Prince William and his wife Catherine visit Clitheroe Community Hospital (Photo by James Glossop / POOL / AFP)

There’s no case for mask mandates

We cannot trust models based on bogus assumptions

Artillery Row

In June this year, Smile Free (a group opposed to mask mandates) wrote an open letter to the NHS chief executives of England, Scotland, Wales and Northern Ireland. The missive — signed by over 2,000 medical and healthcare professionals — called for the lifting of the “requirement” for all staff, patients and visitors to wear a face covering in NHS venues. Citing the most robust sources of scientific evidence from randomised controlled trials in real-world settings, the letter highlighted both the ineffectiveness of masks as a viral barrier; and the potential physical, social and psychological harms associated with their use. Scotland and Wales responded promptly — their attempts to justify their decisions to impose mask requirements in healthcare settings were critiqued in a previous article. Now NHS England has spoken, defending its endorsement of mass masking primarily on the basis of computer modelling.

Inaccurate prophecies spooked Western governments into lockdowns

In a letter dated 4 October 2022, Dame Ruth May (Chief Nursing Officer and national lead for infection control), responding on behalf of Amanda Pritchard (NHS England chief executive), asserted that there was “strong” evidence that widespread use of face coverings achieved a “significant impact” on the prevention of covid-19 transmission. To support this premise she cited a computational modelling study, posted in October 2021. This pre-print paper reported that, based on its model, “universal masking” would achieve a 46 per cent reduction in infections among healthcare workers. Given the substantial amount of robust scientific evidence available, aggregating around the conclusion that — in the real world — masks constitute an ineffective viral barrier, it is astonishing that NHS England is relying on a modelling study to justify its blanket policies. 

There appears to be little recognition of the inauspicious legacy of the epidemiologist, Professor Neil Ferguson. In collaboration with his colleagues at Imperial College London, Ferguson deployed computer modelling to predict the doomsday scenarios of COVID killing 2.2 million Americans and 500,000 people in the UK. Such inaccurate prophecies were largely responsible for spooking Western governments into lockdowns, an unprecedented public-health policy that has led to extensive collateral harms. Now healthcare chiefs are citing a similar modelling study as a key reason for persisting with mask recommendations in our hospitals, health centres and GP practices.

An initial glance at the study highlighted in the NHS England response is sufficient to reveal that it falls well short of an evidential bar that would justify imposing masks on healthy people. As a pre-print paper, it has not been peer reviewed, and it comes with an explicit cautionary note at the beginning of the article that, “it should not be considered conclusive, used to inform clinical practice or referenced by the media as validated information”. Within the body of the article, there are further warnings about the dubious reliability of its findings — for example, references to its reported outcomes as “highly uncertain”. 

Face coverings achieve no appreciable reduction in the transmission of respiratory viruses

Ferguson’s misleading forecasts throughout the covid era powerfully illustrate the limitations of modelling as a way of predicting viral spread and the ensuing consequences. There are many inherent weaknesses to this approach, a crucial one being the sensitivity to initial assumptions. For example, Ferguson and his colleagues overestimated (by at least four-fold) the infection fatality rate of the SARS-CoV-2 virus, an error that significantly contributed to the fear-evoking forecasts of the likely death toll. In plain speak, rubbish in, rubbish out. The modelling study cited by NHS England in defence of its mask requirement clearly harbours the same fundamental flaw. The number of infections purportedly prevented by universal masking is highly dependent upon initial assumption about their effectiveness as a viral barrier. 

As stated previously, the scientific evidence suggests that face coverings achieve no appreciable reduction in the transmission of respiratory viruses. The authors of the study referenced by NHS England clearly recognise this limitation, as indicated by their mentions of “important gaps in the evidence base” and that “evidence around the efficacy of interventions such as wearing surgical masks … is severely lacking”. Yet, despite their acknowledging this reality, their model relies on an initial assumption of mask efficacy. The result? Hey, presto, face coverings will prevent 46,000 infections of healthcare staff. It is astounding that NHS England is relying on such circular logic to defend its controversial mask policies.

This cultural descent into ubiquitous masks in hospitals and health centres is hugely concerning. Policies requiring habitual face coverings are not based on solid empirical evidence; a piece of ill-fitting cloth or plastic does not transform into an impermeable viral barrier by virtue of crossing the threshold of a hospital or health centre. As such, NHS chiefs should reconsider their position on this issue. They must never forget that humane healthcare — delivered with demonstrable warmth and compassion — will always be more effective than the version provided by faceless professionals hidden behind veneers of sterility.

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