The Value of Being Precautious? Charlotte Zemmel discusses the precautionary principle and how it shaped the UK response to COVID-19 The COVID-19 pandemic has revealed diversity in the world's attitude towards healthcare and public welfare. One particularly striking aspect is how social values beyond scientific evidence shaped recommendations in Evidence Based Medicine. Here, I explore how COVID-19 response teams operated according to the principle of precaution. Precaution, as a guiding principle of theory and policy, encourages us to choose the intervention, evidence, and prognosis that is most pessimistic and cautious with respect to the future. Perhaps one key lesson to be learned from the post-COVID-19 ‘new normal’ is that the background values which shape our scientific models have fundamental consequences for our interpretation of scientific knowledge. Here, I explore the analysis and critique of these values by discussing the impact of being precautious on the epidemiological models produced by the UK’s leading COVID-19 response teams. On 26th March 2020, Imperial College London’s COVID-19 response team published their report, The Global Impact of COVID-19 and Strategies for Mitigation and Suppression. Based on a series of models, they predicted that SARS-CoV-2 would cause 40 million deaths globally if left unchecked. The report came at a critical time in public health debates — the UK was set to follow a policy whereby the country would remain entirely open in order to generate herd immunity, where spread of the virus is prevented by enough of the population gaining immunity by contracting the disease and recovering. Imperial’s bleak prognosis catalysed the Prime Minister’s revision of the herd immunity stance whilst the shocking numbers in the report drove many to take the threat of the virus seriously.
assessing the implications of choosing an incorrect hypothesis or disposing of a correct one. According to Rudner’s argument, the choice between a herd immunity response or a lockdown response requires the inclusion of judgements beyond the confines of evidence and data. This is where the precautionary principle was exercised. The poor quality of data in the early stages of the pandemic seemed to further justify a method that proceeded with maximum caution when designing effective public health responses. Furthemore, Rudner’s argument from inductive risk highlights that the less reliable the evidence is, the more essential extra-scientific values become. From looking at practitioners’ opinions on the quality of evidence during the pandemic, it was clear that values akin to the precautionary principle were necessary for good reasoning. Assistant Professor of history and philosophy of science at the University of Pittsburgh, Jonathan Fuller, explained that the focus on modelbased strategies in COVID-19 epidemiology, as opposed to other evidence-based approaches such as population sampling, was the result of the dire quality of evidence collected at the
Which Values Should We Value? | At times when scientists and policymakers are expected to make decisions with potentially harmful consequences for the public, it is intuitive that they should consider the most possible detrimental outcomes of each option in their decision making process. This is the rationale that sits behind the precautionary principle. Since the 1960s, philosophers of science have worked hard to devise an account for how scientists do and should use values such as the precautionary principle in their work. The clearest justification for the use of such values was first articulated by Richard Rudner in 1953: Argument from Inductive Risk (AIR). The argument states that: since no amount of evidence can guarantee that one hypothesis is correct over and above its closest rival, hypothesis choice is always underdetermined. Hence, scientists must use value judgements such as the social, ethical and political implications to navigate the choice by
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The Value of Being Precautious?
Michaelmas 2020
