is, if I can work up a comparison of a fully-flu-vaccinated and fully-COVID-vaccinated-and-boosted individual, I’ll find that the COVID vaccine is way more effective than the typical flu vaccine.

Putting that another way, all these years that I have faithfully gotten the flu vaccine, I had no idea what poor performance flu vaccines offer.  Worth doing, for sure.  But nowhere near as effective as COVID-19 vaccine plus booster.

If I can find the data, and work out the math, I’ll do that final phase of the calculation.  But what I have found to date is that looking into how the U.S. monitors and treats flu is an exercise in turning over rocks and seeing what crawls out from beneath.  Every time I look into the details, I wish that I hadn’t.  So I may or may not get around to my ultimate goal, which is to find these benchmark rates for completely vaccinated individuals.

Post #1400, Part 2: Endemic Omicron


In this post, I’m trying to guess what the world will look like after the current Omicron wave ends.

In a nutshell

  1. The consensus of informed opinion is that COVID-19 will become endemic to the U.S., just another one of the many diseases continuously circulating in the population.
  2. How that will work, exactly, nobody seems to be able to tell you.  I can’t quite get my mind around Omicron (or its successors) just fading into the background, given that it’s both extremely infectious and good at evading the immune system.
  3. Best guess, if you are smart enough to stay fully vaccinated and boostered, your overall risk from Omicron won’t be materially different from your overall risk from flu.  I do a rough cut to show that in this post, and plan to do a more systematic job of that tomorrow.
  4. Why, then, is Omicron stressing out the U.S. hospital systems in ways that the flu never does?  One key is in italics above.  That’s due to the high burden of illness among the unvaccinated.  This really is, still, mostly a pandemic of the unvaccinated.  The second factor is simply the sheer volume of weekly new Omicron cases, which I estimate to be four times the  volume of symptomatic flu cases in a typical peak week of flu season.
  5. And the upside of that is that if you are fully vaccinated, right now you are not facing risks from Omicron that hugely greater than those from flu.  In fact, most of your excess risk isn’t due to the virulence of Omicron compared to flu, it’s due to the high prevalence.  There’s just a lot of Omicron going around right now, compared to flu during flu season.  Once we get past this peak, as long as Omicron remains the dominant variant, in the long run, severe illness risk from COVID-19 risk, for the fully-protected population, should be no higher than the risk from flu.

Source:  Calculated from Virginia COVID-19 data by vaccination status, week ending 12/25/2021.

Looking past the end of the Omicron wave.

Now that Omicron is getting ready to peak in the U.S., it’s time to start thinking past the end of the Omicron wave.

If there is an end.

It appears that the overwhelming scientific consensus is that we’re stuck with COVID-19 permanently.  As in, 90% of qualified scientists thought it was going to be end up endemic here in the U.S. (Reference), just one of many diseases constantly in circulation in the population.  And that consensus dates back a year, when we were merely dealing with the native (Wuhan) strain of it, not the vastly more infectious Omicron strain.

Once upon a time, I figured the 2021/22 winter wave would be the end of the COVID-19 pandemic.  That wasn’t just wishful thinking, or mindless analogy to the 1918 flu pandemic.  My calculated guess was that by the end of this 2021/22 winter wave, nearly everyone would have been either fully vaccinated or infected.  Throw that level of immunity into your basic math for epidemics, chuck some reasonable estimate of infectiousness (“R-nought”), and presto, the pandemic should end.

That involved some wishful thinking.  But I really couldn’t contemplate the alternative.

But Omicron changed the math quite a bit.  Not only is it vastly more infectious than prior strains, it’s able to avoid existing immunity to a far greater degree.   Put those new parameters into the basic pandemic equation and it’s hard to see an end to the pandemic.

I don’t think you even need to bring up the unvaccinated to reach that conclusion.  (Although they they certainly aren’t helping things.)  My guess is that the slow decay of natural immunity over time would continuously generate enough new carriers to keep the disease in circulation, given how contagious it is.  Plus, we don’t have a vaccine good enough to put this particular genii back into the bottle anyway.

If the R-nought for Omicron is somewhere around 15, that means you have to stop 14 out of 15 chains of infection in order to bring this pandemic to a close.  If we take no other precautions against spread of disease, that would require that more than 93% of the population have perfect immunity to Omicron.  It’s not possible to achieve that when vaccine plus booster is only perhaps 70% effective in preventing symptomatic infection with Omicron.

But somehow, even though I believe the scientific consensus on this, I can’t quite get my mind around how “endemic COVID-19” is going to work. 

These are certainly examples of diseases that emerged in the U.S. over the past few decades and are still here.  (Emerged meaning that they weren’t here before.)  They are endemic — just part of the background of everyday life in the U.S.A. now.

AIDS.  Zika.  Multi-drug-resistant tuberculosis.  Lyme.  West Nile.  Legionnaire’s disease.  Dengue.  E. coli that can kill you.  Hantavirus.  Methicillin-resistant Staphylococcus aureus (MRSA).  And so on.

The trouble is, Omicron is qualitatively different from any of those diseases listed above.  And it is different from common highly-contagious diseases that we currently control with long-lasting vaccines, such as the numerous formerly-common diseases of childhood (measles, mumps, rubella, varicella, and so on).

And Omicron is qualitatively different from flu, in that it’s vastly more infectious.  A typical estimated R-nought for seasonal flu is somewhere around 1.5.  For Omicron, it’s about ten times that.

As a result, I can’t find any obvious model for how “endemic Omicron” would play out.   I can’t quite wrap my head around how the world will look with a disease that is:

  • currently quite common.
  • Airborne, so requires no vector and requires no physical contact for infection.
  • About as contagious as a disease can be (I did not come across any diseases with  estimated R-nought materially higher than 15, which is best-guess for Omicron).
  • Sometimes causes acute illness and death (more on that below).
  • Still frequently undergoing major mutations.
  • Able to bypass immunity developed from prior infections with other strains.
  • And for which vaccine-induced immunity fades with half a year.

I don’t think there’s another disease in existence today that matches those characteristics.  And so, I’m having a hard time figuring out how we could possibly have a stable, background pool of that, constantly circulating at low levels in the population.  Something about that description of an endemic disease just doesn’t quite line up with Omicron’s ability for explosive growth due to its high R-nought (infectiousness), combined with its ability to evade much of the immune system.

What happens immediately after the Omicron peak?

We can look at South Africa to see that they’ve had a fairly long “tail” to their Omicron wave.  They peaked around 12/17/2021 — just about the time the U.S. got started.  Cases fell rapidly for about two weeks.  And then the rate of decline slowed.  Four weeks after peak, they’ve still got about 25% of their peak case rate.

The U.K. appears to be following roughly the same trajectory so far.  They are less than two full weeks after their peak, and cases have fallen from about two-thirds, from 200K per day at peak to 70K per day.

If the U.S. were to follow the same trajectory, and if we’re hit our peak this week (say Wednesday 1/19/2022) at around 250 cases per 100K per day, we’ll still be looking at:

  • 80 new cases / 100K / day for around February 1.
  • 60 new cases / 100K / day around February 15.

Just for comparison, in 2021, during the mid-summer lull, we had almost two months when the new case rate never exceeded one-tenth of that.  Those were the months when (e.g.) I went back to going to the gym, and so on, due to the low risk of infection.  Months where I would say we could approach normalcy.

The point is, if you won’t feel safe until there’s relatively little virus in circulation — say as little as there was last summer — you’re going to have to keep your guard up for some months yet.

I realize that I keep talking about the peak of the Omicron wave as something to look forward to.  But, in reality, it’s just another way of saying that this is as bad as it gets.  If we follow the South African trajectory, there will still be plenty of opportunity for infection for at least a month after the peak.

And in the long run? There are too many unknowns right now.

Let me just pretend for the time being that Omicron is the final and most successful mutation of COVID-19.  And so, as the winner of that competition, that’s the one we have to live with.

If I had to pick out the single largest unknown in how “endemic Omicron” works out, it would be whether Omicron can readily re-infect people after an Omicron infection.  It’s already well-established that it has a high re-infection rate among those who have recovered from some other strain of COVID-19.  British research seemed to show that prior infection provided almost no protection against Omicron (reference).  And we’re now seeing the same sort of high reinfection rates that were first observed in South Africa.  Below is a graph from Missouri showing that almost eight percent of recent cases are reinfections.


But nobody knows (yet) whether Omicron can reinfect people readily after a prior Omicron infection.  (Or, if so, I haven’t seen it.)  If Omicron can readily reinfect individuals following a prior Omicron infection, then the population will never achieve much in the way of immunity to Omicron.  We might develop immunity to severe disease, but not immunity preventing any infection.

The second big unknown is how effective the new Omicron-specific vaccines will be.  One is already in production and is slated to be available in March (per this reporting).  I have not seen any data on how much more effective the new vaccine is.  (And, per this reporting, manufacturers are reluctant to jump in for fear that the vaccine will be made obsolete by yet another mutation of COVID).

Let me sum it up to this point.

  • The scientific consensus is that COVID-19 will become endemic.  That is, it will always be circulating at low levels in the population.
  • How that’s going to happen, nobody can tell you.
  • I’m skeptical that we’ll reach some nice, stable background rate.  I think the combination of airborne + extremely infectious + high levels of immune escape just begs to result in outbreaks.
  • Nobody can even start to guess what the long run will look like until we have some handle on whether an Omicron infection confers significant immunity against Omicron, and on how effective the new Omicron-specific vaccines will be.


Comparison of risks between Omicron and flu

Since nobody can tell you what “endemic Omicron” will look like, let me turn it the other way around.  How different are the risks now posed by Omicron and by common seasonal flu? 

I’m not ready to put up the numbers on this one yet, so this is just a teaser for a more complete analysis.  I hope to do a more refined set of numbers as the third and final post in this series.

I already looked at this issue crudely in Post #1364At that point, with that crude comparison, I could already see that the numbers were in the same ballpark.

Now I want to take the most recent U.S. data and ask a very specific question:  How different are the risks to a person concerned enough to get fully vaccinated?  So I’d like to know the risks faced by an individual who gets an annual flu shot (for flu), and an individual who is vaccinated and boostered (for Omicron).

That turns out to be a fairly involved task, because most of the data we have for either disease is for the population as a whole.  So in my final post in this series, I’m going to take the raw numbers and try to “back solve” for the risk faced by the prudent and fully-vaccinated individual.

But I can already tell you that the answers are shaping up to offer some pleasant surprises.  Mainly, as far as I can tell, the case mortality rate for Omicron, for a fully-vaccinated individual, now appears to be roughly the same as for seasonal flu.

Let me do the quick-and-dirty cut of the numbers here, to show you were I’m headed.

Start from the CDC’s estimates of the illness burden of flu, on this CDC web page.  Here, I’ve just ignored the statistical uncertainty (the 95% confidence intervals) and taken the median of values for the past ten US flu seasons.

In a typical year, in the U.S., 1.4% of persons with a symptomatic case of the flu end up in the hospital, and 0.13% die.  And there are about 30M symptomatic cases.  So those are the benchmarks for something we can routinely live with.

The question I want to ask and answer is, how does that case mortality rate compare to the average fully-vaccinated and boostered individual with Omicron?  That’s going to take some back-solving from the observed data.

But just crudely, let me pull out some mortality data from Virginia, putting a two-week lag between case counts and death counts to account for the median time from infection to death.  Here I’m looking at Virginia data broken out by vaccination status, on this web page.

For the past three weeks, the highest mortality rate observed for fully-vaccinated individuals in Virginia was 0.12 per 100K population, for the week ending 1/1/2022.  (Earlier weeks show substantially higher rates, but that’s reaching back into the Delta era.)  Going back two weeks, to the week ending 12/18/2021, the fully-vaccinated population contracted Omicron infections at the rate of 111 per 100K population.  Therefore, my two-week-lag case mortality rate for the fully vaccinated population of Virginia is (0.12/111 =) 0.11%.

Compare to the 0.13% from the table above, for flu.  It’s really not that different.

That’s one week of data, that doesn’t account for flu vaccination, and so on and so forth.  On the other hand, “fully vaccinated” is a mix of those who only have two shots, and those who have also gotten a booster shot.

So it’s a rough cut.  But I think this demonstrates that, once infected, Omicron’s risk for a fully-vaccinated person is probably just about on par with the risk from seasonal flu.

Why does the overall severity of illness from Omicron appear much worse that from flu?  Aside from a larger number of total cases, it’s due entirely to the vaccine-stubborn population.  If you’re smart enough to get vaccinated and boostered, the only excess risk you face from Omicron relative to flu arises because there’s such a high Omicron infection rate right now.  And not because the average case of Omicron has higher severity of illness than the average cost of flu, for the fully-vaccinated population.

Source:  Calculated from Virginia COVID-19 data by vaccination status.

Addendum:  But are there really vastly more new COVID-19 cases each week than there are weekly flu cases in a typical year? Interestingly, the answer is no, there are not.  More, yes.  Vastly more, no.

Right now, at the peak of the Omicron wave, the U.S. is identifying roughly 5.5 million new COVID-19 infections per week. You’d have to guess that for every identified case, there’s another one that was not formally identified.  So that would yield about 11M total new COVID-19 cases each week, in the U.S.

By contrast, the CDC estimates (above) about 30M flu cases in a typical year.  By looking at the weekly data for a typical year (I choose 2017-2018), the peak weeks of flu season typically account for 9 percent of the year’s cases.  Doing the math, in a typical peak flu week, the U.S. gets roughly 2.7M symptomatic flu cases.

The upshot of that our all-time peak Omicron week generates only about 4 times as many cases as our typical peak flu week. 

Post #1400, Part 1: Omicron and luck


This is the first of what I expect to be three posts, trying to look past the peak of the Omicron wave.

These next posts aren’t going to very cheery, so let me gratuitously toss in this graph of how well the U.K. is recovering from its Omicron wave.  In the past two weeks, they’ve gone from 200K cases per day to 80K.

Source:  Google.

There is a light at the end of the tunnel.  We might even see the same sort of rapid decline in cases here in the U.S., once we’re past our peak.

That’s enough good cheer for the time being.  Now it’s back to business.

Will we ever admit how lucky we were, with Omicron?

We dodged a bullet with Omicron.  I’m wondering whether anybody of importance is going to admit that.  And, maybe even have some intelligent discussion about what that means going forward.

Omicron produced much less severe illness, on average, than the prior strain (Delta).  But that was entirely a matter of luck.  If the roll of the genetic dice had turned out differently, we’d be filling mass graves now instead of sending our kids back to school and trying to get on with life.

Why?  As I understand the theory of it, ability to spread is more-or-less the only significant determinant of which variant of COVID becomes dominant.  This is almost by definition. The virus succeeds by spreading.  The better it is at infecting people, the more successful it is.

  • The Alpha (British) variant was about 1.6 times as infectious as the native (Wuhan) strain.
  • The Delta variant was again about 1.6 times as infectious as Alpha.
  • Omicron is maybe 3 times as infectious as Delta.

All other characteristics of a new successful variant are essentially chosen at random.  They are whatever-happened-to-occur on the virus whose mutations made it the most infectious of its generation.  They are the random hitchhikers on whichever ride is fastest.

I want to emphasize that what I just said isn’t just the opinion of some random blogger.  It’s  mainstream scientific thinking on how viruses evolve.  The popular notion that diseases must  get “weaker” as they evolve dates back to the 1800s, and has been “soundly debunked”, per this reporting, (emphasis mine):

As evidence mounts that the omicron variant is less deadly than prior COVID-19 strains, one oft-cited explanation is that viruses always evolve to become less virulent over time.

The problem, experts say, is that this theory has been soundly debunked.

Or, if you prefer a quote from an actual science publication, try this one, (emphasis mine):

“There’s this assumption that something more transmissible becomes less virulent. I don’t think that’s the position we should take,” says Balloux. Variants including Alpha, Beta and Delta have been linked to heightened rates of hospitalization and death — potentially because they grow to such high levels in people’s airways. The assertion that viruses evolve to become milder “is a bit of a myth”, says Rambaut. “The reality is far more complex.”

The upshot is that evolution breeds successful new COVID-19 variants based on their ability to spread, but the virulence of a successful variant is totally random.  As long as most of those who are infected can walk around for a few days infecting others, what happens after that is irrelevant.  Absent an Ebola-like mortality rate, there’s no strong evolutionary pressure on virulence one way or the other.

What if we’d had a different roll of the dice?

Consider where we’d be if Omicron had merely had the same average severity of illness as Delta.   Again, just by chance.

In the U.S., we’ve reached the point where daily new Omicron cases are five times the level seen at the peak of the Delta wave:

If Omicron had the same case hospitalization rate and ICU use rate as Delta, and our behavior did not change, we would have already filled about three-quarters of all U.S. hospital beds with Omicron patients.  More to the point, we’d have filled 150% of U.S. ICU beds with COVID-19 cases.  If we had combined Omicron’s case count with Delta’s severity, we’d have run out of ICU beds a couple of weeks ago.

Source:  Calculated from US DHHS unified hospital dataset.

To a close approximation, the only reason that didn’t happen is chance.  Just plain dumb luck.  That’s all that stood between having a somewhat stressed-out cadre of U.S. ICU nurses, and mass graves for all the COVID-19 cases that needed an ICU bed but couldn’t get it.

But immune escape isn’t random at all.

I want to make just one more grim little point about COVID-19 variants.

The ability of a virus to spread occurs against a background of the existing immunity within the population.  If you’ll read the article cited above, there’s some hint that it is not merely by chance that Omicron is good at re-infecting those who had prior variants, and not merely by chance that Omicron is good at evading immunity established by existing vaccines, which themselves targeted those prior variants.  Those “immune escape” characteristics of Omicron are plausibly (though not definitively) a product of evolutionary pressures.

Just for a moment, consider where Omicron evolved:  South Africa.  In the province where Omicron first emerged, roughly 70% of the entire population had antibodies against the prior strains of COVID-19 (reference).  Omicron emerged in an environment that virtually required that the next winning COVID-19 variant be able to get past immunity to prior COVID-19 strains.

To be clear, that point isn’t just random fear-mongering.  Viral evolution to escape the immune system is part of mainstream scientific thinking.  Scientists were busily predicting the ways that COVID might achieve immune escape long before Omicron was on the scene (reference).

In South Africa, at some point in their Omicron wave, their government noted that about 8 percent of their Omicron cases were re-infections.  That was, at that time, unusual enough to merit notice.

And in the U.S.?  Near as I can tell, it’s starting to look the same.  The only state I know that had the foresight to track reinfections routinely is Missouri.  As of a couple of days ago, nearly 8 percent of infections in Missouri were re-infections (below).  That’s a radical departure from earlier periods, and so presumably that’s due to Omicron.


I want to put a little addendum on this, because the nut-o-verse has this fixed idea that “natural immunity” from infection is superior to what you can get from a vaccine.  So I want to be clear that these are re-infections, not breakthrough infections (infections of vaccinated individuals).  These are people who had recovered from some prior strain of COVID-19, and so had all the “natural immunity” that can provide.  And yet, they were infected all over again Omicron.

In any case, the striking re-infection rate that was noted in South Africa seems to be occurring in the U.S. as well.  And that’s probably not random at all.

On the plus side, I gather that, as with breakthrough infections of vaccinated individuals, re-infections tend to be milder than average.  Even if the virus can evade some parts of your immune system, other parts of your immune system remain primed to fight it.  As a result, a lower portion of individuals with breakthrough infection or re-infection end up with severe cases.

Summary of Part 1

To me, this good news / bad news story — Omicron’s combination of low severity and high infectiousness — reminds me of those times when NASA tells us that Earth just had a near-miss with some heretofore unknown killer asteroid.  I guess we’re supposed to feel good about that, compared to the alternative.  But a rational person can’t help but ask, “what about the next one”?

And that’s where I’ll end Part I

Post #1408: COVID-19 trend to 1/20/2022. Everything remains on schedule


The Omicron wave appears to be unfolding on schedule in the U.S., plus or minus a few outlier states.

The U.S. east coast (Northeast and South Atlantic regions) led the way on the upswing.  Ten days ago, those regions had the highest  new case rates in the nation.  Now they have the lowest.

By contrast, the entire mid-section of the country started later, and is still more-or-less in the upswing portion of this wave.  Those regions are only now starting to top out.

The net result of all of that, for the U.S. as a whole, is that new COVID-19 cases fell seven  percent in the past seven days.


Continue reading Post #1408: COVID-19 trend to 1/20/2022. Everything remains on schedule

Post #1407: COVID-19 trend to 1-19-2022


Daily new COVID-19 cases continue to fall throughout the Northeast region, and are falling particularly rapidly in the NY/NJ area.  By contrast, case counts continue to rise through much of the Midwest, South Central, and Mountain regions.

The result is that the U.S. average new case count continues to decline.  For the past seven days, case counts are down about 3 percent on average. Continue reading Post #1407: COVID-19 trend to 1-19-2022

Post #1406: COVID-19 trend to 1/18/2022, post-peak.


Today almost every state reported data.  This makes the numbers somewhat less uncertain than they were yesterday.  The rate of new cases per 100K per day is unchanged over the past seven days.  I’ll mark the peak of the U.S. Omicron wave as 1/16/2022, almost exactly one month from the date on which new case growth began accelerating. Continue reading Post #1406: COVID-19 trend to 1/18/2022, post-peak.

Post #1405: COVID-19 trend to 1/17/2022, U.S. Omicron peak.


Only about half of states reported new case numbers today, owing to yesterday’s King Day holiday.  That makes it hard to be precise about the exact trend.  That said, a few things are fairly clear.

New case counts are now falling rapidly in New York and New Jersey, and in much of the South Atlantic region.  These are the areas that led on the upside of the Omicron wave, and they are now leading it down.  New York and New Jersey are down by about one-third from their peak rates, seven days after the peak.  The rapid rate of decline is certainly a good sign.

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 1/14/2022, from”  The NY Times U.S. tracking page may be found at

Most of the very largest states reported data.  The major exceptions were Florida and Illinois.  Given that, I’m fairly confident in saying that the U.S. new case count has peaked.  There was essentially no difference between a curve constructed for all states (where I extrapolate the missing data) and a curve constructed solely from the states reporting valid data for yesterday.

Finally, we get confirmation of a short-term peak from the U.S. hospitalization data.  Through yesterday, it appears that total new COVID-19 admissions peaked more-or-less at the same time as new cases.  Which is just about right, for the timing of it.

Source:  Calculated from US DHHS unified hospital dataset.

That said, we’re hardly out of the woods.  Only on state (Maine) has a new case rate below 100 new cases / 100K / day.  Some states (notably Wisconsin)  remain in the rapid-growth phase of their Omicron waves.

But as a country, it looks like we’re over the hump.  We’re running a bit behind Canada and the United Kingdom.  But better late than never.

Source: Google

And, thanks to a generally lower severity of illness of Omicron, so far we’ve done it without stressing large segments of U.S. ICU bed capacity.  In two-thirds of states, COVID-19 cases occupy 30% or more of all available ICU beds.  But in only one state (MD ) do COVID-19 cases occupy more than 40%.

Source:  Calculated from US DHHS unified hospital dataset.

When I think about how this might have turned out – if we’d gotten a variant as infectious as Omicron and as lethal as Delta — I have to conclude that we dodged a bullet with this one.

Post #1404: Apparently, the Governor didn’t read the law, or didn’t care.


In Post #1403, I noted how badly-written the Governor of Virginia’s Executive Order 2 is.  This is the order that guts all mask mandates in K-12 schools in Virginia, starting 1/24/2022.

Along with various grammatical errors, some truly awkward writing, and bizarre rationales (e.g., children’s masks collect parasites), the Governor managed to get the name of the U.S. CDC wrong.  Got it wrong, in the process of  mis-characterizing the CDC’s research on effectiveness of masks in schools.

It looked like somebody threw it together, and never bothered to check anything.  Not the grammar, not the facts, and not the logic.

Turns out, another thing they didn’t bother to check was the law of the Commonwealth of Virginia.

I’m just going to given you a reference to the reporting on this issue, because that explains it clearly.  Read it at this web page, from WJLA.

The gist of it is that the Virginia legislature passed a law last year that required schools to remain open for in-person instruction, and required them to follow the CDC’s advice on mitigating COVID-19 risks.  This was passed with bipartisan support.

On the face of it, that’s typical sound Virginia legislation.  Keep the schools open, but do it as intelligently as you can.  Burden every school district to adhere to national safety standards in this area, as promulgated by CDC.

For my last post on this topic, I looked up the current CDC guidance.  Yep, they still call for universal indoor mask use in schools.

Source:  US CDC (that’s Centers for Disease Control).

Either the Governor was unaware of the law, or chose to ignore the law, or maybe will now claim that the law doesn’t say what it plainly appears to say.

Let me lift a quote from the WJLA reporting, so you can see exactly how clearly this is stated in the law:

The bill also says school districts should "provide such in-person instruction in a manner in which it adheres, to the maximum extent practicable, to any currently applicable mitigation strategies for early childhood care and education programs and elementary and secondary schools to reduce the transmission of COVID-19 that have been provided by the federal Centers for Disease Control and Prevention."

And now, Republicans in Virginia government are claiming that the law doesn’t actually say what it appears to say.  School districts are either setting themselves up to follow the law as written, or to follow Executive Order 2, as they choose. And the net result of the Governor’s Executive Order 2 will be to sow discord and confusion, and force the issue to be settled in the courts.

Post #1403, Why can’t Virginia be more like Florida?


I knew it was too good to last.  Republican mask nuttiness has come to Virginia

Our new Governor has not only rescinded a state-wide mask mandate for K-12 schools, he has barred any school district or school or school teacher from enforcing any sort of mask requirement.  Executive Order 2 (.pdf) takes effect on 1/24/2022.  At that point, there is no longer any state mandate, and any parent can demand that his or her child be allowed to attend any K-12 school without wearing a mask. Continue reading Post #1403, Why can’t Virginia be more like Florida?