Tag Archives: Pandemic

Joe Biden’s Fat Cooked-Goose Tax Plan

03 Saturday Apr 2021

Posted by in Fiscal policy, Taxes

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I recently wrote on this blog about the damaging impact of corporate taxes on workers, consumers, and U.S. competitiveness. Phil Kerpen tweeted the chart above showing the dramatic reduction in the distribution of corporate tax rates across the world from 1980 through 2020. Yes, yes, Joe Biden’s posture as a fair and sensible leader aside, most countries place great emphasis on their treatment of business income and their standing relative to trading partners.

Kerpen’s tweet was a response to this tweet by economist Justin Wolfers:

Apparently, Wolfers wishes to emphasize that Biden’s plan, which raises the statutory corporate rate from 21% to 28%, does not take the rate up to the level of the pre-Trump era. Fair enough, but compare Wolfers’ chart with Kerpen’s (from the Tax Foundation) and note that it would still put the U.S. in the upper part of the international distribution without even considering the increment from state corporate tax rates. Also note that the U.S. was near the top of the distribution in 1980, 2000, and 2010. In fact, the U.S. had the fourth highest corporate tax rate in the world in 2017, before Trump’s tax package took effect. Perhaps Biden’s proposed rate won’t be the fourth highest in the world, but it will certainly worsen incentives for domestic U.S. investment, the outlook for wage growth, and consumer prices.

And in the same thread, Wolfers said this:

That’s certainly true, but let’s talk about those “loopholes”. First, much of U.S. corporate income is “passed though” to the returns of individual owners, so corporate taxes understate the true rate of tax paid on corporate income. Let’s also remember that the corporate tax represents a double taxation of income, and as a matter of tax efficiency it would be beneficial to consolidate these taxes on individual returns.

Beyond those consideration, the repeal of any corporate tax deduction or credit would have its own set of pros and cons. As long as there is a separate tax on corporate income, there is an economic rationale for most so-called “loopholes”. Does Wolfers refer to research and development tax credits? Maybe he means deductions on certain forms of compensation, though it’s hard to rationalize treating any form of employee compensation as income taxable to the business. Then there are the massive tax subsidies extended for investments in renewable energy. Well, good for Wolfers if that last one is his gripe! The CARES Act of 2020 allowed publicly-traded companies to use losses in 2020( presumably induced by the pandemic) to offset income in prior years, rather than carrying them forward. Did Wolfers believe that to be inappropriate? I might object to that too, to the extent that the measure allows declining firms to use COVID to cloak inefficiencies. Does he mean the offshoring of income to avoid U.S. corporate taxes? Might that be related to relative tax rates?

In any case, Wolfers can’t possibly imagine that the U.S. is the only country allowing a variety of expenses to be deducted against corporate income, or credits against tax bills for various activities. So, a comparison of statutory tax rates is probably a good place to start in assessing the competitive thrust of tax policy. But effective tax rates can reveal much more about the full impact of tax policy. In 2011, a study showed that the U.S. had the second highest effective corporate tax rate in the world. Today, among developed countries, the OECD puts the U.S. roughly in the middle of the pack, close to Germany but higher than Canada, Mexico and Japan, and lower than the UK. This article from 2019 reaches the same conclusion, though the rankings and rates differ from the OECD’s calculations. So it’s not as if the U.S. is the only country to offer tax incentives, or “loopholes” in Wolfers’ preferred terminology.

The corporate tax hikes proposed by the Biden Administration are intended to fund the massive outlays in the so-called infrastucture bill, which of course has very little to do with real infrastructure. Both the tax and spending proposals are bad policy. So far, however, passage of the bill is not a given. Let’s hope all of the Republicans and at least one Democrat senator have the sense to vote it down, but I’m not optimistic. The best hope for resistance among Democrats is Joe Manchin of West Virginia, but even he has signaled his support. Biden’s appointment of Gayle Manchin to a key administration post couldn’t have hurt.

Myth Makers in Lab Coats

02 Friday Apr 2021

Posted by in Climate science, Research Bias, Science

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The prestige of some elements of the science community has taken a beating during the pandemic due to hugely erroneous predictions, contradictory pronouncements, and misplaced confidence in interventions that have proven futile. We know that medical science has suffered from a replication crisis, and other areas of inquiry like climate science have been compromised by politicization. So it seemed timely when a friend sent me this brief exposition of how “scientific myths” are sometimes created, authored by Lee Jussim in Psychology Today. It’s a real indictment of the publication process in scientific journals, and one can well imagine the impact these biases have on journalists, who themselves are prone to exaggeration in their efforts to produce “hot” stories.

The graphic above appears in Jussim’s article, taken from a Cambridge study of reporting and citation biases in research on treatments for depression. But as Jussim asserts, the biases at play here are not “remotely restricted to antidepressant research”.

The first column of dots represent trial results submitted to journals for publication. A green dot signifies a positive result: that the treatment or intervention was associated with significantly improved patient outcomes. The red dots are trials in which the results were either inconclusive or the treatment was associated with detrimental outcomes. The trials were split about equally between positive and non-positive findings, but far fewer of the trials with non-positive findings were published. From the study:

“While all but one of the positive trials (98%) were published, only 25 (48%) of the negative trials were published. Hence, 77 trials were published, of which 25 (32%) were negative.“

The third column shows that even within the set of published trials, certain negative results were NOT reported or secondary outcomes were elevated to primary emphasis:

“Ten negative trials, however, became ‘positive’ in the published literature, by omitting unfavorable outcomes or switching the status of the primary and secondary outcomes.“

The authors went further by classifying whether the published narrative put a “positive spin” on inconclusive or negative results (yellow dots):

“… only four (5%) of 77 published trials unambiguously reported that the treatment was not more effective than placebo in that particular trial.“

Finally, the last column represents citations of the published trials in subsequent research, where the size of the dots corresponds to different levels of citation:

“Compounding the problem, positive trials were cited three times as frequently as negative trials (92 v. 32 citations. … Altogether, these results show that the effects of different biases accumulate to hide non- significant results from view.“

As Jussim concludes, it’s safe to say these biases are not confined to antidepressant research. He also writes of the “canonization effect”, which occurs when certain conclusions become widely accepted by scientists:

“It is not that [the] underlying research is ‘invalid.’ It is that [the] full scope of findings is mixed, but that the mixed nature of those findings does not make it into what gets canonized.“

I would say canonization applies more broadly across areas of research. For example, in climate research, empirics often take a back seat to theoretical models “calibrated” over short historical records. The theoretical models often incorporate “canonized” climate change doctrine which, on climatological timescales, can only be classified as speculative. Of course, the media and public has difficulty distinguishing this practice from real empirics.

All this is compounded by the institutional biases introduced by the grant-making process, the politicization of certain areas of science (another source of publication bias), and mission creep within government bureaucracies. In fact, some of these agencies control the very data upon which much research is based (the National Oceanic and Atmospheric Administration, for example), and there is credible evidence that this information has been systematically distorted over time.

The authors of the Cambridge study discuss efforts to mitigate the biases in published research. Unfortunately, reforms have met with mixed success at best. The anti-depressant research reflects tendencies that are all too human and perhaps financially motivated. Add to that the political motivation underlying the conduct of broad areas of research and the dimensions of the problem seem almost insurmountable without a fundamental revolution of ethics within the scientific community. For now, the biases have made “follow the science” into something of a joke.

Revisiting Excess Mortality

31 Sunday Jan 2021

Posted by in Coronavirus, Pandemic

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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.

A Good Historical Backdrop for the Pandemic

07 Monday Dec 2020

Posted by in Pandemic, Public Health

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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.

Lockdowns Subvert Public Health and Life Itself

15 Thursday Oct 2020

Posted by in Coronavirus, Lockdowns, Public Health, Uncategorized

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Acceptance of risk is a necessary part of a good life, and extreme efforts to avoid it are your own business. Government has no power to guarantee absolute safety, nor should we presume to have such a right. Ongoing COVID lockdowns are an implicit assertion of exactly that kind of government power, despite the impotence of those efforts, and they constitute a rejection of more fundamental rights.

Lockdowns have had destructive effects on health and economic well being while conferring little if any benefit in mitigating harm from the virus. The lockdowns were originally sold as a way to “flatten the curve”, that is, to avoid a spike in cases and an overburdened health care system. However, this arguably well-qualified rationale later expanded in scope to encompass the mitigation of smaller and much less deadly outbreaks among younger cohorts, and then to the very idea of extinguishing the virus altogether. It’s become painfully obvious that such measures are not capable of achieving those goals.

In the U.S., the ongoing lockdowns have been a cause célèbre largely on the interventionist Left, and they have been prolonged mainly by Democrats at various levels of government. In a way, this is not unlike many other policies championed by the Left, often ostensibly designed to help members of the underclasses: instead, those policies often destroy or wrongly obviate incentives and promote dependency on the state. In this case, the plunge into dependency is a reality the Left would very much like to ignore, or to blame on someone else. You know who.

The lockdowns have been largely unsuccessful in mitigating the spread of the virus. At the same time, they have been used as a pretext to deny constitutional rights such as the free practice of religion, assembly, and a broad range of unenumerated rights under the “penumbra” of the Bill of Rights and the Ninth Amendment. What’s more, the severity of the economic blow caused by lockdowns has been borne disproportionately by the working poor and the small businesses who employ so many of them.

Lockdowns are deadly. It’s not clear that they’ve saved any lives, but they have massively disrupted the operation of the health care system with major consequences for those with chronic and undiagnosed conditions. The lockdowns have also led to spikes in mental health issues, alcoholism, drug abuse, and deaths of despair. A recent study found that over 26% of the excess deaths during the pandemic were non-COVID deaths. Those deaths were avoidable or accelerated, whereas the lockdowns have failed to meaningfully curtail COVID deaths. Don’t tell me about reduced traffic fatalities: that reduction is relatively small relative to the increase in non-COVID excess deaths (see below).

What proof do we have that lockdowns cause excess deaths? See this study in The Lancet on cancer deaths due to lockdown-induced delays in diagnoses. See this study on UK school closures. See this Oxfam International report on lockdown-induced starvation. Other reports from the UK suggests that lockdown deaths are widespread, having taken nearly 2,800 per week early in the pandemic, and many other deaths yet to occur have been made inevitable by lockdowns. Doctors in the U.S. have warned that lockdowns are a “mass casualty incident”, and a German government study warned of the same.

The Ethical Skeptic (TES) on Twitter has been tracking a measure of lockdown deaths for some time now. The following graphic provides a breakdown of excess non-COVID deaths since the start of the pandemic. The total “pie” shows almost 320,000 excess deaths through September 26th (avoiding less complete counts in recent weeks), as reported by the CDC. COVID accounted for 202,000 of those deaths, based on state-level reporting. Of the remaining 117,000 excess deaths, TES uses CDC data to allocate roughly 85,000 to various causes, the largest (more than half) being “Suicide, Addiction, Abandonment, and Abuse”. Other large categories include Cardio/Diabetes, Stroke, premature Alzheimers/Dementia death, and Cancer Access. Nearly 32,000 excess deaths remain as a “backlog”, not yet reported with a cause by states.

Also of interest in the graphic are estimates of life-years lost. The vast bulk of COVID victims are elderly, of course, which means that any estimate of lost years per victim must be relatively low. On the other hand, most non-COVID, lockdown-related deaths are among younger victims, with correspondingly greater life-years lost. TES’s aggregate estimate is that lockdown-related excess deaths involve double the life-years lost of COVID deaths. Of course, that is an estimate, but even granting some latitude for error, the reality is horrifying!

John Tierney in City Journal cites several recent studies concluding that lockdowns have been largely ineffective in Europe and in the U.S. While Tierney doesn’t rule out the possibility that lockdowns have produced some benefits, they have carried excessive costs and risks to public health going forward, such as lingering issues for those having deferred important health care decisions as well as disruption in future economic prospects. Ultimately, lockdowns don’t accomplish anything:

“While the economic and social costs have been enormous, it’s not clear that the lockdowns have brought significant health benefits beyond what was achieved by people’s voluntary social distancing and other actions.”

Tierney also discusses the costs and benefits of lockdowns in terms of life years: quality-adjusted life-years (QALY), which is a widely-used measure for evaluating of the use of health care resources:

“By the QALY measure, the lockdowns must be the most costly—and cost-ineffective—medical intervention in history because most of the beneficiaries are so near the end of life. Covid-19 disproportionately affects people over 65, who have accounted for nearly 80 percent of the deaths in the United States. The vast majority suffered from other ailments, and more than 40 percent of the victims were living in nursing homes, where the median life expectancy after admission is just five months. In Britain, a study led by the Imperial College economist David Miles concluded that even if you gave the lockdown full credit for averting the most unrealistic worst-case scenario (the projection of 500,000 British deaths, more than ten times the current toll), it would still flunk even the most lenient QALY cost-benefit test.”

We can now count the World Health Organization among the detractors of lockdowns. According to WHO’s Dr. David Nabarro:

“Lockdowns just have one consequence that you must never ever belittle, and that is making poor people an awful lot poorer…. Look what’s happened to smallholder farmers all over the world. … Look what’s happening to poverty levels. It seems that we may well have a doubling of world poverty by next year. We may well have at least a doubling of child malnutrition.”

In another condemnation of the public health consequences of lockdowns, number of distinguished epidemiologists have signed off on a statement known as The Great Barrington Declaration. The declaration advocates a focused approach of protecting the most vulnerable from the virus, while allowing those at low risk to proceed with their lives in whatever way they deem acceptable. Those at low risk of severe disease can acquire immunity, which ultimately inures to the benefit of the most vulnerable. With few, brief, and local exceptions, this is how we have always dealt with pandemics in the past. That’s real life!

COVID, Trump, and Tyrants

11 Sunday Oct 2020

Posted by in Pandemic, Public Health, Trump Administration

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I’ve said this before, but it bears repeating: allegations of the White House’s “poor leadership” and preparedness for COVID-19 (C19) are a matter of selective memory. At the link above, I “graded” Trump’s pandemic job performance through May. Among other things, I said:

“Many have criticized the Trump Administration for not being ‘ready’ for a pandemic. I assign no grade on that basis because absolutely no one was ready, at least not in the West, so there is no sound premise for judgement. I also view the very general charge that Trump did not provide “leadership” as code for either ‘I don’t like him’, or ‘he refused to impose more authoritarian measures’, like a full-scale nationwide lockdown. Such is the over-prescriptive instinct of the Left.”

The President of the United States does not have the constitutional authority to impose a national lockdown, though Trump himself seemed confused at times as to whether he had that power. However, on this basis at least, the ad nauseam denigration of his “leadership” is vapid. At this point, the course of the pandemic in the U.S. is less severe than in several other industrialized countries who didn’t even have Andrew Cuomo around to exacerbate the toll, and it’s still not as deadly in per capita terms as the Asian Flu of 1957-58.

Who exactly was “ready” for C19? Perhaps critics are thinking of South Korea, or parts of South Asia. Those countries might have been “ready” to the extent that they had significant prior exposure to SARS viruses. There was already some degree of immunological protection. Those countries also were exposed to an earlier genetic variant of C19 that was much less severe than the strain that hit most of the western world. These are hardly reasons to blame Trump for a lack of “readiness”.

A related charge I hear all the time is that Trump “ignored the advice of medical experts“, or that he “ignored the science“. Presumably, those “experts” include the darling of the Prescriptive Class, Dr. Anthony Fauci. On February 28, Dr Fauci said:

“Right now, at this moment, there’s no need to change anything you’re doing on a day by day basis.“

All-righty then! So this was the advice Trump “should” have followed. Oh, wait… he did! And Fauci, on March 9, said there was no reason for young, healthy people to avoid cruise ships.

Likewise, Dr. Robert Redfield, Director of the Centers for Disease Control, said the following on February 27:

“The risk to the American public is low. We have an aggressive containment strategy that really has worked up to this time, 15 cases in the United States. Until the last case that we just had in Sacramento we hadn’t had a new case in two weeks.”

Then there is the World Health Organization, which downplayed the virus in January and February, and giving a convincing impression that it servied as a mouthpiece for the CCP.

In fact, the American people were badly harmed by wrongheaded decisions made by the “experts” at the CDC in January and February, when the agency insisted that testing could not proceed until a test of their own design was ready. Then, the first version it approved was discovered to be flawed! This set the testing effort back by well over a month, a delay that proved critical. It’s no exaggeration to say this bureaucratic overreach denied the whole country, and Trump, the information needed to properly assess the spread of the virus.

But let’s think about actual policy once it became clear that the virus was getting to be a serious matter in parts of the U.S. Here’s another excerpt from my post in May:

“Trump cannot be accused of ignoring expert advice through the episode. He was obviously on-board with Fauci, Dr. Deborah Birx, Dr. Robert Redfield, and other health care advisors on the ‘15 Days to Slow the Spread‘ guidelines issued on March 16. His messaging wavered during those 15 days, expressing a desire to fully reopen the nation by Easter, which Vice President Michael Pence later described as “aspirational”. Before the end of March, however, Trump went along with a 30-day extension of the guidelines. Finally, by mid-April, the White House released guidelines for ‘Opening Up America Again‘, which was a collaboration between Trump’s health care experts and the economic team. Trump agreed that the timeline for reopening should be governed by ‘the data’.” 

We should give Trump credit for shutting down flights into the U.S. from China, where the virus originated, late in January. That was an undeniably prescient move. Let’s also not forget that the original intent of the “15 Days” was to prevent hospitals and other medical resources from being overwhelmed. Today, the data show a strong seasonal tendency to the spread of the virus, but medical resources are not close to being overwhelmed, our ability to treat the virus has vastly improved, and its consequences are much less deadly than in the spring. That’s good progress, whatever the President’s detractors may say.

More than anything else, what Trump’s COVID critics fail to understand is that the executive leader of a republic is not possessed of monarchical powers. And in the U.S., the Constitution provides an additional layer of sovereignty for member states of the Union, a manifestation of the federalist principals without which the Union would not have been possible. The 15-day guidelines produced by the White House, and the guidelines for reopening, were consistent with this framework. The states have adapted their own policies to actual conditions and, if their leaders haven’t worn out their goodwill among voters, internal political realities. Those adaptations were often bad from my perspective, or even tyrannical, but sometimes good. That is exactly how our federalist system was designed to work.

Joe’s “Boom”: Mendacity or Memory Loss?

06 Tuesday Oct 2020

Posted by in economic growth, Executive Authority

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Joe Biden has claimed that he and Barack Obama had left Donald Trump with a “booming” economy to start his term in office. Of course, if he had anything to do with economic performance during the Obama Administration, it may have been his oversight of the mismanaged and ineffective “shovel-ready” stimulus program of 2009, For his sake, one might hope (and suspect) his oversight was nominal. In any case, his characterization of the Obama economy is not really accurate, as this editorial at Issues and Insights demonstrates. I could argue with a few of their points, but the thrust of it is correct. The economy weakened in 2015 and 2016, and expectations were for continued slow growth or possibly a recession in 2017 or after. At that point, many economists thought the aging expansion might be on its last legs. But economic growth exceeded expectations after Trump took office. As for job growth, economists predicted relatively sluggish growth in 2017-2019, but actual job growth exceeded those projections by more than three times.

Finally, Biden’s assertion that “Trump caused the recession” was laughable, especially when the punchline is his willingness to “shut down the economy“! He insists “I would listen to the scientists”, presumably the same knuckleheads who don’t understand the public health tradeoffs between the pandemic itself and lockdown risks (and who don’t understand the Constitution). Biden might not understand that the President lacks constitutional powers to demand a nationwide shutdown. Trump was quite sensibly persuaded to leave non-pharmaceutical interventions in the hands of the private sector as well as state and local governments, with guidance from federal health authorities. That some state and local leaders instituted draconian policies, which were largely ineffective and often damaging. was and is a terrible misfortune. The more sensible approach is to  protect the most vulnerable and allow others to gauge their own risks, as we always have in earlier pandemics.

Case Fatality, Stale Ratios and Exaggerated Loss

14 Tuesday Jul 2020

Posted by in Analytics, Pandemic

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I hope someday I won’t feel compelled to write or worry about the coronavirus. However, as the pandemic wears on, it seems to take only a few days for issues to pile up, and I just can’t resist comment. Today I have a couple of beefs with uses of data and concomitant statements I’ve seen posted of late.

People are still quoting case fatality rates (CFRs) as if those cumulative numbers are relevant to the number of deaths we can expect going forward. They are not. Just as hair-brained are applications of cumulative hospitalization and ICU admittance rates to produce “rough and ready” estimates of what to expect going forward. Or, I’ve seen people express hospitalizations as ratios to CFR, as if those ratios will be the same going forward. Again, they are not. Let me try to explain.

The chart below shows the course of the U.S. CFR since the start of the pandemic. It’s taken from the interactive Covid Time Series site. My apologies if you have to click on the chart for decent viewing (or you can visit the site). The CFR at any date is the cumulative number of deaths to-date divided by the cumulative number of confirmed cases. It is a summary of past history, but it is not well-suited to making predictions about death rates in the future. The CFR began to taper a little before Memorial Day, and it is now at about 4% (as of July 13).

Out of curiosity, I also generated CFRs for AZ, CA, FL, GA, and TX, which now average about half of the national CFR. There’s an obvious lesson: if you must use CFRs, understand that they vary from place to place.

Again, CFRs are cumulative. Their changes over time can tell us something about recent trends, but even then they are flawed. For example, case counts have risen dramatically with more widespread testing. Those testing positive more recently are concentrated in younger age cohorts, for whom infections are much less severe. Treatment has improved dramatically as well, so there is little reason to expect the CFR’s of recently diagnosed cases to be as high as the latest CFRs shown above.

There is no easy way to calculate an unflawed “marginal” CFR for a recent period, though an effort to do so might improve the predictive value. Deaths lag behind case counts because the progression from early symptoms to death can take several weeks. Even more vexing for constructing a valid, recent fatality rate is that reporting of deaths is itself delayed, as I explained in my last post. Each day’s report of deaths captures deaths that may have occurred over a period of several weeks in the past, and sometimes many more.

Finally no CFR can capture the true mortality rate of the virus without ongoing, ubiquitous testing. As the state of testing stands, the true mortality rate must reflect undiagnosed cases in the denominator. The CDC’s latest “best” estimate of the true mortality rate is just 0.3%, and 0.05% for those aged 50 years or less. Those figures are based on serological tests for the presence of antibodies to C19 in more random samples of the population. Those findings reflect the extent of undiagnosed and/or asymptomatic cases.

The point is one shouldn’t be too blithe about throwing numbers around like 4% mortality based on the CFR, or even 1% mortality as a “nice, round number”, without heavy qualification. Those numbers are gross exaggerations of what we are likely to see going forward.

The same criticisms can be leveled at claims that hospitalizations will proceed at some fixed ratio relative to diagnosed cases, or some fixed ratio relative to deaths. Again, new cases tend to be less severe, so hospitalizations are likely to be a much lower ratio to cases than what is reflected in cumulative totals. Because of improved treatment, the ratio of deaths to hospitalizations will be much lower in the future as well.

CFRs are not a useful guide to future COVID deaths. The true mortality rate is a much better baseline, particularly for subsets of the population matching the current case load. Finally, and this is the only disclaimer I’ll bother to provide today, we all know that suffering is not confined to terminal cases, and it is not confined to the hospitalized subset. But don’t exaggerate the extent of your preferred interpretation of suffering by applying inappropriate cumulative calculations.

 

Cases Climb, Most Patients Faring Better

30 Tuesday Jun 2020

Posted by in Pandemic, Public Health

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There’s been much speculation about whether recent increases in confirmed cases of COVID-19 (first chart above) will lead to a dramatic increase in fatalities (second chart). More generally, there is curiosity or perhaps hope as to whether the virus is not as dangerous to these new patients as it was early in the pandemic. I have discussed this point in several posts, most recently here. Based on the national data (above), we’re at the point at which an upturn in deaths might be expected. Based on the experience of many individual states, however, deaths should have trended upward by now, but they haven’t done so. Cases are generally less severe and are resolving more quickly.

Of course, more testing produces more cases (though there has been a mild uptick in test positivity over the past two weeks), but that doesn’t really explain the entire increase in cases over the past few weeks. In particular, why are so many new cases in the south? After all, there is evidence that the virus doesn’t survive well in warm, humid climates with more direct sunlight.

As I have mentioned several times, heavy use of air-conditioning in the south may have contributed to the increase. Nate Silver speculates that this is the case. The weather warmed up in late May and especially June, and many southerners retreated indoors where the air is cool, dry, and the virus thrives. Managers of public buildings should avoid blasting the AC, and you might do well to heed the same advice if you live with others in a busy household. In fact, nearly all transmission is likely occurring indoors, as has been the case throughout the pandemic. At the same time, however, with the early reopening of many southern states, younger people flocked to gyms, bars and other venues, largely abandoning any pretense of social distancing. So it’s possible that these effects have combined to produce the spike in new cases.

Some contend that the protests following George Floyd’s murder precipitated the jump in confirmed cases. Perhaps they played a role, but I’m somewhat skeptical. Yes, these could have become so-called super-spreader events; there are certain cities in which the jump in cases lagged the protests by a few weeks, such as Austin, Houston, and Miami, and where some cases were confirmed to be among those who protested. But if the protests contributed much to the jump, why hasn’t New York City seen a corresponding increase? Not only that, but the protests were outside, and the protests dissuaded many others from going out at all!

The trend in coronavirus fatalities remains more favorable, despite the increase in daily confirmed cases. One exception is New Jersey, which decided to reclassify 1,800 deaths as “probable” COVID deaths about six days ago. You can see the spike caused by that decision in the second chart above. Reclassifications like that arouse my suspicion, especially when federal hospital reimbursements are tied to COVID cases, and in view of this description from Bloomberg (my emphasis):

“… those whose negative test results were considered unreliable; who were linked to known outbreaks and showed symptoms; or whose death certificates strongly suggested a coronavirus link.”

Deaths necessarily lag new cases by anywhere from a few days to several weeks, depending on the stage at the time of diagnosis and delays in test results. The lag between diagnosis and death seems to center on about 12 – 14 days. Thus far, there doesn’t appear to be an upward shift in the trend of fatal cases, but the big updraft in cases nationally only started about two weeks ago. More on that below.

Importantly, a larger share of new cases is now among a younger age cohort, for whom the virus is much less threatening. The most vulnerable people are probably taking more precautions than early in the pandemic, and shocking as might seem, there is probably some buildup in immunity in the surviving nursing home population at this point. We are also better at treatment, and there is generally plenty of hospital capacity. And to the extent that the surge in new cases is concentrated in the south, fewer patients are likely to have Vitamin D deficiencies, which is increasingly mentioned as a contributor to the severity of coronavirus infections.

I decided to make some casual comparisons of new cases versus COVID deaths on a state-by-state basis, but I got a little carried away. Using the COVID Time Series web site, I started by checking some of the southern states with recent large increases in case counts. I ended up looking at 15 states in the south and west, and I added Missouri and Minnesota as well. I passed over a few others because their trends were basically flat. The 17 states all had upward trends in new cases over the past one to two months, or they had an increase in new cases more recently. However, only four of those states experienced any discernible increase in daily deaths over the corresponding time frames. These are Arizona, Arkansas, Tennessee, and Texas, and their increases are so modest they might be statistical noise.

Again, deaths tend to lag new cases by a couple of weeks, so the timing of the increase in case counts matters. Five of the states were trending upward beginning in May or even earlier, and 13 of the states saw an acceleration or a shift to an upward trend in new cases after Memorial Day, in late May or June. Of those 13, the changes in trend occurred between one and five weeks ago. Six states, including Texas, had a shift within the past two weeks. It’s probably too early to draw conclusions for those six states, but in general there is little to suggest that fatal cases will soar like they did early in the pandemic. Case fatality rates are likely to remain at much lower levels.

We’ll know much more within a week or two. It’s very encouraging that the upward trend in new cases hasn’t resulted in more deaths thus far, especially at the state level, as many states have had case counts drift upward for over a month. If it’s going to occur, it should be well underway within a week or so. Much also depends on whether new cases continue to climb in July, in which case we’ll be waiting in trepidation for whether more deaths transpire.

Suspending Medical Care In the Name of Public Health

23 Saturday May 2020

Posted by in Health Care, Pandemic

≈ 3 Comments

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Step back in time six months and ask any health care professional about the consequences of suspending delivery of most medical care for a period of months. Forget about the coronavirus for a moment and just think about that “hypothetical”. These experts would have answered, uniformly, that it would be cataclysmic: months of undiagnosed cardiac and stroke symptoms; no cancer screenings, putting patients months behind on the survival curve; deferred procedures of all kinds; run-of-the-mill infections gone untreated; palsy and other neurological symptoms anxiously discounted by victims at home; a hold on treatments for all sorts of other progressive diseases; and patients ordinarily requiring hospitalization sent home. And to start back up, new health problems must compete with all that deferred care. Do you dare tally the death and other worsened outcomes? Both are no doubt significant.

What you just read has been a reality for more than two months due to federal and state orders to halt non-emergency medical procedures in the U.S. The intent was to conserve hospital capacity for a potential rush of coronavirus patients and to prevent others from exposure to the virus. That might have made sense in hot spots like New York, but even there the provision of temporary capacity went almost completely unused. Otherwise, clearing hospitals of non-Covid patients, who could have been segregated, was largely unnecessary. The fears prompted by these orders impacted delivery of care in emergency facilities: people have assiduously avoided emergency room visits. Even most regular office visits were placed on hold. And as for the reboot, there are health care facilities that will not survive the financial blow, leaving communities without local sources of care.

A lack of access to health care is one source of human misery, but let’s ask our health care professional about another “hypothetical”: the public health consequences of an economic depression. She would no doubt predict that the stresses of joblessness and business ruin would be acute. It’s reasonable to think of mental health issues first. Indeed, in the past two months, suicide hotlines have seen calls spike by multiples of normal levels (also see here and here). But the stresses of economic disaster often manifest in failing physical health as well. Common associations include hypertension, heart disease, migraines, inflammatory responses, immune deficiency, and other kinds of organ failure.

The loss of economic output during a shutdown can never be recovered. Goods don’t magically reappear on the shelves by government mandate. Running the printing press in order to make government benefit payments cannot make us whole. The output loss will permanently reduce the standard of living, and it will reduce our future ability to deal with pandemics and other crises by eroding the resources available to invest in public health, safety, and disaster relief.

What would our representative health care professional say about the health effects of a mass quarantine, stretching over months? What are the odds that it might compound the effects of the suspension in care? Confinement and isolation add to stress. In an idle state of boredom and dejection, many are unmotivated and have difficulty getting enough exercise. There may be a tendency to eat and drink excessively. And misguided exhortations to “stay inside” certainly would never help anyone with a Vitamin D deficiency, which bears a striking association with the severity of coronavirus infections.

But to be fair, was all this worthwhile in the presence of the coronavirus pandemic? What did health care professionals and public health officials know at the outset, in early to mid-March? There was lots of alarming talk of exponential growth and virus doubling times. There were anecdotal stories of younger people felled by the virus. Health care professionals were no doubt influenced by the dire conditions under which colleagues who cared for virus victims were working.

Nevertheless, a great deal was known in early March about the truly vulnerable segments of the population, even if you discount Chinese reporting. Mortality rates in South Korea and Italy were heavily skewed toward the aged and those with other risk factors. One can reasonably argue that health care professionals and policy experts should have known even then how best to mitigate the risks of the virus. That would have involved targeting high-risk segments of the population for quarantine, and treatment for the larger population in-line with the lower risks it actually faced. Vulnerable groups require protection, but death rates from coronavirus across the full age distribution closely mimic mortality from other causes, as the chart at the top of this chart shows.

The current global death toll is still quite small relative to major pandemics of the past (Spanish Flu, 1918-19: ~45 million; Asian Flu, 1957-58: 1.1 million; Hong Kong flu, 1969: 1 million; Covid-19 as of May 22: 333,000). But by mid-March, people were distressed by one particular epidemiological model (Neil Ferguson’s Imperial College Model, subsequently exposed as slipshod), predicting 2.2 million deaths in the U.S. (We are not yet at 100,000 deaths). Most people were willing to accept temporary non-prescription measures to “slow the spread“. But unreasonable fear and alarm, eagerly promoted by the media, drove the extension of lockdowns across the U.S. by up to two extra months in some states, and perhaps beyond.

The public health and policy establishment did not properly weigh the health care and economic costs of extended lockdowns against the real risks of the coronavirus. I believe many health care workers were goaded into supporting ongoing lockdowns in the same way as the public. They had to know that the suspension of medical care was a dire cost to pay, but they fell in line when the “experts” insisted that extensions of the lockdowns were worthwhile. Some knew better, and much of the public has learned better.