Month: February 2022

 

The U.S. now stands at 47 new COVID-19 cases per 100K population per day, down 81% from the peak.  Only two states remain above 100 per day (KY, ID).  The majority of states are below 50; five states are below 25 new cases per 100K per day (NY-NJ-CT, MD-DC).

Cases are down 39% in the past seven days, a bit slower than in the recent past.

As I said in recent posts, I think the decline in the official new case count is being exaggerated, probably as a result of the growing use of home testing using over-the-counter rapid tests.  As an alternative measure that should be unaffected by that, new COVID-19 hospitalizations are down 55% from the Omicron wave peak. Continue reading Post #1433: COVID-19 trend to 2/14/2022, maybe the beginning of a slowdown.

 

The U.S. now stands at 63 new COVID-19 cases per 100K per day, down 43 percent in the last seven days, and down almost three-quarters from the 1/16/2022 peak of the Omicron wave.

Just eight states remain about 100 cases / 100K population per day, and no states exceed 200.

So far, there is still no clear sign of any letup in the rate of descent.  That makes the U.S. experience unusual (possibly unique) by international standards. 

Could this lengthy, steady, and extremely rapid descent reported positive cases be a consequence of some sort of problem with the data, such as the rise of in-home testing?

Turns out, the answer to that is yeah, it just might.  Hospitalizations and deaths are not falling anywhere near as fast as reported cases.  Best guess, that only started to happen in early January.

Continue reading Post #1431: COVID-19 trend to 2/10/2022. The trend is good. Maybe too good. Revisiting the home-testing issue.

 

New COVID-19 cases continue to fall in the U.S. We’re now down to 74 new cases per 100K population per day.  The 7-day rate of decline is 44%, not materially different from yesterday’s 45%.

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 2/9/2022, 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

My gut reaction to today’s new data is that we’d passed the point of most rapid descent, and that the rate of decline will now begin to taper off, as we have seen in other countries.  As far as I can tell, there is no objective information to support that.

Here are the ten states that have led the way in the U.S. Omicron wave, plotted in logs so that a constant percentage decline shows as a straight line.  If the ends of those lines are bending toward flat, it’s a pretty subtle effect so far.

 

If there is a dark cloud on the near-term horizon, it’s the BA.2 variant (a.k.a., son-of-Omicron).  The CDC “Nowcast” projection pegs this at 3.6% of all U.S. cases, as of the week ended 2/5/2022.

Source:  CDC COVID data tracker, accessed 2/9/2022.

You might reasonably say, what’s the big deal?  BA.2 doesn’t appear to be any more virulent than Omicron, but it is more easily transmitted.  Original estimates were that it was about 50% more transmissible than Omicron, but more recent estimates put it closer to one-third more infectious than Omicron (reference).  Results from both Denmark and the U.K. appear to agree on that figure (reference).  If it becomes the prevalent strain, that will result in just so many more infections, all other things equal, and slow down our presumed “return to normalcy”.

Well worth noting, the CDC “Nowcast” model shows this strain’s share tripling every week.  On the one hand, you have to take that with a grain of salt, given the small numbers and the uncertainties involved.  On the other hand, if those projections are right, and accounting for the timing of the CDC data (that 3.6 figure would have been reached somewhere around 2/2/2022, BA.2 would be come the dominant strain in the U.S. approximately 2/19/2022, or ten days from today.  But weigh that fear-mongering against the observation that the growth of BA.2 has been all over the map, in various European countries, and that no country actually saw its share of BA.2 grow that rapidly.  My guess, based on European growth rates, is that this preliminary “Nowcast” estimate likely overstates the true rate of growth. 

The fact remains that BA.2 took over Denmark in a matter of weeks, but so far it remains a minor issue in most European countries.  Coincidence or not, it’s worth noting that Denmark still hasn’t reached a clear peak in its Omicron wave, despite having started that wave before the U.S. did.  Draw what conclusions you will from that sample of one.

Source:  Johns Hopkins University via Google Search

Finally, there is a bright side to transitioning from pandemic to endemic with as infectious a variant as possible, as long as that variant is relatively benign.  There’s no guarantee what the next new variant will bring.  Maybe the next one will be as virulent as Delta, or worse.  But that won’t matter unless that new variant is better able to spread better than the reigning champion, which will be either Omicron or son-of-Omicron.  The tougher those are to beat, from an infectiousness standpoint, the less likely we are to have some new and possibly far more virulent strain of COVID-19 take over.

It is truly a case of better the devil you know than the devil you don’t.  Looks like we will probably be able to deal with Omicron OK.  Plausibly we can deal with BA.2 OK.  Both owing to their much-reduced infectiousness and the ability of a booster shot to provide significant protection.  It’s probably better if we can stick with this variant as our endemic COVID-19, rather than roll the genetic dice and face something new.

 

The U.S. is now at 78 new COVID-19 cases per 100K population per day.  That’s down 45 percent over the past seven days.  Since late January, that number has fallen by a more-or-less steady 10 cases per day.

Cases have now fallen by more than two-thirds since the 1/16/2022 peak of the Omicron wave.

Continue reading Post #1427: COVID-19 trend to 2/7/2022, linear descent continues

 

Let me start with an anecdote.

I went to two different farmers’ markets over the weekend.  These were open-air markets, sparsely attended.   And it was a breezy day, to boot.

In neither case did I think there was any reason whatsoever to wear a mask.  In both cases, I ended up wearing a mask.  Not because I thought it made sense, but because I wanted to fit into the crowd.  In both cases, the overwhelming majority of people in the marketplace were masked.

I’ve now gone full circle on pandemic mask use.  Early on, I couldn’t fathom why people weren’t using face masks.  Now, at least in some cases, I can’t fathom why they are.

In today’s news, I see that two East Coast Democratic governors have set a rough timetable for rolling back K-12 school mask mandates (per this reporting.)  This is in response to the declining new case counts for Omicron.  Right now, it looks like both of them are shooting for a March end of their respective school mask mandates.

In my humble opinion, that’s how it should be done.  They are accepting responsibility for this key part of school safety during the pandemic and they are actively managing it.  They are planning an orderly transition from masked to non-masked in-person K-12 instruction, based on what I hope are public health objectives.  In any case, for this group activity we call school, everyone in the group will be given the same signals regarding mask use, and when it’s time to take off the masks, everyone can be assured that the decision was done with some forethought as to the common risks involved in that.

This is good, if only because this approach avoids chaos and strife.  Within the large-group activity we call public school, everyone will get the same set of instructions.

Contrast this with the Virginia approach, where the Governor took no ownership at all over this key school safety issue.  Instead of managing the transition for the benefit of all, he issued an executive order to create individual parental-based exceptions to local mask mandates.  It allowed parents to exempt their children, one-by-one, based on their opinions (i.e., political leanings) rather than any public health criteria for the student body as a whole.  As an extra added bonus, it fairly clearly conflicted with existing Virginia statute, and as a result it has now ended up in court.

Which is bad, unless generating chaos and strife is part of your political agenda.

At any rate, because K-12 school is a group activity, run by the government, there likely will be some form of guidance in most places.  Some sort of mask use guidance.  If only because in most places, somebody responsible is supposed to be looking out for the health and welfare of the students as a whole.

We adults are not so lucky.  We’re each going to have to make our own individual decisions about mask use.  And as far as I can see, so far, that’s going to be based on the same amorphous social norms that governed masking up in the first place.  To the extent that dropping the masks will be enforced, it’ll be through peer pressure, not through any explicit advice from any government agency.

In short, as an adult, nobody’s going to tell you that masks are no longer needed. 

Not in the U.S, at any rate.  Other countries seem to be testing the waters for treating Omicron like seasonal flu, e.g., Spain.  But here in the U.S., I doubt the CDC is ever going to come out and say that masks should no longer be used.

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Yet a third way to compare Omicron risk versus typical flu risk:  Brief background.

Let me not belabor this.  This is the third in a series of posts that asks the following question:

How low does the U.S. Omicron case load need to get, before the risk posed by Omicron is no higher than that posed by typical seasonal flu?

In Post #1400-3, I did the crude calculation for all persons pooled together, and came up with 16 new cases per 100K population per day.  That calculation was absolutely straightforward and easy to check.

In Post #1400-4, I refined that by generating a separate estimate for the boostered population alone.  That gave me a benchmark of 40 new COVID-19 cases per 100K population per day.   The number is higher because boosters provide significant protection against Omicrion.

But that calculation was anything but transparent.  And it was an extremely conservative estimate, in that I only account for the impact of vaccine and booster on the likelihood of getting infected, not on any further reduction in hospitalizations or deaths once infected.

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A duh-piphany, or the most obvious way to compare Omicron risk to flu risk.

The main point of this exercise is to compare the risk of hospitalization or death under Omicron, to hospitalization or death from seasonal flu.

In which case, why don’t I .. uh … just compare those rates directly?  If I want to compare them based on deaths and hospitalizations, then simply do that.  Tabulate Omicron hospitalization and death rates on a 100K population basis, and compare those to typical seasonal flu.

It’s an eclat d’oh.

I mean, when the Omicron hospitalizations per 100K gets down to the level of flu hospitalizations per 100K, then by definition, the average person’s risk of getting hospitalized for Omicron matches the risk of being hospitalized for flu.  No further calculation needed, unless you want to try to separate out the boostered, vaccinated, and un-vaccinated populations.

Disease burden of flu in terms of deaths and hospitalizations per day and per 100K population.

I want to compare Omicron risk to risk from flu on a typical day during “flu season”.

The first issue is that I could not find any hard-and-fast CDC definition of flu season.  It’s just defined as the months — typically winter through early spring — around the peak of this curve.  Typically, somewhere around five months out of the year.

Source:  Calculated from CDC burden of flu, 2017-2028 season, assuming 30M total symptomatic flu cases for the entire year.

I’m going to define “flu season” as those weeks with an estimated 500K symptomatic flu cases or more.  In the example above, “flu season” lasted 18 weeks, and accounted for just about 70 percent of all flu cases during the year.

Source:  CDC disease burden of flu.

Based on that, and rounding the numbers, I come up with the following table comparing hospitalization and mortality rates for typical U.S. seasonal flu and the current levels of Omicron:

On a typical day in flu season, the U.S. sees 2100 flu hospitalizations.  Currently, with Omicron, we’re seeing an estimated 12,000 hospitalizations per day.  Based on that, for the U.S. as a whole, Omicron cases would have to fall to about 17.5 per day before the hospitalization risk from Omicron matched that of typical seasonal flu, for the average American.

(The mortality data are harder to use because a) deaths lag cases by a couple of weeks, and b) we’re only a few weeks past the Omicron peak.  So, compare to the current case count, we’re looking at far too many deaths.  And, accordingly, the ratio of current Omicron deaths to typical flu deaths is much larger than the current ratio of Omicron hospitalizations to typical flu hospitalizations.)

As you can see, all I have really done is re-create my first analysis.  Pooling all individuals together, you’ll have the same hospitalization risk for Omicron as for flu if Omicron gets down to 17.5 new cases / 100K / day.  (My initial analysis came out with 16 new cases / 100K / day).

The only value-added here is that this now directly translates into a COVID-19 daily hospitalization count.  That information is available on a timely basis for all states, via the CDC COVID data tracker.

For now, I’m just going to leave it at that.  Without being very precise about it, this is just another way of saying that at some point when Omicron cases get into the 10’s per 100K per day, your risk of severe illness from Omicron is no higher than your risk of severe illness from flu.

Tomorrow, I’ll take the final step in this process.  I’m going to combine and clean up all the results, and translate them into a set of state-level thresholds comparable to the data publicly available on the CDC COVID data tracker.  With that, you should be able to take those thresholds, bring up the CDC data from your state, and identify the time (if any) at which Omicron risk is below typical flu risk for the average resident, and for the fully-boostered resident, of your state.

 

The U.S. COVID-19 case numbers continue to be surprisingly good.  The decline in new COVID-19 case counts continues to accelerate.  The U.S. now stands at 100 new cases per 100K population per day, down 40% in the past seven days.  Most states are now below 100 new cases / 100K / day.

Continue reading Post #1425: COVID-19, last update for this data reporting week.