Author: chogan@directresearch.com

Post #1483: COVID-19 trend to 4/13/2022

 

The U.S. stands at just over 10 new COVID-19 cases per 100K population per day, up 15% in the past seven days.  In the Northeast region, cases are rising at a steady 40% per week.

The CDC came out with another month of seroprevalence data.  As of January, there was still no evidence of any increase in the number of unreported infections.  As of January, that analysis showed 1.9 actual infections for every one that had been reported.  That was actually lower than in prior months.  Either a) January was too soon to start seeing those missing infections, b) post-infection antibodies fade fast enough that the seroprevalence survey itself is missing the earliest infections now, or c) something else is preventing those infections from showing in the seroprevalence data.

Source: CDC

Here are a couple of previous monthly readings, for comparison.  More-or-less, the CDC seroprevalence survey has always shown that there were two true infections for every one reported, plus-or-minus.

Post #1482: COVID-19 trend to 4/12/2022, hospitalizations turn upward.

 

The U.S. remains at roughly 10 new COVID-19 cases per 100K population per day, up 10 percent in the past seven days.  In the Northeast region, new cases are rising almost 40 percent per week.  In the South Atlantic, they are still falling at an average rate of 25 percent per week.

This week, the count of daily new hospitalizations began to rise slightly.  It had been falling since the peak of the Omicron wave.  This is useful, because it validates that the slight uptick in new case counts is probably real, and not some artifact of data reporting.

Meanwhile, as if the quality of the data weren’t bad enough already — what with home testing displacing officially-tabulated testing, and with the end of “free” (that is, federal-taxpayer-paid) testing in the U.S. — that quality of the official new-case counts continues to deteriorate.  Eleven states now report case counts just once or twice a week.  The resulting “jump” in the new case count occurring with the weekly reporting make it hard to tell real changes from mere reporting errors.  The lags in reporting also mean that the reported data will respond even more sluggishly to any true changes in trend.

What with everybody having decided that this is over, the cumulative increases kind of creep up on you.  With this latest round of reporting, Washington DC is now over 40 new cases per 100K per day.  A cluster of Northeast states is in the high-20s to low-30s.

 

Continue reading Post #1482: COVID-19 trend to 4/12/2022, hospitalizations turn upward.

Post #1481: COVID-19, rising case counts, reimposed mask mandates

 

The U.S. is now back to 10 new COVID-19 cases per 100K population per day, up 15% in the past seven days.  That’s still far from uniform.  New cases continue to decline in some parts of the country.  By contrast, we’re starting to see sporadic re-imposition of mask mandates in locations with significant upticks in cases. Continue reading Post #1481: COVID-19, rising case counts, reimposed mask mandates

Post #1479: COVID-19, still on hold in the U.S.

 

Surprisingly, the U.S. currently has about 9 new COVID-19 cases per 100K population, same as it’s been for three weeks now.

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 4/7/2022, 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

Cases continue to increase in the Northeast.  If there’s any rhyme or reason to what’s happening in the rest of the country, it’s beyond me.  Basically, we’re on hold, waiting to see what, if anything, happens next.

Map courtesy of datawrappe.de

Best guess, this is what endemic COVID-19 looks like in the U.S.

And I’m already starting to get a sense of how this does and does not differ from (e.g.) endemic flu.

Contemplating the recent Gridiron Club super-spreader event.  How does flu spread, compared to Omicron?

And so, if we’re going to have to live with this level of Omicron in circulation, what are the implications compared to (e.g.) living with flu, as we have done all of our lives?

First, this brings the discussion right back to the start of the pandemic.  Does flu spread only via droplets (fairly large particles that rapidly fall to the ground), or via aerosols (tiny particles that are airborne and can travel significant distances).  With droplet transmission, the six-foot social distancing rule keeps you safe.  Not so with aerosols.

Evidence suggests that flu spreads via both droplets and aerosols, but if I had to guess, I’d say the consensus is that droplet spread is more important for flu than it is for COVID.  The CDC still maintains that flu is spread via droplets, period.   You can read that on this CDC web page, where there is no mention of aerosol transmission.  But the CDC said that about COVID-19, too, until enough scientists twisted their arms that they grudgingly changed their language to include aerosol transmission.  Other research pretty strongly suggests that flu, like COVID-19, may also spread via aerosols (reference). And still other research suggests that airborne transmission of flu via aerosols is pretty common (“at least half”, reference).

With flu, as with COVID-19, people begin to be infectious before onset of symptoms, and remain infections for many days afterward (reference CDC).  That said, the mix of symptomatic and asymptomatic days is different.  It appears that flu is only infectious for one day prior to symptom onset, whereas in the typical case of COVID I think it was two to three days.   Also, only about 16 percent of flu cases are asymptomatic (I can’t find the reference for that), versus perhaps 40 percent of COVID (from an old statement by Dr. Fauci).

Flu appears much hard to spread, on average, than Omicrion.  The “R-nought” for the current strain of Omicron has been estimated to be somewhere around 22.  (That is, absent any immunity or protections, the average infected individual would have gone on to infect 22 others).  Seasonal flu, by contrast, has a typical R-nought of about 1.3.

Flu has super-spreader events (reference), but they appear to be far more rare than COVID-19 super-spreader events.

In general, the tendency to spread via large clusters of infections is the “overdispersion” factor or K factor.  The K for COVID-19 has been estimated to be as low as 0.1 (reference).  Perhaps 80 percent of infected individuals never spread the disease, and most spread occurs from large clusters attributable to a handful of individuals.  For flu, by contrast, the K is closer to one.  Spread in that case is far more uniform, much closer to the case where each person spreads it to just one or two others.

Interestingly, that high K factor for COVID-19 — the propensity for super-spreader events — should change (and apparently has changed)  as the pandemic progresses.  Once you start getting a lot of immunity in the population, massive superspreader events become less likely.  That’s the gist of the discussion in this NEJM article: “Overdispersion was thought to be an unstable trait that would disappear, with transmission becoming more uniform and higher overall. That transition appears to have occurred as newer variants take over.”

As any parent will tell you, kids play a huge role in spreading seasonal flu and colds. As this article in The Lancet put it,  “Children and adolescents contribute more to the transmission of common cold betacoronaviruses and influenza than they do to the emerging betacoronaviruses.”  For COVID-19, by contrast, they played a far smaller role.  The initial studies of the Wuhan outbreak found no child-to-parent transmission whatsoever.

Finally, with vaccination and a booster, it’s not clear that the rate of severe outcomes from Omicron infection is worse than for typical flu.  At least, not for the vaccinated and boostered individual.  (This is all based on earlier analysis, e.g., Post #1430).  CDC data show a roughly 1.4 percent case hospitalization rate for flu.  By contrast, our current case hospitalization rate for Omicron is around 6 percent.  But much of that is for the unvaccinated. By calculation, the case hospitalization rate for the vaccinated and boostered should be about 18% of the raw average, or about (6% x 18% =) 1.1%.  This slurs over the impact of vaccination on flu hospitalizations.   But it shows that the rates for the vaccinated/boostered population are certainly in the same ballpark.

This, of course, does not include the risks of any other intermediate-level outcomes from COVID, including loss of sense of smell and taste, or any of the “long COVID” symptoms, including lasting cardiovascular and neurological damage.

That said, if I focus on the acute, severe outcomes, the risk from a case of flu and a case of Omicron are not hugely different, for the vaccinated and boostered population.

Here’s how I sum all that up.

Your risk of catching flu is a lot more obvious than your risk of catching COVID-19.  It’s more likely to be one-to-one transmission.  The person transmitting it is more likely to appear to be sick.  You provide more protection to yourself with that six-foot social distancing rule.  You are more likely to catch it from your kids, and less likely to catch it in some massive infection event at some communal gathering.

For Omicron, by contrast, the risk is higher that you’re going to catch it via long-distance (aerosol) transmission from some asymptomatic stranger.  You aren’t likely to get it from your kids, and you don’t have to be within six feet of somebody to get a good dose.  And it’s far more likely that the person who gives you a dose of COVID doesn’t know they have it and doesn’t appear under the weather.

And so, at the end of the day, I think that large gatherings of closely-packed strangers are going to bear a risk of COVID-19 infection that does not occur — or does not occur to the same degree — with normal seasonal flu.   With flu, maybe it’s mostly good enough to avoid those who are sniffling and sneezing in that kind of situation.  With Omicron, you’re still going to face risk of infection even if you do that.

All other things equal, if flu and COVID had identical incidence rates, the apparently-healthy person sitting six feet behind you, drinking a beer and cheering on the team, represents a far higher risk to you for of Omicron infection that of seasonal flu infection.  And, accordingly, I think that a cautious person is going to have more reason to avoid large indoor crowds than in the past, when flu was really the only worry. 

I think that’s a permanent change, and there’s no obvious way to mitigate it.  It’s just a consequence of a disease that will, on average, mess you up at least as badly as seasonal flu, but gets transmitted in stealthier ways, at greater distances, and in larger clusters.

Post #1478: COVID-19 trend to 4/6/2022, still no U.S. trend, but an interesting curve-ball from the U.K.

 

 

The U.S. remains at about 9 new COVID-19 cases per 100K population per day, roughly unchanged from a week (or two or three) ago.  The regions continue to diverge, with the Northeast showing a steady growth in daily new cases.

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 4/7/2022, 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 Continue reading Post #1478: COVID-19 trend to 4/6/2022, still no U.S. trend, but an interesting curve-ball from the U.K.

Post #1477: COVID-19 non-trend to 4/4/2022. BA.2 dud. No flu. Inopportune 2nd COVID booster.

 

The U.S. remains at 9 new COVID-19 cases per 100K per day, unchanged from a week ago.  The different regions of the U.S. diverge, with continued new-case increases on the East Coast offset by declines in the South Central and Pacific regions.

That said, even though the U.S. curve hasn’t turned upwards, this is starting to look like every other inflection point on the curve.  As the individual regions go their own separate ways, the “strands” that form the graph appear to be unraveling.  Historically, that’s been a strong signal that the U.S. curve is likely to make a change in direction.

Continue reading Post #1477: COVID-19 non-trend to 4/4/2022. BA.2 dud. No flu. Inopportune 2nd COVID booster.

Post G22-009, the second-biggest waste of time in the U.S.A.

Traditional, unconditional, last-frost date

I had planted a few cold-hardy vegetables in my garden weeks prior to last weekend’s deep freeze.  I put in some snow peas, potatoes, beets, garlic, onions. 

It got down below 20F briefly on one of those nights.  I can now say that all of those appear to have survived, with just a bit of TLC.   That was in the form of capping the bed with radiant barrier, then adding a piece of plastic for air-tightness.  (See Post G21-018, or my just-prior garden posts.)

It’s no surprise that we had a freeze.  Our nominal “last frost date” is somewhere around April 22,so these plants were in the ground almost two months ahead of that.  Instead, the interesting thing is that I had two weeks’ warning that the freeze would occur.  The fourteen-day forecast accurately predicted that there would be a freeze that weekend, although the original forecasts understated the depth of that freeze.

This leads me to ponder the implications of reasonably-accurate long range weather forecasting and our “last-frost” dates.  Folklore guidelines (“plant peas on St. Patrick’s Day”) and science-based “last frost date” guidelines predate the era of supercomputers that make long-range forecasting possible.   Weather is still chaotic in the mathematical sense, and so not predictable at very long intervals, but we now have two-weeks-ahead temperature forecasts that are reasonably accurate.

I already rang the changes on this once, in post G21-005, Your 70th percentile last frost date is actually your 90th percentile last frost date.  What you typically see cited as your “last frost date” is the date on which, historically, frost only occurred after that date around 30 percent of the time.  But that’s an unconditional probability, as if you would plant on that date regardless.  If, by contrast, you check your 14-day forecast on that date, and refrain from planting if frost is in the forecast, then you’ll convert that to a 90th percentile last-frost date.  That conditional probability — chance of frost after that date, conditional on a frost-free 14-day forecast — gives you a much higher chance of avoiding a freeze after that date.

The upshot is that a reasonable prediction of the two weeks following the “last frost date” shifts the odds attached to that date considerably.  It’s actually a lot safer to plant frost-sensitive plants on that date, in the modern world, than it was in the era when no forecasts extended more than three days.  As long as you make that decision conditional on the extended forecast, and you’re smart enough not to plant if it looks like frost any time in the next two weeks.

At present, we’re creeping up on 14 days prior to our April 22 “last frost date”. And I’m pondering — just as an exercise in probability and statistics — whether that same math works 14 days in advance of the date. 

And I’m pretty sure it does.  If the 14-day forecast were completely accurate, then the conditional 70th percentile last frost date in this area would be April 9th.  No frost in the forecast through April 22 would mean that the conditional odds of frost occurring after April 9 would be the same as the unconditional odds after April 22.

That is, April 9 is our conditional 70th percentile last frost date.  If we have a decidedly frost-free 14 day forecast at that point, planting on that date bears the same risk of frost damage as planting blindly on April 22.

The only uncertainty there is in how accurate the 14-day forecast actually is, for daily low temperature.

Weather forecasts seem to be one of the few true ephemera of the digital age.  They are published, and then they are replaced with the next day’s forecast.  Nobody cares about yesterday’s forecast, other than those who have some deep professional interest in forecast accuracy.  Accordingly, where you can look up the actual weather 14 days ago, I haven’t yet located a database that lets me look up the actual weather forecast 14 days ago.

So that’s going to have to remain an unknown, for the time being, unless I want to try to compile the data, for my location, day-by-day, myself.  Or if I can find existing research that addresses this exact question of predicting a frost.  So I’ll just have to leave that as saying that if the 14-day forecast shows lows that are well above freezing, then you can probably move your traditional (unconditional) 70th percentile last-frost date up by two weeks.

But is this just the second-biggest waste of time in the U.S.?

The second-biggest waste of time in the U.S.A. is doing something really well that doesn’t need to be done at all.  (I heard that in a time-use seminar I attended decades ago.)

In the fall, frost protection has some clear advantages.   The plants are already grown, the produce is already ripening.  Protection from an unexpected early frost is a matter of saving garden produce that would otherwise be lost.

But as I hustle about protecting my plants in the spring, it invites the obvious question:  Just how much am I gaining by planting these crops early? And to that, I will add not just planting early, but the whole process of starting seeds indoors, regardless of the planting date.

In reality, is this really just an example of the second-biggest waste of time in the U.S.?

Ultimately, while some plants may grow in the cold, they tend to grow slowly.  At some level, that’s just basic chemistry.  The rate at which a typical chemical reaction proceeds roughly doubles with every 10 degrees C of temperature increase.  Sure, plants will develop enzymes to speed those processes in colder temperatures.  But it doesn’t take a genius to notice that while they will grow, they sure won’t grow very fast.

What prompts this is my peas, which are now all of about 2″ high.  And it’s getting on close to a month after they went into the ground.  Is  that head start worth it, compared to simply waiting for the nominal last-frost date and planting them then?

In short, I’m beginning to suspect that my current setup — plant early, provide frost protection, but no greenhouse — might just be the least efficient of all possible worlds.  All the hassle of early planting, and (almost) none of the benefit.

Without a greenhouse structure (or poly tunnel, or similar) to warm the daytime air and soil temperatures, it seems like most of what I’ve done is to induce my plants to try to grow under inhospitable conditions.  And they are responding accordingly.

Back when I was a low-effort gardener, I seldom mucked around with any type of early planting.  I’d start seeds a couple of weeks before I planted them, just to be able to have a tiny visible plant to stick in the ground.  (And so, have better chance of survival for (say) tomato plants.)  But my opinion then was that the gains from very early planting were minimal.  Give it a couple of weeks, and the (e.g.) peas planted later in the year will have effectively caught up with those planted earlier.

As a result, I’m now wondering whether I’ve been taking all this early-planting advice from people who do early planting and have some type of greenhouse arrangement on top of those early plantings.  From what I’m observing so far, that would make a lot more sense than just sticking plants in the ground and protecting them from freezing as needed.

When I briefly Google for this topic, all I see is people touting the benefits of early planting.  In effect, a series of statements that you’ll get more out of your garden if you do it.  I’m not seeing any quantification of just how much more you get, from early planting alone (i.e., with frost protection but not a greenhouse or poly tunnel).

So, before I get any further caught up in this effort to see just how much I can push that last-frost date, and just how well I can protect those tender plants from frost, it seems like I need to assess the cost/benefit tradeoff.

I’ve proven that I can plant well in advance of that last-frost date.  I can do that very well, thank you.  But should I do that?  I don’t think I’ve really answered that question.  And, in particular, should I do that without some sort of setup to warm the daytime air and soil temperatures?

Maybe early planting without a greenhouse really is just the gardening equivalent of the second-biggest waste of time in the U.S.A.  Clearly, that needs to be the next thing I test.  For that, I need some sort of cheap, safe, low-effort greenhouse or poly tunnel.  One that minimizes the chances that I’m going to bake my plants to death.

So that’s the next thing on the agenda.  Replant what’s in my garden, one month after the original planting date. And work up a greenhouse covering that, as a lazy gardener, I can live with.

Post #1476, COVID-19, ditto. Plus, news of a wonder drug out of Australia.

 

Roughly 9 /100K/ day, roughly unchanged.  Rapid new case growth on the East Coast, rapid new case decline on the West Coast and South Central regions.

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 4/2/2022, 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

Australia is seeing a second Omicron wave, similar to that in the U.K.  Their current new case rate is about 20 times the rate in the U.S., and is still currently rising.

Source:  Johns Hopkins data via Google search

Because this is Australia’s first big COVID wave, we have no hard data on the likely seasonality (or lack thereof) of COVID in Australia.  The U.S. has seasonality on its side, as we head into summer, they are heading into winter.  But it’s not as if winters are terribly cold.  (e.g., typical August highs in Sydney are around 65F.)

Australia has had little bumps in their hospitalization rate for COVID-19 prior to this, but no huge run-ups in the new-case numbers.  And, for whatever reason, their case hospitalization rate is tiny compared to that of the U.S.   Currently, they have more than twice as many new cases per day, but the U.S. has more than five times as many people in the hospital with COVID.  The implication is that the Australia case-hospitalization rate for COVID-19 is about one-tenth that of the U.S.

In any case, on March 1 Australia added Merck’s oral anti-viral Molnupiravir to their formulary,  for high-risk individuals.  What caught my eye is that the most recent test of that showed that 100% of a sample of 92 infected persons appeared COVID-free after three days of treatment, compared to 78% of those given a placebo.  (Per this news reporting.)

The only reason to bring it up is the optics of that 100% figure.  It’s rare to see any treatment show up as 100% effective, in any mid-sized trial, of anything.  So that appears to be getting significant press in Australia of late, given their ongoing COVID-19 surge.

That said, while this one study seemed to show that this drug wiped out COVID-19, other studies have shown that it is less effective at preventing hospitalization than other approved anti-virals in the U.S. (reference).

So, YMMV.

FWIW, that’s one of three anti-virals currently approved or given an emergency use authorization by the U.S. FDA for use with COVID-19.  (Reference).  We seemed to have approved it for emergency use just prior to the Australians.

All of these antivirals have some fairly significant side-effects.  As a rule, sure, they muck around with viral DNA or RNA replication.  And they do the same for human DNA or RNA.  For example, this one isn’t approved for anyone under 18 because it affects bone and cartilage growth.

And yet, the trick with all of those is that you have to start the drug early.  In this case, the guideline is to start within five days of symptom onset.  So you have to make a judgement call regarding the likely severity of your COVID versus the likely severity of the side-effects of these COVID treatments.

I have not yet stumbled across data on how many U.S. COVID patients have been treated with these anti-virals.