The Land of the Free Shows it’s Time to Lose the Lockdowns

The Land of the Free Shows it’s Time to Lose the Lockdowns

WILL JONES for Lockdown Sceptics

No surge as schools open in the UK, no surge as Texas throws off restrictions, free states like Florida and Georgia doing no worse than lockdown states – is anyone in Government watching the real world or are they too busy gawping at the curves of Neil Ferguson’s latest model?

Jeffrey A. Tucker at AIER has gathered together some of the alarmist predictions made about Texas that have, so far, not come to pass:

  • California Governor Gavin Newsom said that opening Texas was “absolutely reckless.”
  • Vanity Fair went over the top with this headline: “Republican Governors Celebrate COVID Anniversary With Bold Plan to Kill Another 500,000 Americans.”
  • There was the inevitable Dr. Fauci: “It just is inexplicable why you would want to pull back now.”
  • Robert Francis “Beto” O’Rourke of Texas revealed himself to be a full-blown lockdowner: It’s a “big mistake,” he said. “It’s hard to escape the conclusion that it’s also a cult of death.” He accused the Governor of “sacrificing the lives of our fellow Texans… for political gain.”
  • James Hamblin, a doctor and writer for the Atlanticsaid in a Tweet liked by 20K people: “Ending precautions now is like entering the last miles of a marathon and taking off your shoes and eating several hot dogs.”
  • Bestselling author Kurt Eichenwald flipped out: “Goddamn. Texas already has FIVE variants that have turned up: Britain, South Africa, Brazil, New York & CA. The NY and CA variants could weaken vaccine effectiveness. And now idiot @GregAbbott_TX throws open the state.” He further called the Government “murderous.”
  • Epidemiologist Whitney Robinson wrote: “I feel genuinely sad. There are people who are going to get sick and die bc of avoidable infections they get in the next few weeks. It’s demoralising.”
  • Virus guru Michael Osterholm told CNN: “We’re walking into the mouth of the monster. We simply are.”
  • Joe Biden famously said that the Texas decision to open reflected “Neanderthal thinking”.
  • The chairman of the state’s Democratic Party said: “What Abbott is doing is extraordinarily dangerous. This will kill Texans. Our country’s infectious-disease specialists have warned that we should not put our guard down, even as we make progress towards vaccinations. Abbott doesn’t care.”
  • The CDC’s Rochelle Walensky didn’t mince words: “Please hear me clearly: At this level of cases with variants spreading, we stand to completely lose the hard-earned ground we have gained. I am really worried about reports that more states are rolling back the exact public health measures we have recommended to protect people from COVID-19.”

Are any of these experts and commentators now reconsidering their fundamental assumptions and examining the data? What do you think?

The coronavirus has certainly surprised many of us in the past year, defying expectations by being more deadly in Europe and North and South America than it was in South East Asia, while in Africa and India it surprised by its mildness.

The lazy mainstream assumption that the differences between countries are explained primarily by their restrictions or interventions has not been borne out by any of the studies that have examined the real world data rather than relying on models that bake-in assumptions of lockdown efficacy.

One of those studies, by eminent Stanford scientists Jay Bhattacharya (co-author of the Great Barrington Declaration), John Ioannidis and colleagues, published in the European Journal of Clinical Investigation, has come under criticism since it was published at the start of January. The authors have now responded to that criticism, defending their paper in the journal.

It includes some great quotations from these two pillars of the sceptic movement:

Some suggest that New Zealand’s effective control can be ascribed to its highly restrictive lockdowns. 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.

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.

They did admit to one mistake – which actually made their case stronger:

We note that, by mistake, we cumulated the case counts for the Netherlands twice. Correcting this, the trend for the Netherlands points more strongly to enhanced case spread with more restrictive measures (0.08 (0.00-0.17) versus Sweden and 0.13 (-0.11-0.37) versus South Korea.

They do not think much of the models popular among lockdowners, which typically beg the question by assuming what they are trying to prove:

An underlying theme in the letters is that COVID-19’s epidemic trajectories have been difficult to characterise, and have traced trajectories that often seem disconnected from the policies aimed at modifying these trajectories. … The past year has revealed puzzling patterns of epidemic dynamics that have defied models that attribute much epidemic control to policies. At the time of this writing, cases and deaths are declining across most locations, despite models’ predictions to the contrary.

This points to a more generalised and pernicious challenge: how should NPI [non-pharmaceutical intervention] effects be studied? Simulation models are clearly problematic because their results are a direct function of input assumptions. Observational studies, especially using causal inference methods, have advantages. However, when the underlying dynamics are non-linear and the policies are deeply endogenous, as in this case, attribution is precarious. This limitation is shared by all observational assessments of NPI effects.

They conclude that the scientific literature does not support the use of lockdowns, the harms of which are known and large, whereas the benefits are unproven and, on current evidence, weak-to-non-existent.

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.

Worth reading in full, as is Jeffrey Tucker’s piece in AIER on Texas and the open states.


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