In early December I said that 2020 all-cause mortality in the U.S. would likely be comparable to figures from about 15 years ago. Now, Ben Martin confirms it with the chart below. Over time, declines in U.S. mortality have resulted from progress against disease and fewer violent deaths. COVID led to a jump in 2020, though some of last year’s deaths were attributable to policy responses, as opposed to COVID itself.
Here’s an even longer view of the trend from my post in December (for which 2020 is very incomplete):
As Martin notes sarcastically:
“Surprising, since the US is undergoing a ‘century pandemic‘ – In reality it is an event that’s unique in the last ‘15 years’”
The next chart shows 2020 mortality by month of year relative to the average of the past five years. Clearly, excess deaths have occurred compared to that baseline.
Using the range of deaths by month over the past 20 years (the blue-shaded band in the next chart), the 2020 figures don’t look quite as anomalous.
Finally, Martin shows total excess deaths in 2020 relative to several different baselines. The more recent (and shorter) the baseline time frame, the larger the excess deaths in 2020. Compared to the five-year average, 364,000 excess deaths occurred in 2020. Relative to the past 20 years, however, 150,000 excess deaths occurred last year. While those deaths are tragic, the pandemic looks more benign than when we confine our baseline to the immediate past.
Moreover, a large share of these excess deaths can be attributed to non-COVID causes of death that represent excesses relative to prior years, including drug overdoses, suicide, heart disease, dementia, and other causes. As many as 100,000 of these deaths are directly attributable lockdowns. That means true excess deaths caused by COVID infections were on the order of 50,000 relative to a 20-year baseline.
As infections subside from the fall wave, and as vaccinations continue to ramp up, some policy makers are awakening to the destructive impacts of non-pharmaceutical interventions (lockdown measures). The charts above show that this pandemic was never serious enough to justify those measures, and it’s not clear they can ever be justified in a free society. Yet some officials, including President Biden and Anthony Fauci, still labor under the misapprehension that masks mandates, stay-at-home orders, and restaurant closures can be effective or cost-efficient mitigation strategies.
I just quit Facebook for good, and it’s about time! Over the years my posts there became focused on links to my blog, SacredCowChips. In fact, I started the blog as a vehicle for longish-form refutation of nitwitted ideas to which I was regularly exposed on Facebook. Of course, nitwitted ideas are all too common in economic and political discourse, so there is always a deep vein of blog-worthy material. Facebook has no monopoly on that! More recently, COVID became a primary vehicle for foolish policy and commentary, which gave me plenty to write about.
What strikes me now is how much inspiration I drew from the purveyors of nonsense on Facebook. And when I say “inspired”, I mean it excited me to write posts that I knew would drop their jaws. Again, there are infinite sources of wrongheaded thinking and non-thinking acceptance of “woke” BS outside my circle of former Facebook friends. Still, I wonder whether posting my articles there gave me an extra thrill because I knew those people and could stick it right under their noses.
I’d say my hope was to persuade except I couldn’t help giving in to my disdain for “sacred cows.” Those aren’t really confined to one side of the political aisle, either. I’ll find a way to piss off everyone eventually. People of all stripes take pieces of received wisdom without subjecting them to logical scrutiny, and they don’t like to be told they’re wrong. I’m sure that led certain “friends” to “unfollow” me on Facebook. There’s no way of knowing, but it really didn’t bother me. What bothered me a little was when friends who agreed with me were too chickenshit to “like” a post. I know some had business interests to protect and couldn’t afford to alienate the crowd, but some people are more daring in that regard, to which I must accord some respect.
I now find myself on several platforms dominated by folks more amenable to my largely libertarian point of view. But I feel much more as if I’m “singing to the choir”. Also, I’m concerned that articles might get lost amid a sea of posts appealing to similar “mood affiliations”.
Here’s another concern: since I posted “On Leaving Facebook”, in which I was highly critical of the tech giants, my readership has plunged. Granted, I haven’t posted in six days due to travel and reorienting my social media connections. Nevertheless, I find the downturn in views and visitors to my blog highly coincidental and suspicious.
Even after all that, however, I’m still eager to continue writing about issues that are important to me. As part of that, I’ll find plenty of inspiration in the dumb reports of woke journalists, pundits, and politicos. And after all, the Biden Administration and Congress are full of busybodies who are so set on “doing something” that they will propose all sorts of moronic public policies. No, inspiration won’t be a problem!
Cartman is awesome! Haha! But really, that kind of reaction to the dominant social media platforms is well deserved, especially given their recent behavior. Listen to this: my wife’s church held a service of hymns and prayer for “healing the nation” on Tuesday. The church’s IT administrator posted an advance notice about the service on the church’s Facebook wall. There was nothing overtly political about the notice or the service itself. Nevertheless, somehow FB deemed the notice subversive and blocked it! We are not dealing with decent or reasonable people here. They are pigs, and we don’t have to do business with them.
A number of years ago, a woman told me FB was “the Devil!” She was very good natured and I laughed at the time. But there are many reasons for people to wean themselves from social media, or at least from certain platforms. The web abounds with testimony on lives improved by quitting FB, for example, and there are forums for those who’ve quit or would like to. There’s also plenty of practical advice on “how to leave”, so there is definitely some interest in getting out.
Ditching FB offers a certain freedom: you can eliminate the compulsion to check your news feed and escape those feelings of obligation to “like” or comment on certain posts. These are distractions that many can do without. No more efforts to “unsee” expressions of foot fetish narcissism! Free of the pathetic virtue signals that seem to dominate the space. And quitting might be especially nice if you’re keen on cutting ties with certain “frenemies”. Almost all of us have had a few. This study found that quitting FB results in less time online (surprise!) and more time with family and friends (pre-COVID lockdowns, of course). It also found that quitting leads to less political polarization! Imagine that!
There’s no question that FB helped me make new friends and reconnect with old ones. It also led to overdue severing of ties with a few toxic individuals. I know I’m likely to lose contact with people I truly like, and that’s too bad, but in most cases I must leave it up to them to stay in touch (read on). Obviously, there are many ways to stay in contact with friends you really want to keep.
As for politics (and seemingly every aspect of life has been politicized), now is a very good time to quit FB if you believe in free expression, the value of diverse opinion, and a free marketplace of ideas. FB doesn’t want that. As the episode at my wife’s church demonstrates, FB has been brazenly selective in suppressing opinion, like other prominent social media platforms. It was obvious well before the presidential election, and it has become intolerable since.
How To Defacebook
There are voices that counsel patience with the tech giants. They recommend a strategy of diversification across platforms, without necessarily quitting any of them. I can understand why certain people might prefer that route. It’s well nigh impossible to migrate an extended family to another platform, for example. However, juggling several accounts can be a problem of time management. And for me, this all boils down to a matter of disgust. It’s time to stick it to FB.
This rest of this post offers some practical advice on quitting FB and more thoughts on how and why I’m doing it. This will also appear on some speech-friendly platforms, so if you see it there and you haven’t quit FB, do it! You’re already halfway there.
The first decision is whether to quit outright or deactivate. Many don’t have the fortitude to stay away if they merely deactivate, and maybe they just need a break. For others, FB has earned an enmity that can only be satisfied by leaving for good. Count me among the latter.
You should reclaim all of your data before you quit: you can download it to a zip file, which will include all of your photos, chats, “About” information, your friends’ birthdays, etc… While it’s been claimed that shutting your account will cleanse Facebook of all your data, that’s not entirely the case. For example, your friends might still retain chats in which you participated. In fact, I’m not convinced all of your data isn’t permanently in FB’s possession, if not the NSA’s, but we might never know.
You should also change your login credentials on other online accounts linked to FB. You should be able to identify some or maybe all of those by looking at the password section in “Settings”. I’m not sure whether scrolling though and checking all the apps listed in Settings will help — it didn’t help me identify anything that the password section did not.
It’s a good idea to keep Messenger up for a while in case any of your friends want to inquire or find a way to stay in touch. That’s fine, but to really rid yourself of FB, you must part with Messenger eventually. Of course, you’ll lose Instagram and WhatsApp when you quit FB. I don’t use those, so it won’t be a problem for me.
Then there are the “I’m Going To Quit!” status updates, sometimes laced with sadness or anger. I haven’t found those particularly appealing in the past… I’ve often wondered if they were merely ploys to get attention. But things have changed. I will add this post to my wall and leave it there for a few days. My *noble* intent is to help others quit, and to do my small part to foster a more competitive social media environment. Another way to communicate your departure would be to use Messenger to inform selected friends, but that’s more work. And by the way, in anticipation of my stop date, I’ve been culling my friends list more aggressively than ever.
Once you pull the trigger and click “Delete”, your account will remain active for a few days. Don’t be a sucker. Delete the app on your phone. Wait it out. Forget about it!
Again, there was never a better time to dump FB. Beyond any emotionally corrosive aspects of social media, the last straw should be the selective censorship of political views, shadow bans, outright bans, and deletion of groups. Lately, it’s been like witnessing the early transition from Weimar to the Third Reich. We can only hope the full transition will remain unfulfilled.
For a company protected from liability under Section 230 of the Telecommunications Act, FB’s refusal to respect First Amendment rights and to abide diversity of opinion is shocking. Don’t tell me about fact checking! Facebook fact checkers are politically motivated hacks, and the new “oversight board” is not likely to help you and me. The presumption underlying Section 230 is that these platforms are not publishers, but having abandoned all pretense of impartiality, they should not be entitled to immunity. Moreover, they have tremendous market power, and they are colluding in an effort to consolidate political power and protect their dominant market position.
Big Tech, and not just FB, has been flagrant in this hypocrisy. These firms have deplatformed individuals who’ve questioned the legitimacy of the presidential election, and there is plenty to question. But they refuse to censor Antifa and BLM rioters, antisemites, state terrorists, and genocidal tyrants from around the world, including the Chinese Communist Party. More recently, FB and other platforms have condemned supporters of President Trump, as if that support was equivalent to endorsing those who stormed the Capital on June 6th. And even if it were, would an objective arbiter not also condemn leftist violence? How about equal condemnation of the Antifa and BLM rioters who ravaged American cities throughout last summer? Or those who rioted at the time of Trump’s inauguration?
The social media platforms won’t do that. FB is bad, but Twitter is probably the worst of them all. I quit using Google years ago due to privacy concerns, but also because it became obvious to me that it’s search results are heavily biased. Amazon pulled the rug out from under Parler, and I will quit using Amazon when my Prime membership is up for renewal unless Jeff Bezos starts singing a different tune by then. These companies are anticompetitive, but there are other ways to buy online, and there is plenty of other video programming.
The power of Big Tech is not absolute. Remember, there are alternatives if you choose to quit or diversify: check out MeWe, Clouthub, Rumble (video hosting), Gab, Signal, and Telegram, for example (see this interesting story on the latter two). And Parler, of course, if it manages to find a new hosting service or wins some kind of emergency relief against Amazon.
Message me for my contact information or my identity on other platforms, or you can always find my ruminations at SacredCowChips.net. You can even share them on FB (if they’ll let you), at the risk of alienating your “woke” friends! So long.
The pandemic outlook remains mixed, primarily due to the slow rollout of the vaccines and the appearance of new strains of the virus. Nationwide, cases and COVID deaths rose through December. Now, however, there are several good reasons for optimism.
The fall wave of the coronavirus receded in many states beginning in November, but the wave started a bit later in the eastern states, in the southern tier of states, and in California. It appears to have crested in many of those states in January, even after a post-holiday bump in new diagnoses. As of today, Johns Hopkins reports only two states with increasing trends of new cases over the past two weeks: NH and VA, while CT and WY were flat. States shaded darker green have had larger declines in new cases.
A more detailed look at WY shows something like a blip in January after the large decline that began in November. Trends in new cases have clearly improved across the nation, though somewhat later than hoped.
While the fall wave has taken many lives, we can take some solace in the continuing decline in the case fatality rate. (This is not the same as the infection mortality rate (IFR), which has also declined. The IFR is much lower, but more difficult to measure). The CFR fell by more than half from its level in the late summer. In other words, without that decline, deaths today would be running twice as high.
Some of the CFR’s decline was surely due to higher testing levels. However, better treatments are reducing the length of hospital stays for many patients, as well as ICU admittance and deaths relative to cases. Monoclonal antibodies and convalescent plasma have been effective for many patients, and now Ivermectin is showing great promise as a treatment, with a 75% reduction in mortality according to the meta-analysis at the link.
Reported or “announced” deaths remain high, but those reports are not an accurate guide to the level or trend in actual deaths as they occur. The CDC’s provisional death reports give the count of deaths by date of death (DOD), shown below. The most recent three to four weeks are very incomplete, but it appears that actual deaths by DOD may have peaked as early as mid-December, as I speculated they might last month. Another noteworthy point: by the totals we have thus far, actual deaths peaked at about 17,000 a week, or just over 2,400 a day. This is substantially less than the “announced” deaths of 4,000 or more a day we keep hearing. The key distinction is that those announced deaths were actually spread out over many prior weeks.
A useful leading indicator of actual deaths has been the percentage of ER patients presenting COVID-like illness (CLI). The purple dots in the next CDC chart show a pronounced decline in CLI over the past three weeks. This series has been subject to revisions, which makes it much less trustworthy. A less striking decline in late November subsequently disappeared. At the time, however, it seemed to foretell a decline in actual deaths by mid-December. That might actually have been the case. We shall see, but if so, it’s possible that better therapeutics are causing the apparent CLI-deaths linkage to break down.
A more recent concern is the appearance of several new virus strains around the world, particularly in the UK and South Africa. The UK strain has reached other countries and is now said to have made appearances in the U.S. The bad news is that these strains seem to be more highly transmissible. In fact, there are some predictions that they’ll account for 30% of new cases by the beginning of March. The South African strain is said to be fairly resistant to antibodies from prior infections. Thus, there is a strong possibility that these cases will be additive, and they might or might not speedily replace the established strains. The good news is that the new strains do not appear to be more lethal. The vaccines are expected to be effective against the UK strain. It’s not yet clear whether new versions of the vaccines will be required against the South African strain by next fall.
Vaccinations have been underway now for just over a month. I had hoped that by now they’d start to make a dent in the death counts, and maybe they have, but the truth is the rollout has been frustratingly slow. The first two weeks were awful, but as of today, the number of doses administered was over 14 million, or almost 46% of the doses that have been delivered. Believe it or not, that’s an huge improvement!
About 4.3% of the population had received at least one dose as of today, according to the CDC. I have no doubt that heavier reliance on the private sector will speed the “jab rate”, but rollouts in many states have been a study in ineptitude. Even worse, now a month after vaccinations began, the most vulnerable segment of the population, the elderly, has received far less than half of the doses in most states. The following table is from Phil Kerpen. Not all states are reporting vaccinations by age group, which might indicate a failure to prioritize those at the greatest risk.
It might not be fair to draw strong conclusions, but it appears WV, FL, IN, AK, and MS are performing well relative to other states in getting doses to those most at risk.
Even with the recent increase in volume, the U.S. is running far behind the usual pace of annual flu vaccinations. Each fall, those average about 50 million doses administered per month, according to Alex Tabarrok. He quotes Youyang Gu, an AI forecaster with a pretty good track record thus far, on the prospects for herd immunity and an end to the pandemic. However, he uses the term “herd immunity” as the ending share of post-infected plus vaccinated individuals in the population, which is different than the herd immunity threshold at which new cases begin to decline. Nevertheless, in Tabarrok’s words:
“… the United States will have reached herd immunity by July, with about half of the immunity coming from vaccinations and half from infections. Long before we reach herd immunity, however, the infection and death rates will fall. Gu is projecting that by March infections will be half what they are now and by May about one-tenth the current rate. The drop will catch people by surprise just like the increase. We are not good at exponentials. The economy will boom in Q2 as infections decline.”
That sounds good, but Tabarrok also quotes a CDC projection of another 100,000 deaths by February. That’s on top of the provisional death count of 340,000 thus far, which runs 3-4 weeks behind. If we have six weeks of provisionals to go before February, with actual deaths at their peak of about 17,000 per week, we’ll get to 100,000 more actual deaths by then. For what it’s worth, I think that’s pessimistic. The favorable turns already seen in cases and actual deaths, which I believe are likely to persist, should hold fatalities below that level, and the vaccinations we’ve seen thus far will help somewhat.
I see references to “long COVID” or “long-haul COVID” almost every day. No, it’s not an extended COVID infection or an extra scary version of COVID. It’s about lingering or new symptoms after recovery from the infection. Reportedly, these symptoms range from fatigue or anxiety to joint pain. Sometimes they are rather unusual afflictions such as “COVID toes”, described as rashes or red spots on toes. Sebastian Rushworth notes that there is “no hard evidence that long COVID is a distinct entity”. It was essentially invented on social media by groups of individuals who connected to discuss various post-COVID symptoms. Rushworth says:
“The most common symptoms in people with long covid (defined in the study as still having symptoms after four weeks) were fatigue (98%) and intermittent headache (91%). … symptoms of long covid are extremely unspecific, so it is probable that long covid is actually a whole bunch of different things, of which I would think post-viral syndrome is likely a significant part.”
Post-viral syndrome should not be a big surprise, since COVID is, well, a virus! PVS can last for months and commonly has the following symptoms:
Those sound familiar. PVS symptoms are thought to be a consequence of the body’s effort to fight off a virus, including the lingering effects of a strong immune response and the inflammation it can induce. Such an immune response can lead to even greater problems for those with a genetic predisposition for autoimmune diseases like diabetes. It happens. But none of this is new or unique to COVID.
While PVS and autoimmune diseases are very real, the unbridled panic over COVID has led to a few false claims. “COVID toes” is one of them. Moreover, the pandemic precipitated an avalanche of poor-quality academic research, rushed in an effort to produce useful findings. Some of that research is implicated in the COVID myths we’ve heard. An example discussed at the last link is the incidence of heart inflammation or myocarditis in COVID patients. This was all over the media in the months leading up to the college football season, as young athletes were said to be vulnerable. In fact, it’s incidence among COVID patients is fairly rare, and it’s not unique to COVID.
COVID can be a nasty infection, primarily for the aged and those with pre-existing conditions, including obesity. PVS is an unfortunate reality for many patients. But “long-COViD” is merely a varied collection of post-viral symptoms. Many of them are vague and usually self-diagnosed. Long COVID is, as Rushworth says, “basically whatever the person who thinks they have it says it is.” That the media has promoted long COVID and its varied manifestations as something wholly new, including a few probable “imagifestations” (to coin a term), is one more example of the “panic porn” to which we’ve been subjected during the pandemic.
Here’s one of the many entertaining videos made by people who want to convince you that hospitals are overrun with COVID patients (and here is another, and here, here, and here). That assertion has been made repeatedly since early in the pandemic, but as I’ve made clear on at least two occasions, the overall system has plenty of capacity. There are certainly a few hospitals at or very near capacity, but diverting patients is a long-standing practice, and other hospitals have spare capacity to handle those patients in every state. Those with short memories would do well to remember 2018 before claiming that this winter is unique in terms of available hospital beds.
An old friend with long experience as a hospital administrator claimed that I didn’t account for staffing shortfalls in my earlier posts on this topic, but in fact the statistics I presented were all based on staffed inpatient or ICU beds. Apparently, he didn’t read those posts too carefully. Moreover, it’s curious that a hospital administrator would complain so bitterly of staffing shortfalls in the wake of widespread hospital layoffs in the spring. And it’s curious that so many layoffs would accompany huge bailouts of hospital systems by the federal government, courtesy of the CARES Act.
In fairness, hospitals suffered huge declines in revenue in the spring of 2020 as elective procedures were cancelled and non-COVID patients stayed away in droves. Then hospitals faced the expense of covering their shortfalls in PPE. We know staffing was undercut when health care workers were diagnosed with COVID, but in an effort to stem the red ink, hospitals began laying-off staff anyway just as the the COVID crisis peaked in the spring. About 160,000 staffers were laid off in April and May, though more than half of those losses had been recovered as of December.
Did these layoffs lead to a noticeable shortfall in hospital capacity? It’s hard to say because bed capacity is a squishy metric. When patients are discharged, staffed beds can ratchet down because beds might be taken “off-line”. When patients are admitted, beds can be brought back on-line. ICU capacity is flexible as well, as parts of other units can be quickly modified for patients requiring intensive care. And patient ratios can be adjusted to accommodate layoffs or an influx of admissions. Since early in the fall, occupancy has been overstated for several reasons, including a new requirement that beds in use for observation of outpatients with COVID symptoms for 8 hours or more must be reported as beds occupied. However, there are hospitals claiming that COVID is stressing capacity limits, but nary a mention of the earlier layoffs.
So where are we now in terms of staffed hospital occupancy. The screen shot below is from the HHS website and represents staffed bed utilization nationwide. 29% of capacity is open, hardly a seasonal anomaly, and there are very few influenza admissions thus far this winter, which is rather unique. 37% of ICU beds are available, and COVID patients, those admitted either “for” or “with” COVID, account for less than 18% of inpatients, though again, that includes observational beds.
Next are the 25 states with the highest inpatient bed utilization as of January 7th. Rhode Island tops the list at just over 90%, and eight other states are over 80%. In terms of ICU utilization, Georgia and Alabama are very tight. California and Arizona are outliers with respect to proportions of COVID inpatients, 41% and 38%, respectively. Finally, CA, GA, AL and AZ are all near or above 50% of ICU beds occupied by COVID patients.
So some of the states reaching the peak of their fall waves are pretty tight, and there are states with large numbers of very serious cases. Nevertheless, in all states there is variation across local hospitals to serve in relief, and it is not unusual for hospitals to suffer wintertime strains on capacity.
Los Angeles County is receiving much attention for recent COViD stress placed on hospital capacity. But it is hard to square that narrative with certain statistics. For example, Don Wolt notes that the state of California reports available ICU capacity in Southern CA of zero, but LA County has reported 10% ~ 11% for weeks. And the following chart shows that LA County occupancy remains well below it’s July peak, especially after a recent downward revision from the higher level shown by the blue dashed line.
Interestingly, the friend I mentioned said I should talk with some health system CEOs about recent occupancies. He overlooked the fact that I quoted or linked to comments from some system CEOs in my earlier posts (linked above). It’s noteworthy that one of those CEOs, and this report from the KPI Institute, propose that an occupancy rate of 85% is optimal. This medical director prefers a 75% – 85% rate, depending on day of week. These authors write that there is no one “optimal” occupancy rate, but they seem to lean toward rates below 85%. This paper reports a literature search indicating ICU occupancy of 70% -75% is optimal, while noting a variety of conditions may dictate otherwise. Seasonal effects on occupancy are of course very important. In general, we can conclude that hospital utilization in most states is well within acceptable if not “optimal” levels, especially in the context of normal seasonal conditions. However, there are a few states in which some hospitals are facing tight capacity, both in total staffed beds and in their ICUs.
None of this is to minimize the challenges faced by administrators in managing hospital resources. No real crisis in hospital capacity exists currently, though hospital finances are certainly under stress. Yes, hospitals collect greater reimbursements on COVID patients via the CARES Act, but COVID patients carry high costs of care. Also, hospitals have faced steep declines in revenue from the fall-off in other care, high costs in terms of PPE, specialized equipment and medications, and probably high temporary staffing costs in light of earlier layoffs and short-term losses of staff to COVID infections. The obvious salve for many of these difficulties is cash, and the most promising source is public funding. So it’s unsurprising that executives are inclined to cry wolf about a capacity crisis. It’s a simple story and more appealing than pleading for cash, and it’s a scare story that media are eager to push.
Both the Pfizer and the Moderna COVID vaccines require two doses, with an effectiveness of about 95%. But a single dose may have an efficacy of about 80% that is likely to last over a number of weeks without a second dose. There are varying estimates of short-term efficacy, and but see here, here, and here. The chart above is for the Pfizer vaccine (red line) relative to a control group over days since the first dose, and the efficacy grows over time relative to the control before a presumed decay ever sets in.
Unfortunately, doses are in short supply, and getting doses administered has proven to be much more difficult than expected. “First Doses First” (FDF) is a name for a vaccination strategy focusing on delivering only first doses until a sufficient number of the highly vulnerable receive one. After that, second doses can be administered, perhaps within some maximum time internal such as 8 – 12 weeks. FDF doubles the number of individuals who can be vaccinated in the short-term with a given supply of vaccine. Today, Phil Kerpen posted this update on doses delivered and administered thus far:
Dosing has caught up a little, but it’s still lagging way behind deliveries.
As Alex Tabbarok points out, FDF is superior strategy because every two doses create an average of 1.6 immune individuals (2 x 0.8) instead of just 0.95 immune individuals. His example involves a population of 300 million, a required herd immunity level of two-thirds (higher than a herd immunity threshold), and an ability to administer 100 million doses per month. Under a FDF regime, you’ve reached Tabarrok’s “herd immunity” level in two months. (This is not to imply that vaccination is the only contributor to herd immunity… far from it!) Under the two-dose regime, you only get halfway there in that time. So FDF means fewer cases, fewer deaths, shorter suspensions of individual liberty, and a faster economic recovery.
An alternative that doubles the number of doses available is Moderna’s half-dose plan. Apparently, their tests indicate that half doses are just as effective as full doses, and they are said to be in discussions with the FDA and Operation Warp Speed to implement the half-dose plan. But the disadvantage of the half-dose plan relative to FDF is that the former does not help to overcome the slow speed with which doses are being administered.
Vaccine supplies are bound to increase dramatically in coming months, and the process of dosing will no doubt accelerate as well. However, for the next month or two, FDF is too sensible to ignore. While I am not a fan of all British COVID policies, their vaccination authorities have recommended an FDF approach as well as allowing different vaccines for first and second doses.
Anthony Fauci has repeatedly increased his estimate of how much of the population must be vaccinated to achieve what he calls herd immunity, and he did it again in late December. This series of changes, and other mixed messages he’s delivered in the past, reveal Fauci to be a “public servant” who feels no obligation to level with the public. Instead, he crafts messages based on what he believes the public will accept, or on his sense of how the public must be manipulated. For example, by his own admission, his estimates of herd immunity have been sensitive to polling data! He reasoned that if more people reported a willingness to take a vaccine, he’d have flexibility to increase his “public” estimate of the percentage that must be vaccinated for herd immunity. Even worse, Fauci appears to lack a solid understanding of the very concept of herd immunity.
There is so much wrong with his reasoning on this point that it’s hard to know where to start. In the first place, why in the world would anyone think that if more people willingly vaccinate it would imply that even more must vaccinate? And if he felt that way all along it demonstrates an earlier willingness to be dishonest with the public. Of course, there was nothing scientific about it: the series of estimates was purely manipulative. It’s almost painful to consider the sort of public servant who’d engage in such mental machinations.
Immunity Is Multi-Faceted
Second, Fauci seemingly wants to convince us that herd immunity is solely dependent on vaccination. Far from it, and I’m sure he knows that, so perhaps this too was manipulative. Fauci intimates that COVID herd immunity must look something like herd immunity to the measles, which is laughable. Measles is a viral infection primarily in children, among whom there is little if any pre-immunity. The measles vaccine (MMR) is administered to young children along with occasional boosters for some individuals. Believe it or not, Fauci claims that he rationalized a requirement of 85% vaccination for COVID by discounting a 90% requirement for the measles! Really???
In fact, there is substantial acquired pre-immunity to COVID. A meaningful share of the population has long-memory, cross-reactive T-cells from earlier exposure to coronaviruses such as the common cold. Estimates range from 10% to as much as 50%. So if we stick with Fauci’s 85% herd immunity “guesstimate”, 25% pre-immunity implies that vaccinating only 60% of the population would get us to Fauci’s herd immunity goal. (Two qualifications: 1) the vaccines aren’t 100% effective, so it would take more than 60% vaccinated to offset the failure rate; 2) the pre-immune might not be identifiable at low cost, so there might be significant overlap between the pre-immune and those vaccinated.)
Vaccinations approaching 85% would be an extremely ambitious goal, especially if it is recommended annually or semi-annually. It would be virtually impossible without coercion. While more than 91% of children are vaccinated for measles in the U.S., it is not annual. Thus, measles does not offer an appropriate model for thinking about herd immunity to COVID. Less than half of adults get a flu shot each year, and somewhat more children.
Fauci’s reference to 85% – 90% total immunity is different from the concept of the herd immunity threshold (HIT) in standard epidemiological models. The HIT, often placed in the range of 60% – 70%, is the point at which new infections begin to decline. More infections occur above the HIT but at a diminishing rate. In the end, the total share of individuals who become immune due to exposure, pre-immunity or vaccination will be greater than the HIT. The point is, however, that reaching the HIT is a sufficient condition for cases to taper and an end to a contagion. If we use 65% as the HIT and pre-immunity of 25%, only 40% must be vaccinated to reach the HIT.
A recent innovation in epidemiological models is the recognition that there are tremendous differences between individuals in terms of transmissibility, pre-immunity, and other factors that influence the spread of a particular virus, including social and business arrangements. This kind of heterogeneity tends to reduce the effective HIT. We’ve already discussed the effect of pre-immunity. Suppose that certain individuals are much more likely to transmit the virus than others, like so-called super-spreaders. They spur the initial exponential growth of a contagion, but there are only so many of them. Once infected, no one else among the still-susceptible can spread the virus with the same force.
Researchers at the Max Planck Institute (and a number of others) have gauged the effect of introducing heterogeneity to standard epidemiological models. It is dramatic, as the following chart shows. The curves simulate a pandemic under different assumptions about the degree of heterogeneity. The peak of these curves correspond to the HIT under each assumption (R0 refers to the initial reproduction number from infected individuals to others).
Moderate heterogeneity implies a HIT of only 37%. Given pre-immunity of 25%, only an additional 12% of the population would have to be infected or vaccinated to prevent a contagion from gaining a foothold for the initial exponential stage of growth. Fauci’s herd immunity figure obviously fails to consider the effect of heterogeneity.
How Close To the HIT?
We’re not as far from HITs as Fauci might think, and a vaccination goal of 85% is absurd and unnecessary. The seasonal COVID waves we’ve experienced thus far have faded over a period of 10-12 weeks. Estimates of seroprevalence in many localities reached a range of 15% – 25% after those episodes, which probably includes some share of those with pre-immunity. To reach the likely range of a HIT, either some additional pre-immunity must have existed or the degree of heterogeneity must have been large in these populations.
But if that’s true, why did secondary waves occur in the fall? There are a few possibilities. Of course, some areas like the upper Midwest did not experience the springtime wave. But in areas that suffered a recurrance, perhaps the antibodies acquired from infections did not remain active for as long as six months. However, other immune cells have longer memories, and re-infections have been fairly rare. Another possibility is that those having some level of pre-immunity were still able to pass live virus along to new hosts. But this vector of transmission would probably have been quite limited. Pre-immunity almost surely varies from region to region, so some areas were not as firmly above their HITs as others. It’s also possible that infections from super-spreaders were concentrated within subsets of the population even within a given region, in certain neighborhoods or among some, but not all, social or business circles. Therefore, some subsets or “sub-herds” achieved a HIT in the first wave, but it was unnecessary for other groups. In other words, sub-herds spared in the first wave might have suffered a contagion in a subsequent wave. And again, reinfections seem to have been rare. Finally, there is the possibility of a reset in the HIT in the presence of a new, more transmissible variant of the virus, as has become prevalent in the UK, but that was not the case in the fall.
Tyler Cowen has mentioned another possible explanation: so-called “fragile” herd immunity. The idea is that any particular HIT is dependent on the structure of social relations. When social distancing is widely practiced, for example, the HIT will be lower. But if, after a contagion recedes, social distancing is relaxed, it’s possible that the HIT will take a higher value at the onset of the next seasonal wave. Perhaps this played a role in the resurgence in infections in the fall, but the HIT can be reduced via voluntary distancing. Eventually, acquired immunity and vaccinations will achieve a HIT under which distancing should be unnecessary, and heterogeneity suggests that shouldn’t be far out of reach.
Anthony Fauci has too often changed his public pronouncements on critical issues related to management of the COVID pandemic. Last February he said cruises were fine for the healthy and that most people should live their lives normally. Oops! Then came his opinion on the limited effectiveness of masks, then a shift to their necessity. His first position on masks has been called a “noble lie” intended to preserve supplies for health care workers. However, Fauci was probably repeating the standing consensus at that point (and still the truth) that masks are of limited value in containing airborne pathogens.
This time, Fauci admitted to changing his estimate of “herd immunity” in response to public opinion, a pathetic approach to matters of public health. What he called herd immunity was really an opinion about adequate levels of vaccination. Furthermore, he neglected to consider other forms of immunity: pre-existing and already acquired. He did not distinguish between total immunity and the herd immunity threshold that should guide any discussion of pandemic management. He also neglected the significant advances in epidemiological modeling that recognize the reality of heterogeneity in reducing the herd immunity threshold. The upshot is that far fewer vaccinations are needed to contain future waves of the pandemic than Fauci suggests.
In advanced civilizations the period loosely called Alexandrian is usually associated with flexible morals, perfunctory religion, populist standards and cosmopolitan tastes, feminism, exotic cults, and the rapid turnover of high and low fads---in short, a falling away (which is all that decadence means) from the strictness of traditional rules, embodied in character and inforced from within. -- Jacques Barzun