This document summarizes a study that compared science-based frameworks for risk-informed decision support across life science and engineering disciplines. The study found conceptual differences in how risk is defined and measured, as well as differences in procedural risk frameworks and scientific risk frameworks. A generic framework is proposed that takes a holistic, evidence-based, and long-term sustainability approach to risk assessment and management. Contact information is provided for the authors to request a full report.

1. Comparison of Science-based Frameworks
for Risk-informed Decision Support Across
Life Science and Engineering Disciplines
GRF – 3rd One Health Summit
Davos, 3-6 October 2015
L. Nielsen, J. Schlundt, M. H. Faber
Technical University of Denmark

2. Background
• The Global Decision Support Initiative (GDSI) at the
Technical University of Denmark
1. Support global, national, industrial and private decision
makers with evidence based decision basis
2. Development of a Generic Framework for decision Support
3. Implementation of an Open Decision Support Platform
4. Domain Applications
5. Global Expert Network
6. Education initiatives

3. The Study
• Purpose of the situation assessment report
Identify and report on the present best practices on science
based frameworks for risk informed decision support across
life science and engineerng disciplines
- Understanding of risk, metrics of risk, sustainability
- Interpretation of uncertainty
- Systems representation
- Methods of risk analysis, assessment, management
- Interface between risk information and decision making
- Risk acceptance
- Risk communication

4. Key Findings:
Risk Concepts & Perspectives
Risk
Concept
R=E
Expected value/
expected utility
Computing Sciences, Civil
Engineering , Transport,
Insurance
R=PC
Probability (Scenarios)/
Consequences
Civil Engineering, Major
Hazard Accident
(industrial), Natural
Hazards, Microbial Hazards
in Food and Environment
R=C (U)
Consequences/Damage
(and Uncertainty)
Chemical Hazards in Food
and Environment,
Occupational Health and
Safety, Fire Safety,
Transport Safety
R=ISO*
Effect of uncertainty on
objectives
Project/Program risk
management

5. Key Findings:
Procedural Risk Frameworks
Risk
Management
Risk
Assessment
Risk Analysis
System
(scope)
Definition
Hazard
Identification
Risk
Estimation
Risk
Evaluation
Risk
Acceptance
Risk
Treatment
Risk Control
Decision-
making
Monitoring
Risk management framework in the context of civil engineering according to
the Joint Committee on Structural Safety (JCSS 2008)

6. Key Findings:
Procedural Risk Frameworks
Risk assessment
Hazard/Efffect
assessment
Hazard
identification
Identify effects
of concern
Dose-response
assessment
Exposure
assessment
Emission rates
Product
applications
Product lifecycle
Environmental
distribution
Local scale Regional scale
Exposure levels
Risk
characterization
PEC/PNEC
Integration
Risk
management
Reporting
Management
review
Risk Assessment framework for environmental risk according to Technical
Guidance Documents on Risk Assessment for New and Existing Substances
(2003)

7. Key Findings:
Procedural Risk Frameworks
Quantitative Sustainability Assessment is guided by the LCA framework (ISO
14040: 2006; modified; ILCD 2010)

8. Key Findings:
Scientific Risk Frameworks
• Differences in interpretations of probability (frequentistic or
Bayesian)
• Differences between deterministic (point estimate) or probabilistic
approaches
• Application of socio-economic models and methods
• Theoretical principles and methods applicable across disciplines
– Bayesian Decision Theory
– Bayesian Probabilistic Nets
– Value of Information
– Socio-economic models for risk acceptance criteria, e.g. Life Quality
Index (LQI)
– Synergy between LCA and RA

9. Conclusions
 Conceptual differences of risk affect procedural risk
frameworks as they apply different boundary conditions for what
is termed risk analysis, risk assessment and risk management.
 Conceptual differences of risk affect scientific risk
frameworks in how risk is measured: the principles,
methodologies and metrics.
 A significant drawback of most existing frameworks is that they
do not sufficiently facilitate the potential for utilizing
evidence and/or indications of evidence.
 Terminology raises a host of challenges for risk
communication, risk analysis risk management and risk
governance from interpretation of meaning to whether and how
different activities in the overall analytical process are separated
and who has ownership and accountability for the various phases.

10. Generic Framework
for Sustainability and
Risk-Informed Decision Support

11. Generic System
Representation

12. Key Messages
• Holistic – assessment and management should not be
seen as separate domains
• System theory view – interdependencies, system
boundaries
• Long-term – inter- and intra-generational sustainability
considerations
• Evidence-based – updated on basis of VoI (pre-
posterior and posterior Bayesian analysis)

13. Thank you for your attention!
For a copy of the full report, please contact Linda Nielsen
Questions?

14. Contact Information
Linda Nielsen
Independent Consultant
lindanielsen2012@gmail.com
+45 20 72 36 93
Domains: natural hazards risk assessment and management, risk
governance, risk perception, communication and early warning
Michael Havbro Faber
Professor of Risk and Safety
mihf@byg.dtu.dk
+45 45 25 17 47
Domains: civil engineering, risk and reliability assessment, Bayesian
decision modeling, life safety, risk acceptance
Jørgen Schlundt
Professor
JSCHLUNDT@NTU.EDU.SG
+65 65 13 80 76
Domains: food safety, zoonoses, global burden of foodborne diseases, risk
assessment, risk governance