The video is a Finnish talk I gave as part of a webinar series of the Institute for Health and Welfare (THL). I discuss the three scales of pandemic response: That of a) self-determined individuals, b) self-organised communities and c) governmental strategy choice in aiding these. Related, highly unpolished thoughts in English below. Slides here!
How should we think about changing people’s behaviour to mitigate pandemic threat? The starting point is to consider targets of interventions as complex systems. This means that biopsychosocial determinants such as capability, opportunity and motivation act together to create the current state of a system which is a person; aggregates of individuals define the state of a system which is a household, aggregates of which form a community, a society, and so forth. Each of these systems is of a different size, i.e. scale, and fulfills multiple roles in pandemic response – the redundancy brought about by overlap of functions performed by each element (say, individuals’ social distancing, and a community’s agreement to postpone cultural events to mitigate physical contact) is what largely ensures resilience of a system in crisis situations. In other words, information about intervention targets need to be framed as taking place within multi-level socio-ecological system, where tradeoffs between intervention nuance and scale exist. Figure below depicts this idea, and also underlines the mismatch when a large-scale unit, such as the government, attempts to dictate specifics of how e.g. schools or kindergartens should arrange their safety procedures, instead of acknowledging that “people are experts of their own environment”.
The above picture depicts a complexity profile, here a heuristic tool for considering intervention ownership. Any pandemic response must strike a balance between interventions that reach large audiences but (in spite of e.g. digital mass tailoring) are relatively homogenous, and interventions that reach small audiences but are highly tuned to their contexts. As long as the system performing the intervention remains the same, there is a fundamental tradeoff between complexity and scale, although changes in the system may allow increasing the area under the curve. Only individuals or small groups can perform ultra-local actions, and there are efforts where a larger governance structure is inevitable; those actions should be handled by agents at the appropriate scale. For example, a group of friends can come up with ideas to mingle safely, while e.g. city officials must make the decision to require quarantines and testing of incoming travellers. Horizontal axis depicts increasing audience size, from individuals to families, communities and countries. Blue line indicates the amount of nuance each entity can take into account, as depicted on the vertical axis.
Recently, we collected a sample of about 2000 people, who answered a survey on social psychological factors affecting personal protective behaviours such as mask use. As may be obvious, there are many open questions regarding implications of a cross-sectional analysis to the “real world”. Empirically evaluated social psychological phenomena are always embedded in time, making them to an extent idiographic and contextual, hence any generalisations to policy actions have to be considered in the light of nomothetic knowledge of complex systems. That is, the question of how we increase protective behaviours in the society is a multifaceted problem, requiring any actions to acknowledge the complexity of the system the behaviours take place in, and how they interact with other actions affecting community transmission. In my view, this is best done with the classical statement “First, do no harm” in mind.
A foremost condition for responsible application of science-based policy is a consideration of how the decision ought to be done, such that the costs of null effects are minimal. Finland has undertaken a suppression strategy common to European and Northern American countries, where increasingly stringent restrictions are gradually put in place while case numbers rise, and removed while cases decline. This sets different demands to individuals’ protective motivation and other personal resources (aka “pandemic fatigue”), compared to an elimination strategy, where relatively short but highly aggressive measures are taken to draw cases to zero. In the latter approach, most restrictions are lifted from case-free communities or countries, while applying border testing and quarantines to ensure the continued safety of the region’s inhabitants. In this latter case, provided that that future outbreaks are small and/or travel from regions with ongoing community transmission is low, local elimination ensues, and failures to increase protective behaviours imply – by necessity – a smaller impact than when attempted in a locale, safety of which depends mostly on personal protective behaviours.
Another consideration is that of systemic negative unintended side-effects of applying behavioural science recommendations to policy. Based on nomothetic knowledge of complex social systems and the results presented here, it is possible to give the following recommendations:
- Citizens’ sense of autonomy in choosing how to carry out the official pandemic mitigation recommendations should be fostered, without overlooking the necessity of feeling competence as well as camaraderie in the actions. This can be done with communication but perhaps more importantly, by facilitating people’s self-organisation tendencies and empowering them to design their own local responses, at the lowest scale (individual, family, neighbourhood, city/town, county, etc.) each of which is feasible to perform. This ensures local strengths get maximally applied, without severing functions, which are invisible to a governmental authority.
- Local norms (family, friends, other people in the indoor spaces one visits) ought to be stewarded to the direction which is necessary for pandemic control; this can again be done via communication, but based on literature on mitigating pandemics, it’s possible to hypothesise longer-lasting behavioural effects stemming from involving agentic individuals in the risk management of their surroundings.
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