A State of Fear: How the UK government weaponised fear during the Covid-19 pandemic, Laura Dodsworth [the two towers ebook .txt] 📗

Journalists, politicians and pundits state that lockdowns work, as though it is undisputed fact. As a result, politicians tighten and loosen the lockdown screws at will. There is no serious opposition. How have lockdowns become the new orthodoxy, when they were never recommended before 2020 and there was no evidence that they worked? Rather than opposition to the evidential and conceptual framework for lockdown, the problem, as defined by the political opposition, and Boris Johnson himself, is that we didn’t lock down ‘earlier and harder’.8 We appear to be doubling down on false assumptions.

Regardless, lockdowns cannot be judged solely according to whether they avert death and illness from one virus. If we put aside all consideration of the acceptable reach of government and the imposition on our liberty, there are economic, social and health costs caused by lockdown. The government has shied away from a quantitative assessment of the policy, presumably because the numbers just would not stack up. Civitas9 produced a report using the standard UK government and NHS’s QALY (Quality Adjusted Life Years) calculations and found that the cost per QALY saved ranged from £96,000 to £1.97 million, depending on how successful lockdowns might have been (and the assumptions in the report are quite generous). To contextualise this, the NHS’s upper limit is £30,000 per QALY.

But did lockdowns save lives?

Deaths in England and Wales peaked on 8 April 2020, which (given the lag between infection and death), implies that infections peaked and started to decrease before the lockdown on 23 March. This has been acknowledged by Chief Medical Officer Chris Whitty, who said that the R-number was decreasing before the national lockdown.10 This has been attributed to both voluntary behaviour changes and to the natural bell curve of a virus.

Simon Wood, a professor of statistics at the University of Edinburgh, wrote for The Spectator that ‘although the estimated fatal infections were in retreat before each lockdown, the daily deaths were surging each time that a lockdown was called. The psychological pressure that this puts on the decision makers is obvious.’11 This is very plausible – when the pressure is at its worst, politicians are under greater pressure to ‘pull a lever’, to do something to slow transmission. Less generously, the lockdowns also happen to have been timed to almost be credited with declines which had just begun.

It feels counterintuitive that restrictions do not limit the spread and death toll of coronavirus in the way that the Imperial model expected. However, there are now 34 studies and analyses which show that lockdowns do not work, with countries and states with fewer or no restrictions frequently outperforming countries and states with some of the most strict lockdowns. The American Institute for Economic Research12 has listed and summarised the 34 reports, which would be an ideal resource for those interested in learning more.

In the interest of balance, I should say that the WHO published an article13 on 31 December 2020 which said ‘large scale physical distancing measures and movement restrictions, often referred to as “lockdowns”, can slow COVID-19 transmission by limiting contact between people’. It did not link to any evidence supporting this, but I have collated a few papers which find evidence in favour of lockdowns in the endnotes.14

Assessing mandatory stay-at-home and business closure effects on the spread of COVID-19,15 from academics at Stanford University, concluded: ‘in summary, we fail to find strong evidence supporting a role for more restrictive NPIs in the control of COVID in early 2020. We do not question the role of all public health interventions, or of coordinated communications about the epidemic, but we fail to find an additional benefit of stay-at-home orders and business closures. The data cannot fully exclude the possibility of some benefits. However, even if they exist, these benefits may not match the numerous harms of these aggressive measures. More targeted public health interventions that more effectively reduce transmissions may be important for future epidemic control without the harms of highly restrictive measures.’16

Oxford University’s Centre for Evidence-Based Medicine (CEBM) analysed excess mortality for 2020 across 32 countries. They used excess mortality instead of ‘Covid deaths’, to avoid problems with recording and classification of deaths and they used age-adjusted mortality to take into account differences in the average age of populations. It’s a simple matter to look at the table and see that excess mortality does not obviously correlate with the severity of lockdowns.

To highlight one example, Sweden is often cited as a counter-factual to the UK’s policies because it did not impose strict lockdown measures throughout the year. It kept all retail and hospitality and most schools open and imposed no restrictions on private gatherings. According to CEBM, Sweden only had a 1.5% increase in age-adjusted mortality. England and Wales, with the strictest lockdown in the developed world, saw a 10.5% increase in age-adjusted mortality.

Johan Carlson, Director of the Public Health Agency of Sweden, said: ‘Some believed that it was possible to eliminate disease transmission by shutting down society. We did not believe that and we have been proven right.’17

How does the Imperial modelling handle this counter-factual? Interestingly, as Simon Woods noted in The Spectator, ‘to accommodate this anomaly their model treats the final March intervention in Sweden (shutting colleges and upper years secondary schools) as if it was lockdown. As many others have pointed out, that’s a strange way to model the set of data that most directly suggests that lockdown might not have been essential.’18

As economist David Paton pointed out in his article ‘The myth of our “late” lockdown’,19 the November national lockdown in England ‘had no observable impact on hospitalisations or deaths at all. And although both have fallen very significantly over the past couple of months, all the indicators tell us that infections were decreasing well before the third national lockdown in January, even in regions not already placed in the highest Tier 4 restriction level.’ Often, proponents of lockdowns do not take the time lag between infections and hospitalisations and deaths