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Managing food chain risks: the role of uncertainty
Richard Shepherd
University of Surrey
Project partners
Person responsible Organisation
Richard Shepherd University of Surrey
Andy Hart Central Science Laboratory
Gary Barker Institute of Food Research
Simon French Manchester Business School
John Maule Leeds University Business School
Uncertainty
• There are known knowns
– there are things that we know that we know
• There are known unknowns
– that is to say, there are things that we now know we don't know
• But there are also unknown unknowns
– there are things we do not know we don't know
• And each year we discover a few more of those unknown unknowns
Donald Rumsfeld, US Secretary of Defense
Winner of Plain English Campaign ‘Foot in Mouth Award’ 2003
Cynefin model of decision contexts
Knowable
Cause and effect can be determined with sufficient data
The realm of scientific inquiry
Known
Cause and effect understood and predictable
The realm of scientific knowledge
Complex
Cause and effect may be explained after the event.Social
systems
Chaotic
Cause and effect not discernable
Snowden (2002)
Need to communicate uncertainty
• Need for:– Transparency– Openness
• If uncertainty subsequently found it will lead to problems of credibility
• ‘… the need to be open about uncertainty and to make the level of uncertainty clear when communicating with the public’
HM Government Response to the BSE Inquiry (2001)
Presenting uncertainty to the public
• Admission of uncertainty (Johnson and Slovic, 1995)– More honest– Less competent
• Public preferences (Frewer et al. 2002)– Public want information on uncertainty– More accepting of uncertainty when due to
scientific process than lack of interest or action by government
Project objectives
• Develop interactive web-enabled tools for quantitative assessment of risks and uncertainty
• Use participatory methods to ensure web-enabled tools, etc. appropriate for stakeholders
• Develop methods to predict consumer behaviour driven by perceptions of risk and uncertainty
• Develop improved methods for communicating with stakeholders
• Test, evaluate and demonstrate improved approaches in case studies of food contamination and microbiological hazards
Food chain 1
Food chain 2
Food chain 3
Modular food chain models
Each module includes production, processing, storage, retail, cooking etc.
Dietary risk modelling
National diet survey data
2D Monte Carlo engine
Post-processing & analysis
Long-term extrapolation
Participatory Processes
‘Live’ groups• Stakeholder
workshops• citizen juries• focus groups
Web enabled interactions
Surveys
All stages of process: from problem definition to
interpretation, decision-making, communication
Predicting changes in consumer behaviour
Analyse effects of communication and management actions
Predict dietary changes
Case studies
Achemical
contaminant
Amicrobial
contamination
Acrisis
scenario
Specialist user
Decision-making forums
Lay public and stakeholders
Communication and decision support interfaces
Results for technical reports
Test alternate scenarios and management options
Lay user:What if?
Risk to me?
Media
direct via internet
indirect
Models, systems and processes designed and validated with respect to
Modules within the project
Participatory processes
• Participatory methods– Stakeholder workshops – Citizens’ juries– Focus groups– Scenarios to stimulate discussion
• Runs throughout project to:– Inform initial developments and ensure processes and
web-enabled tools appropriate for stakeholders– Test in case studies
Dietary risk modelling
• Develop web-based tools based on CSL probabilistic tool• Probabilistic methods of risk assessment:
– Take account of variability and uncertainty– Usually aimed at specialists
• Hierarchical 2D Monte Carlo to quantify uncertainties• Expand to include:
– Other contaminants and pathogens– Long term exposures– Suitable for non-technical users– ‘What if’ tools
Modular food chain models
• Managing risk across the food chain
• Modularisation of food chain– Production, processing, storage, consumption
• Dependencies across the chain - concentrations of agent a function of: – Control measures– Performance criteria
• Build set of uncertainty distributions
Predicting changes in consumer behaviour
• Impact on consumer behaviour of communication and management actions
• Issues addressed:– Risk information v direct recommendation– Personal relevance of information– Presentation of uncertainty– Numerical/verbal presentation of uncertainty
• Predict consumer behaviour changes
Communication and decision support interfaces
• Communication dependent on how different actors understand and think about risk
• Mental models
• Social representations
• Test using scenarios
Case studies
• Chemical - pesticide– Data available – Amenable to probabilistic modelling
• Microbiological - cross contamination with campylobacter– Undercooked chicken– Mainly caused by cross contamination
• Scenario with unanticipated risk– Hypothetical scenarios– Rapid response
Key audiences
• Natural and social scientists• Stakeholders throughout the food chain
– Producers– Manufacturers– Risk managers and regulators
• General public(s)• Communication through:
– Dissemination activities– Stakeholder workshops
Concluding comments
• Interdisciplinary research– Natural sciences– Social sciences
• Quantitative assessment and modelling of risks and uncertainty across the food chain
• Stakeholder involvement and participatory processes
• Effective communication with the public and stakeholders