As reminders…

Alpha–Variant first identified in the UK

Beta–Variant first identified in South Africa

Gamma–Variant first identified in Brazil

Delta–Variant first identified in India

Omicron–Variant first identified in South Africa

Updating the chart above:

Ancestral: B.1.1.529 Omicron

Transmissibility: All the +

Immune Evasiveness: All the +

Vaccine Effectiveness: Check (for hospitalization)

Also as a reminder:

Coronavirus Update–

–“All models are wrong, but some are useful.”

That’s an important saying to burn into your brain when anyone is modelling anything, but especially in biology and medicine, where the variables are many and not nearly as well understood as we would like.

Some models, of course, turn out to be utterly useless. This pandemic has not been particularly kind to some schools of epidemiologists, and a good run down for one sent by a UK reader is here.

–Worth mentioning that the UK will be abandoning all current COVID restrictions as the omicron wave has clearly passed. How much of that is belated CYA for Boris Johnson’s “Party Gate” scandals of holding holiday parties when the rest of the UK was not allowed to last month is in the eye of the beholder–but is at least consistent with extremely low Rt for the UK right now.

–In fact, a similarly low Rt to South Africa after its omicron wave crested. I expect this will be the general trend with omicron.

And on cue, you are already getting NYT “explainer” articles/emails this week highlighting that some of the early hit East Coast states are also seeing precipitous drops in new cases. Indiana’s data looks like confirmation that it peaked omicron late last week. Which would be nice. The testing volume continuing to go back to normal would be lovely. I think the US as a whole is well on the way to peaking omicron by the end of the month. To highlight variability within the US though, I have reader anecdotal evidence suggesting activity is quite high in the mountain states like Colorado right now.

–Our US readers can now get at home COVID test for four, direct from the US government here, if you have not already signed up for them. They will ship in 7-12 days, and assuming no delivery hiccups (like being stolen off a train in LA while the train is stuck in supply chain limbo, which is now a big thing per some news reports), will arrive just in time for the rapid decline phase of the omicron wave at your house for rapid COVID testing, should you need one.

These are rapid antigen tests, and should be stable on the shelf for awhile if you don’t need them immediately. Not every school and workplace accepts an at home rapid antigen test for their COVID testing and control policies, so check before you rely solely on these for those purposes. At a minimum though, it’s a quick way to determine if you really should undergo the hassle of more sensitive and specific PCR confirmation of a positive rapid COVID antigen test. More on that in a moment, because that was a story this week too.

There is no direct charge for these tests to you–tax dollars have already been dedicated to purchase these tests. In addition, a rules change now requires health insurers to cover up to 8 COVID tests per month. So if you have been using more than that and paying out of pocket because your insurer is a dick, at least that has changed a smidge.

You will also be able to pick up N95 masks at CVS in the US next week as well, again at no direct cost to you (tax dollars already paid for these as part of a strategic national reserve of these masks).

–Worth mentioning that the rapid antigen tests have recently come under fire in headlines this week, as they are not as sensitive nor as specific as PCR testing. Further, since many of them rely on identifying the spike protein of SARS-CoV-2, the mutant spike protein of omicron in particular may be reducing the sensitivity of certain tests. So far, the evidence suggests that asymptomatic “infection” may be especially challenging to the antigen tests. On the other hand, spread of SARS-CoV-2 from an asymptomatic person is pretty rare, as we have discussed many times before.

The real problem (and what the article writers miss) is that this is just math.

Let’s assume for a second that our rapid at home antigen test is 60% sensitive (will detect SARS-CoV-2 if it is actually there in 60 out of 100 people with SARS-CoV-2 really present) and 99.8% specific (will call 998 out of 1000 people who really don’t have SARS-CoV-2 negative). Put another way, it gets positive “right” 60% of the time and negative “right” 99.8% of the time.

And before you accuse me of being mean to the rapid antigen tests with that sensitivity number, that’s the high estimate for papers from CDC and the University of Utah that have measured the sensitivity and specificity of the Abbott Binax Now, a very popular commercial antigen test available in the US.

Now let’s test 50 million people with that, since everyone and their brother is getting omicron and everyone is testing like crazy right now–with these home kits especially, since omicron is a little more mild and a time slot for PCR is harder to come by due to demand. We’ll assume the PCR positivity rate for individuals in Indiana is close, so about 20% of that 50 million people actually have SARS-CoV-2. So 10 million of our 50 million actually have COVID.

Following so far?

Good.

They take our home antigen test. It’s 60% sensitive, so it detects 6 million out of the 10 million positive. That means 4 million people had a false negative though–and that’s enough as a raw number for some reporter’s friend to bitch to them about a case like in the article, where a false negative before a holiday gathering led to a positive person being in the room with grandma.

On the flip side, our 99.8% specific rapid antigen test correctly calls 39.92 million of the people who truly don’t have SARS-CoV-2 negative. There are only 80,000 false positive tests in this scenario–which, given the tens of millions, is not bad. 99.8% is a great specificity for a clinical assay. Test in the millions though and that 0.2% false positive rate will creep out of the word work though.

–“So what’s the best way to interpret my new government issued rapid antigen test, assuming those sensitivity and specificity numbers?” I hear you ask, Hypothetical Reader.

In consultation with your healthcare professional is my best answer, and thank you for understanding ; )

So let’s say you have symptoms and reason to suspect COVID, and use one of your government issued or off-shelf, insurance covered rapid antigen tests at home. In fact, we need to specifically assume that your chances of actually having COVID were 20% (or better) for the following calculations. So like close contact with known positive, or massive omicron wave rolling into town.

If your chances of having COVID were less than that before you took the test, the math changes. I’ll show that in a second.

So I cannot stress enough–assuming you have 20% chance of having COVID -before ever taking the test-, and you take a rapid antigen test for COVID… .

1) …and your rapid antigen test is positive:

Your chances of actually having COVID are now 98.7%. A second test, or confirmatory PCR, is HIGHLY likely to be positive for COVID too, and your best bet is to treat the result as confirmation that you have, indeed, caught the ‘rona. The test is (generally) good if it goes.

2) …and your rapid antigen test is negative:

Your chances you do NOT actually have COVID are now 90.9%. Which means ~9% of the time, that will be a false negative, and COVID is really lurking in your airway somewhere. So most likely negative. But if that 9% chance that the negative test is wrong could be significant to you or a family member/close contact, you can always follow up with a more specific PCR result. Regardless, if you have symptoms, stay the f*** away from people anyways.

–Those are pretty reasonable numbers to assume for your use of an at home rapid antigen test right now, but again, always consult your healthcare professional and thank you for understanding.

–Just to show you what happens, though, if you take a rapid antigen test when you are LESS likely to actually have COVID…. So we test 50 million people, but only 1 million people actually have COVID, as the wave has crested etc., and our sensitivity and specificity remain 60% and 99.8% respectively. Now if your test turns positive, your chance of actually having COVID is only 86%. And if your test was negative, the chances you do not actually have COVID are 99.2%.

So note the clinical accuracy will shift depending on how rampant SARS-CoV-2 is around you, and thus likely to be the true cause of your symptoms. Make sense?

–No, you will not be able to judge with high precision what your chances of having COVID are before taking your test (your healthcare professional might do a better job given your specific symptoms and how many other COVID patients they have been seeing lately). The assumptions we made for the 1) and 2) above are good ballparks though, right now. If I were in South Africa, where COVID is pretty muted, I might be leaning towards our second example.

–This math, where a certain number of false positives and false negatives are inevitable, and across a large enough population become pretty large numbers of clinically significant “misses”, is why the “zero COVID” policies failed, and will fail where they are continuing to be attempted, like China. At some point, there is a critical mass of infected patients where these clinically significant misses will happen and will catalyze new clusters.

Or think of it this way. If China screens a city of 50 million people with the rapid antigen for say, a thousand true active cases, then MOST of the positives will be false positives. If we do the same math with 60% sensitivity and 99.8% specificity, here’s what happens under their draconian “Zero COVID” policy:

You flat out miss 400 of the true positive cases. They continue to wander the city, infecting others.

You quarantine a little under 100,000 false positive cases (versus 600 actual COVID patients you detected and quarantined). These 100,000 people had the antigen test erroneously pop positive, but they did NOT actually have COVID. Some of them you will quarantine with the 600 actual COVID patients you found, now increasing the chance that some of the false positives will be true positive by the time they leave quarantine.

In either case, your chances of control, especially with the highly infectious omicron variant, are far less than you might otherwise think. Your only hope is that shutting entire cities down squashes the Rt of the virus enough to make up for all the clinically significant whiffs that your assay has made.

That China is having to prolong lockdowns, and extend to more and more geographies, should not be a surprise, especially if it is indeed omicron on the loose there (which seems inevitable).

–Following up previous reports, New York and California press released (I have not found peer reviewed publication of the data yet) that prior infection with COVID was -more- protective than vaccination against severe COVID from the delta variant in the run up to Thanksgiving. This is consistent with the two large Israeli studies that suggested prior infection might be more protective against severe COVID. Safe to say preponderance of evidence is growing that the CDC’s own study showing prior infection was not as effective as vaccination against hospitalization and death is the outlier.

Regardless, the important piece to remember about vaccination is that it has, thus far, consistently shown that it reduces your chance of hospitalization or worse from COVID by about 10 fold.

–The WHO endorsed two COVID treatments, one early and one late. Because of the manufacturer of one of them, I cannot comment any further, and thank you for your understanding.

Combination of socioeconomic and COVID science:

–Switching to models that may not be as useless, The Economist has a model running that attempts to estimate excess deaths due to the pandemic, which is simply the rate of death over the “expected” amount for the pandemic years versus previous years. This is a similar method to the actuarial data we mentioned a couple weeks ago (buried in the Dr. Malone section). They are looking at excess deaths to capture those who died of COVID (but were not tested), those who died with a positive COVID test (but of something else entirely) and deaths due to the social pressures etc. of lockdowns and supply shortages, like delayed treatments as health care systems were swamped or addictions/overdose/depression.

You can find The Economist’s model here. What is interesting to me is that The Economist model has excess deaths in the US at about 30% higher (at least than official COVID only numbers) and this is close to the total excess deaths that insurance company CEOs have reported (40% higher versus pre-pandemic deaths).

You may find this surprising, but the pandemic has not been a real good time across the board. As we mentioned before, the excess deaths will have socioeconomic ripple effects. Not only because of the loss of so many excess people, and the holes that leaves in the social and economic fabric, but the damage this has done to institutional credibility.

I think it also worth mentioning that those ripples gradually coalesced into waves after previous severe pandemics The Spanish Flu is likely an anomaly, as it was wrapped up in the “War to End All Wars” had already done significant damage to institutions in Europe in particular, and set in motion WW2, which -really- reset the globe and civilization. The Black Death may be a little more typical, where, oddly echoing the wage and inflation pressures now active, the relationship of the peasantry to the landed gentry was reset. Quite simply, there were now fewer peasants to do the work, meaning those who survived could demand a better deal–especially since their leadership utterly botched it. We mentioned before that this eventually became the Renaissance. We also mentioned that this was a little variable, as Russia and Poland, for example, went a little more authoritarian. As you watch the headlines, it is tempting to speculate if you are reading and hearing echoes of this past.

As far as all these changes go, I’m not even going to try to predict. I’m a doctor, not a prophet. There are too many variables at play for anyone to be an accurate prognosticator, and because of those variables, different directions for different people and places seem probable.

Regardless, we are in very early innings of the socioeconomic ripples. “Things that have changed since COVID” turns up early in the Google suggestion bar, the results go for pages, and they started writing those in 2020.

As much as we long for the “good old days” of 2018, that world is increasingly distant. The Bonfire of the Institutional Credibilities rises high, spitting sparks and casting long shadows, in stark relief. A furnace of princes, and it’s just heating up. Will Shadrach, Meshach and Abednego emerge, and will a vision of something better join them and rise within the crucible?

We won’t know for awhile. In fact, I suspect the shape of the world after COVID will take the rest of this decade to form, and this decade has greater chances than most to be one that makes a century.

–Also interesting in that Economist model of excess deaths is that China is clearly misrepresenting its COVID statistics. Surprising no one. After all, there were articles in the Lancet earlier in the pandemic showing nearly 1 million in Wuhan alone with SARS-CoV-2 antibodies months after outbreak, and before vaccination, exceeding the official number of COVID cases in China at that point by many fold. The Economist model looking at other indicators of higher all cause mortality pegs China underestimating the impact of COVID there by 17,000%.

The ripples will hit everyone.

–If excess deaths among the working aged were 30-40% higher in China as they were in the US, the following from Mike Avery at RaboBank is worth consideration (emphasis mine):

“Not so much market focus was placed on the Chinese demographic data also released, which showed a further precipitous decline in births that some demographers believe is still over-reporting the actual numbers (as they say so did past data when looking at births vs. school enrollment and hukou registration numbers). If the present trend is maintained –and marriage rates continued to fall sharply in 2021; and nobody else has turned that kind of demographic decline around so far– then by 2100, China’s population will be less than that of the US, and even by 2050 there will be 200m fewer people. Yes, there will be automation: but there are going to have to be *a lot* of robots to keep GDP growing at the kind of goal-seeking rates we associate as normal in China.”

The bold is a shocking statistic, and although China is aging more rapidly than some (and less than others–Japan and Germany for instance), this trend of reduced births has been spreading across the globe. There have been some who have argued that the next great challenge for the world is solving a more functional aging. Inactivity and getting older are not the way to achieve it. Automation will help some. But there is a large and growing unmet need for more active seniors. Otherwise, the medical bills (90% of lifetime healthcare spending is done in the last year of life) will threaten to bankrupt nations. How will the dwindling number of parents care for both children and their parents at the same time? What about the increasing many who will reach old age, and its current slate of debilitative diseases, with no children to support them? How will societies care for them?

Most of these debilitating, chronic diseases of aging are managed, not cured. It’s akin to taking your car in because a tire is flat, and being told the fix is a smaller replacement tire that will work, but you won’t be able to go as fast or as far, and you are now committed to these replacement tires every month for the rest of the life of the car. And oh by the way, common side effect of the replacement tire is the air conditioning sometimes won’t work. But the car will still run!

That’s a great strategy for the business of the mechanic shop, but it’s not exactly what the owner wants to hear.

Similarly, the guys and gals on the business side of campus love a drug that you take for a long time to control a disease. Something like antibiotics, which you take for just a little while, and then only maybe a few times in a decade, because it cures the bacterial infection is not as easy to fund. The projected ROI from the antibiotic project on their spreadsheets makes them more likely to invest in something else instead–something that will manage disease for a longer period.

You have done the greatest good in medicine when the patient no longer needs you. That’s great medicine, but bad business, as all you have then is the incidence of new disease. If you wonder why your healthcare system is so dysfunctional across its parts, it’s because the attempt to run something as a business that does not work well as a traditional business when it is run best for the patients.

The best medicine keeps the other parts of society’s production -productive-, and for longer.

All of that is a long way of wondering how we meet the problem of an aging world, especially some -rapidly- aging parts of it, with the usual model of business.

And again, if you can explain to me how you can use form and use a DAO like I’m 6, or know someone who can, reach out! : )

–Going back to the Rabobank quote and consequences of the shrinking Chinese population on China specifically, as it relates to COVID, again, wonder if the same 30-40% excess deaths among the 18-64 set in the US is also true in China.

Because the demographic data suggesting a rapidly aging, shrinking China implies that they cannot afford to lose any of those 18-64 year olds. Or at least the 18-40ish set, which are the prime demographic to contribute to “new births” to reverse the alarming trend.

Again, not an expert, but those numbers if correct suggest a few things. First, companies that have bet big on a rising, consuming middle class for the next century in China may wind up off sides sooner than they think. Second, as far as Taiwan goes, that could change the calculus in a couple ways. If they were ever going to militarily reunify Taiwan, there may be voices in the CCP that say the longer they wait, the fewer numbers on their side. Alternatively, that may actually raise the cost of military action, as soldiers they lose in a war are the exact ages they can increasingly NOT afford to lose at all, and still have the kind of China they envision in 2100.

So anyone, or any news program you follow, with all the HOT TAKES about what is going to happen–be very skeptical. There are a LOT of moving parts. And again, VERY early innings right now.

–Finally, your chances of catching coronavirus most places in the world are equivalent to the chances you should crank it up for this one: https://www.youtube.com/watch?v=gr_eVcCAUXo

<Paladin>