Tag: William and Mary

 

I’m going to continue to track Omicron for a while longer yet, at William and Mary.  William and Mary is only updating their data weekly so I guess I’ll post once a week, if there’s anything to write about.

I doubt that many will read these posts.  Most  W&M parents found out about this blog via a W&M-moderated Facebook group.  The moderators of that group have banned discussion of COVID-19, so I suspect that most on that group will never get back to this blog.

Enough said.  Most of the value-added here is that I keep track of the historical data.  That’s not available on the W&M COVID dashboard.

Based on two weeks of data, the new case rate at William and Mary seems fairly steady at 5 to 7 newly-diagnosed COVID-19 cases per day.

That most recent rate of 7-per-day translates to roughly 100 new cases per 100K students per day.

Contrast to Virginia as a whole:  That’s just a touch higher than the rate for 18-24 year olds in Virginia as a whole, which I estimate to be 77 / 100K / day, for the seven days ending 2/7/2022, based on Virginia Department of Health data.

Contrast to last semester:  That’s maybe four times higher than the peak post-move-in rate last semester.  After the initial post-return-to-campus wave had died off, the highest rate observed was 11 new cases in the week ending 12/10/2021.  That’s under 2 per day on average:

That said, Omicron has a much lower average severity than the Delta variant that was prevalent at the end of last semester.  For example, looking at the Virginia data, if I date the start of the Omicron wave to roughly 12/17/2021, then so far there have been zero deaths in the 18-24 age bracket, from Omicron, in the whole of Virginia.

If I had to sum it up, I would say two things.

First, there does appear to be some need for further vigilance.  COVID-19 has not disappeared from the campus.  That 100 cases per 100K per day rate is high by historical standards.  And I need to remind myself that these numbers didn’t just happen.  The relatively high new case rate occurred in an environment with fairly stringent COVID-19 hygiene in place.

That said, the rate at William and Mary isn’t much different from the rate for Virginians age 18-24 as a whole.  And once you factor in the much lower average severity per case, the health impact of the current case rate probably isn’t much different from the impact of Delta at the end of last semester.

In any case, the numbers are up from last year.  I see that as no cause for alarm, but no clear justification to relax, either.

Finally, I should note the obvious:  Pre-return testing seems to work pretty well at preventing a big return-to-campus outbreak.  This isn’t exactly a controlled experiment, but the one semester when W&M didn’t do pre-return testing, they ended up with a large number of active cases on campus, as shown in the last chart above.  The semesters when pre-return testing was required, that didn’t happen.

 

For the week ending last Friday, there were six new COVID-19 cases found at William and Mary.   So the rate is back under one new case per day on average.

Source:  Calculated from William and Mary COVID-19 dashboard.

In hindsight, that little blip of 11 new cases in the prior week might plausibly be attributed to infections acquired over Thanksgiving.  If you think of W&M as a bubble of sorts (98%-vaccinated, mask-mandated, rule-enforced, low infection rate), Thanksgiving forced students to step outside the bubble in large numbers.  It wouldn’t be a surprise if they brought a few cases back to campus.

The timing is about right.  My best guess, for the U.S. as a whole, is that it takes an average of about 4 to 5 days for symptoms to appear following infection, and then about another 5 or 6 days for the typical individual to seek care, be tested, and have the test results tabulated.  Call it 10 days on average.  Which would mean that the bulk of infections incurred around Thanksgiving would show up in the data for the week ending 12/10/2021.

We’ll never know for sure one way or the other.  But the timing is right.

Luck

I guess it seems a bit compulsive to have continued to track this, given the low infection rate.  But not all colleges have been as lucky as W&M.  In particular, Cornell shut down just four days ago due to an outbreak of COVID.  Apparently, what they have is an outbreak of Omicron.  Which tore through the student body despite a mask mandate and a 97% vaccination rate.

And if you’re of a mind to indulge in some gloom and doom, note that Cornell was not the only instance.  Most of these new campus outbreaks are being attributed to likely Omicron infections, as they are all occurring in places with vaccination rates similar to those of William and Mary.

So, lucky.  I think that’s the correct term.  That’s an odd word, given all the precautions taken by W&M administration and students.  But if you look at Cornell, and other cases like Cornell, that appears to be the right word for it.

Our kids appear to have brought back just good old Delta, after Thanksgiving.  So we got a little bump in cases, but that’s the end of it.  If a few of them had stumbled across Omicron, my guess is that we’d be singing a different tune.

Omicron, my fringe opinion.

Let me preface this with a few old saws.

Free advice is usually worth what you paid for it.  Opinions are like belly buttons, everybody has one.  YMMV.  So take this FWIW.

I’ve been tracking the data on Omicron just about as carefully as a person outside of the official U.S. public health bureaucracy can.  And I’m a Ph.D. health economist, so I’ve had a lot of experience dealing with the ins and outs of health care data.

My opinion on Omicron now falls far, far outside of the mainstream.  In a nutshell, I’m betting that the U.S. Omicron wave will be short and sharp, that it might lead to more peak cases than the just-prior Delta waves (but not vastly so), and that despite that, we’ll see far fewer hospitalizations and deaths than we’re seeing under Delta.

If you want to see how I arrived at that opinion, just start reading back through my last dozen or so posts.  Starting with what I posted earlier today (Post #1356),  on the peak of the Omicron wave in South Africa now occurring just three-and-a-half weeks after the first cases of it were detected.

So what’s my best guess for W&M, next year?

For sure, when W&M students return to campus near the end of January 2022, they will do so under Omicron, not Delta.  That’s a given at this point.  The U.S. will likely pass the point where Omicron is the dominant strain some time next week (Post #1353).

In addition, I’ll bet that the U.S. Omicron wave will have already peaked in mid-January.  Weeks before the late-January general return to campus.  How fast new Omicron cases will fall, after the peak, is yet to be determined.  It’s well worth continuing to watch South Africa in that regard.  I’m not even going to hazard a guess absent hard data.

By that time, if the severity of the typical Omicron infection is as low as I believe it to be, that fact should be apparent from South African data, as well as data from Great Britain.  In other words, if the typical Omicron case really is as mild as I think the preliminary data show (see prior posts), it should be hard to ignore that.

But that’s not going to stop people from trying.  As of mid-January 2022, our official public health infrastructure might still be telling us that it’s just too soon to tell about the overall severity of Omicron relative to Delta.  As I noted in my just-prior post, they more-or-less have an ethical duty to do that for as long as possible.

At that point, colleges will face some interesting choices about return to campus.  And we can all be glad that we aren’t college administrators.

Best available evidence shows that two shots of vaccine doesn’t produce much of an antibody response to Omicron.  In other words, Omicron blows past the standard two-dose vaccination regimen.   That’s how you can have a huge outbreak on a campus that’s 97% vaccinated.  But three vaccine shots, by contrast, produces some reasonable antibody response (though only about half as much for Omicron as occurs for Delta).

Given that, I would be completely unsurprised if W&M requires everyone to have a booster shot before returning to campus.  If I were running the show, that’s the first thing I’d do.  And, given that it takes time to build immunity, they’re going to have to announce that no later than in early January.  Which will be good timing, because the U.S. should be squarely in the grip of a large wintertime wave of Omicron just about then.

At which point, my sincere hope is that folks will just roll up their sleeves and get it done.  In the hopes of having something approaching a normal semester.   Because, after that, the tools consist of things that are a lot more disruptive, both of quality of life and quality of education.

If it were up to me, the obvious next step would be to mandate not just use of masks, but use of high-filtration masks. I’d require use of NIOSH-certified N95 masks (respirators).  Those are no longer in short supply (you can pick them up at Home Depot, e.g.).  Given that they are cheap and plentiful now, it’s not like recommending N95 masks for all is a novel idea (see Post #977).  And that can easily be enforced because every NIOSH-certified N95 mask has to have that literally printed on the mask.

That said, when I supplied my daughter with a “mask sampler” of masks that I judged to be adequate, the hands-down winner was an ear-loop-style KF94 mask.  It was the LG Airwasher, to be precise: See Post #1236 and Post #1246.  So at some level, it’s not entirely about the best possible mask.  It’s about getting people to wear the best mask that they are willing to wear.  Possibly, the school administration would merely encourage people to wear only good masks, and provide a list of masks that meet some standards of adequate filtration, if the list needs to be broader than NIOSH-certified N95.

That said, my emphasis on quality masks reflects my own take on the data (see, e.g., Post #935, If you have 10-cent lungs, by all means, wear a 10-cent mask.)  You might also check out Post #942, where I do the math to show why an N95 results in exposure to vastly less viral load than a typical cloth or procedure mask.

Once you get past a) better vaccines and b) better masks, things get fairly intrusive in terms of the educational and social experience on campus.  We’re back to remote learning, hybrid classes, restrictions on social gatherings, no indoor dining.  And all the rest of that stuff.

So if you don’t like vaccines or masks, well, guess what?  Nobody does (see All the masks I’ve ever loved, Post #987).  It’s just a question of the lesser of evils.  I’d rather see on-campus learning, masked, than remote learning in any form.

Finally, what’s going to make this all the more interesting is that W&M administrators will have to make all these choices in advance.  Which, given how fast Omicron appears to be moving, means they’ll probably be making them around the time Omicron is peaking in the U.S.  And that will almost certainly be before any official U.S. pronouncement regarding the severity of Omicron relative to Delta.

In other words, those decisions are going to have to be made when things are looking pretty bleak.  I’m sure glad that’s not my job.

Source:  Calculated from William and Mary COVID-19 dashboard.

Not sure quite what to make of that.

New case rates have ticked up in Virginia as a whole, consistent with a “winter wave” of COVID (Dark line on the graph below).

Source:  Calculated from NY Times Github COVID-19 data repository.

I guess that’s not a particularly worrisome level of new cases.  And there’s not much that you can do anyway, as the semester is nearly over.

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All the things we did last year at this time

With this endless pandemic, I find it helpful to look back and see how things have changed for the better.  In this case, it’s interesting to compare the end of the semester this year to last year.

What I find most striking is that this year, nobody is making noises about the need to quarantine returning college students.  Last year, that was very much in the news (Post #988, November 2 2020.)  Nor am I seeing recommendations for COVID-19 testing prior to return to home, which I believe was more-or-less the norm last year.

This year, with a much more muted winter wave of COVID, and vaccination for more-or-less everyone who wants it, I guess the risks are just that much lower.  Or we’re that much more tired of dealing with it.  Or some combination of the two.

That said, end-of-semester is a good time to make some ballpark estimates of risk of spreading disease.  Not to be morbid, but to get some sort of a handle on the odds.  Last year, everybody was offering advice about quarantining your college student.  This near, nobody’s saying anything.  Either way, you might want to step back and ask the simple question:  Given the rate of new cases on campus, what are the odds that my kid is going to come home asymptomatic but infectious with COVID-19?

The above is an abbreviated version of the calculation given in Post #988 cited above.  It isn’t rocket science.  You start with new cases showing up on the William and Mary campus at a rate of 19 new cases per 6600 on-campus students for the last two weeks.  From that, you take a guess as to how many students will be leaving the campus in an infectious-but-asymptomatic state.  That guess will depend critically on how many days you think the average infected student remains infectious-but-asymptomatic.  I have assumed a generous 8.6 day average period (calculation shown in Post #988).

Anyway, my best guess is somewhere around 1 in 600.  Or so. FWIW.  One in 600 will return home in an asymptomatic but infectious state.  Again, not rocket science.  That’s the same as saying that a bit over a week’s worth of new cases will walk off the campus undiscovered.

There’s one big problem with applying last year’s calculation to this year’s data.  Last year, there was campus-wide testing, and it presumably identified asymptomatic cases.  This year, there was no systematic effort to test and find asymptomatic cases.  This year, we ought to add in a fudge factor for those undiagnosed, asymptomatic cases.  Best guess, historically, 40 percent of COVID-19 cases have been asymptomatic.  So you’d not-quite-double the estimate, to account for the missing asymptomatic cases.

On the other hand, an infected student doesn’t necessarily translate to spread of disease.  Even in the pre-vaccine era, there was no guarantee that an infected household member would spread it with in the household.  That “secondary attack” only occurred in about 15 percent of cases.  Now, with vaccines, I’d have to guess that only a tiny fraction of those students will go on to spread COVID at home.

The upshot of that last bit is that the likelihood of my kid coming home and spreading COVID-19 in the household is much less than the one-in-600 cited above.  One in several thousand, at a guess.

Even as vague as all that is, I find it helpful to ballpark the risk.  Best guess, there’s something like a one-in-several-hundred chance that your kid is going to come home with COVID-19, and be infectious, and not know it.  And the odds of that actually leading to an infection within your household are one in several thousand, best guess.

It’s not one-in-a-million, but it’s not one-in-a-hundred either.  Scale your response (if any) accordingly.  For our part — vaccinated and boostered — we’re just not even going to give it a thought.  YMMV.

Omicron?

Students return to campus on 1/26/2022, or seven weeks from now.  Based on the South African experience, and what is now predicted for Great Britain,  Omicron will be the dominant strain in the U.S. long before then.  It should take a month, at the outside, to go from first discovered cases to dominant strain.

My point is, this year, students are leaving the campus under Delta.  They’ll be returning to the campus under Omicron.

Oddly enough, for a guy who’s clearly been worrying about this a lot, I don’t think Omicron is going to be a problem.  I think it’s going to be an asset.  My prediction is that it’s going to spread like crazy, but very few individuals are going to get very sick from it.

(This, despite the fact that two vaccine doses alone does not protect you from an Omicron infection.  Two doses might give you some protection against a serious case (e.g., one requiring hospitalization).  But with two vaccine doses only, people seem to mount essentially no antibody response to Omicron.  You need three doses (two plus booster), or two doses plus prior infection, to generate significant antibody response to Omicron.)

In any case, my projection of widespread-but-mostly-harmless Omicron is based on my reading of the data out of South Africa, which you can see in my just-prior posts.  The widespread part is pretty much a given.  The “mostly harmless” is my reading of some tenuous data.  I should be on firmer ground there in a week, so when I update these numbers a week from now, I’ll provide my best guess on how Omicron is going to play out in the U.S.

However it plays out, that’s what we’ll be facing when students return to campus next year.

 

The semester is nearly over, so this now hardly matters.  But I’m still tracking the cumulative count of COVID-19 cases for the semester, each Friday.   Still seeing them at rate of a less than one a day.

Source: Tabulated from William and Mary COVID dashboard, last accessed 12/4/2021.

 

There’s still a low but persistent rate of new COVID-19 cases each week among William and Mary students.  It’s under one new case per day, on average.

The last entry below is through the Wednesday before Thanksgiving.

Source:  Calculated from the William and Mary COVID-19 dashboard.

Source:  Calculated from the William and Mary COVID-19 dashboard, accessed 11/13/2021

2021 Winter wave in brief.

Things look great at William and Mary, but for the U.S. as a whole, it looks like the winter wave has started.

Last year, the winter wave started in the Midwest states.  Eventually, all areas of the country saw a mid-winter increase in daily new cases.  Last year, the South Atlantic states ran a month or two behind the Midwest.  The Midwest peaked around Thanksgiving, the South Atlantic did not peak until mid-January 2021.

This year, new cases turned upward in the Midwest around Halloween. And now, about six weeks later, it looks like cases are just starting to rise in the South Atlantic states.

That’s later than last year, plausibly due to much warmer weather in the middle of the country this year, compared to last.  Below are maps for October 2020 and October 2021.  Last year (top) was much colder than normal in the middle of the country, this year (bottom) has been much warmer than normal.

In any case, below, that little upturn in cases at the right edge of the graph may not look like much.  But it’s more-or-less right on time to be the start of the winter wave in Virginia this year.  The fact that several adjacent states (NC, VA, WV, MD, DE) all show the same pattern suggests that it’s weather-related, and not just a statistical fluke in (say) Virginia’s case counts.

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 11/13/2021, 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 best guess is that the little upturn above is, in fact, the start of the winter wave in Virginia.  At this point, there’s no telling where that’s going to go.

I guess I’ll mark the start of the U.S. winter wave at 10/25/2021.  That’s when the U.S. daily new case count reached that most recent minimum.  In the past seven days, new case counts rose 9% for the U.S. as a whole, and were  rising in all regions except the Pacific region.

You’d think we wouldn’t have a winter wave this year, with all the people who’ve been vaccinated or have recovered from infection.  But the example of Europe pretty clearly shows us that a winter wave is possible.

When I look at the numbers, I estimate (guess) that we’re in roughly the same situation as we were last winter, in terms of the ability of the virus to spread (the “R-effective”).

Compared to last winter, we have:

• Higher levels of population immunity (best guess 71% now versus about 10% in October 2020).
• A far more infectious variant of COVID-19 (best guess, R-nought of 5 for Delta, versus maybe 2.5 for last year’s native strain, meaning that without any preventive measures, each person infected with the Delta variant would have infected an average of five others.)
• Much lower levels of COVID-19 hygiene (no restrictions on public gatherings, mask-wearing down from 95% in the middle of last year’s winter wave to 60% now).

When I run that through a crude formula, including my own estimate for the impact of peak COVID-19 hygiene, and an assumption that current COVID-19 hygiene is, on net, half as effective, I come up with:

• R-effective last winter 1.035
• R-effective this winter 1.075

I wouldn’t put a lot of faith in either number.  I’m just saying that the magnitudes of these effects are in the ballpark of cancelling each other out.  It’s entirely possible that we’ll have a winter wave despite having 59% of the population fully immunized, and a further large percentage with some immunity due to prior infection.

Source:  CDC COVID data tracker.

To recap:  Best guess, that level of vaccination, plus all the prior infections, is just about enough immunity to offset the greater infectiousness of Delta and the reduction in COVID-19 hygiene.

Finally, FWIW, in the popular press you’ll hear the rise in cases attributed to people spending more time indoors.  Near as I can tell, that’s more-or-less nonsense.  In the modern world, there’s maybe one hour’s difference in total indoor time, winter-versus-summer, for the average adult.  There’s far more evidence to suggest that flu season is a result of dry indoor air.  Low relative humidity reduces the body’s ability to clear way inhaled pathogens (“mucocilliary clearance”) and otherwise reduces the effectiveness of the immune system at fighting respiratory illnesses.  I lay out the evidence for various hypotheses regarding why we have a winter flu (and now, coronavirus) season in Post #894 about relative humidity and flu.

 

I’m continuing to track this just because you can’t easily recover the history of case counts off the William and Mary COVID-19 dashboard.

I would classify this week’s seven new cases as no different from new case rate for the past six weeks.  In other words, I wouldn’t read anything into it.

Source:  Calculated from William and Mary COVID-19 dashboard, last accessed 11/5/2021.

If you read any of the rest of my blog — and there’s no reason you should — you can see that I’m still waiting for any sign of a U.S. winter COVID-19 wave.

So far, there’s nothing.  Just a little flattening of the trend in the past two weeks.  Same thing appears to be happening in Canada.

But in the U.S. South, and Virginia in particular, the COVID-19 new case rate continues on a modest downward trend.

If that changes, I’ll surely note it in these William and Mary posts.

For now, no news is good news.

Source:  Calculated from William and Mary COVID-19 dashboard.

Six new cases this week, compared to five last week.

Source:  Calculated from William and Mary COVID-19 dashboard accessed 10/23/2021.

As with the national numbers (just-prior post), things seem to have settled into an equilibrium.  No evidence of a coming winter wave of COVID.  No evidence that it’s going away any time soon, either.

Source:  Calculated from William and Mary COVID-19 dashboard.

Is there anything else worth noting?  I don’t think so.

With numbers this low, I’d love to start talking about the potential for false positives.  False positives in the sense of tests results showing the presence of COVID-19 in individuals who never actually had COVID.  If that were common enough, then maybe the trickle of cases currently being observed is actually zero true new cases, and we’re just seeing these results of some small false positive rate.

But I think that’s wishful thinking.  It’s far more likely that , in reality, there is still some low rate of infections circulating among the student body.

Let me work through the arithmetic on that as best I can.

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False positive COVID-19 DNA (PCR) tests

It’s tough to talk about false positive DNA (PCR) tests for COVID-19, for several reasons.

First, all the pandemic-denier nuts come out in full force as soon as you raise the topic.  That tends to poison rational discussion when people start claiming that (e.g.) it’s all a hoax, it’s all false testing, and so on.

So I need to start this by averring that I am not a nut.  I’m just trying to run down the numbers.

Second, that aside, it’s difficult to get an estimate of the false-positive rate for DNA (PCR) COVID-19 tests, because, hey, how else can you be sure somebody had COVID-19?  In practice, a positive PRC test is taken as the gold standard for somebody actually having COVID-19.  How can you test the gold standard?

That said, the American College of Pathology (ACP) says that, in practice, COVID-19 DNA (PCR) tests have 98% to 99% “specificity”.  That is, there’s a roughly 1 to 2 percent false positive rate.  (Per this reference).  Other seemingly legitimate studies put the false-positive rate between 0.8% and 4.0% (per this reference, in The Lancet).

I’d call that the same ballpark.  How they know that, I haven’t a clue.  But two seemingly authoritative source more-or-less agree, that’s good enough for me.

Third, there’s a separate confounding issue of PCR tests flagging individuals who actually had COVID-19, have recovered, and yet retain fragments of (dead) viral DNA on and in their nasal membranes.  I have yet to see any quantitative estimate of that, but that is, as I understand it, part of the reason that they don’t want you to get re-tested once you’ve tested positive and have recovered from all symptoms.  Not sure if that’s contained within the false-positive rates cited above, or not.

Fourth, there may be a re-testing protocol for positives.  I don’t think that’s done for COVID-19, but if so — if you double-checked every positive with a second test, and required two positives in a row — that would eliminate false positives due to (e.g.) mishandling of specimens in the lab.  (It would also likely eliminate a lot of true positives, as the DNA test has a pretty substantial false negative rate.)

Finally, and relevant here, the false-positive rate depends on the pre-testing probability that disease is present.  It’s much more of an issue for screening testing — where you test everybody on a population, regardless of symptoms — than testing-for-cause (for those with symptoms or known exposure).

For that last point, I would love to have a single-sentence explanation that anybody could understand, but I don’t.  Will it suffice to say that if somebody has every symptom of COVID-19 and tests positive, there’s little reason to question the validity of the test.  By contrast, an out-of-the-blue positive result, in somebody with no symptoms and no know exposure, should be subject to a higher degree of skepticism.

That pretest-probability effect contributes to the decision not to do screening testing on populations thought to have low probability of infection (such as vaccinated students, in our case).  Aside from the cost of the test, if the actual infection rate is low enough, you reach the point where much of what you are doing is incorrectly forcing healthy people to quarantine, due to false-positive test results.

So, crudely put, false positives are mostly a problem for screening testing, in a population with a low true positive rate.

As I understand it, the only screening testing at William and Mary is weekly testing of the un-vaccinated.  Those now account for just 2% of the student population, or maybe 130 students of the roughly 6600 student residents in and around the Williamsburg campus.

For the vaccinated 98%, testing is only being done for cause.  William and Mary only tests for symptoms or known close contact with an infected individual.  That should be true even for high-risk populations such as student athletes, as the NCAA says that screening testing is not necessary for vaccinated athletes (per the “Resocialization” document on the NCAA website).  The dashboard also includes positives that reported by students who had themselves tested, without having the testing done by William and Mary.

Consistent with that, last week William and Mary performed 162 new tests, but only tested 20 new individuals.  I’m guessing that the bulk of those tests were weekly screenings for the un-vaccinated, and so did not include new (not-previously-tested) students.

If the false-positive rate really is about what the ACP said it was — maybe 1 to 2 percent — then you’d expect maybe a false positive or two per week to arise out of the screening testing.  It’s tough to say.  A lot would depend on the particulars of which test, which lab, which procedures, and so on.  Out of testing-for-cause, I’d guess the expected false positive rate would be a tiny fraction of one test per week.

In other words, no matter how I slice it, using a realistic estimate of the in-the-field false positive rate from a reputable source, I can’t come up with five false positives.

If we knew more we could probably rule it out definitively.  But given the information that is public, my conclusion is that we have to assume that COVID-19 is still, in fact, circulating at low levels within the William and Mary student population.