Over the past week or so I’ve begun to wonder whether I should turn my curiosity about pandemic policy-making and related actor behaviour into a more serious investigation. One of the reasons is that, like Harvard’s Sheila Jasanoff has observed, I’ve noted the prominence of future projections and associated forms of model-based analysis. Additionally, specific aspects are clearly important such as the attention given to worst case scenarios (including the question of which scenarios are attended to) and whether they’re given credence. Another reason is that I find the expectations dynamics to be interesting and they appear to be an important aspect of decision processes and strategy formation. Lastly, the case of the pandemic may suggest lines of inquiry that can inform theory-building.
Some of these thoughts related to some of my general criticisms of future-oriented activities – which can be called ‘foresight’ activities, ‘futures thinking’, futures studies, the discipline of anticipation, etc – and of related activities aimed to the development of ‘futures literacy’. The dominant focus tends to be placed on methods (e.g. to develop scenarios or produce a forecast) but, in my view, there’s too little attention on theory. Though there are notable exceptions (such as practitioners who have developed theories that guide their practice), overall such activities remain, for the most part, thoroughly undertheorised.
For now, I mainly intend to continue monitoring developments, particularly in dynamic places like Europe, as I give ideas like the high-level ones noted below further thought. But some aspects can be briefly noted.
Something that interests me is social patterns in responses to anticipatory knowledge-claims and the effects of such responses and the associated patterns. The coronavirus pandemic may offer some important examples which could be investigated. For example, both the UK government and Swedish Public Health Agency were presented with similar worst case scenario style projections of potential deaths from COVID-19 but staff at the Swedish Public Health Agency were more skeptical than the UK government and its advisers. Similar projections were also reported to have had an impact on the White House though they appear to have had far greater impact on UK policy. This suggests potential lines of inquiry which may offer both practical lessons and more theoretical insights (for a similar inquiry assessing actor practices and expectations see Fligstein et al, 2017).
Related decision-making is increasingly the subject of fiery debate. For example, some epidemiologists from Oxford University contend that the UK Prime Minister and his advisers “panicked the country into shutting down”. Other observers hold different views, including the team from Imperial College London who contend that the introduction of unprecedented lockdowns in the UK and elsewhere in Europe saved millions of lives. (Others, in response, argue that such claimed ‘effects’ are largely illusory).
A further initial observation is that the dominance of particular knowledge practices is being debated. For example, some epidemiologists are calling for less emphasis to be placed on projections and related modelling and for more emphasis to be placed on empirically interrogating what’s happening on-the-ground and responding to such developments and emerging dynamics. If such a shift was to occur it would be a dramatic shift in practices.
Over coming months and years we’ll get a better sense of whether the dramatic projections made during the March-April period were a reasonable warning of what could happen if mitigating actions weren’t taken. Some observers contend that the current situation in Sweden indicates that the worse case scenarios were implausible – with some early claims-making about herd immunity thresholds and dynamics – though others suggest that we ought to wait and see what emerges over the fall and winter period (in the Northern Hemisphere) as well as over the full lifecyle of the pandemic. My non-expert feeling is that it’s currently too early to judge this (with any confidence) and some commentators have perhaps made a very ‘early crow’ which risks being proven wrong.
If it turns out that such claims were greatly exaggerated then an important question will be why did some governments and related actors interpret them as credible forecasts or scenarios (e.g. the UK government and its main advisors) when others didn’t; and, on the hand, if they turn out to have been reasonable worse case scenarios the reverse would need explanation (e.g. why the Swedish Public Health Agency and its senior epidemiologists were unreasonably dismissive of such projections and didn’t modify their policies).
Here in the Australian context it is commonly claimed that “worst-case scenario coronavirus modelling saved Australia from catastrophe” despite the increasing conviction such modelling was highly flawed. This is a claim that also could be evaluated.
A worry articulated by one Australian infectious disease specialist is that “if you overdo the predictions at the beginning [of the pandemic] people may eventually say ‘this is garbage, I won’t do anything’. This would be a worry” (link).
Additionally, the attention being given to worse case style future scenarios and forecasts during this pandemic has got me thinking about a further question: when actors give greater (or less) attention to dramatic worst case scenarios how does this influence their broader expectations about the future?
David Wallace-Wells’ book The Uninhabitable Earth was one prompt to think more about this question. In this book Wallace-Wells advocates for greater consideration of worst case possibilities with a focus on climate change and its potential implications. He contends that “when we dismiss worst-case possibilities, it distorts our sense of likelier outcomes” (p.8), thus arguing for giving greater attention to such possibilities to correct our understanding of likelier outcomes. In contrast, I’ve begun to wonder whether such a focus on worst case scenarios (and/or forecasts) distorts our sense of likelier outcomes. This is a question that might be empirically interrogated regarding pandemic policies (or other issues).
It perhaps stands to reason that if disaster style scenarios are taken to be credible and are given a high level of attention then this will influence the kinds of futures that actors think are likely to occur (with or without mitigating actions). Such future expectations could have an anchoring effect and/or influence other perceived possibilities.
Coming back to the current pandemic, one possibility is that those actors who internalised worst case scenarios as plausible futures could have a hard time believing more favourable scenarios. If this is correct, such dynamics could continue to influence their expectations and policy-making even if these worst case scenarios later come to be judged to be implausible. The relevance of such questions will depend a little on how the pandemic plays out.
More broadly, the ‘futures’ and foresight literatures offer few insights into the likely (or potential) effects of attending to worst case scenarios under different conditions, nor related tendencies such as a tendency to foreground and attend to the worst case and give too little attention to other possibilities (or the reverse). At best, some practitioners express high-level ideas like the belief that it is necessary to develop worst case scenarios to get people to act differently, but little theorisation of such effects has been done.
A further potential line of inquiry concerns the relationship between what scenarios get foregrounded (and backgrounded) and actors’ knowledge practices, which in turn may reinforce such tendencies. My basic sense of this – which needs to be further considered empirically – is that actors tendencies can influence their consideration of facts and evidence, such as where actors “reinterpret troubling facts in a positive light” (Fligstein et al., 2017) – a phenomenon Karen Cerulo terms ‘best case vision’ – and generally marginalise discordant information. Again, the pandemic may offer lines of inquiry.
Related dynamics may be at work when an actor has stated opinions very publicly, such as the phenomenon of “bolstering” (see Mercier & Sperber, 2011). Actors may feel pressure to defend such opinions and this could bias their knowledge practices.
A few final thoughts: I’ve noted with interest critical comments made about epidemiologists and their tendencies (as these are perceived). I’ve heard comments such as “epidemiologists like disaster scenarios”. Related comments are made about their alleged tendencies to produce overly pessimistic or gloomy analyses. Given the prominent role of epidemiologists in this pandemic there might be the opportunity to study epidemiologists to explore potential socially structured tendencies and their causes (see Cerulo, 2006).
Second, on the topic of worst case scenarios it’s also interesting to think about which get emphasised and which get marginalised and why. This is another potential line of inquiry. Worst case scenarios in which we fail develop a COVID-19 vaccine (or only develop vaccines with poor or limited efficacy) don’t seem to be given much consideration, despite the challenges that have been faced with coronaviruses. Infectious disease specialists such as Professor Peter Collignon from Australian National University have voiced related concerns and he argues that “it’s not ‘when’ the coronavirus vaccine, it’s a big ‘if’.”
If my experience is any guide, suggesting that we might not have a vaccine (or an effective one) seems to be somewhat “taboo”. It’s a possibility that people don’t want to contemplate.
This brings me to my other final thought. The coronavirus pandemic may offer opportunities to study broader expectation dynamics such as false hopes (and related forms of wishful thinking) and the situatedness of expectations.
For instance, something I’ve observed is that actors’ vaccine expectations appear to often be related to their policy preferences. Actors who favour suppression of the virus and holding out for a vaccine often have more optimistic vaccine expectations, whereas those with other policy preferences often have more pessimistic expectations. At the moment actors advocating “aggressive suppression” have won the policy argument in Australia but perhaps this approach may be grounded in flawed expectations and/or naive hopes.
Though STS scholars have studied the situatedness of expectations in innovation processes, including in emerging biotechnologies, to the best of my knowledge this hasn’t been studied for the development of novel vaccines and new vaccine technology platforms.