GCRI · Campaigns

Decision analysis for risk communication

Decision analysis under uncertainty structures the choices communicators and the authorities they serve must make: whether to speak before evidence settles, which audiences and channels to prioritise, and when to adapt or end a campaign. It makes trade-offs between reach, equity, cost and the risk of harm explicit and open to scrutiny.

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01Register

Decision analysis for risk communication on the record.

Method recordSTEM method
  1. MethodDecision analysis under uncertainty
  3. Applied inCampaigns
  6. Canonical pageSTEM Commons
02Application

What decision analysis under uncertainty does here.

Decision analysis under uncertainty provides structured methods for choosing among options when outcomes are uncertain and objectives conflict. It makes trade-offs and value judgements explicit. In information and public trust and society and human development, decision analysis helps choose actions that perform acceptably across interconnected risks and uncertain futures. It clarifies when to act now and when to keep options open. The canonical description is on the STEM Commons.

Communicating before the evidence settles

Early communication with stated uncertainty is weighed against waiting for better evidence, using value-of-information reasoning and the risks of silence, so the timing choice and its assumptions are on record.

Choosing channels and audiences

Options are scored against reach, accessibility, equity, cost and risk of harm, with weights elicited from stakeholders, and the ranking is tested for sensitivity to those weights.

Adapt, continue or end

Decision points are set in advance with the evidence that would trigger adapting, continuing or ending a campaign, so later choices are not driven by sunk costs or favourable metrics alone.

03Monitor

Uncertainty analysis.

The screen a team would use to follow this method: its measures, states and decisions. Names are examples and values are illustrative.

Uncertainty analysis

Campaigns · Decision analysis for risk · Run R-2791

Sensitivity rankedGCRI · Campaigns

Total-order sensitivity

Output distribution

Inputs

People reachedLognormalpeople, statedexpert elicitation
Knowledge gainNormalscore change, statedexpert elicitation
Consent records completeLognormal of participants, statedexpert elicitation
Preparedness actions takenBeta of households, statedexpert elicitation
Uncertainty analysis: the screen’s structure, terms and states for Campaigns.Example names and illustrative values; a design, not a record or a live system.
04Data

What the method consumes.

Datasets and records used by decision analysis under uncertainty on this platform, with the role each plays and the label its values carry. Sources are listed in the source register.

DataRoleLabel
Expert elicitation recordsJudgements where data are thinESTIMATED
Stakeholder preference surveysWeights on criteria such as reach, equity and costREPORTED
Pre-test and evaluation resultsEvidence on how options performOBSERVED
Budget and resource recordsWhat each option requiresPublished statistics
05Simulator

A threshold model of collective behaviour.

Each agent acts once enough of its contacts have; small changes in the mean threshold or the early movers decide whether the behaviour stays local or cascades through the population. Teaching model with stated illustrative values, not a prediction.

Controls

Mean threshold (share of neighbours)
18%
Spread of thresholds
8 points
Early movers
2.0% of people
Contacts per person
8

Readouts

Share who acted in the end
100%
Global cascade
Yes
Steps to settle
10
Numbers, methods and sources
StepShare who have acted (%)
02.0
18.0
222.5
340.0
455.8
569.8
683.0
792.5
897.5
9100.0
10100.0

Methods

  1. Threshold models of collective behaviour Granovetter (1978), American Journal of Sociology 83
  2. Global cascades on random networks Watts (2002), PNAS 99
  3. Complex contagions Centola and Macy (2007), American Journal of Sociology 113
  4. One-at-a-time sensitivity (tornado) Saltelli and others (2008), Global Sensitivity Analysis: The Primer, Wiley

Data

No observed data enters this model: it runs on the teaching values set by the controls, to be replaced with a programme’s own evidence.

A threshold model of collective behaviour. Illustrative teaching model: it runs on the values set by the controls, not on measured data. Methods: Threshold models of collective behaviour (Granovetter (1978), American Journal of Sociology 83); Global cascades on random networks (Watts (2002), PNAS 99); Complex contagions (Centola and Macy (2007), American Journal of Sociology 113).

Across the six pillars, led by Nexus Consortium

06Validation

How results are checked.

Analyses are checked through sensitivity analysis, peer review and stakeholder scrutiny. Retrospective review compares decisions with outcomes.

CheckHow it is done
Sensitivity analysisWeights and probabilities are varied to show which of them drive the choice
Explicit value judgementsEach criterion and weight is recorded with who set it and why
Robustness across scenariosOptions are tested against several plausible futures, not one expected case
Retrospective reviewDecisions are compared with what followed, separating the quality of the judgement from the luck of the outcome

Results depend on elicited probabilities and preferences that may be biased. Deep uncertainty can make expected value comparisons misleading.

07Methods and evidence

How decision analysis for risk communication is modelled, measured and tested.

The model, its assumptions, its data and its uncertainty, in the form a scientist or engineer would check. Structures follow published methods. The values drawn are illustrative, not findings.

System model

The couplings between the systems in decision analysis for risk communication: signs of influence, a reinforcing and a balancing loop, and cross-links where stress jumps.

++−+InformationSocietyCommunitiesEconomyR reinforcingB balancing
Causal loop diagram from the page’s systems; signs show the direction of influence. Illustrative structure for a system dynamics or network model, not estimated couplings.
FAIR guiding principles · GO FAIR and FORCE11W3C PROV · World Wide Web ConsortiumGuidance on consistent treatment of uncertainties · IPCCCEOS Analysis Ready Data · Committee on Earth Observation Satellites
08Connections

Topics that rely on this method.

09Stewardship

Who maintains the method.

Systemic Risk Management stewards decision analysis under uncertainty for the Consortium and reviews how it is applied across platforms.

Canonical page: Decision analysis under uncertainty

10Connected

Where this page leads across the Consortium.

11Questions

Questions and answers.

What are the limits of decision analysis under uncertainty in this field?
Results depend on elicited probabilities and preferences that may be biased. Deep uncertainty can make expected value comparisons misleading.
How are results checked?
Analyses are checked through sensitivity analysis, peer review and stakeholder scrutiny. Retrospective review compares decisions with outcomes.
Are the values on this page real?
The data names, roles and checks are real descriptions of practice. The canvas shows a design of the method’s use, not a run; no result is reported here.
Where else is this method applied?
The canonical method page lists every platform that applies it.
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