Category Archives: Coronavirus

Blow Me Down: Obesity, Age, and Aerosol-Borne Particles

09 Friday Apr 2021

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Super-spreading events are gatherings at which one or more attendees are already harboring an infection and manage to transmit it to a number of others. These people, in turn, spread it to their close contacts, possibly at the same event. Super-spreading has dominated the transmission of COVID-19. These transmissions have almost always taken place indoors in spaces with limited ventilation, and they have usually involved close or prolonged contact. In addition, super-spreading originates with a small subset of infected individuals. That’s essentially what the chart above shows. It ranks individual subjects by their exhaled quantity of aerosolized particles per liter of air.

For more than a year, we’ve also known that obesity and age are associated with more severe COVID infections. Now, it’s startling to learn that obese and/or older, infected individuals are more prone to transmitting virus: this study found that a high body mass index (BMI) is associated with significantly greater quantities of exhaled aerosol, and that age has a similarly strong association. So called BMI-years, or age x BMI, has an extremely powerful association with the exhalation of aerosol-borne particles. The authors, David A. Edwards, et al, believe this is a consequence of the properties of mucus produced by different individuals in response to infections and how their lungs and airways handle it. The authors say:

“Our findings indicate that the capacity of airway lining mucus to resist breakup on breathing varies significantly between individuals, with a trend to increasing with the advance of COVID-19 infection and body mass index multiplied by age (i.e., BMI-years). Understanding the source and variance of respiratory droplet generation, and controlling it via the stabilization of airway lining mucus surfaces, may lead to effective approaches to reducing COVID-19 infection and transmission. … ”

“Surfactant and mucin compositional and structural changes, driven, in part, by physiological alterations of the human condition—including diet (10), aging (11), and COVID-19 infection itself (12)—may therefore be anticipated to alter droplet generation and droplet size (7) during acts of breathing.”

So there is substantial variation in the exhalation of aerosol-borne particles across individuals. In the study, less than 20% of healthy subjects produced more than 156 particles per liter of air, accounting for 80% of the exhaled particles. This defined their so-called “super-spreader” cohort. The association of BMI-years and exhaled particles was less pronounced but still positive within the “low-spreader” cohort.

Edwards, et al speculate that these fine droplets might help explain the greater severity of COVID infections among the elderly and obese. Not only does the breakup of mucus into tiny droplets cause these individuals to exhale aerosols more profusely, it probably also leads to deep penetration into their lung tissue.

This knowledge might be broadly applicable to infectious diseases, and SARS viruses in particular. The elderly know they are vulnerable. It’s not clear that the obese have viewed themselves as vulnerable, but they should, even in the age of “body positivity“. And not only are they vulnerable: they appear to pose an elevated hazard to others. I came across a couple of sardonic comments that got right to the apparent elephant in the room: “Instead of a mask mandate, how about a push-up mandate?”; and “Instead of a vaccine passport, how about a BMI passport?”

The debate about how to care for the most vulnerable is ongoing, but the mere mention of regularities like those identified by the study might lead to proposals for coercive policies. But first, a few practical points to bear in mind: 1) while the study identifies a major risk factor for transmission, it must be replicated by others, and there must be research into the underlying reasons for the phenomenon; 2) while the obese and seniors may be more likely to super-spread, not all of them are super-spreaders; and 3) as a matter of policy, how would “super-spreaders” be defined? What would be the cutoff BMIs at various ages? No matter what was decided, restrictive policies predicated on mere statistical associations would involve gross injustices to a large number of individuals.

With the degree of acquired immunity already in the population and fairly widespread voluntary vaccination (since alarmists have scared the bejeezus out of everyone), the whole issue might seem moot. It’s not, however, because COVID-19 is likely to become endemic, the immunities of some individuals might erode more quickly than expected, new and more dangerous variants might arise, and new SARS viruses are likely to emerge with time.

In a pandemic, however, and even without knowing who is infected, it is ethically barbaric to probabilistically isolate classes of individuals, whether based on age, BMI, or anything other than contagious status. The social cost is simply unacceptable. Instead, public health authorities should provide information to those at high risk, facilitate vaccination for those who desire it, and promote rapid, at-home tests. This is essentially a deregulatory agenda relative to the mindless lockdown approaches favored by so many public health experts.

Everyone must balance their own personal risks and rewards. Based on the study of exhaled particles discussed above, some might shun the obese and seniors until the threat has passed. Some of the obese and elderly might shun each other. That might be another regrettable dimension of the costs of a pandemic. On the other hand, perhaps more of us will respond to the unquestionably positive incentives for weight loss, of which we’re almost all aware.

CDC Wags Finger; Diners Should Wag One Back

09 Tuesday Mar 2021

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The CDC’s new study on dining out and mask mandates is a sham. On its face, the effects reported are small. And while it’s true most of the reported effects are statistically significant, the CDC acknowledges a number of factors that might well have confounded the results. This study should remind us of the infinite number of spurious and “significant” correlations in the world. Here, the timing of the mandates (or their removal) relative to purported effects and seasonal waves is highly suspicious, and as always, attributing causality on the basis of correlation is problematic.

On one hand, the CDC’s results are contrary to plentiful evidence that mandates are ineffective; on the other hand, the results are contrary to earlier CDC “guidance” that masks and limits on indoor dining are “highly effective”. Nevertheless, the latest report has massive propaganda value to the CDC. The media lapped up the story and provided cover for Democrats eager to pass the COVID (C19) relief package. Likewise, the Biden Administration is apparently committed to the narrative of an ongoing crisis as cover for continued attempts to shame political opponents in states that have elected to “reopen” or remain open.

Right off the bat, the study’s authors assert that the primary mode of transmission of C19 is from respiratory droplets. This is false. We know that aerosols are the main culprit in transmission, against which cloth masks are largely ineffective.

Be that as it may, let’s first consider the findings on dining. There was no statistically significant effect on the growth rate of cases or deaths up to 40 days after restrictions were lifted, according to the report. In fact, case growth declined slightly. There was, however, a small but statistically significant increase after 40 days. The fact that deaths seemed to “respond” faster and with greater magnitude than cases makes no sense and suggests that the results might be spurious.

The CDC offers possible explanations the long delay in the purported impact, such as the time required by restaurants to resume operations and early caution on the part of diners. These are speculative, of course. More pertinent is the fact that the data did not distinguish between indoor and outdoor dining, nor did it account for other differences in regulation such as rules on physical distancing, intra-county variation in local government mandates, and compliance levels.

Finally, the measurement of effects covered 100 days after the policy change, but this window spans different stages of the pandemic. There were three waves of infections during 2020, which correspond to the classic Hope-Simpson pattern of virus seasonality. One was near year-end, but as each of the first two waves tapered (April-May, August-September), it should be no surprise that many restrictions were lifted. Within two months, however, new waves had begun. Karl Dierenbach notes that most of the reopenings occurred in May. Here’s how he explains the pattern:

“The map on the left shows counties where there was no on-premises dining (pink) in restaurants as of the beginning of May (4/30). … The map on the right shows that by the end of May, almost the entire country moved to allow some on-premises dining (green).”

“In the 100 days after May 1, cases nationwide fell slightly, then began to rise, and then plateaued.”

“And what did the CDC find happened after restaurants were allowed (changing mostly in May) to have on-premises dining? … Surprise! The CDC found that cases fell slightly, then began to rise, and then plateaued.”

The summer “mini-wave” is typical of mid- and tropical-latitude seasonality. Thus, the CDC’s findings with respect to dining restrictions are likely an artifact of the strong seasonality of the virus, rather than having anything to do with the lifting of restrictions between waves.

What about the imposition of mask mandates? The CDC’s findings show a much faster response in this case, with statistically significant changes in growth during the first 20 days. Another indicator of spurious correlation is that the growth response of deaths did not lag that of cases, but in fact deaths have reliably lagged cases by over 18 days during the pandemic. Again, the CDC’s caveats apply equally to its findings on masks. A large share of individuals adopted mask use voluntarily before mandates were imposed, so it’s not even clear that the mandates contributed much to the practice.

It’s a stretch to believe that mask mandates would have had an immediate, incremental effect on the growth of cases and deaths, given probable lags in compliance, exposure, and onset of symptoms. Moreover, a number of mask mandates in 2020 were imposed near the very peak of the seasonal waves. Little wonder that the growth rates of cases and deaths declined shortly thereafter.

We’ve known for a long time that masks do little to stop the spread of viral particles. They become airborne as aerosols which easily penetrate the kind of cloth masks worn by most members of the public, to say nothing of making contact with their eyes. The table below contains citations to research over the past 10 years uniformly rejecting the hypothesis of a significant protective effect against influenza from masks. There is no reason to believe that they would be more effective in preventing C19 infections.

The CDC’s report on dining restrictions and mask mandates is a weak analysis. They wish to emphasize their faith in non-pharmaceutical interventions (NPIs) to minimize risks. They do so at a time when the vaccinated share of the most vulnerable population, the elderly, has climbed above 50% and is increasing steadily. Thus, risks are falling dramatically, so it’s past time to weigh the costs and benefits of NPIs more realistically. The timing of the report also seemed suspicious, coming as it did in the heat of the battle over the $1.9 trillion COVID relief bill, which subsequently passed.

It’s also a good time to note that zero risk, including “Zero COVID”, is not a realistic or worthwhile goal under any reasonable comparison of costs and benefits. Furthermore, NPIs have proven weak generally (also see here); claims to the contrary should always make us wary.

CDC Flubs COVID Impact on Life Expectancy

03 Wednesday Mar 2021

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The CDC choked on a new analysis estimating COVID-19’s impact on U.S. life expectancy as of year-end 2020: they reported a decline of a full year, which is ridiculous on its face! As explained by Peter B. Bach in STAT News, the agency assumed that excess deaths attributed to COVID in 2020 would continue as a permanent addition to deaths going forward. Please forgive my skepticism, but isn’t this too basic to qualify as an analytical error by an agency that subjects its reports to thorough vetting? Or might this have been a deliberate manipulation intended to convince the public that COVID will be an ongoing public health crisis. Of course the media has picked it up; even Zero Hedge reported it uncritically!

Bach does a quick calculation based on 400,000 excess deaths attributed to COVID in 2020 and 12 life-years lost by the average victim. I believe the first assumption is on the high side, and I say “attributed to COVID” as a reminder that the CDC’s guidance for completing death certificates was altered in the spring of 2020 specifically for COVID and not other causes of death. Furthermore, if our objective is to assess the impact of the virus itself, under no circumstances should excess deaths induced by misguided lockdown policies enter the calculation (though Bach entertains the possibility). Bach arrives at a reduction in average life of 5.3 days! Of course, that’s not intended to be a projection, but it is a reasonable estimate of COVID’s impact on average lives in 2020.

The CDC’s projection essentially freezes death rates at each age at their 2020 values. We will certainly see more COVID deaths in 2021, and the virus is likely to become endemic. Even with higher levels of acquired immunity and widespread vaccinations, there will almost certainly be some ongoing deaths attributable to COVID, but they are likely to be at levels that will blend into a resumption of the long decline in mortality rates, especially if COVID continues to displace the flu in its “ecological niche”. I include the chart at the top to emphasize the long-term improvement in mortality (though the chart shows only a partial year for 2020, and there has been some flattening or slight backsliding over the past five years or so). As Bach says:

“Researchers have regularly demonstrated that life expectancy projections are overly sensitive to evanescent events like pandemics and wars, resulting in considerably overestimated declines. … And yet the CDC published a result that, if anything, would convey to the public an exaggerated toll that Covid-19 took on longevity in 2020. That’s a problem.”

There were excess deaths from other causes in 2020, which Bach acknowledges. Perhaps 100,000 or more could be attributed to lockdowns and their consequences like economically-induced stress, depression, suicide, overdoses, and medical care deferred or never sought. The Zero Hedge article mentioned above discusses findings that lockdowns and their consequences, such as unemployment spells and lost education, will have ongoing negative effects on health and mortality for many years. The net effect on life expectancy might be as large as 11 to 12 days. Again, however, I draw a distinction between deaths caused by the disease and deaths caused by policy mistakes.

The CDC’s estimate should not be taken seriously when, as Kyle Smith says, there is every indication that the battle against COVID is coming to a successful conclusion. Public health experts have not acquitted themselves well during the pandemic, and the CDC’s life expectancy number only reinforces that impression. Here is Smith:

“We have learned a lot about how the virus works, and how it doesn’t: Outdoor transmission, for the most part, hardly ever happens. Kids are at very low risk, especially younger children. Baseball games, barbecues, and summer camps should be fine. Some pre-COVID activities now carry a different risk profile — notably anything that packs crowds together indoors, so Broadway theater, rock concerts, and the like will be just about the last category of activity to return to normal.”

But return to normal we should, and yet the CDC seems determined to poop on the victory party!

Hooray For Florida!

22 Monday Feb 2021

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It’s been said that many of the so-called “heroes” of the COVID pandemic who’ve been celebrated by the media are actually villains, and perhaps Governor Andrew Cuomo of New York should top the list. He saw to it that retirement homes were seeded with infected patients by ordering them returned their care homes rather than admitted to hospitals. Deaths in these facilities mounted, and they mounted faster than Cuomo’s administration was willing to admit. But the media and even Democrat state legislators have begun to take note, which is practically a miracle!

It seems equally true that some vilified by the media for their COVID response are actually heroes. Governor Ron DeSantis of Florida might deserve top honors here. Having spent the last month in Florida, I can attest that the business and social environment here is quite open compared to my home state (despite the presence of a few freaked out northerners who can’t quite fathom how stupid they look wearing masks on the beach). Florida’s infections, hospitalizations, and deaths have been lower than in California, New York, and many other states where lockdown measures have been stringent. (The first chart below is just a little busy…)

As I’ve written for much of the past year, COVID is far more dangerous to the elderly than anyone else, particularly those with co-morbidities. It’s also true that blacks (and some other minorities) are more vulnerable than whites, but if we want to save more black lives, we’re still better off prioritizing the elderly than racial groups. DeSantis understands this, and Florida is among the leaders in vaccinating the elderly population. (States don’t report this data on a uniform basis):

This approach to saving lives is obvious, yet critics at outlets like NBC News insist that DeSantis must be pandering to the senior population in Florida. Well, one wouldn’t want to be responsive to voters who happen to face high mortality risks, right? Others such as horror writer Stephen King have jumped onboard to offer their bumbling public health expertise as well.

There were many experts and the usual collection of numbskulls on social media who were wrong about Florida. DeSantis handled the pandemic as it should have been handled elsewhere. But the propaganda to the contrary goes unabated. For example, this article is pathetic. Can these people be serious? Or are they really that stupid? This goes for the Biden Administration as well, which had entertained the notion of imposing federal travel restrictions on Florida!

The political attacks on Florida and its governor reveal the extent to which opponents wish to ignore the evidence in plain sight. The data on COVID outcomes put the lie to the narrative of a public health emergency requiring massive restrictions on personal liberty. We know those policies are powerless to control the course of the contagion. The pandemic, however, was the key to convincing the public to accept a more authoritarian role for government. It’s a blessing that not everyone bought in, and that there are places like Florida where you can still go about your business in approximate normalcy.

COVID Cases Decline Despite New Variants

19 Friday Feb 2021

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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”.

Revisiting Excess Mortality

31 Sunday Jan 2021

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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

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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.

Long COVID: a Name For Post-Viral Syndrome

15 Friday Jan 2021

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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.

Cash Flows and Hospital Woes

10 Sunday Jan 2021

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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.

Let’s Do “First Doses First”

06 Wednesday Jan 2021

Posted by in Coronavirus, Vaccinations

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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.