Tag Archives: Non-Pharmaceutical interventions

Spate of Research Shows COVID Lockdowns Fail

27 Sunday Dec 2020

Posted by in Lockdowns, Public Health

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For clarity, start with this charming interpretive one-act on public health policy in 2020. You might find it a little sardonic, but that’s the point. It was one of the more entertaining tweets of the day, from @boriquagato.

A growing body of research shows that stringent non-pharmaceutical interventions (NPIs) — “lockdowns” is an often-used shorthand — are not effective in stemming the transmission and spread of COVID-19. A compendium of articles and preprints on the topic was just published by the American Institute for Economic Research (AEIR): “Lockdowns Do Not Control the Coronavirus: The Evidence”. The list was compiled originally by Ivor Cummins, and he has added a few more articles and other relevant materials to the list. The links span research on lockdowns across the globe. It covers transmission, mortality, and other health outcomes, as well as the economic effects of lockdowns. AIER states the following:

“Perhaps this is a shocking revelation, given that universal social and economic controls are becoming the new orthodoxy. In a saner world, the burden of proof really should belong to the lockdowners, since it is they who overthrew 100 years of public-health wisdom and replaced it with an untested, top-down imposition on freedom and human rights. They never accepted that burden. They took it as axiomatic that a virus could be intimidated and frightened by credentials, edicts, speeches, and masked gendarmes.

The pro-lockdown evidence is shockingly thin, and based largely on comparing real-world outcomes against dire computer-generated forecasts derived from empirically untested models, and then merely positing that stringencies and “nonpharmaceutical interventions” account for the difference between the fictionalized vs. the real outcome. The anti-lockdown studies, on the other hand, are evidence-based, robust, and thorough, grappling with the data we have (with all its flaws) and looking at the results in light of controls on the population.”

We are constantly told that public intervention constitutes “leadership”, as if our well being depends upon behavioral control by the state. Unfortunately, it’s all too typical of research on phenomena deemed ripe for intervention that computer models are employed to “prove” the case. A common practice is to calibrate such models so that the outputs mimic certain historical outcomes. Unfortunately, a wide range of model specifications can be compatible with an historical record. This practice is also a far cry from empirically testing well-defined hypotheses against alternatives. And it is a practice that usually does poorly when the model is tested outside the period to which it is calibrated. Yet that is the kind of evidence that proponents of intervention are fond of using to support their policy prescriptions.

In this case, it’s even worse, with some of the alleged positive effects of NPI’s wholly made-up, with no empirical support whatsoever! So-called public health experts have misled themselves, and the public, with this kind of fake evidence, when they aren’t too busy talking out of both sides of their mouths.

COVID Externalities: the Costs and Benefits of Intervention

13 Sunday Dec 2020

Posted by in Coronavirus, Public Health, Social Costs

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This post offers a simple representation of the argument against public non-pharmaceutical interventions (NPIs) to subdue the COVID-19 pandemic. The chart below features two lines, one representing the presumed life-saving benefits of lockdown measures or NPI stringency, and another representing the costs inflicted by those measures. The values on the axes here are not critical, though measures of stringency exist (e.g., the University of Oxford Stringency Index) and take values from zero to 100.

The benefits of lives saved due to NPI stringency are assigned a value on the vertical axis, as are the costs of lives lost due to deferred health care, isolation, and other stressors caused by stringency. In addition, there are the more straightforward losses caused by suspending economic activity, which should be included in costs.

One can think of the benefits curve as representing gains from forcing individuals, via lockdown measures, to internalize the external costs of risk inflicted on others. However, this curve captures only benefits incremental to those achieved through voluntary action. Thus, NPI benefits include only extra gains from coercing individuals to internalize risks, while losses from NPI stringency are captured by the cost curve.

My contention is that the benefits of stringency diminish and may in fact turn down at some point, and that costs always increase in the level of stringency. In the chart, for what it’s worth, the “optimal” level of stringency would be at a value of 2, where the difference between total benefits and total costs is maximized (and where the benefits of incremental stringency are equal to the marginal costs or losses). However, I am not convinced that the benefits of lockdown measures ever exceed costs, as they do in the chart above. That is, voluntary action may be sufficient. But if the benefits of NPIs do exceed costs, it’s likely to be only at low levels of stringency.

To the extent that people are aware of the pandemic and recognize risk, the external costs of possible infectiousness are already internalized to some degree. Moreover, there is mutual risk in most interactions, and all individuals face risks that are proportional to those to which they expose others: if your contacts are more varied and your interactions are more frequent and intimate, you face correspondingly higher risks yourself. After all, in a pandemic, an individual’s failure to exercise caution may lead to a very hard internalization of costs if an infection strikes them. This mutuality is an element absent from most situations involving externalities. And to the extent that you take voluntary precautions, you and your contacts both benefit. Nevertheless, I concede that there are individuals who face less risk themselves (the young or healthy) but who might behave recklessly, and they might not internalize all risk for which they are responsible. Yes, stringency may have benefits, but that does not mean it has net benefits.

Even if there is some meaningful point at which NPIs are “optimized”, government does not possess the knowledge required to find that point. It lacks detailed knowledge of both costs and benefits of NPIs. This is a manifestation of the “knowledge problem” articulated by Friedrich Hayek, which hampers all efforts at central planning. In contrast, individual actors know their own tolerance for risk, and they surely have some sense of the risks they create in their normal course of affairs. And again, there is a strong degree of proportionality and voluntary internalization of mutual risks.

While relying on voluntary action is economically inefficient relative to an ideal, full-information and perfectly altruistic solution, it is at least based on information that individuals possess: their own risk profile and risk preferences. In contrast, government does not possess information necessary to impose rules in an optimal way, and those rules are rife with unintended consequences and costs inflicted on individuals.

My next post will present empirical evidence of the weakness of lockdown measures in curbing the coronavirus as well as the high costs of those measures. The coronavirus is a serious infection, but it is not terribly deadly or damaging to the longer-term health of the vast majority of people. This, in and of itself, should be sufficient to demonstrate that the array of non-pharmaceutical interventions imposed in the U.S. and abroad were and are not worthwhile. People are capable of assessing risks for themselves. The externality argument, that NPIs are necessary because people do not adequately assess the risk they pose to others, relies on an authority’s ability to assess that risk, and they invariably go overboard on interventions for which they underestimate costs. COVID is not serious enough to justify a surrender of our constitutional rights, and like every concession to government authority, those rights will be difficult to recover.

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.

Virus Visuals and Non-Pharmaceutical Interventions

19 Saturday Sep 2020

Posted by in Government Failure, Pandemic

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There are a bunch of nice graphs below summarizing the course of the coronavirus (C19) pandemic in different countries, as well as their policy responses. The charts are courtesy of Kyle Lamb, who has been an unlikely (in my mind…) but forceful voice regarding the pandemic over the past few months. I’m sorry if the resolution in some of the charts is poor, but I hope you can click on them for a better view.

The data reported in the charts goes through September 12. The first few charts below are “mirror charts”: they show newly diagnosed C19 cases by day on top, right-side up; on the bottom of each chart are C19-attributed deaths, but the vertical axis is inverted to create the “mirror effect”. The scales on the bottom are heavily stretched compared to the top (deaths are much smaller than cases), and the scales for different countries aren’t comparable. The patterns are informative nevertheless, and I’ll provide per capita deaths separately.

Let’s start with the U.S., where the early part of the pandemic in the spring was quite deadly, while the second, geographically distinct “wave” of the pandemic was less deadly. It looks bad, but the high number of deaths in the spring was partly a consequence of mismanagement by a few prominent government officials in the Northeast, most glaringly Governor Andrew Cuomo of New York. The full pattern for the U.S. combines different waves in different regions. The overall outcome to-date is 622 deaths per million of population.

Then we have charts for (deaths/mil in parens): the UK (628), Italy (591), Spain (653), France (467), Germany (114), the Netherlands (364), and Switzerland (240), which all have had second waves in cases, of but hardly any noticeable second wave in deaths, at least not yet:

And finally, we have Sweden (576), which had many deaths during the first wave, but very few now. Overall, to-date, Sweden has faired better than the U.S., Spain, the UK, and Italy — not to mention Belgium (870), for which I don’t have mirror charts.

There are several points to make about the charts:

First, the so-called second wave this summer has not been as deadly as the virus was in the spring. The U.S. is not an exception in that regard, though it did have more C19 deaths than the other countries. The count of U.S. deaths in the summer was partly due to C19 false positives under a much heavier testing regime, as well as “death laundering” by public health authorities that looks suspiciously like a politicization of the attribution process: C19 deaths over the summer have been well in excess of what would be expected from C19 hospitalizations and ICU admissions. It’s also evident that deaths are being reallocated to C19 from other natural causes, as this chart from The Ethical Skeptic shows (compare the bright line for 2020 to the (very) dim but tightly clustered baselines from prior years):

Second, most of the charts for Europe (not Sweden) show a late summer escalation in cases, though cases in Spain and Germany appear to have crested already. If an uptrend in deaths is to follow, it should become noticeable soon. Thus far, the wave certainly looks less threatening. 

Finally, it’s noteworthy that Sweden’s early experience, which was plagued by mismanagement of the virus’ threat to the nursing home population, later transitioned to a dramatic fading of cases and deaths. There has been no late summer wave in Sweden as we’ve seen elsewhere. This despite Sweden’s far less stringent non-pharmaceutical interventions (NPIs). Sweden’s deaths per million of population are now less than in the US, the UK, Italy, Spain, and Belgium, and most of those differences are growing.

All of the other countries discussed above have had far more stringent lockdown policies than Sweden, and at far greater economic cost. The following charts show some cross-country comparisons of an Oxford University index of NPI stringency over time. It combines a number of different dimensions of NPIs, such as mask mandates, restrictions on public gatherings, and school closures. The first chart below shows the U.S. and the UK contrasted with Sweden. The other countries discussed above are shown in separate charts that follow. 

In the U.S., there has been tremendous variation across states in terms of stringency due to the federalist approach required by the U.S. Constitution, but overall, the Oxford measure for the U.S. has been broadly similar to the UK over time, with the largest departures from one another at the start of the pandemic.   

   

The stringency of NPIs over the full pandemic depends on their day-by-day strength as well as their duration at various levels. One could measure stringency indices and deaths at various points in time and produce all kinds of conflicting results as to the efficacy of NPIs. On the whole, however, these charts suggest that stringent NPIs hold no particular advantage except perhaps as a way to temporarily avoid overwhelming the health care system. Even the original “flatten the curve” argument acknowledged that the virus could not be avoided indefinitely at a reasonable cost via NPIs, especially in an otherwise free society.

Note that most of these countries eased their NPIs after the initial wave in the spring, but several remained far more stringent than Sweden’s policies. That did not prevent the second wave of cases, though again, those were far less deadly.

As Jacob Sullum writes, and what is increasingly clear to honest observers: lockdowns tend to be ineffective and even destructive over lengthy periods.

A working paper from the National Bureau of Economic Research finds that four different “stylized facts” about the growth in C19 deaths are consistent across countries and states having different policy responses to the virus. The authors say:

“… failing to account for these four stylized facts may result in overstating the importance of policy mandated [non-pharmaceutical interventions] for shaping the progression of this deadly pandemic.“

Here’s Bill Blain’s discussion of the inefficacy of lockdowns. And here is Donald Luskin’s summary of his firm’s research that appeared in the WSJ, which likewise casts extreme doubt on the wisdom of stringent NPIs.

The virus is far from gone, but this summer’s wave has been much more docile in both Europe and the U.S. There are reasons to think that subsequent waves will be dampened in many areas via the cumulative immunity gained from exposure thus far, not to mention improvements in treatment and knowledge regarding prophylaxis such as Vitamin D supplements. Government authorities and their public health advisors should dispense with the pretense that stringent NPIs can mitigate the impact of the virus at a reasonable cost. These measures are constitutionally flawed, impinge on basic freedoms, and look increasingly like government failure. Risk mitigation should be practiced by those who are either vulnerable or fearful, but for most people, particularly children and people of working age, those risks no longer appear to be much worse than a bad year for influenza.