The social amplification of risk & zoonotic disease outbreaks

1. D Duckett, J S Busby, S Onggo Lancaster University The social amplification of risk & zoonotic disease outbreaks Department of Management Science, Lancaster University

2. Social amplification of risk • Laypeople not going along with expert assessment • A source of disproportionate response • An obstacle to progress • The need to manage the ‘issue’ (Leiss 2001) as well as substance • The Social Amplification of Risk Framework (Kasperson et al 1988) • Signals that get magnified or diminished • Secondary or ripple effects that are generated • Applied with apparent success to BSE, WJD, SARS... • The trouble with SARF • The idea of a real, ‘accurate’ risk that’s amplified (Rayner 1988) • The implication that amplification should be overcome (Rip 1988) • The response (Kasperson et al 2003) as a motte-&-bailey defence

3. Social amplification of risk • Keeping amplification but only as an attribution (Busby et al, 2009) • Can produce objective outcomes: polarised risk perceptions • Helps explain how people resist systematically different views • Encourages reflexive understanding • Not ‘X is amplifying’ but ‘why is X attributing attenuation to us?’ • Important when people understand risks socially • A project applying this idea to zoonotic disease outbreaks • Fieldwork looking at how people explain their responses to risk • Simulation modelling exploring the consequences of amplification • Funded by EPSRC jointly with NCZR Social actors Risk input to attribute Amplification of risk Social processes produces to Amplified risk Other social actors

4. Fieldwork: how people talk about risk & amplification • A natural starting point to look at attributions in discourse surrounding risk • Qualitative analysis of rich textual data in which people make sense of • zoonotic cases • Lay Focus Groups • PhD students from management related disciplines • Veterinarian PhD students • Retired lay people • Mothers of young children • Expert individual & group interviews • Regulators • Farming interests • Epidemiologists • Virologists • Veterinarians • Science journalists

5. Fieldwork: categories of attribution • Several forms of amplification attribution are evident in the data Consequence Retrospective Corrective Ancillary Gap Anticipatory Media Transboundary Maverick-led Plot Actors constructing amplification labels Other actors as objects of amplification labels and as authors of counter-claims

6. Fieldwork: important points • Amplification is relational • Social relationships determine how risk responses are viewed as • amplified or attenuated & are often contested • Amplification often then attributed as an instrumental strategy • Eg informercial campaigns, import/export policies, media headlines • Authoritative and lay assessments are by no means equal • But authorities may benefit from understanding attributions to them

7. Modelling social risk amplification as an attribution • A 2-actor system dealing with a single event • Both actors form risk judgments based on same datum • But also taking account of the other’s expressed risk beliefs • And correcting for remembered, perceived amplifications Memory of public amplification Industry + – Amplification attributed to public Communicated risk level + + – Independent risk level – + Espoused risk level Amplification attributed to industry + + + Corrected risk level Memory of industry amplification + – Public

8. Modelling social risk amplification as an attribution • This is unstable • The 2 actors’ risk levels diverge strongly over time • Following eg changes in datum and anticipations • Although memory limits lead to saturation of polarisation • Simple refinements preserve instability • Delays & imperfections in observation and remembering • Other actors assumed to distort in opposite sense Risk level 10-0 10-1 10-2 10-3 10-4 10-5 10-6 Public Industry Independent Time

9. Modelling social risk amplification as an attribution • Stability only when actors accept other views uncritically • Despite shared datum • And memory reset at the start of the event • No attempt at calibration so timescales uninformative • Sensitivity of critical time for polarisation to reach threshold • Exogenous factors (discounting, anticipation) have little effect

10. Modelling social risk amplification as an attribution • Adding features • Endogenising the weighting given to others’ beliefs • Reflecting the role of distrust (eg Frewer 2003) • Determined by perceived distortion, bias, wrongness • And perception of confusion (eg Bergeron and Sanchez, 2005) • Determined by rate of change of risk belief • Capturing the link to and effect of behaviour • Perception affects demand, exposure & assessment • Assumed to be corrective • Action may be easy yet seem disproportionate (Rip 2006)

11. Modelling social risk amplification as an attribution • Adding features • Endogenising the weighting given to others’ beliefs • Reflecting the role of distrust (eg Frewer 2003) • Determined by perceived distortion, bias, wrongness • And perception of confusion (eg Bergeron and Sanchez, 2005) • Determined by rate of change of risk belief • Capturing the link to and effect of behaviour • Perception affects demand, exposure & assessment • Assumed to be corrective • Action may be easy yet seem disproportionate (Rip 2006) Memory of public amplification Industry + – Amplification attributed to public Communicated risk level + Amenity demand subsystem + – Independent risk level – + Espoused risk level Amplification attributed to industry + + + Corrected risk level Distrust & confusion subsystem Memory of industry amplification + – Public

12. Modelling social risk amplification as an attribution • Now distrust and confusion limit & even overcome polarisation Risk level 10-2 10-3 10-4 10-5 Public Industry Independent Time

13. Conclusion • Social risk amplification looks important for managing outbreaks • Supporting idea that risk beliefs can be systematically mistaken • But it’s hard to accept it as an objective description • Based on the distortion of a true level of risk • Moving to the idea of amplification as a subjective attribution... • Shows structure: different categories & significance • Has consequences: likely polarisation with saturation • And suggests for policy makers... • The need to be careful in anticipating distortion among publics • The value of asking why others attribution amplification to you