Lockdowns Historically Failed

The word “lockdown” was unfamiliar to most of us until March 2020. The rising tide of Covid-19 cases that month prompted public health officials to advocate a lockdown for “fifteen days to slow the spread” as it was promoted. Now, nearly two years later, it seems a good time, if somewhat belated, to evaluate why that course was chosen and how effective it was in containing the virus.

Phillip W. Magness and Peter C. Earle give us a good history of the effectiveness of lockdowns in an article published in The Wall Street Journal. Before March 2020, the mainstream scientific community, including the World Health Organization, strongly opposed lockdowns and similar measures against infectious disease. Those conclusions came from historical analysis of pandemics and an awareness that society wide restrictions have severe socioeconomic costs and almost entirely speculative benefits. Our pandemic response, premised on lockdowns and closely related “non-pharmaceutical interventions,” or NPIs, represented an unprecedented and unjustified shift in scientific opinion from where it stood a few months before the discovery of Covid-19.

Just a year before in March 2019, WHO held a conference in Hong Kong to consider NPI measures against pandemic influenza. The WHO team evaluated a quarantine proposal – “home confinement of non-ill contacts of a person with proven or suspected influenza” – less indiscriminate than the Covid lockdowns. They called attention to the lack of data to support such a policy, noting that “most of the currently available evidence on the effectiveness of quarantine on influenza control was drawn from simulation studies, which have a low strength of evidence.” The WHO issued a statement that large-scale home quarantine was “not recommended because there is no obvious rationale for this measure.”

The conclusions of the WHO were supported by a September 2019 report from Johns Hopkins University Center for Health Security. They stated, “In the context of a high-impact respiratory pathogen, quarantine may be the least likely NPI to be effective in controlling the spread due to high transmissibility.” This was especially true of a fast-spreading airborne virus.

Where did they come up with these conclusions? The Covid-19 pandemic is certainly not the first, or the last, pandemic to spread throughout the world. Perhaps the greatest, though tragic, experience came with the Spanish flu pandemic of 1918. In 2006, the WHO issued a report following their study of this pandemic and concluded “forced isolation and quarantine are ineffective and impractical.” In particular, they referenced the example of Edmonton, Alberta, where “public meetings were banned; schools, churches, colleges, theaters, and other public gathering places were closed; and business hours were restricted without obvious impact on the epidemic.” Using data from a 1927 analysis of the Spanish flu in the U.S., the study concluded that lockdowns were “not demonstrably effective in urban areas.”

It is precisely in urban areas where we have seen the greatest emphasis on lockdowns, especially in New York and Los Angeles.

Medical historian, John Barry, who wrote the standard account of the 1918 Spanish flu, concurred about the ineffectiveness of lockdowns. “Historical data clearly demonstrate that quarantine does not work unless it is absolutely rigid and complete.” This statement comes from a report in 2009, summarizing the results of a study of influenza outbreaks on U.S. Army bases during World War I. Of 120 training camps that experienced outbreaks, 99 imposed on-base quarantines and 21 did not. Case rates between the two categories of camps showed “no statistical difference.” Barry concluded, “If a military camp cannot be successfully quarantined in wartime, it is highly unlikely a civilian community can be quarantined during peacetime.”

This begs the question why lockdowns were promoted in March, 2020. Even the once heralded, but now embattled, Dr. Anthony Fauci questioned the wisdom of lockdowns in January, 2020. When the Wuhan region of China imposed harsh restrictions on January 23, 2020, Fauci said, “That’s something that I don’t think we could possibly do in the United States. I can’t imagine shutting down New York or Los Angeles. Historically, when you shut things down, it doesn’t have a major effect.”

It seems the blame for the lockdowns that began in March, 2020, falls at the feet of the Imperial College London. In April, 2020, the journal Nature credited the Imperial team, led by Neil Ferguson, with developing one of the main computer simulations “driving the world’s responses to Covid-19.” The New York Times described it as the report that “jarred the U.S. and the U.K. into action.”

After predicting catastrophic casualty rates for an “unmitigated” pandemic, Ferguson’s model promised to bring Covid-19 under control through increasingly severe NPI policies, leading to event cancellations, school and business closures, and ultimately lockdowns. Ferguson produced his model by recycling a decades-old influenza model that was noticeably deficient in tis scientific assumptions. For one thing, it lacked a means of even estimating viral spread in nursing homes.

Magness and Earle say the record of Mr. Ferguson’s previous models should have been a warning. In 2001 he predicted that mad cow disease would kill up to 136,000 people in the U.K., chastising conservative estimates of only 10,000. The actual death toll by 2018 was only 178. He also miscalculated predictions of catastrophes for mad sheep disease, avian flu and swine flu that never panned out.

These authors calculated the performance of Imperial’s Covid-19 predictions in 189 different countries at the first anniversary of their publication, March 26, 2021. Not a single country reached the predicted mortality rates of their “unmitigated spread” or even the “mitigation model” – the latter premised on social-distancing measures similar to what many governments enacted. For example, Imperial predicted up to 42,473 Covid deaths in Sweden under mitigation and 84,777 under uncontrolled spread. The country, which famously refused to lock down, had some 13,400 deaths in the first year.

All of this should be a warning to those who would impose lockdowns again, in the face of rising case numbers, but not deaths, from the new Omicron variant. By now it should be clear to everyone that “following the science” does not mean lockdowns.


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