The release of Matt Hancock’s WhatsApp messages in the ‘Lockdown files’ has been an eye-opener for many who are now realising that government policy-making during the pandemic was at the mercy of a small cabal who felt they knew best and who were more concerned about their reputations than the health and wellbeing of the population. Effective policy-making must weigh scientific evidence and balance it against other societal and economic considerations but the ‘Lockdown files’ have laid bare the fact that political advantage and points scoring were really the main drivers of behaviour for much of the pandemic.

As one example, consider the controversial issue of mask-wearing, where the WhatsApp messages reveal that masks in schools were introduced to avoid an argument with Nicola Sturgeon, with no consideration of the potential harms of this intervention. This is an outrage, particularly, as a Department for Education report last year suggested that mask-wearing, surely unsurprisingly, had significantly increased anxiety in marginalised and vulnerable students.

Some might think that the ‘Lockdown files’ are yesterday’s news, but policy continues to be made on the legacy of the political decisions taken during the pandemic. Just a couple of months ago, when you might have thought it was safe to return to ‘normal’ life after the Covid years, we were being asked to wear face masks again, with the aim of protecting the NHS. Reinforcing the political nature of the policy response to the pandemic, the mask debate was framed in The Guardian as being tantamount to a culture war. It is not, it is a debate about evidence and how to appraise it.

We are not experts in the ability of masks to reduce airborne virus transmission, but we know enough about human psychology and behaviour to know that none of us can assess any evidence without bringing a prior set of beliefs and biases to it. We have written previously that the academy suffered from an extraordinary degree of ‘group-think’ during the pandemic, leading to a remarkable consensus about the measures that should be taken to deal with the spread of Covid.

The group-think has many explanations, but fear is the one that has been robustly shown to determine beliefs and influence judgments. The ‘Lockdown files’ confirm that fear was used deliberately to ‘scare the pants of us’ to enhance compliance with the rules and restrictions. Interventions that are effective in reducing risks would help to mitigate these fears, and so scared people will have a natural, and largely unconscious, predisposition to interpreting the data on interventions in ways that support their effectiveness.

We contend that this has happened in the case of face masks. Many academics have interpreted the very weak mixed, messy, and inconclusive evidence in a way that suggests that masks work because they would feel better if they did. But no behaviour sits in a vacuum and people respond to wearing a mask in a host of sometimes unpredictable ways that make it extremely difficult to properly account for the effectiveness of masks in the community. We need more and better data, of course, and an updated Cochrane Collaboration Systematic review including the effectiveness of mask-wearing suggests that they do not do much at all, if anything, to prevent illness for Covid-type diseases. But we also need procedures for overcoming the biases that all of us bring to bear on any issue.

Adversarial collaboration, whereby people whose prior beliefs differ work together on a research question, is one well-established but rarely used way of doing this. Those who would feel better if masks did work should work with those who would feel better if masks did not work. We could then have more faith that the conclusions would be more fact-based than value driven. Adversarial collaboration is predicated on us being honest about our prior beliefs – and to agree that we should seek to capture all the possible ripple effects of any policy as well as the immediate consequences of dropping a policy pebble into the pond of human experience.

This means that it would be nowhere near enough to determine the effectiveness of masks in reducing transmission risks to recommend their use. To do so would be to fall into the kind of ‘situational blindness’ we witnessed throughout the pandemic, whereby we focus only on virus risks at the exclusion of everything else individuals and society care about. We would therefore also need to know whether face coverings affect the development of young children, interaction with vulnerable populations, the civic participation of deaf people, and so much more besides in an inclusive society.

We admit that our prior beliefs are to care much more about these effects than any possible effects of masks on reducing virus risks. We are open to collaborating with the many academics and practitioners out there who feel differently to us. In this way, we can more properly and accurately estimate the full range of costs and benefits of masks or any other policy intervention. Evidence on the facts of the matter can never resolve the value judgments about whose costs and benefits matter most but it can serve to flush out the various trade-offs that we are willing to make in policy-making.

Policy-makers should also be open to different views, voices, and interpretations of the evidence. We are left wondering why those in power felt that policy-making in a such haphazard, biased, and ill-informed manner through WhatsApp messaging was an acceptable way to manage the pandemic response. Through adversarial collaboration and other processes of decision-making, such as committees made up of more diverse interests and expertise, we must ensure that better processes are in urgently put in place for the next health, economic and social crisis that will surely present itself before too long.

Source – https://www.spectator.com.au/2023/03/masking-science-with-politics-in-the-covid-era/