Increasing Preparedness for Extreme Events using Plausibility‐Based Scenario Planning: Lessons from COVID‐19

Abstract

A striking feature of COVID-19 is many countries' low level of preparedness for it, despite pandemics being a known threat. This raises a question as to the reasons for this underpreparedness. While preparedness should have better reflected pandemics' long-run inevitability and potentially catastrophic impact, government-planning horizons are short term, and the attentiveness of policymakers is bounded and subject to multiple demands. Preparedness is therefore affected by the fundamental uncertainty surrounding the exact nature, timing, and impact of a pandemic. While a subjective probability is attributable to such an event's occurrence, just like it is any other, if founded on scant knowledge and perceived as being low it may inhibit preparedness. Under such circumstances, preparedness may be better served by a focus on plausibility. Moreover, any tendency for policymakers to disregard highly uncertain, low-probability, yet highly impactful events of this type is exacerbated by their "fat-tailed" distribution, which obscures their potential extremity. This article considers how plausibilitybased scenario planning can increase preparedness for extreme events like a global pandemic, thereby reducing overconfidence in continued business-as-usual in their face, and emphasizing precaution in their wake. In so doing, the article contributes to what in this journal has recently been called "type B," "generic and fundamental" risk science, which is concerned with identifying better ways to present and communicate uncertainties. In focusing on plausibilitybased scenario planning, the article highlights a method seldom previously discussed in relation to risk science, yet one that can contribute much to this type B component of it.

Is seeking certainty in climate sensitivity measures counterproductive in the context of climate emergency? The case for scenario planning

“…Secondly, notwithstanding this technical problem, even if it were possible within the Bayesian framework to add more possibilities over time as they are revealed, this would anyway at some point require the downgrading of the probability of ex ante included possibilities due to the finite amount of likelihood available and the requirement that probabilities sum to unity (the so-called problem of "additivity"). This downgrading of probability may contribute to highly impactful and extreme outcomes being overlooked or dismissed by policymakers (Derbyshire, 2022). Thirdly, reserving a portion of probability for these possibilities revealed over time, which is then "consumed" as these possibilities are revealed so that downgrading of the probability of ex ante included possibilities is avoided, does not help because the amount of reserve needed is unknown ex ante (Derbyshire, 2017;Shackle, 1955).…”

“…Moreover, stringent action to prevent harm can be adjusted downwards, whereas, insufficiently stringent action due to a lack of certainty about its need cannot be retrospectively adjusted upwards. As such, there is an asymmetry to precaution in the presence of known unknowns and surprise that can influence multiplicative effects with irreversible impact (Taleb, 2020;Derbyshire, 2022). In the context of climate change, therefore, it is essential to place a premium on prudential conduct that allows for degrees and types of uncertainty and facets of fundamental uncertainty.…”

“…Given the problem under scrutiny is anthropogenic change to the climate, this is an important tension. The precautionary principle, and the accelerating and irreversible nature of climate change, suggests we should far prefer a type I precautionary 'error' of overresponse over a type II of underresponse (Derbyshire, 2022). However, uncertainty itself can have different effects and these depend in part on how evidence and argument 8 And this is to say nothing regarding the role economic theory and research has played in inducing delay because of "Integrated Assessment Models" (IAMs), such as the "Dynamic Integrated model of Climate and the Economy" (DICE).…”

“…It may then, be more appropriate in policy terms to seek an evidence-informed approach to managing uncertainty, since such approaches may be better able to address the need to overweight urgent prudential responses. Moreover, given that uncertainty itself can have different effects on policy and behaviour and these depend in part on how evidence and argument are framed, we would argue there are multiple reasons to develop a scenario focused decision framework (SFDF) (Derbyshire, 2022(Derbyshire, , 2020aDerbyshire and Giovannetti, 2017). Unlike standard predictive approaches, SFDF have the great advantage of being exploratory, deliberative, inclusionary, diverse and developmental and this can encourage integrative problem solving policy as well as empowerment and persuasion of stakeholders, which in the case of climate emergency is everybody (for work that emphasizes aspects of this see Workman et al, 2021Workman et al, , 2020Sharmina et al, 2019;Moallemi and Malekpour, 2018).…”

Global systemic risk and resilience for novel coronavirus in postpandemic era

“…Another work in relation to preparedness is given by Derbyshire ( 2021 ) who considers how plausibility‐based scenario planning can increase preparedness for extreme events like a global pandemic, thereby reducing overconfidence in continued business‐as‐usual in their face, and emphasizing precaution in their wake. In so doing, Derbyshire's work contributes to “type B,” “generic and fundamental” risk science, which is concerned with identifying better ways to present and communicate uncertainties.…”