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“Death and Lockdowns”

Flavio Bartmann points to this post by John Tierney criticizing lockdown policies for coronavirus, which begins:

Now that the 2020 figures have been properly tallied, there’s still no convincing evidence that strict lockdowns reduced the death toll from Covid-19. But one effect is clear: more deaths from other causes, especially among the young and middle-aged, minorities, and the less affluent.

The best gauge of the pandemic’s impact is what statisticians call “excess mortality,” which compares the overall number of deaths with the total in previous years. That measure rose among older Americans because of Covid-19, but it rose at an even sharper rate among people aged 15 to 54, and most of those excess deaths were not attributed to the virus.

I have not looked at the 2020 figures myself, but I’ll take Tierney’s word on this until informed otherwise.

I have mixed feelings about the above-linked post. The general points seem reasonable–in a pandemic, the optimal level of social and economic activity is not zero; it’s somewhere between zero and the status quo. But, as in much discussion of this sort, I think he underestimates the role of individual behavior. “Lockdown” is not a thing in itself. At some points he gets close to this realization as when he says that Sweden didn’t have a lockdown but the people in Sweden took sensible precautions. Lockdowns can be viewed as a solution to a coordination problem.

Tierney quotes someone as saying lockdowns are “the single worst public health mistake in the last 100 years.” That’s pretty ridiculous, no? I mean, really, at this point I wanted to stop right there and say: Hey, you’re a reporter, right? Push back on that silly quote! Let’s inject some sanity into this discussion, ok? On the other hand, I agree that things have sometimes gone too far, like when they removed the nets from the local basketball courts this past spring.

Ini summary, I agree with some of what is said in that post but I don’t like the one-sided polemical tone. I guess the author would argue that a polemic is necessary given extreme statements on the other side, and maybe he’s right, but I still don’t like it. There’s been a lot of research on the effects of lockdowns etc., and he seems to only link to one side of the story. If he wants to disagree with studies whose conclusions differ from where he stands, that’s fine, but I’d prefer to see him engage with the debate rather than just give link after link from one side. This can be seen from the article’s subtitle: “There’s no proof that lockdowns save lives but plenty of evidence that they end them.” You could flip this around: “There’s no proof that lockdowns end lives but plenty of evidence that they save them.” The point is, there’s no proof of anything here but there’s plenty of evidence on both sides. So I find the article frustrating, even if I also find the author’s own frustration understandable. Exaggeration has a role in political and even in scientific debate but I don’t have to like it.

P.S. Commenter Brian points to this post from someone called Gideon MK that seems much more thoughtful and reasonable. Unfortunately, “thoughtful and reasonable” is not always what gets the attention.

81 Comments

  1. Michael Weissman says:

    Tierney does his usual.

    On the one hand really hard evidence: “Researchers predicted that the social and economic upheaval would lead to tens of thousands of “deaths of despair” “
    On the other hand you just have “Some researchers reported early in the pandemic that lockdowns slowed viral spread and reduced mortality, but those conclusions were based on mathematical models …”
    Quite a contrast.

    Then you have the contrast between on the one hand a model that over-predicted Swedish death totals and on the other hand the far more reliable Bhattacharya, according to whose reassuring IFR calculations only slightly more than 100% of the US has had Covid.

  2. Joshua says:

    > But preliminary reports point to some obvious lockdown-related factors. There was a sharp decline in visits to emergency rooms and an increase in fatal heart attacks due to failure to receive prompt treatment.

    This is the same crap we’ve seen all along. I.e., we don’t actually know what the effect would have been on emergency room visits had there been no interventions. There’s evidence suggesting it might have been no better, or even worse if there were no interventions to reduce the rate of spread of the virus.

    It’s just more of a clear reluctance to think probabilistically. Instead, people just rely on a theoretical counterfactual assumption (in this case emergency visits would have been better absent interventions) without realizing they’re doing so. It’s just straight up and simplistic conflation of correlation and causation.

    That’s not to say that these aren’t important questions to interrogate – or that assumptions should be made in the other direction. But I do find it depressing that so many people engage in such facile analysis – usually in service of an (often not intentional) ideological agenda.

    • Joshua says:

      The aspect that’s been bugging me the most lately is that the “lockdown death” crowd NEVER takes into account the fact that the precipitating conditions where the strongest interventions were implemented would be predictive of comparatively worse outcomes, and thus just trying to reverse engineer from a comparison of outcomes to evaluate the efficacy of interventions just makes no sense without controlling for the precipitating conditions.

      And why don’t people see the importance of controlling for confounds when they compare outcimes in different localities to assess emtge efficacy of interventions?

      This just seems to me like basic epidemiology, and basic logic for that matter. Yet we see not only armchair epidemiologists but renown epidemiogists making these fundamental errors. As much as I have gotten used to the ubiquity of motivated reasoning, it’s still depressing to see it so often manifest in how people look at COVID.

      • kj says:

        Many people only see confounds when the data isn’t in their favor.

        The “lockdowns kill” crowd gladly compare Sweden to hard hit countries, but argue confounds prevent comparing it against Norway or Finland.

        The “lockdowns save” crowd happily compared California to Florida until the last couple months when California mostly caught up in per capita deaths. Now they note confounds. Similar phenomena with US vs Europe.

        • Joshua says:

          jk –

          I agree. Watching how many people flip on confounding variables is almost like a sport. And often people ignore the ideological orientation associated with how confounds are handled, as if they think the near uniform direction of association with ideology is just a coincidence.

        • Georgette says:

          I think a lot of the debate on social issues is really a debate on confounding and when to take it into account. California and Florida can’t be compared despite their similarity as destinations for vacationers and re-location.

      • Meg says:

        Yeah… I find it difficult to take anyone seriously if they don’t mention the fact that early on one of the major reasons lockdowns were undertaken was because there was not going to be enough space and staff to take care of people in hospitals. Not JUST people with Covid but anyone else who needed to be taken care of in a hospital.

        This was not a theoretical issue. It was an issue that came up every day in the hospital my husband worked at. And his ID group saw the problem coming in January and by February they had worked with the critical care department to convince the hospital system they should reschedule elective procedures in preparation for saving room for all sorts of critically ill patients. They changed staffing for several groups, ramped up availability of locum tenens healthcare workers, cancelled vacation for full time employees, reduced office hours for any groups that also worked in the hospital.

        The ability of some patients to get seek preventative care was reduced for a few
        months. By the summer, they had brought things back to normal (mostly).

        There may be increased mortality in the long term due to delayed diagnoses, but the vast majority of the excess mortality of 2020 is due to Covid-19. Some of it due to direct mortality in people who were never tested, and some due to people who could not get emergency medical treatment. The lock down didn’t CAUSE the inability of people to get emergency treatment. It was an effort to make it possible for people to still have access to that treatment.

        The probable covid deaths include people who died of non-respiratory causes (strokes (ischemic and hemorrhagic), clots in vital organs)) as well as respiratory causes. One hallmark of covid is patients satting very low but not feeling short of breath. Those situations cause people to delay contacting emergency services or doctors offices, sometimes too long to ever contact them.

        And comparing the US to any country with universal health care is basically a non-starter. There is absolutely no way to know how people’s choices for seeking care are affected when many people in the US don’t have access to healthcare outside of an emergency room. And those emergency rooms were often overfilled housing patients with covid for days because there wasn’t room for them anywhere else in the hospital.

        The article offers no evidence of things that could only have been driven by lockdowns as increasing over previous years. If that data were credibly offered all we could say is that X number of people died because of lockdowns. And then you could try to estimate whether that was bigger than the probable minimum number of deaths prevented (by decreasing number of people who died as a direct result of covid, or decreasing the demand for medical services to below the supply). If you can’t estimate at least one of those numbers you can’t say anything at all about how BAD lockdowns were.

        I honestly don’t think people either appreciated how dire the situation was in hospitals for months at a time, or if they did, they have forgotten.

        • Paul Flusk says:

          Meg, you miss out a key point. Human behaviour would have changed the moment individuals were refused healthcare treatment on a capacity basis. The issue I have with Covid response – that a false sense of security was generated amongst highly vulnerable categories, accounting for the majority of deaths.

          If triage had been widely publicised, CEV individuals would have treated leaving their home as an absolute last resort.

          Lockdowns were excessive, for one reason. It was never “whole population” activity that was the problem. It was intergenerational mixing. You can see this from pretty much every Christian/Catholic country in the world around Christmas time.

          The UK now was over 50% of its under 25 cohort modelled as having been infected. This group has seen fewer than 20 deaths, of around 19 million UK infections so far.

          Hospital situations were dire, because they admitted people for treatment that had little hope of survival, whilst cancelling elective for those with a very good chance of survival. What is required is a mindset change amongst medical practitioners that in times of a pandemic, there is x resource (which in most nations, is provided wholly by economic activity, which requires protecting as much as the population’s health). if pandemic requirement y exceeds x, then losses amongst dry tinder (built up by effective flu vaccination programmes) are going to have to happen.

    • Michael J says:

      > Instead, people just rely on a theoretical counterfactual assumption (in this case emergency visits would have been better absent interventions) without realizing they’re doing so.

      I agree. This happens a lot and is not specific to covid, to the extent that I think this should be considered a zombie. If there’s one thing about causal inference that I wished was emphasized and taught more widely is that an effect of an intervention is defined with respect to a counterfactual, so being precise about what that counterfactual is is essential. Using a strawman counterfactual does no good.

  3. Emilio Lobato says:

    On the other hand, there’s this scientific research: https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwab062/6169297

    Sheltering In Place and The Likelihood Of Non-Natural Death
    Ralph Catalano, M Maria Glymour, Yea-Hung Chen, Kirsten Bibbins-Domingo

    Abstract
    Increasing hospitalizations for COVID-19 in the United States (US) and elsewhere have ignited debate over whether to reinstate shelter-in-place policies adopted early in the pandemic to slow the spread of infection. The debate includes claims that sheltering in place influences deaths unrelated to infection or other natural causes. Testing this claim should improve the benefit/cost accounting that informs choice on reimposing sheltering in place. We use time-series methods to compare weekly non-natural deaths in California to those in Florida. California was the first state to begin, and among the last to end, sheltering in place while sheltering began later and ended earlier in Florida. During weeks when California had shelter-in-place orders in effect, but Florida did not, the odds that a non-natural death occurred in California rather than Florida were 14.4% below expected levels. Sheltering-in-place policies likely reduce mortality from mechanisms unrelated to infection or other natural causes of death.

  4. paul alper says:

    From Wikipedia
    https://en.wikipedia.org/wiki/John_Tierney_%28journalist%29

    “His 1996 article “Recycling Is Garbage” broke the New York Times Magazine’s hate mail record and was praised by libertarians for bringing “libertarian ideas to America’s big-government bible”.[13] Critics complained that in the article he quoted “not a single representative of the recycling industry”, but did cite the head of “an environmental consulting business for hire to solid waste companies”.[12] In a 2001 column, Tierney cited a study suggesting that global warming would boost the U.S. economy.[12]”

  5. Flavio Bartmann says:

    A comparative analysis is needed. The effects of the lockdowns depend on how strictly they are enforced and complied with. In places such as South Korea, China, and New Zealand they worked and the result was an almost complete elimination of the disease and the number of deaths (comparatively) exceedingly small. In the US, Western Europe, and Latin America there was strong resistance to the lockdowns and widespread non-compliance. Not surprisingly, the number of deaths was high and everyone extremely frustrated.

    • Joshua says:

      Imo, it’s meaningless to try to evaluate the efficacy of “lockdowns” by comparing countries like South Korea or Taiwan to the US or western Europe by comparing outcomes if you don’t control for factors like testing and tracing and isolating, or mask-wearing, or the timing of implementation and relaxation of interventions, or rates of international travel (particularly to/from hotspots early on), or age profiles or availability to work at home or access to healthcare or baseline health/comorbidities, SES and race/ethnicity, etc.

      Compliance certainly seems important but to say it depends “strictly on how they’re enforced” is far too simplistic, imo.

      • Steve says:

        +1 Plus, nations like New Zealand didn’t really lock dow. They quarantined specific groups when needed. If you let the virus spread for months as we did to the point where you have hundreds of thousands of infected, you can’t really quarantine other than telling people to “shelter in place” with no real enforcement. We should retire the word “lock down”. It doesn’t mean anything. And, people have to stop making comparisions between different periods of the exponential growth of the virus. A policy that could have a huge impact at the beginning of an outbreak could be worthless after the virus has reach a certain level of spread.

      • confused says:

        …or the fact that Taiwan and New Zealand are islands and South Korea effectively is (its only land border is rather impassable).

        The non-scientific “story” I see is that strict measures work *if you are relatively isolated and catch it fairly early* (Taiwan, NZ, South Korea, Australia, Iceland), but if the virus was already everywhere it doesn’t do much (there seems no clear relationship between US states’ measures and death rates).

        On the other hand – death rates in the Old World tropics seem to be much lower than the New World tropics, across different types of governments, huge wealth/resources disparities, etc. I haven’t seen a convincing explanation why. So it’s also conceivable that South Korea etc. had an easier problem for some reason.

        I think New Zealand and Iceland still support the general “story” though.

  6. Steve says:

    The CDC estimates 597,097 excess deaths in the US in 2020, with 526,028 were attributable to COVID. How much of those 71,065 non-COVID excess deaths can actually be attributed to various so-called lock-down policies? And, of course, how many lives were saved by those policies (or simply by people limiting their interactions on their own)?. Certainly, more than 71,065. I will never understand the mentality of those at the start of this pandemic that just refused take it seriously. They now want to rewrite history and argue that the real problem was the lock downs. There is unequivocal evidence from Taiwan, Japan, Australia, New Zealand, that there was a way to keep infection rates low and continue to keep economies functioning. Actually quarantining those infected and exposed. Quarantining whole buildings or neighborhoods.

    • Kyle C says:

      Fox News created this narrative by repeating it day after day after day from the start. Lockdown liberals would kill people with their foolishness. Now a lot of people genuinely remember the history that way.

    • AllanC says:

      TL;DR no opinion on your apparent main point but your comparison is found wanting.

      I don’t have much of an opinion of the majority of your post or what I take to be your main point. However, the comparison of deaths you make is a rather unsophisticated one. What needs to be compared is the net reduction in quality of life for all those currently on this planet, which includes things such as an additional year locked up with an abusive partner, etc. Even if you want to dismiss the ideal as unattainable (it is hard to calculate without significant subjective assessments of value), at the very least you want to compare years lost, which is not the same thing as current deaths. For example, those not being screened for cancer as a result of the lockdowns have, as an average group, an expected decrease in loss of life because early detection was not possible for some non-trivial subset of them. And it appears to me that a rational person would want to take such things into account when discussing outcomes (is it an outcome of the policies in place? Yes. Is it an important outcome? Yes. Therefore, it should be taken into account) Moreover, you have other issues with taking death tallies as they come, such as comorbidity.

      • Phil says:

        AllanC,
        Sure, you’ve gotta take into account all of those things you say…but on the other side, you have to estimate what would have happened _without_ ‘lockdowns’, however they are defined. How many deaths would there have been, how many businesses would have failed, etc. etc. It’s not like, absent the lockdowns, people would have continued business as usual. To give a specific example, ascribing all of the excess heart attack deaths to the lockdowns is ridiculous: people were avoiding hospitals because they thought if they went to the hospital they might get COVID, it’s not like hospitals weren’t admitting heart attack victims.

        And of course, you’re right that counting lives and deaths is not sufficient, you also have to count quality-of-life problems…but that cuts the other way too: when characterizing what would have happened in the absence of lockdowns, don’t just count deaths, also count the other negative effects of COVID infections.

        • AllanC says:

          I agree! Which is why I used the term “net” to indicate that the relevant characteristics in the counterfactual also need to be estimated. This is by no means an easy task though I surmise not impossible. That said, I would suspect much simplification is required that only allows us to get so close to the ideal; and even then, the large inherent error may make the comparison a moot exercise.

          The reason for my comment was that Steve was employing a poor, un-caveated comparison as support for his particular view. I feel it to be a bit dishonest to make a foolish comparison and act (with much apparent vigor) like it demonstrates something credible.

          In general, I think the lockdowns (or apparent lockdowns) have been net beneficial. Without question many things could have been done better the world over. But who am I to judge people making decisions under such uncertainty, at such rapid pace, and at such scale? I think the world has actually done fairly well here and that is encouraging.

          • Phil says:

            Quantifying what actually happened is a tall order but we can certainly try it: how many women were beaten by their domestic partners, how many children are traumatized in this way or that way, and so on.

            But quantifying what would have happened in the absence of the lockdowns…it’s not that we can’t try to do that but this requires a model of what would have happened under the counterfactual scenario (which would first have to be defined, of course. If state and local governments hadn’t done ‘lockdowns’ do we assume they would have passed no COVID-related regulations whatsoever? Or what, exactly?). I’m not even sure there are current models that can be adjusted to do decent hindcasting to ‘predict’ what actually happened, much less to predict what would have happened under whatever non-lockdown scenarios we might define.

            So…I don’t disagree with what you (AllanC) are saying — the net effect of the COVID response cannot be measured in excess deaths alone, and years of life lost would probably be a better or at least coequal measure as deaths anyway — but I _also_ agree with Steve’s point that it’s ridiculous to suggest (as some people do) that if we just hadn’t done those darn lockdowns the pandemic wouldn’t have been a big deal.

            • mpledger says:

              But there are good things that happened in lockdown too. People worked from home and recovered the hours that they would use in commuting. People used the excess time for cooking healthier food, doing more low impact exercise (e.g. walking) and spending time crafting.

              While there were couples in lockdown who had back outcomes what about all the couples who had positive outcomes? Those who took pleasure in being able to spend more time with their partner.

            • confused says:

              Yeah – it depends hugely on what would have actually happened.

              I mean, one can argue that if 200 million people in the US lose 25% of their quality of life for 1 year, that’s 50 million “effective years of life”, which if the average loss from a COVID death is say 10 years, that’s equivalent to 5 million avoided COVID deaths – clearly impossible.

              But how much less would the “lack of quality of life” have been in an “official advice is to ignore COVID” scenario? How much would fear have driven behavior?

    • Anoneuoid says:

      I will never understand the mentality of those at the start of this pandemic that just refused take it seriously.

      WHO continues to advise against the application of travel or trade restrictions to countries experiencing COVID-19 outbreaks.

      https://www.who.int/news-room/articles-detail/updated-who-recommendations-for-international-traffic-in-relation-to-covid-19-outbreak

      Would you like to see more quotes like this?

      • Phil says:

        There’s plenty of stuff in those recommendations that is clearly wrong, but I see no evidence that the WHO wasn’t taking the pandemic seriously. Quite the contrary:

        They emphasize “Control measures that focus on prevention, particularly through regular hand washing and cough hygiene, and on active surveillance for the early detection and isolation of cases, the rapid identification and close monitoring of persons in contacts with cases, and the rapid access to clinical care, particularly for severe cases.”

        Also “Travellers returning from affected areas should self-monitor for symptoms for 14 days and follow national protocols of receiving countries.”

        And “For countries which decide to repatriate nationals from affected areas, they should consider the following to avoid further spread of COVID-19: exit screening shortly before flight; risk communication to travellers and crew; infection control supplies for voyage; crew preparedness for possibility of sick passenger in flight; entry screening on arrival and close follow-up for 14 days after arrival.”

        “Countries should intensify surveillance for unusual outbreaks of influenza-like illness and severe pneumonia and monitor carefully the evolution of COVID-19 outbreaks, reinforcing epidemiological surveillance.”

        All the nonsense about not interfering with international trade is kind of offensive, but I’m sure this is not what Steve was referring to when he talks about people not taking the pandemic seriously. Also, that document is from the end of February, which, yeah, was late enough that they should have known better, but eventually even the WHO came around to talking sense on this stuff, whereas there are people who are _still_ in denial a year later.

        • Anoneuoid says:

          There’s plenty of stuff in those recommendations that is clearly wrong, but I see no evidence that the WHO wasn’t taking the pandemic seriously.

          At the time I was prepping and setting up backup solar systems because it looked so bad based on the information available. So, I was taking it seriously. They were not.

          • dhogaza says:

            “At the time I was prepping and setting up backup solar systems…”

            How many planets in your backup solar system and what did you use for the sun?

            Sorry, couldn’t help myself, can’t be serious all the time :)

          • Anonymous says:

            Maybe you were taking it seriously on February 29 but by March 6 your conclusion what that it really wasn’t very scary and by March 29 you claimed there wasn’t a single official datapoint indicating there was a real problem due to this virus.

            • Anoneuoid says:

              Correct. As soon as the data came out showing it was not very bad I switched to not being concerned. That is exactly when the media started making a big deal out of it and created the hysteria that lead to putting everyone on ventilators to fill up the ICUs for weeks with low survival rate, sending covid patients into nursing homes, etc.

              Keep listening to the same people.

              • Anoneuoid says:

                We observed an abundance of patients admitted to hospital within 7 days of vaccination (Figure 3). Discussed below are potential reasons for this trend in admissions:

                • Most vaccinated hospitalised patients were infected shortly before or around the time of vaccination, and the remainder after vaccination but before immunity had developed (immunization).

                • Elderly and vulnerable people who had been shielding, may have inadvertently been exposed and infected either through the end-to-end process of vaccination, or shortly after vaccination through behavioural changes where they wrongly assume they are immune.

                • An additional hypothesis, that we cannot exclude in this analysis, is that some people had recent asymptomatic COVID-19 and vaccination precipitated admission. Previously asymptomatic or paucisymptomatic PCR positive patients may experience symptoms likened to COVID-19 symptoms including fever due to vaccination. This happens within 48 hours of the vaccination and usually resolves within 48 hours [1].

                https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/973183/S1143_Hospitalised_vaccinated_patients_during_the_second_wave__2_.pdf

                Wow, this data shows 10x higher risk of hospitalized covid in the week after vaccination than before. And they still don’t mention the lymhocytopenia.

  7. Yariv says:

    “That measure rose among older Americans because of Covid-19, but it rose at an even sharper rate among people aged 15 to 54, and most of those excess deaths were not attributed to the virus.”

    People aged 15 to 54 normally don’t die all that much, so “an even sharper rate” probably just comes from dividing by a smaller denominator.

    there’s also this paragraph the piece,
    “When statisticians at the Centers for Disease Control totaled the excess deaths for age groups through the end of September, they reported that the sharpest change—an increase of 26.5 percent—occurred among Americans aged 25 to 44.”

    But if you follow the link, you find that Americans ages 25 to 44 were dying at about 10% higher rates in Jan-Feb 2020 (Fig 2 of that link). Insidious things, these lockdowns, reaching back through space and time to kill all these people before they were even instituted.

  8. Michael Weissman says:

    Tierney downplays the difference between Sweden and other Nordic countries that took stronger official measures.
    Current total deaths/100k and increase rate:
    Sweden 128 0.2
    Denmark 41 ~0.02
    Norway 15 ~0.02
    Finland 12 ~0.02.

    He makes the point that the other Nordics didn’t keep their strong measures in place indefinitely but eased up when they could. True- and that was a big reason for strong measures early, to allow easing up later.

  9. JFA says:

    I couldn’t confirm his numbers on excess deaths for 15-54 year-olds. That’s an interesting way to slice the data, and the restricted use files might contain the necessary information to compute those numbers. The public-use files for excess deaths from the CDC group the ages as “under 25 years”, “25-44”, “45-64”, “65-74”, “75-84”, and “85 years and older”. The under 25 group had little change from the baseline. If he wanted to do his own analysis, he could look at excess deaths grouped by some definition of lock down by state. I could not access the reference he uses for data on 15-54 year-olds. The abstract says that the analysis looks at excess deaths from March to May, but Tierney says it looked at March to November and proceeds to give numbers that wouldn’t make sense for a March to May analysis. That letter concludes: “Further research is needed to assess the cause of such excess deaths and introduce safeguards to reduce such deaths in the future.” So I’m not really quite sure how to interpret Tierney’s interpretation.

    Note that excess deaths (in all age groups except for under 25) started rising in March (with the initial wave). Many of the non-Covid causes of deaths Tierney wants to use to explain the non-Covid causes of death would not have that kind of immediate impact. The sources he references for specific non-covid causes of deaths do not segment their analyses by age or wouldn’t affect the 15-54 year-old age group. He points to increased heart attack deaths (which could very well have been induced by Covid as there is evidence that Covid can have detrimental effects on the circulatory system) but the reference doesn’t break down the data by age (except for noting the mean (standard deviation) age for the data they analyze was 68 (13), so most of the individuals covered in the data are not in the age group he is concerned about). Then he points to reductions in cancer screenings. That could certainly have detrimental impacts in the future, but it is unlikely to cause a huge contemporary spike in the number of deaths. Then he points to increased dementia deaths… not too many 15-54 year-olds with dementia.

    He points to increased vehicle deaths, but it’s a leap to say those were *caused* by lock downs, except for people engaging in (i.e CHOOSING) riskier behavior on emptier roads. I think the most interesting data point is on deaths from overdose but that is made in passing (even though that’s where you’d expect to see the most immediate impact of non-Covid causes of death). A quick check of gun deaths finds that preliminary data suggest around 41,500 gun deaths in 2020 while 2019 saw about 40,000. If you think the pandemic would cause an huge increase in suicides, you’d expect to see a large increase in deaths from firearms since most suicides use guns (and about half of gun deaths are suicides). Tierney claims there are 34,000 excess deaths in the 15-54 year old age group between March and November. I just don’t see any of his explanations making up much of his claimed non-Covid excess deaths.

    When referencing county level death data, he suggests low and minority houses were disproportionately affected by lock. The reference says this, “Excess deaths not assigned to Covid-19 were even higher than predicted by our model in counties with high income inequality, low homeownership, and high percentages of Black residents, showing a pattern related to socioeconomic disadvantage and structural racism.” This says nothing about lockdowns. Georgia, with lots of counties with high income inequality and high percentages of black residents, wasn’t in lock down for most of last year.

    As you noted, much of this probably would have occurred due to people’s behavioral changes. He doesn’t mention that the financial situation of many people did not deteriorate that much. Until the end of the summer (through which time the excess deaths in the 25-44 age category remained elevated), anyone unemployed received very generous benefits (some even making more money once unemployed); the use of pawn shops tanked; and consumer spending by low-income households recovered to January 2020 levels by June of 2020 (according to research by Raj Chetty). Certainly there is heterogeneity, but the data don’t present a straight forward narrative of massive economic hardship that would lead to an massive increase in deaths of despair.

    Even when some states opened up at the beginning of May, there wasn’t an immediate increase in economic activity. I have no doubt that some of the increase in non-Covid deaths are due to how society responded to Covid… and maybe a subset of that is due to lockdown measures, but Tierney’s piece is a hot mess of data being interpreted in a very one-sided way.

  10. Joshua says:

    The popular gambit these days is to not refer to total deaths but “excess deaths” (which is less useful than “P-scores”) But he downplays the differences with that metric in the Nordics, with a bland “hasn’t done as well” description.

    https://ourworldindata.org/grapher/excess-mortality-p-scores

    -snip-

    Preliminary data from EU statistics agency Eurostat compiled by Reuters showed Sweden had 7.7% more deaths in 2020 than its average for the preceding four years. Countries that opted for several periods of strict lockdowns, such as Spain and Belgium, had so-called excess mortality of 18.1% and 16.2% respectively.

    Twenty-one of the 30 countries with available statistics had higher excess mortality than Sweden. However, Sweden did much worse than its Nordic neighbours, with Denmark registering just 1.5% excess mortality and Finland 1.0%. Norway had no excess mortality at all in 2020.

    • Joshua says:

      https://www.reuters.com/article/us-health-coronavirus-europe-mortality-idUSKBN2BG1R9

      Plus, the “dry tinder” theory loses steam once you start evaluating the 2nd and 3rd waves in Sweden – as even if you think the “dry tinder” theory has explanatory power, it would have some kind of a limit and lose salience over time as more people died. Deaths rates in Sweden are still much higher than in the other Nordics after a much higher death rate for more than a year. How much “dry tinder” is there?

      And, he tries to hide the pea – when he argues that the areas in Sweden hit hard early weren’t hit hard later. Stockholm was hit the hardest in all three waves.

      Each of his points can be similarly deconstructed. It’s just cherry-picking and bad faith reasoning all the way down.

      • Dzhaughn says:

        Plenty of dry trinder, in the theory. Any death counting without adjusting for population vulnerability is suspect. Age adjustment is a crude proxy for this.

        Try this: I would bet a reasonable amount that, in the USA and Europe, we will see substantially decreased deaths from pneumonia in the next few years. Thanks (but no thanks) to COVID.

        Biden should launch the National Pneumonia Awareness Program now and point to its fantastic results in 3 years. If only it didn’t take 3 years to get the website up…

        • Joshua says:

          But equating “vulnerability” to flu deaths the previous year is questionable. There could be many factors that correlate with vulnerability. For example, lower deaths from flu in previous years could actually be predictive of lower deaths from COVID this year because it means that the healthcare facilities are better equipped to deal with respiratory viruses.

          There was a study which showed, looking over a longer term period, that flu deaths from the year previous were not predictive of excess deaths in Sweden krrlarivr to other Nordics) – but longer term tends were, and and would predict a lower death rate from COVID in Sweden.

          I tried looking for the link but can’t seem to find it again.

  11. >Tierney quotes someone as saying lockdowns are “the single worst public health mistake in the last 100 years.” That’s pretty ridiculous, no? I mean, really, at this point I wanted to stop right there and say: Hey, you’re a reporter, right? Push back on that silly quote! Let’s inject some sanity into this discussion, ok?

    Is it so ridiculous? I mean you don’t have to agree, but I feel like the variance on “effects of lockdowns” has to be pretty high given how many areas of life they affect. All else equal, high variance means that the probability of them being the “single best public health success” is higher than it would be with lower variance, but the probability of them being the “single worst public health mistake” is also higher than it would be with lower variance. I can’t think of a single public health policy with a wider reach than lockdowns; it doesn’t have to be too bad per person to be in sum the single worst public health mistake if we take an utilitarian perspective.

    Then again, if you restrict to trivialities like “removing nets from basketball fields” the variance won’t seem as high. “Trying hard to socially isolate young people”, on the other hand, could end up causing some real damage or it could end up just fine; it’s high variance.

    • Joshua says:

      > . I can’t think of a single public health policy with a wider reach than lockdowns;

      How do you know yhe variance is high? Maybe they had little differential effect.

      Here’s what Tierney says:

      > There’s still no proof that lockdowns save any lives—let alone enough to compensate for the lives they end.

      As Andrew discussed above, “proof” is an unrealistic standard here, and saying that it should be required in this context suggests to me ignorance of risk assessment in the face of high uncertainty, and I would guess (not that I understand much about Bayesian probability), not particularly Bayesian.

    • Matt Skaggs says:

      “Is it so ridiculous? I mean you don’t have to agree, but I feel like the variance on “effects of lockdowns” has to be pretty high given how many areas of life they affect.”

      That’s not why it is ridiculous. It is ridiculous because of Thalidomide.

    • Andrew says:

      Matty:

      First, I don’t think that removing nets from basketball courts is trivial. I mean, sure, that’s just one thing, but the big picture was an active discouragement of people going outside, along with cops wasting their time policing the playgrounds rather than fighting crime.

      Second, here are a few public health policies with major malign effects I can think of during the past century: promotion of cigarette smoking, meat-and-dairy-heavy dietary recommendations, subsidies for sugary processed food, subsidies for driving/parking/etc., overuse of antibiotics in animal feed, allowing the essentially unrestricted promotion of oxycontin, not outlawing leaded gasoline earlier. . . I have a feeling we could come up with a bunch more with much bigger and clearer negative effects than lockdowns.

      • @Andrew: sure, removing nets from basketball courts isn’t trivial in some sense, but in another sense it pales in comparison to the kind of of restrictions there have been in other places. In China, people were locked into their houses by force. In Europe, people were punished just for being outside their house even during the day, talk about wasting police resources there. Dying people have had to die alone because hospitals were not allowed to let in their families. Lots of young, single people living alone went a little crazy during the lockdown, hopefully this didn’t push them into an unhealthy equilibrium. There has been all kinds of suffering associated to lockdowns. Maybe the US has just been much better at this than most places, but most places have had very repressive lockdowns with really harsh effects. Then there have been all kinds of weird second order effects like “increase in government debt” or “businesses failing” that have an unclear relationship to lockdowns; as are the second order effects from normalizing heavy handed responses like lockdowns. I’m not saying I’m sure the effects are large, but I’m saying they might be; i.e. the variance on this is very high.

        Your examples are mostly US-centric, also from a philosophical perspective “not outlawing X when it should have been outlawed” seems like morally it isn’t as bad as “outlawing Y when it should have been allowed”; the same goes for “promotion” and “recommendation”. So this is really not as clear to me as it is to you; I guess “all kinds of restrictions for a year” is hard to compare with “slightly more people smoke” in terms of its effects.

        • Joshua says:

          Matty –

          > “not outlawing X when it should have been outlawed” seems like morally it isn’t as bad as “outlawing Y when it should have been allowed”;

          Why? I’m guessing that certainly we could both create scenarios where you wouldn’t apply that maxim.

          • Joshua: I don’t think we could, but it’s really a question of moral/logical axioms so there’s no use having a discussion over it. I guess Huemer’s “In Praise of Passivity” is a good read if you’re interested in these kinds of philosophical questions – http://www.owl232.net/papers/passivity.htm

            • Joshua says:

              Well you may well be right about differing axiomatic “priors…

              But for my clarification…

              Locality A doesn’t outlaw murder and has an
              anomalously high murder rate.

              Locality B fines people 50 bucks for not wearing masks in stores when evidence later shows conclusively that wearing masks does nothing to prevent infections.

              Is that a fair example? If so, does the maxim still apply?

              And while an exchange might be pointless from the perspective of reaching agreement or changing viewpoints, I’d still be interested in reading why you think the maxim is universally valid (if that is what you’re saying).

  12. MJM-WA says:

    As a non-statistician who follows this blog for Andrew’s posts and the insightful discussions, I often find myself wondering how to then think about the subject under discussion. One of the lengthier and more involved comments above practically had me convinced that we should continue the lockdowns and the transfer payments since they really do seem to be helping as opposed to inflicting any damage on the country. But my take away is instead that while we can poke at statements made by writers like Tierney in an article such as he has written, we need to nevertheless step back and ask what we think of how the points all fit together… and what we think of the thesis under discussion.
    This is a quite educational discussion which isn’t surprising since his blog has a very well-informed audience!

    • Anoneuoid says:

      You need to ask the stats people why poverty and stress were long held to lead to substantially shorter lifespan but the hysteria (not just lockdowns) is always assumed to have no effect.

      I personally know someone who basically stopped leaving their house to this day and had seizures from anxiety meds, and another person who threw out their back by stretching after hiding in their home for months.

      What research has there been on this?

      • Joshua says:

        > but the hysteria (not just lockdowns) is always assumed to have no effect.

        Always? Really?

        • Anoneuoid says:

          Please share it if it exists.

          • Joshua says:

            How do you know what anyone “assumes,” let alone what everyone assumes all the time?

            You really need to let us in on your secret mind-reading methodology.

            • Anoneuoid says:

              By default an effect is assumed zero. That is the same as not including it in the model.

              If you know of a paper that doesn’t do this please share it.

              • AllanC says:

                I am partial to your conjecture that people tend to think of non-measured variables as if they have no effect, which is the reason for their non-collection. However, it is plausible that things are sometimes thought to be important but measurement rather intractable, so they do not incorporate those things into the model. In which case non-inclusion is not indicative of an assumed lack of effect but an inability to measure to a reasonable standard.

                Though in the latter circumstance one would think proper scientific reporting to dictate those potentially important non-measured variables be highlighted explicitly. But not everyone adheres to that…space limitations, etc. Consequently, just because it is not discussed does not mean people did not think about it or think it important; and so I reject your conjecture that if it is not talked about or incorporated it is assumed to be a zero effect by the researcher. To be clear I am making a distinction between assumed by the researcher and assumed by the model (I take your comments to refer to the researcher and not the model but feel free to clarify if I have that wrong).

                That said, if something seems rather easily measured and is not included in a study, then on the balance of probabilities, I think that indicative of the researchers assuming non-importance (or at the very least ignorance of potential importance).

              • Anoneuoid says:

                I’m not referring to any internal thought process. That is a strawman Joshua made up.

                I’m referring to the actual models that estimate deaths due to covid.

                Obviously we implicitly round assumed negligible factors to zero all the time. That is fine… unless there is huge literature saying it is not negligible, which is the case here.

              • Joshua says:

                Anoneuoid –

                > but the hysteria (not just lockdowns) is always assumed to have no effect.

                In line with AllanC’s response…

                This logic implies that *everyone* assumes that *all parameters* not included in *all models* are *always* “assumed” to have no effect.

                Once again, you don’t actually know what people do and don’t assume.

              • Andrew says:

                Anon and Joshua:

                Enough, again! Please make your points once and then stop. Otherwise this is cluttering our comments section.

              • Joshua says:

                AllanC –

                > I am partial to your conjecture that people tend to think of non-measured variables as if they have no effect,

                I would guess that every few modelers “assume” that stress related to something like a pandemic has no material impact on public health outcomes.

                But the rest of your comment nicely summarizes my main point…and I would say that this part

                > “or at the very least ignorance of potential importance” is an important caveat – with the important added on caveat that sometimes “ignorance” is a subjectively defined qualification. Sometimes not everyone agrees as to what’s important.

              • Joshua says:

                Done.

      • dhogaza says:

        “I personally know someone who basically stopped leaving their house to this day and had seizures from anxiety meds, and another person who threw out their back by stretching after hiding in their home for months.”

        It’s unclear why “hiding on one’s home” would cause someone to throw out their back by stretching.

        But speaking of anecdotal evidence, five people in my extended social circle have died of covid-19, the youngest 24.

        I’ll have to admit, though, that they are no longer at risk of throwing out their backs.

      • dhogaza says:

        “You need to ask the stats people why poverty and stress were long held to lead to substantially shorter lifespan but the hysteria (not just lockdowns) is always assumed to have no effect.”

        What an interesting comment. You mention press-driven hysteria over and over again, and suggest that the press should just shut up about covid.

        But, seriously, do you think the stress level suffered by health care workers was just “hysteria”, driven by the press? Do you think that was somehow going to be kept secret? How about the stress of watching a loved one slowly die? And the fear of catching it yourself after seeing the effects in your community? Is this “hysteria”, driven by the press?

        People’s fears weren’t without reason, you know.

        And, frankly, I’ve not seen any hysteria where I live. Concern, yes. A willingness to take recommended public health measures, yes. Hysteria, now.

        Your hyperbole doesn’t really help your argument, IMO, whatever it is you think you’re trying to argue for.

    • YGW says:

      Can you link to a comment with lockdown effects analysis, you’ve mentioned?

    • Christian Hennig says:

      Well, the first things to acknowledge are that (a) lockdowns help (stopping the spreading of the virus – as somebody living in Italy and seeing over a year how numbers always go down where there are “red zones” with many zone changes of regions now as “sample size” – though not independent of course – no doubt about this), and (b) lockdowns do inflict damage (as is obvious to everyone as well). A balance has to be struck, and of course depending on where people stand determines where they prefer to do that. One-sided accounts like the linked one, and the big number of people who over there seem to agree with it, are really sad to see.

  13. Brian says:

    I thought this article from epidemiologist Gideon M.K. is a balanced post on the topic that actually looks at the evidence. I don’t think we can expect much from a writer like John Tierney.

    https://gidmk.medium.com/what-are-the-negative-effects-of-covid-19-lockdowns-8f77dddf19bb

  14. Francois says:

    To Andrew:

    If you don’t recall, the Dr. who’s being quoted is one of the coauthors of the dubious IFR studies out of Stanford you criticized back last year.

  15. There are at least 3 obvious problems here:

    1) Various countries with strict lockdowns had negative excess deaths, meaning that less people died than usual; that runs counter to what one would expect if lockdowns were a source of a net increase in deaths.
    2) Lockdowns can limit non-COVID-19 deaths as well, such as automobile deaths, childhood mortality, etc.
    3) The evidence does not show suicide rates increase in response to lockdowns.

    So I’m unimpressed by Tierney’s article, especially since it’s posted on City Journal, a website known for peddling politically-motivated denialism on topics such as climate science. So it’s surprising to see them do the same on COVID-19 to suit their right-wing agenda.

    Anyway, sources below for those who want to learn more on the 3 points above:

    “Cross-country comparisons of COVID-19: Policy, politics and the price of life”
    “Impact of COVID-19 lockdown policy on homicide, suicide, and motor vehicle deaths in Peru”
    “Sheltering in place and the likelihood of non-natural death”
    “A comparison of COVID-19 epidemiological indicators in Sweden, Norway, Denmark, and Finland”
    Not peer-reviewed: “The World Mortality Dataset: Tracking excess mortality across countries during the COVID-19 pandemic”
    Not peer-reviewed: “The effectiveness of lockdowns: Learning from the Swedish experience” ( http://archive.is/yo5Ac#selection-985.0-985.268 )
    Non-peer-reviewed: “Do lockdowns bring about additional mortality benefits or costs? Evidence based on death records from 300 million Chinese people”

    https://gidmk.medium.com/what-are-the-negative-effects-of-covid-19-lockdowns-8f77dddf19bb [with: https://twitter.com/GidMK/status/1371045429232631810 ]
    https://data.cdc.gov/NCHS/Monthly-Counts-of-Deaths-by-Select-Causes-2020-202/9dzk-mvmi
    [with: https://twitter.com/tylerblack32/status/1367239480130740224 ]
    https://twitter.com/CovidSerology/status/1295627931910156288 [ https://twitter.com/CovidSerology/status/1292385837104025601 ]
    https://twitter.com/jburnmurdoch/status/1354158357754601472
    https://www.bloomberg.com/opinion/articles/2020-09-17/child-mortality-covid-19-lockdowns-may-have-saved-kids-lives
    https://twitter.com/GidMK/status/1336493616097681412

  16. MarkD says:

    Beside summary pointed by @Brian, orth a read of Bendavid/Ioannidis et al’s response letter to critiques on a study already discussed also in this blog https://onlinelibrary.wiley.com/doi/pdf/10.1111/eci.13553

    Also a look at Ioannidis’ sum up here “Epidémiologie du COVID-19 : les preuves, les risques et les malentendus” https://www.youtube.com/watch?v=8KzZXvT1g-k

    Note the ‘dry-tiner’ paper linked by Tierney is the “16 Possible Factors …” which discusses more broadley the differences between Sweden and its nordic neighbours and links the specific study https://hectordrummond.com/2020/08/22/covid-19-excess-deaths-dry-tinder-and-the-winter-deaths-seesaw/. Yes they hoped for no 2nd wave, but check overall vs 1st vs 2nd -wave numbers e.g. here https://www.lavoce.info/archives/71653/covid-19-numeri-senza-spiegazione/

    For Asia vs ‘west’, note there are also virus’ and population’s genetics at play https://www.nature.com/articles/s41419-020-02995-9 https://faseb.onlinelibrary.wiley.com/doi/10.1096/fj.202002097 https://f1000research.com/articles/10-196/v1 https://www.medrxiv.org/content/10.1101/2020.11.22.20236414v1

    ‘Hard’ vs ‘Soft’ -lockdown is a complex issue with short and long terms effects – what works at small scale may be disruptive at large scale e.g. https://voxeu.org/article/how-economic-effects-covid-19-lockdowns-different-regions-interact-through-supply-chains – here they’re trying to track the downsides https://collateralglobal.org/research – which derailed from the epidemiology tracks much into the political and moral realms, e.g. https://www.medrxiv.org/content/10.1101/2021.01.11.21249549v1 https://phys.org/news/2020-06-politics-pandemics-countries.html https://pubmed.ncbi.nlm.nih.gov/33546144/ https://www.otago.ac.nz/news/news/releases/otago758988.html https://www.politico.eu/article/coronavirus-pandemic-eu-rule-of-law-report/ not to mention the vaccine diplomacy.

    (sorry for no/bad formatting – wish there’s a preview …)

    • Joshua says:

      MarkD –

      This is quite remarkable:

      > In contrast to the suggestions in the letters, we left countries such as Denmark and New Zealand out not because they would demonstrate patterns that would support the role of restrictive measures, but exactly because the paltry spread of COVID-19 in these countries would prevent learning anything meaningful about the role of NPIs in these countries.2

      We anticipated separability challenges in identifying any nonpharmaceutical intervention’s (NPI) effect when analyzing changes in growth rates from a baseline of little (or, in many subnational units, no) growth. In our regression framework, no NPI would likely show a meaningful effect in Denmark or New Zealand where case growth rate was low, both before and after NPIs were implemented (hence no meaningful changes in case growth). We could have noted ex ante that we selected countries with more meaningful virus spread, though we do note that “Additional countries could provide more evidence, especially
      countries that had meaningful epidemic penetration.”

      For countries like New Zealand with tepid epidemic growth, it is statistically and intuitively apparent that teasing apart which, among all the measures implemented, had worked is impossible. Viral entry and spread in New Zealand was limited relative to the US, and more amenable to control. Less restrictive NPIs may well have been sufficient to maintain epidemic control. Some suggest that New Zealand’s effective control can be ascribed to its highly restrictive lockdowns.5

      That opinion, unfortunately, has no evidence to support it beyond the anecdotal. As of March 2021, the highest
      death rates globally have occurred in countries that used prolonged and very restrictive measures, while the lowest death rates occurred in countries with more diverse responses. This is of course no proof of the futility of lockdowns, but it does call into question any claims of a much-worse counterfactual with less restrictive measures.

      -snip-

      So they will exclude NZ and Den because they had low rates of infection prior to NPIs initiated, but include countries with high rates of infection prior to initiation of NPIs, w/o controlling for the differential impact of the prior rates of spread when analyzing the efficacy of interventions across countries.

      Sure, there’s a logic that you can’t disaggregate the impact of the different NPI measures of there’s no freakin’ virus, but instead of acknowledging that’s a structural problem with their analysis, they double down by treating the effect of prior conditions selectively.
      It’s like a parody.

      Also, I managed to sit through a small portion of that video. It’s like the Tierney piece in its one-sidedness. But I had to give up when he spoke about the Danish RCT on masks, and described how the authors had a hard time publishing and saying it’s because people “didn’t like” the findings… Such a twisted way to reference a touchstone of the anti-masking crowd (I see many people saying that the Danish study “proves masks don’t work”), where the anti-maskers routinely ignore important aspects of the RCT: it could only tell if masks had a greater than 50% effect, it couldn’t tell anything about masks as source control, it was underpowered, and obviously it should be taken with a grain of salt anyway because of the inability to control for factors like compliance.

      Ioannidis’ advocacy and willingness to embrace the inane one-sided rhetoric is one of the more remarkable features of the pandemic.

      • MarkD says:

        “Experience from past pandemics has shown vast differences in disease spread across different locations, irrespective of measures taken, and we are seeing the same variability with COVID-19. Ignoring these plain-to-see epidemiologic patterns is a disservice to public health and society. In terms of country selection, our analysis examines 4 countries more than the analysis after which it is fashioned (1.7x) and 2 countries less than a prominent, but problematic, modeling study of lockdown effects (0.8x).6–9 We invite any researchers to add countries to our analysis: we made all the code available in large part for this exact reason.”

        and

        “The issue of lags and timing seems to be a common concern, but makes no difference to the findings or interpretation. The timing of each NPI in each subnational unit of each country is explicitly modeled in the variables. Introducing a lag does not alter any of the principal 𝑃𝑜𝑙𝑖𝑐𝑦𝑝𝑐𝑖𝑡findings: those findings are driven by the similarity in the growth patterns of case counts between the compared countries, irrespective of any lags. We invite the letter-writers (and others) to introduce sensible lags into the statistical models and re-run the analyses (code and data are publicly available).”

        so anyone can double-check their approach with a set of countries of choice.

        E.g. others (with their own approach) https://www.medrxiv.org/content/10.1101/2021.02.11.21251580v2 concluded that

        “Mandatory shelter-in-place policies were associated with 3 to 4 fold lower population adjusted mortality in the US model and 11 fold lower in the European one. We conclude that voluntary policies are less effective, based on historical precedent and the current analysis.”

        where (for EU)

        “In Europe, we compared Norway’s mandatory shelter-in-place policy to Sweden’s voluntary one.”

        Of course the ‘Swedish difference’ has both praisers e.g. https://spectrum.ieee.org/biomedical/ethics/dont-be-too-quick-to-judge-swedens-covid19-policy and detractors, e.g. https://spectrum.ieee.org/tech-talk/biomedical/ethics/swedens-actual-covid-policy-herd-immunity

        Bendavid at al’s conclusion isn’t a clear-cut advocacy of full laissez-faire, rather a concern for more-harm-than-good in the broader scope:

        “In all, we maintain that the science plausibly supports beneficial, null, or harmful impacts on epidemic outcomes of highly restrictive measures, such as mandatory stay-at-home and business closures. Given their many uncontestable harms to health and society, we believe that the extant literature does not provide strong support for their effectiveness at reducing case spread, and should be subjected to careful, critical, and rigorous evaluation. If the benefits of such measures are negligible (or worse), their perpetuation may be, on balance, detrimental to the health of the public.”

        Positing that hard-lockdown / stay-at-home orders / universal-masking mandates are paramount to address pandemics regardless of personal freedoms & rights is a slippery slope (for current democracies of course) – e.g. see https://www.europarl.europa.eu/doceo/document/TA-9-2020-0307_EN.html https://read.dukeupress.edu/jhppl/article-abstract/45/6/997/165294/Democracy-Capacity-and-Coercion-in-Pandemic (paywall,just the abstract) besides previous links.

        • Joshua says:

          MarkD –

          > Given their many uncontestable harms to health and society,

          So there it is again. This statements rests on a presumed counterfactual, without even a cursory acknowledgement of that situation. Is it “uncontestable” that there are “many harms” *caused* by highly restrictive measures? Sure, if you make some blanket counterfactual assumptions.

          During their media campaigns they sometimes attempt to extend their counterfactual to say that “precision shielding” would be more beneficial. Well of course if we could fully protect the most vulnerable the outcomes would have been better. But given that there are huge numbers of vulnerable people, and that effectively isolating them would necessarily be very difficult and very expensive and disruptive in many ways and undoubtedly have unintended consequences, such a blanket hand-wave to “precision shielding” looks to me like just extending the facile counterfactual assumption problem.

          > If the benefits of such measures are negligible (or worse), their perpetuation may be, on balance, detrimental to the health of the public.”

          I recently saw a Jordan Peterson clip where he said that (paraphrasing) he suspects that if you did the statistics properly that medicine, “independently of public health” (whatever that means), kills more people than it saves. Overall the net consequences of hospitals is negative. It’s just a guess and of course it could be wrong. But it could also could not be wrong.

          This is meaningless crap. Except that it’s malignant meaningless crap. And it’s being targeted to a specific audience with tangible consequences.

          > “The issue of lags and timing seems to be a common concern, but makes no difference to the findings or interpretation. The timing of each NPI in each subnational unit of each country is explicitly modeled in the variables.

          IMO – comparing across nations to determine the efficacy of interventions is a fundamentally flawed model – particularly when, as in their case, they select inputs to the model in a way that will necessarily skew the outcomes. Now they are renown epidemiologists and very smart and I”m just an Internet schlub, but it seems to me that if you want to assess the efficacy of NPIs, you need to look longitudinally within given countries and compare trends before to after the interventions were implemented. Of course, even there you’re going to have confounding factors, but I think they’d be reduced significantly as compared to cross-country comparisons.

          > Positing that hard-lockdown / stay-at-home orders / universal-masking mandates are paramount to address pandemics regardless of personal freedoms & rights is a slippery slope (for current democracies of course)

          Sure, everyone likes a slippery slope argument. Positing that governments have no role in limiting the spread of a pandemic, and consequently placing no limits on reckless and irresponsible members of society disregarding risk and infecting others, is a slippery slope.

      • dhogaza says:

        “In contrast to the suggestions in the letters, we left countries such as Denmark and New Zealand out not because they would demonstrate patterns that would support the role of restrictive measures, but exactly because the paltry spread of COVID-19 in these countries would prevent learning anything meaningful about the role of NPIs in these countries.”

        And yet they approve of the very flawed (if you accept what the lead author himself says about it) Danish study regarding masks because they interpret it as proving that this particular NPI doesn’t work?

        • MarkD says:

          “A new, good-quality, open-label trial of 6024 community-dwelling adults in Denmark evaluated the effects of wearing a surgical mask outside of the house, at a time when mask wearing in the community was neither recommended nor common.”
          https://www.acpjournals.org/doi/full/10.7326/L20-1429

          that’d be the ‘very flawed’ DANMASK-19 according to you. Yet it’s deemed enough here to up the level of evidence from ‘insufficent’ to ‘low’ for any mask use versus nonuse in community settings (I was a bit baffled given the conclusion there: “… Although the difference observed was not statistically significant, the 95% CIs are compatible with a 46% reduction to a 23% increase in infection. … The data were compatible with lesser degrees of self-protection.”)
          Seems many have a strong stance on these matters out of personal beliefs such that also stats get creative reinterpretation https://www.bmj.com/content/371/bmj.m4586/rr-7
          Ok, as long as it doesn’t creep into law.

      • Howard Edwards says:

        “In our regression framework, no NPI would likely show a meaningful effect in Denmark or New Zealand where case growth rate was low, both before and after NPIs were implemented (hence no meaningful changes in case growth).”

        There’s a graph of NZ Covid cases between late March and early May 2020 which uses government data at

        https://thespinoff.co.nz/society/10-05-2020/covid-19-live-updates-may-10-two-new-cases/

        NZ went into a heavy lockdown on March 25 2020 – no meaningful change huh?

        By the way – is the Manhattan Institute for Policy Research (MI) called “a leading free-market think tank” because the concept of thinking has tanked altogether?

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