Category Archives: Pandemic

The Great Unmasking: Take Back Your Stolen Face!

28 Friday Jan 2022

Posted by in Masks, Pandemic

≈ Leave a comment

Tags

, , , , , , , , , , , , , , , , , , , , , , , , ,

Right at the start of the pandemic, Dr. Anthony Fauci insisted that masks were unnecessary, which was in line with the preponderance of earlier evidence. Later, he sowed confusion — and distrust — by claiming he said that to discourage a run on masks, thus preserving supplies for the medical community. That mix-up put a stain on his credibility among those who were paying attention, and the reversal was simply bad policy given what is well established by the evidence on mask efficacy.

No Mas, No Mask!

Despite my own doubts about the efficacy of masks, I went along with masking for a while. It gave me a chuckle to see people wearing them outside, especially runners, or on solo drivers. We knew by then that contracting Covid outside was highly unlikely. I was also amused by the idiotic protocols in place at many restaurants, where it was just fine to remove them once you walked a few feet to sit at your table, as if aerosols indoors were bound within narrow bands of altitude. Finally, I had reservations about the health consequences of frequent masking, which have certainly been borne out. Restricting air flow is generally not good for human health! Neither is trapping bits of sputum and hot, exhaled moisture rich in microbes right up against one’s muzzle. Still, I thought it polite to wear a mask in places of business, and I did so for a number of months. “Oh, but should I double mask?”, I asked myself? Gross! Just Shut*Up!

In time it became apparent that the cloth and paper masks we were all wearing were a waste of effort. Covid is spread via fine aerosols and generally not droplets. That’s important because the masks in common use cannot block a sufficient level of Covid particles from escaping nor from penetrating through gaps and through the fiber itself. Neither can N95s if not fitted properly, as so many are not. And none of these masks can protect your eyeballs! When tens of thousands of tiny beads of aerosol are released with each cough or exhalation, a mask that stops 70% of them will not accomplish much.

The evidence began to accumulate that mask mandates were completely ineffective at “stopping the spread” of Covid. I then became an ardent anti-masker. I generally don’t wear them anywhere except medical buildings, and then only because I refuse to defer normal medical care, the consequences of which have been tragic during the pandemic. I have told clerks “I don’t need a mask”, which is true, and they have backed off. I have turned on my heal at stores that refuse to give on the issue, but like masks themselves, the signs on the doors are usually more for show than anything else. So I walk right past them.

Now, the Biden Administration has decided to provide to the public 400 million N95 masks — on the taxpayer! It’s a waste of time and money. But the timing is incredible, just as the Omicron wave crashes on it’s own. It will be one more worthless act of theatre. But don’t doubt for a moment that Joe Biden, when no one remembers the timing, will claim that this action helped defeat Omicron.

Mask Choices

What is the real efficacy of masks in stopping the spread of Covid aerosol emissions? Cloth masks, including bandanas and scarves, are still the most popular masks. Based on casual observation, I suspect most of those masks aren’t washed as frequently as they should be. People hang them from their rear view mirrors for God knows how long. Beyond that, cloth masks tend to fit loosely and protect from aerosols about as well as the disposable medical or surgical masks that are now so common. Which is to say they don’t provide much protection at all.

But can that be? Don’t surgeons think they help? Well yes, because operating rooms can be very splattery places. Besides, it’s rude to sneeze into your patient’s chest cavity. Protection against fine aerosols? Not so much.

Face shields are “transparently” useless, offering no barrier against floating aerosols whatsoever except a fleeting moment’s protection against those blown directly into the wearer’s face. Then there are respirator masks: N95 and KN95, which are essentially the same thing. The difference is that KN95s must meet Chinese performance standards rather than U.S. standards. Both must filter and capture 95% of airborne particles as small as 0.3 microns. Covid particles are smaller than that, but the aerosol “beadlets” in which they are swathed may be larger, so the respirators would appear to be a big step up from cloth or surgical masks. R95 and P95 masks are made for protection against oil-based particles. They seem to be better overall due to thicker material and tighter fit with an overhead strap and extra padding.

Measuring Mask Efficacy

A thorough assessment of these mask types is documented in a 2021 paper published in The Physics of Fluids. Here are the baseline filtration efficiencies measured by the authors with an ideal mask fit relative to exhalation of 1 micron aerosols:

  • Cloth_______40%
  • Surgical____47%
  • KN95_______95%
  • R95_________96%

These are simply the filtration efficiencies of the respective barrier materials used in each type of mask, as measured by the researcher’s tests. Obviously, cloth and surgical masks don’t do too well. Unfortunately, even the N95 and KN95 masks never fit perfectly:

“It is important to note that, while masks … decrease the forward momentum of the respiratory jet, a significant fraction of aerosol escapes the masks, particularly at the bridge of the nose.”

Next, the authors assess the “apparent” filtration efficiencies of masks measured by relative aerosol concentrations in an enclosed space, measured two meters away from the source, after an extended period. This is a tough test for a mask, but it amounts to what people hope masks can accomplish: trapping aerosols containing bits of crap on material surrounding the nose and mouth, and for many hours. Here are the results:

  • Cloth___________9.8%
  • Surgical_______12.4%
  • KN95__________46.3%
  • R96____________60.2%
  • KN95-Gap______3.4%
  • KN95-Valve____20.3%

Cloth and surgical masks don’t do much to reduce the aerosol concentrations. Both the KN95 and R95 masks capture a meaningful share of the aerosols, but the R95 is a bit more effective. Remember, however, that the uncaptured share is a stand-in for the many thousands of virus particles that would remain suspended within the indoor space, so the filtration efficiency, while far superior to cloth or surgical masks, would do little to mitigate the spread of the virus. The KN95-Gap case is a test of a more “loosely fitted” mask with 3 mm gaps, which the authors say is realistic. Under those circumstances, the KN95 is about as good as nothing. Finally, the authors tested a well-fitted KN95 equipped with a one-way discharge valve. While its efficiency was better than cloth or surgical masks, it still performed poorly. The authors also found that various degrees of air filtration were far more effective in reducing aerosol concentrations than masks.

On the subject of mask fit, I quote Dr. Robert Lending, who has regularly chronicled pandemic developments for patients in his practice since the start of the pandemic:

“N95 type masks cannot be worn by men with beards. They must be so tightly fitted that they leave deep creases in your face. Prior to Covid-19, when hospital employees had to wear them for TB exposure prevention, they were told not to wear them for more than 3 hours at a time. They had to be fit-tested and gas leak-tested. … The N95 knockoffs such as the KN95s are not as good. N95 with valves do not protect others from you. There are now many counterfeit N95s for sale. … Obviously, N95s were never meant to be worn for 8-12 hours; and certainly not by youth and school children. If you are wearing an N95 and you can smell anything, such as aroma in a restaurant when you walk in, perfume, cologne, coffee, citrus, foul odors, etc.; then your fit is not correct and that N95 is worthless.”

Other Evidence

Another kind of evidence on mask efficacy is offered by randomized control trials (RCTs) in mitigating transmission of the influenza virus across a variety of settings, including hospital wards, schools, and neighborhoods of varying characteristics. A meta-analysis of 44 such RCTs published in the Cochran Library in late 2020 found that surgical masks make little or no difference to the spread of the virus. In a small set of RCTs from health care settings, the authors found that N95 and P95 masks perform about as well as surgical masks in limiting transmission.

An excellent review of research on mask efficacy appeared in City Journal last August. The author, Jeffrey H. Anderson, was fairly awestruck at the uniformity of RCT evidence that masks are ineffective. One well-publicized RCT purporting to show the opposite relied on effects that were negligible. Meanwhile, other research has shown that state-level mask mandates are ineffective at reducing the spread of the virus. Finally, here is a nice “cheat sheet” containing links to a number of mask studies.

Children

Children in many parts of the country are forced to wear masks at school. It’s well-established, however, despite wailing from teachers’ unions, that Covid poses extremely low risks to children. And there is no shortage of evidence that constant masking has extremely negative effects on children. The stupidity has reached grotesque proportions. Now, some school districts are proposing that children wear N95 masks! This is unnecessary and cruel, and it is ineffective precisely because children will be even less likely to use them properly than adults, who are generally not very good at it. From the last link:

“If N95s filter so well, why are respirators an ineffective intervention? Because masking is a behavioral intervention as much as a physical one. For respirators to work, they must be well fitting, must be tested by OSHA, and must be used for only short time windows as their effectiveness diminishes as they get wet from breathing.

“Fit requirements and comfort issues are untenable in children who have small faces and are required to wear masks for six or more hours each day. For these reasons, NIOSH specifically states that children should not use respirators, and there are no respirators that are approved for children. These views are shared by the California Department of public health. Concerns about impaired breathing and improper use outweigh potential benefits. There are no studies on the effectiveness of respirators on children because they are not approved for pediatric use.”

Rip It Off

At this point in the Omicron wave, which appears to have crested, we’re basically dealing with a virus that is less lethal than the flu and, for most people, comparable to the common cold. It’s a good time for the timid to shed their masks, which didn’t help contain the spread of the virus to begin with. And masks do more harm than has generally been acknowledged, especially to children. So stop the bullshit. Take off your mask, and leave it off!

Scary New Variant or Omicrommon Cold?

08 Wednesday Dec 2021

Posted by in Coronavirus, Pandemic, Uncategorized

≈ Leave a comment

Tags

, , , , , , , , , , , , , ,

The political motives behind the naming of the Covid Omicron variant might prove to be a huge irony. The Greek letter Xi was skipped by the World Health Organization (WHO), undoubtedly to avoid any symbolic association between Covid and the Chinese dictator Xi Jinping. After all, he’s probably determined to bury discussion of the leak at the Wuhan lab that was the probable cause of this whole mess. The WHO was happy to provide cover. The irony is that the Omicron variant might well bring on a more gentle phase of the pandemic if early indications can be trusted. But in that case, my guess is Chairman Xi wouldn’t have appreciated the twist even if WHO had called it the Xi variant.

The Omicron variant was identified in the Gauteng Province of South Africa and announced by national health authorities on November 24th. The earliest known sample was taken on November 9th. The variant was subsequently diagnosed in a number of other countries, including the U.S. It has a large number of mutations, and initial reports indicated that the variant was spreading extremely fast, having suddenly outcompeted other variants to account for the majority of new cases in South Africa. It is apparently highly contagious. Moreover, Omicron has been diagnosed among the vaccinated as well as those having immunity from prior infections, which is usually more effective and durable than vaccination. Thus, it is said to have “immune escape” properties. Scary indeed!

However, Omicron seems to have been around much longer than suggested by its initial diagnosis in late November (and see this link for an extreme view). Cases in a number of countries show that it is already global; the lags involved in diagnosis as well as earlier contacts with spreaders suggest that Omicron’s origin could have been as early as late September. That means the spread has not been quite as fast as the first alarming reports suggested.

The reported symptoms of the Omicron variant have been quite mild, with fatigue being the most noteworthy. Omicron appears to have taken one mutation from the common cold, which, like Covid-19, is a type of coronavirus. And while there has been a surge in hospitalized cases in South Africa, most of these are said to be “incidental”. That is, these patients were admitted for other problems but happened to test positive for the Omicron variant. As we’ve seen throughout the pandemic, the data is not always reliable.

It’s too early to draw definite conclusions, and this variant might prove to be more dangerous with time. In fact, some say that South Africa’s experience might not be representative because of its young population and high natural immunity. It also happens to be early summer there, when higher vitamin D levels help to boost immunity. So, there is a great deal of uncertainty about Omicron (and see here). Nevertheless, I’ll risk a jinx by momentarily contemplating an outcome that’s not terribly far-fetched.

Viruses mutate in ways that help ensure their survival: they must not kill too many of their hosts, which means the usual progression is toward less lethal variants. They may become more contagious, and new variants must be contagious enough to outcompete their ancestors. Viral interference can sometimes prevent multiple viruses from having a broad coexistence. That’s the likely phenomenon we witnessed when the Covid pandemic coincided with the virtual disappearance of the flu and other respiratory viruses. More to the point, it’s the same phenomenon that occurred when the Spanish Flu was eventually outcompeted by less deadly variants.

So it’s possible that a mild Omicron will put the pandemic behind us. If it proves to be as contagious and as mild as it appears thus far, it would likely displace Delta and other variants as the first phase of a new, endemic malady. That might even cut into the severity of the current seasonal wave. The Ethical Skeptic tweets thusly:

“So was Omicron an ultra fast-mutating magic terminator variant? A gift from God, or aliens…? … Or natural virility/genetic profile derived from a previous variant conferring immunity …”

That would be a wonderful outcome, but Omicron’s arrival in the northern hemisphere just as winter gets underway contributes to the uncertainty. It’s severity during the northern winter could be far worse than what we’ve seen in South Africa. We can hope this variant isn’t one truly deserving of Chairman Xi’s name.

CDC Makes a Bum Lead Steer: Alternate Reality vs. The Herd

16 Sunday May 2021

Posted by in Herd Immunity, Pandemic

≈ 2 Comments

Tags

, , , , , , , , , , , , , , , , , , , ,

Jordan Schachtel enjoyed some schadenfreude last week when he tweeted:

“I am thoroughly enjoying the White House declaring COVID over and seeing the confused cultists having a nervous breakdown and demanding the continuation of COVID Mania.”

It’s quite an exaggeration to say the Biden Administration is “declaring COVID over”, however. They’re backpedaling, and while last week’s CDC announcement on masking is somewhat welcome, it reveals more idiotic thinking about almost everything COVID: the grotesquely excessive application of the precautionary principle (typical of the regulatory mindset) and the mentality of “zero COVID”. And just listen to Joe Biden’s tyrannical bluster following the CDC announcement:

“The rule is now simple: get vaccinated or wear a mask until you do.

The choice is yours.”

Is anyone really listening to this buffoon?Unfortunately, yes. But there’s no federal “rule”, unless your on federal property; it constitutes “guidance” everywhere else. I’m thankful our federalist system still receives a modicum of respect in the whole matter, and some states have chosen their own approaches (“Hooray for Florida”). Meanwhile, the state of the pandemic looks like this, courtesy of Andy Slavitt:

False Assertions

The CDC still operates under the misapprehension that kids need to wear masks, despite mountains of evidence showing children are at negligible risk and tend not to be spreaders. Here’s some evidence shared by Phil Kerpen on the risk to children:

The chart shows the fatality risk by age (deaths per 100,000), and then under the assumption of a 97% reduction in that risk due to vaccination, which is quite conservative. Given that kind of improvement, an unvaccinated 9 year-old child has about the same risk as a fully vaccinated 30 year-old!

The CDC still believes the unvaccinated must wear masks outdoors, but unless you’re packed in a tight crowd, catching the virus outdoors has about the same odds as a piano falling on your head. And the CDC insists that two shots of mRNA vaccine (Pfizer or Moderna) are necessary before going maskless, but only one shot of the Johnson and Johnson vaccine, even though J&J’s is less effective than a single mRNA jab!

Other details in the CDC announcement are worthy of ridicule, but for me the most aggravating are the agency’s implicit position that herd immunity can only be achieved through vaccination, and its “guidance” that the unvaccinated should be dealt with coercively, even if they have naturally-acquired immunity from an infection!

Tallying Immunity

Vaccination is only one of several routes to herd immunity, as I’ve noted in the past. For starters, consider that a significant share of the population has a degree of pre-existing immunity brought on by previous exposure to coronaviruses, including the common cold. That doesn’t mean they won’t catch the virus, but it does mean they’re unlikely to suffer severe symptoms or transmit a high viral load to anyone else. Others, while not strictly immune, are nevertheless unlikely to be sickened due to protections afforded by healthy vitamin D levels or because they are not obese. Children, of course, tend to be fairly impervious. Anyone who’s had a bout with the virus and survived is likely to have gained strong and long-lasting immunity, even if they were asymptomatic. And finally, there are those who’ve been vaccinated. All of these groups have little or no susceptibility to the virus for some time to come.

It’s not necessary to vaccinate everyone to achieve herd immunity, nor is it necessary to reach something like an 85% vax rate, as the fumbling Dr. Fauci has claimed. Today, almost 47% of the U.S. population has received at least one dose, or about 155 million adults. Here’s Kerpen’s vax update for May 14.

Another 33 million people have had positive diagnoses and survived, and estimates of seroprevalence would add perhaps another 30 million survivors. Some of those individuals have been vaccinated unnecessarily, however, and to avoid double counting, let’s say a total of 50 million people have survived the virus. Some 35 million children in the U.S. are under age 12. Therefore, even if we ignore pre-existing immunity, there are probably about 240 million effectively immune individuals without counting the remaining non-susceptibles. At the low end, based on a population of 330 million, U.S. immunity is now greater than 70%, and probably closer to 80%. That is more than sufficient for herd immunity, as traditionally understood.

The Herd Immunity Threshold

Here and in the following section I take a slightly deeper dive into herd immunity concepts.

Herd immunity was one of my favorite topics last year. I’m still drawn to it because it’s so misunderstood, even by public health officials with pretensions of expertise in the matter. My claim, about which I’m not alone, is that it’s unnecessary for a large majority of the population to be infected (or vaccinated) to limit the spread of a virus. That’s primarily because there is great variety in individuals’ degree of susceptibility, social connections, aerosol production, and viral load if exposed: call it heterogeneity or diversity if you like. Variation across individuals naturally limits a contagion relative to a homogeneous population.

Less than 1% of those who caught the virus died, while the others recovered and acquired immunity. The remaining subset of individuals most vulnerable to severe illness was thus reduced over time via acquired immunity or death. This is the natural dynamic that causes contagions to slow and ultimately peter out. In technical jargon, the virus reproduction rate “R” falls below a value of one. The point at which that happens is called the “herd immunity threshold” (HIT).

A population with lots of variation in susceptibility will have a lower HIT. Some have estimated a HIT in the U.S. as low as 15% -25%. Ultimately, total exposure will go much higher than the HIT, perhaps well more than doubling exposure, but the contagion recedes once the HIT is reached. So again, it’s unnecessary for anywhere near the full population to be immune to achieve herd immunity.

One wrinkle is that CIVID is now likely to have become endemic. Increased numbers of cases will re-emerge seasonally in still-susceptible individuals. That doesn’t contradict the discussion above regarding the HIT rate: subsequent waves will be quite mild by comparison with the past 14 months. But if the effectiveness of vaccines or acquired immunity wanes over time, or as healthy people age and become unhealthy, re-emergence becomes a greater risk.

Sub-Herd Immunity

A further qualification relates to so-called sub-herds. People are clustered by geographical, social, and cultural circles, so we should think of society not as a singular “herd”, but as a collection of sub-herds having limited cross-connectivity. The following charts are representations of different kinds of human networks, from Nathan D. Grawe’s review of “The Rules of Contagion, by Adam Kucharski:

Sub-herd members tend to have more degrees of separation from individuals in other sub-herds than within their own sub-herd. The most extreme example is the “broken network” (where contagions could not spread across sub-herds), but there are identifiable sub-herds in all of the examples shown above. Less average connectedness across sub-herds implies barriers to transmission and more isolated sub-herd contagions.

We’ve seen isolated spikes in cases in different geographies, and there have been spikes within geographies among sub-herds of individuals sharing commonalities such as race, religious affiliation, industry affiliation, school, or other cultural affiliation. Furthermore, transmission of COVID has been dominated by “super-spreader” events, which tend to occur within sub-herds. In fact, sub-herds are likely to be more homogeneous than the whole of society, and that means their HIT will be higher than we might naively calculate based on higher levels of aggregation.

We have seen local, state, or regional contagions peak and turn down when estimates of total incidence of infections reach the range of 15 – 25%. That appears to have been enough to reach the HIT in those geographically isolated cases. However, if those geographical contagions were also concentrated within social sub-herds, those sub-herds might have experienced much higher than 25% incidence by the time new infections peaked. Again, the HIT for sub-herds is likely to be greater than the aggregate population estimates implied, The upshot is that some sub-herds might have achieved herd immunity last year but others did not, which explains the spikes in new geographic areas and even the recurrence of spikes within geographic areas.

Conclusion

It’s unnecessary for 100% of the population to be vaccinated or to have pre-existing immunity. Likewise, herd immunity does not imply that no one catches the virus or that no one dies from the virus. There will be seasonal waves, though muted by the large immune share of the population. This is not something that government should try to stanch, as that would require the kind of coercion and scare tactics we’ve already seen overplayed during the pandemic. People face risks in almost everything they do, and they usually feel competent to evaluate those risks themselves. That is, until a large segment of the population allows themselves to be infantalized by public health authorities.

COVID Cases Decline Despite New Variants

19 Friday Feb 2021

Posted by in Coronavirus, Pandemic

≈ Leave a comment

Tags

, , , , , , , , ,

For weeks, even months, we’ve been hearing about dangerous new mutations of the coronavirus, and they’ve been identified in cases in the U.S. There’s a UK strain, a South African strain, a Brazilian strain, and still others, which differ in seemingly minor ways. Nevertheless, these variants are said to be more infectious. It’s also been reported that the South African and Brazilian strains might resist antibodies from prior infections from earlier strains.

Kyle Lamb has provided the following charts to put things in perspective:

Just to round things out, here is the trend in cases worldwide:

There is a great deal of concern about the new variants. A search for “COVID-19 variants” turns up plenty of scary articles. However, there is some evidence that the new variants are not as dangerous as alarmists contend. The resistance to specific antibodies does not necessarily imply resistance to protection by T-cells. As Youyang Gu points out, even if a new strain becomes “dominant”, that does not imply that cases will reverse their decline. This study indicates that the Pfizer vaccine is protective against both the UK and South African strains, and there is evidence that other vaccines offer adequate protection as well (and see here).

The charts demonstrate that the new strains haven’t arrested or reversed the declines in infections witnessed worldwide since early January. That doesn’t mean the mutations haven’t made a difference: perhaps the declines would have been faster in their absence. And we don’t know what the future will hold as the virus in various forms becomes endemic. Still, it’s reassuring to see that the increased transmissibility of the new strains hasn’t overcome factors that have contributed to the recent declines, which in all likelihood are related to increasing immunity in the population with a minor assist from vaccinations (thus far). As Lamb wryly notes about the recent declines in transmission: “Just saying”.

Teachers Unions and Educational Hostage-Taking

14 Sunday Feb 2021

Posted by in Education, Pandemic, Unions

≈ 1 Comment

Tags

, , , , , , , , , , , , , , , , , , ,

Intelligent public policy is all too often undermined by policy makers incapable of properly assessing risks. The Biden Administration is setting new standards in this regard with its so-called “return to school” effort. It’s difficult to know how much of it is sheer stupidity and how much is pandering to teachers unions. Equal parts is probably a reasonable approximation.

The public teachers unions have consistently opposed reopening since remote learning began last spring, despite reams of data showing the safety of school environments. Even the CDC agrees! Oh, but wait: the CDC just issued new guidelines for reopening, which among other things require six feet of distancing rather than the three feet Director Rochelle Walensky claimed was adequate just a few months ago. Obviously, this reduces the number of students many existing school buildings can accommodate.

COVID transmission in schools is “extremely rare”. And in addition, remote education is sorely lacking in effectiveness. Teachers who truly care about educating their students should be giving the unions an earful. Not only has learning been compromised, but remote learning has increased the achievement gap between the best students and those in the lower part of the distribution.

Private schools have been open and as the map above shows, public schools in a number of states are largely open to in-person learning. Where that’s not the case, public school buildings are often still being used by children. They’re under the supervision of adults, but not teachers! As Matt Welch says:

“… many of the empty school buildings in largely closed districts are not in fact empty—they are filled with kids, being supervised by adults, just not adults who belong to teachers unions.”

Incidentally, many adults with children now at home, rather than in school, have been forced to leave the labor force, and many of them are women. As Michael Watson asks, why are advocates of working women so silent on this point? And this is to say nothing of the health care workers diverted, during a pandemic, from patient care by the need to manage children at home.

In December, Joe Biden promised to reopen “most” K – 12 schools within his first one-hundred days in office. Shortly after his inauguration, that promise became “most” K – 8 schools. As Welch notes, now the goal has been made a bit more precise, and it’s a complete sham: the Administration wants at least half of schools to be “open” for in-person learning at least one day a week! But we’re already well ahead of that! (And see here.)

On top of that, the federal government is playing the interloper here: reopening is not a federal decision. Ah, but Biden wants $130 billion in federal money earmarked to aid schools in their reopening efforts. Anthony Fauci has decided the stimulus is necessary for schools to reopen, his latest in a series of embarrassing policy flip-flops. The funds targeted at schools would be spent in a variety of ways, including PPE, COVID tests, new ventilation systems, and enhancement of remote learning to accommodate smaller (and distanced) in-person class sizes. Some of the funds are likely to make their way into teacher pay and to shore up pensions. One thing is certain: the unions want that money, and they will come back for more!

The unions also argue that teachers should be prioritized for vaccines, which would place them ahead of groups facing drastically higher risks. This is flat-out callous, insane, and evil. Again, the risk of COVID to teachers and children is low, while the elderly population faces staggeringly higher risks. Vaccinating teachers ahead of the elderly would cost many thousands of lives on balance.

This article from Education Next by Darrell Bradford describes the conditions for reopening demanded by teachers unions as the culmination of several years of activism. The unions contributed mightily to Joe Biden’s election campaign, of course. Their overwrought posture on teacher safety aside, the unions’ obstinance on the question of reopening is intended as leverage in the legislative push for Biden’s school aid package. Here’s Bradford:

“In other words, if you’ve wondered what a national teacher strike might look like and what might cause teachers across the country to arrest local economies and subject millions of students to instruction that may lock in deep learning losses, it’s just like this.”

The schools are safe, remote learning is substandard, and isolation is damaging to children’s’ emotional well being. Union demands for continuing limitations on in-person learning and requirements for reopening are not just unreasonable, but dastardly. That the Biden Administration is crafting its reopening policy and spending initiatives to appease the unions is motivated more by politics than the interests of children and their families. It’s time for parents and other true advocates to let their school administrators, elected representatives, and government officials know that the unions do not have their children’s interests at heart. And well-informed teachers should demand that their union representatives stop playing politics with the educational goals to which they’ve devoted their careers.

Revisiting Excess Mortality

31 Sunday Jan 2021

Posted by in Coronavirus, Pandemic

≈ Leave a comment

Tags

, , , , , , , ,

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.

COVID Now: Turning Points, Vaccines, and Mutations

20 Wednesday Jan 2021

Posted by in Coronavirus, Pandemic, Vaccinations

≈ Leave a comment

Tags

, , , , , , , , , , , , , , , , , , ,

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.

Allocating Vaccine Supplies: Lives or “Justice”?

29 Tuesday Dec 2020

Posted by in Pandemic, Public Health, Uncategorized, Vaccinations

≈ 1 Comment

Tags

, , , , , , , , , , , , , , ,

There are currently two vaccines in limited distribution across the U.S. from Pfizer and Moderna, but the number and variety of different vaccines will grow as we move through the winter. For now, the vaccine is in short supply, but that’s even more a matter of administering doses in a timely way as it is the quantity on hand. There are competing theories about how best to allocate the available doses, which is the subject of this post. I won’t debate the merits of refusing to take a vaccine except to say that I support anyone’s right to refuse it without coercion by public authorities. I also note that certain forms of discrimination on that basis are not necessarily unreasonable.

The vaccines in play all seem to be highly effective (> 90%, which is incredible by existing standards). There have been a few reports of side effects — certainly not in large numbers — but it remains to be seen whether the vaccines will have any long-term side effects. I’m optimistic, but I won’t dismiss the possibility.

Despite competing doctrines about how the available supplies of vaccine should be allocated, there is widespread acceptance that health care workers should go first. I have some reservations about this because, like Emma Woodhouse, I believe staff and residents at long-term care facilities should have at least equal priority. Yet they do not in the City of Chicago and probably in other areas. I have to wonder whether unionized health care workers there are the beneficiaries of political favoritism.

Beyond that question, we have the following competing priorities: 1) the vulnerable in care homes and other elderly individuals (75+, while younger individuals with co-morbidities come later); 2) “essential” workers of all ages (from police to grocery store clerks — decidedly arbitrary); and 3) basically the same as #2 with priority given to groups who have suffered historical inequities.

#1 is clearly the way to save the most lives, at least in the short-run. Over 40% of the deaths in the U.S. have been in elder-care settings, and COVID infection fatality rates mount exponentially with age:

To derive the implications of #1 and #2, it’s more convenient to look at the share of deaths within each age cohort, since it incorporates the differences in infection rates and fatality rates across age groups (the number of “other” deaths is much larger than COVID deaths, of course, despite similar death shares):

The 75+ age group has accounted for about 58% of all COVID deaths in the U.S., and ages 25 – 64 accounted for about 20% (an approximate age range for essential workers). This implies that nearly three times as many lives can be saved by prioritizing the elderly, at least if deaths among so-called essential workers mimic deaths in the 25 – 64 age cohorts. However, the gap would be smaller and perhaps reversed in terms of life-years saved.

Furthermore, this is a short-run calculation. Over a longer time frame, if essential workers are responsible for more transmission across all ages than the elderly, then it might throw the advantage to prioritizing essential workers over the elderly, but it would take a number of transmission cycles for the differential to play out. Yes, essential workers are more likely to be “super-spreaders” than work-at-home, corporate employees, or even the unemployed, but identifying true super-spreaders would require considerable luck. Moreover, care homes generally house a substantial number of elderly individuals and staff in a confined environment, where spread is likely to be rampant. So the transmission argument for #2 over #1 is questionable.

The over-riding problem is that of available supply. Suppose enough vaccine is available for all elderly individuals within a particular time frame. That’s about 6.6% of the total U.S. population. The same supply would cover only about 13% of the younger age group identified above. Essential workers are a subset of that group, but the same supply would fall far short of vaccinating all of them; lives saved under #2 would then fall far short of the lives saved under #1. Quantities of the vaccine are likely to increase over the course of a few months, but limited supplies at the outset force us to focus the allocation decision on the short-term, making #1 the clear winner.

Now let’s talk about #3, minority populations, historical inequities, and the logic of allocating vaccine on that basis. Minority populations have suffered disproportionately from COVID, so this is really a matter of objective risk, not historical inequities… unless the idea is to treat vaccine allocations as a form of reparation. Don’t laugh — that might not be far from the intent, and it won’t count as a credit toward the next demand for “justice”.

For the sake of argument, let’s assume that minorities have 3x the fatality rate of whites from COVID (a little high). Roughly 40% of the U.S. population is non-white or Hispanic. That’s more than six times the size of the full 75+ population. If all of the available doses were delivered to essential workers in that group, it would cover less than half of them and save perhaps 30% of minority COVID deaths over a few months. In contrast, minorities might account for up to two-thirds of the deaths among the elderly. Therefore, vaccinating all of the elderly would save 58% of elderly COVID deaths and about 39% of minority deaths overall!

The COVID mortality risk to the average white individual in the elderly population is far greater than that faced by the average minority individual in the working age population. Therefore, no part of #3 is sensible from a purely mathematical perspective. Race/ethnicity overlaps significantly with various co-morbidities and the number of co-morbidities with which individuals are afflicted. Further analysis might reveal whether there is more to be gained by prioritizing by co-morbidities rather than race/ethnicity.

Megan McArdle has an interesting column on the CDC’s vaccination guidelines issued in November, which emphasized equity, like #3 above. But the CDC walked back that decision in December. The initial November decision was merely the latest of the the agency’s fumbles on COVID policy. In her column, McArdle notes that the public has understood that the priority was to save lives since the very start of the pandemic. Ideally, if objective measures show that identifiable characteristics are associated with greater vulnerability, then those should be considered in prioritizing individuals who desire vaccinations. This includes age, co-morbidities, race/ethnicity, and elements of occupational risk. But lesser associations with risk should not take precedence over greater associations with risk unless an advantage can be demonstrated in terms of lives saved, historical inequities or otherwise.

The priorities for the early rounds of vaccinations may differ by state or jurisdiction, but they are all heavily influenced by the CDC’s guidelines. Some states pay lip service to equity considerations (if they simply said race/ethnicity, they’d be forced to operationalize it), while others might actually prioritize doses by race/ethnicity to some degree. Once the initial phase of vaccinations is complete, there are likely to be more granular prioritizations based on different co-morbidities, for example, as well as race/ethnicity. Thankfully, the most severe risk gradient, advanced age, will have been addressed by then.

One last point: the Pfizer and Moderna vaccines both require two doses. Alex Tabarrok points out that first doses appear to be highly effective on their own. In his opinion, while supplies are short, the second dose should be delayed until all groups at substantially elevated risk can be vaccinated…. doubling the supply of initial doses! The idea has merit, but it is unlikely to receive much consideration in the U.S. except to the extent that supply chain problems make it unavoidable, and they might.

Harbingers of COVID Fade, But Not the Pretense for Hysteria

17 Thursday Dec 2020

Posted by in Coronavirus, Pandemic, Vaccinations

≈ Leave a comment

Tags

, , , , , , , , , , , ,

My pre-Thanksgiving optimism about a crest in the fall wave of the coronavirus has been borne out for the Midwest and Mountain states in the U.S. These regions were the epicenter of the fall wave through October and most of November, but new cases in those states have continued to decline. Cases in a number of other states began to climb in November, however, contributing to a continuing rise in total new cases nationally. Some of these states are still in the throes of this wave, with the virus impacting subsets of the population that were relatively unscathed up till now.

My disclaimer: COVID is obviously a nasty virus. I don’t want to get it. However, on the whole, it is not a cataclysm on the order of many pandemics of the past. In fact, excess deaths this year will add just over 10% to projections of total deaths based on a five-year average. That level puts us in line with average annual deaths of about twenty years ago. And many of those excess deaths have been caused by our overreaction to the pandemic, not by the virus itself. As my endocrinologist has said, this is the greatest overreaction in all medical history. Unfortunately, a fading pandemic does not mean we can expect an end to the undue panic, or pretense for panic, on the part of interventionists.

This post will focus largely on trends in newly diagnosed COVID cases. I have been highly critical of our testing regime and COVID case counts because the most prominent diagnostic test (PCR) falsely identifies a large number of uninfected individuals as COVID-positive. However, case numbers are widely tracked and it’s fairly easy to find information across geographies for comparison. Deflate all the numbers by 30% if you want, or by any other factor, but please indulge me because I think the trends are meaningful, even if the absolute level of cases is inflated.

I’ll start with the good news and work my way down to states in which cases are still climbing (all of the following charts are from @Humble_Analysis (PLC)). The first chart is for the Great Plains, where cases peaked a little before Thanksgiving and have continued to fall since then. That peak came about six weeks after it began in earnest and cases have faded over the last four weeks.

Next we have the Mountain states, where again, cases peaked around Thanksgiving, though Idaho saw a rebound after the holiday. You’ll see below that a number of states had a distinct drop in new cases during the week of Thanksgiving. There was somewhat of a pause in testing during that week, so the subsequent rebounds are largely due to a “catch-up” at testing sites, rather than some kind of Thanksgiving-induced spike in infections.

Back to the Mountain region, the peak came an average of about six or seven weeks into the wave, but the duration of the wave appears to have been longer in Montana and Wyoming.

Here are the Southern Plain states, where cases plateaued around Thanksgiving (though cases in Missouri have clearly declined from their peak). In this region, case counts accelerated in October after a slow climb over the summer.

The situation is somewhat similar in the Midwest. where cases have generally plateaued. There were some post-Thanksgiving rebounds in several states, especially Tennessee. The wave began a little later in this region, in mid- to late October, and it is now seven to eight weeks into the wave, on average.

Here are the Mid-Atlantic states, which may be showing signs of a peak, though North Carolina has had the greatest caseload and is still climbing. These states are about seven weeks into the wave, on average.

The Northeast also shows signs of a possible peak and is about seven weeks into the wave, except for Rhode Island, which saw an earlier onset and the most severe wave among these states.

And finally we have the South, which is defined quite broadly in PLC’s construction. It’s a mixed bag, with a few states showing signs of a peak after about seven weeks. However, cases are still climbing in several states, notably California and Florida, among a few others.

Oregon and Washington were skipped, but they appear as the Pacific NW in the following chart, along with aggregations for all the other regions. Maine is Part of the “Rural NE”, which was also skipped. The fall wave can be grouped roughly into two sets of regions: those in which waves began in late September or early October, and those where waves began in early to mid-November. The first group has moved beyond a peak or at least has plateaued. The latter group may be reaching peaks now or one hopes very soon. It seems to take about seven weeks to reach the peak of these regional waves, so a late December peak for the latter group would be consistent.

Justin Hart has a take on the duration of these waves, but he does so in terms of the share of emergency room (ER) visits in which symptoms of COVID-like illness (CLI) are presented. CLI tends to precede case counts slightly. Hart puts the duration of these waves at eight to ten weeks, but that’s a judgement call, and I might put it a bit longer using caseloads as a guide. Still, this color-coded chart from Hart is interesting.

If this sort of cyclical duration holds up, it’s consistent with the view that cases in many of the still “hot” states should be peaking this month.

Aggregate cases for the U.S. appear below. The growth rate of new cases has slowed, and the peak is likely to occur soon. However, because it combines all of the regional waves, the duration of the wave nationwide will appear to be greater than for the individual regions. COVID-attributed deaths are also plotted, but they are reported deaths, not by date of death (DOD) or actual deaths, as I sometimes call them. Deaths by DOD are available only with a lag. As always, some of the reported deaths shown below occurred weeks before their reported date. Actual deaths were still rising as of late November, and are likely still rising. However, another indicator suggests they should be close to a peak.

A leading indicator of actual deaths I’ve discussed in the past now shows a more definitive improvement than it did just after Thanksgiving, as the next chart shows. This is the CLI share discussed above. An even better predictor of COVID deaths by actual DOD is the sum of CLI and the share of ER patients presenting symptoms of influenza-like illness (ILI), but ILI has been fairly low and stable, so it isn’t contributing much to changes in trend at the moment. There has been about a three-week lead between movements in CLI+ILI and COVID deaths by DOD.

(The reason the sum, CLI+ILI, has been a better predictor than CLI alone is because for some individuals, there are similarities in the symptoms of COVID and the flu.)

The chart shows that CLI peaked right around the Thanksgiving holiday (and so did CLI+ILI), but it remained on something of a plateau through the first week of December before declining. Some of the last few days on this chart are subject to revision, but the recent trend is encouraging. Allowing for a three-week lead, this indicates that peak deaths by DOD should occur around mid-December, but we won’t know exactly until early to mid-January. To be conservative, we might say the latter half of December will mark the peak in actual deaths.

The regional COVID waves this summer and fall seem to have run their course within 10 – 12 weeks. Several former hot spots have seen cases drop since Thanksgiving after surges of six to seven weeks. However, there are several other regions with populous states where the fall wave is still close to “mid-cycle”, as it were, showing signs of possible peaks after roughly seven weeks of rising cases. The national CLI share peaked around Thanksgiving, but it did not give up much ground until early December. That suggests that actual deaths (as opposed to reported deaths), at least in some regions, will peak around the time of the winter solstice. Let’s hope it’s sooner.

Successive waves within a region seem to reach particular subsets of the population with relatively few reinfections. The 10 – 12 week cycle discussed above is sufficient to achieve an effective herd immunity within these subsets. But once again, a large share of the vulnerable, and a large share of COVID deaths, are still concentrated in the elderly, high-risk population and in care homes. The vaccine(s) currently being administered to residents of those homes are likely to hasten the decline in COVID deaths beginning sometime in January, perhaps as early as mid-month. By then, however, we should already see a decline underway as this wave of the virus finally burns itself out. As vaccines reach a larger share of the population through the winter and spring, the likelihood of additional severe waves of the virus will diminish.

Lest there be any misunderstanding, the reasons for the contagion’s fade to come have mostly to do with reaching the effective herd immunity threshold within afflicted subsets of the population (sub-herds). Social distancing certainly plays a role as well. Nearly all of that is voluntary, though it has been encouraged by panicked pronouncement by certain public officials and the media. Direct interventions or lockdown measures are in general counter-productive, however, and they create a death toll of their own. Unfortunately, the fading pandemic might not rein-in the curtailment of basic liberties we’ve witnessed this year.

Post-Script: Let’s hope the side effects of the vaccines are not particularly severe in the elderly. That’s a little uncertain, because that sub-population was not tested in very high numbers.

A Good Historical Backdrop for the Pandemic

07 Monday Dec 2020

Posted by in Pandemic, Public Health

≈ 2 Comments

Tags

, , , , , , ,

In this short post I’m trying to do my part to put our pandemic experience in perspective. Lord knows, I was on the low side in my U.S. case-load “guesstimate” last March, as well as the number of deaths induced by COVID. (A number of others, using highly sophisticated models, erred more severely in the opposite direction.) I also failed to anticipate the strength of the later seasonal waves we’ve experienced — I was excessively optimistic as the first wave ebbed. But now, as the fall wave is showing some signs of topping out, what can we say about the pandemic in historical perspective? I came across an interesting chart that sheds some light on the question.

In terms of all-cause mortality, we’ve clearly seen a bump upward this year. Take a look at the chart below. It shows deaths per million (DPM) of population (from all causes). Try clicking on it if it’s hard to read, or turn your phone sideways. See the little blip on the lower right? That’s our pandemic year through August. The blip made 2020, at least through August, look something like a normal year of the early 2000s.

The visible spike early in 2020 was the spring wave, which was concentrated on the east coast. Of course, the fall wave will yield another spike, probably a bit higher than the first. Nevertheless, against the historical backdrop, this chart shows that the magnitude of our current public health crisis is relatively minor.

If you scan to the left from 2020, you can see that DPM this year would have appeared normal around 2005. Remember how bad it was back in aught-five…. all the death? Yeah, me neither. That’s perspective.

The chart also reflects several mild flu seasons over the past few years. Because the flu, like COVID-19, tends to hit the elderly and infirm the hardest, the “soft” DPM numbers over the past few years support the theory that the population included a fair amount of so-called “dry tinder” for COVID as we entered the year.

One other note on the chart: the DPMs are “age-adjusted”, meaning that age groups are weighted for comparisons across countries with differing age distributions (not what we’re doing here). In this case, the DPM values are weighted based on the population in the year 2000.

It’s amazing how so many have bought into the narrative that the current pandemic is historically bad. Yes, our DPMs are high relative to the last decade, but a significant number of those deaths were caused not by COVID, but by our own overreaction to the virus. That’s something else I failed to anticipate in the spring. It’s something we can put behind us now, however, if only we’re willing to put our experience in perspective. Unfortunately, many public officials, along with their public health advisors, continue to promote the deluded view that the virus can only be stopped by stopping our lives, our educations, our earnings, our health, and our sanity.