Cost-benefit of risk reduction
Avoided losses from a prevention measure are estimated across hazard scenarios and compared with costs, with discounting, distribution of benefits and uncertainty reported beside the result.
GCRI · Disaster Resilience and Recovery
Decision analysis under uncertainty is how this platform frames the hard choices of disaster risk management: where to invest in prevention, when to act on a forecast, and how to sequence recovery. It makes options, objectives and uncertainties explicit so that authorities can examine and defend their choices.
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 disaster and crisis and climate and hazards, 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.
Avoided losses from a prevention measure are estimated across hazard scenarios and compared with costs, with discounting, distribution of benefits and uncertainty reported beside the result.
The cost of acting when no hazard follows is weighed against losses avoided by acting in time, to choose trigger thresholds for anticipatory action.
Recovery projects are compared against criteria such as restored services, equity, risk reduction and cost, with weights agreed with the recovery authority.
The screen a team would use to follow this method: its measures, states and decisions. Names are examples and values are illustrative.
Disaster resilience · Decision analysis for disaster · Run R-5493
| Deaths per 100,000 (Sendai A) | Lognormal | rate, stated | expert elicitation |
| Affected people (Sendai B) | Beta | people, stated | expert elicitation |
| Direct economic loss (Sendai C) | Beta | local units, stated | expert elicitation |
| Damage to critical infrastructure (Sendai D) | Beta | facilities, stated | expert elicitation |
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.
| Data | Role | Label |
|---|---|---|
| Disaster loss databases | Loss inputs | REPORTED |
| Hazard models | Event probabilities | MODELLED |
| Programme cost records | Option costs | OBSERVED |
| Stakeholder-elicited weights | Objectives | DECLARED |
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.
How far the outlook for decision analysis for disaster risk could spread, shown as ranges rather than a single line.
Analyses are checked through sensitivity analysis, peer review and stakeholder scrutiny. Retrospective review compares decisions with outcomes.
| Check | How it is done |
|---|---|
| Sensitivity to discount rate | Results are recomputed across a range of discount rates and reported |
| Distributional analysis | Who gains and who bears costs is shown alongside totals |
| Assumption register | Every assumption is listed and reviewed with the commissioning authority |
Results depend on elicited probabilities and preferences that may be biased. Deep uncertainty can make expected value comparisons misleading.
Process explorer · Process
10 steps·4 stages
Process
In IPCC AR6 Working Group II, climate risk results from interactions between hazards and a system's exposure and vulnerability, and responses can add risk.
Outline of an external standard or method, from its public sources. It describes what the framework says, not a record of any run. It does not show that Nexus or any partner performs, certifies or approves a step. A gate is a step of the method, never a Nexus approval.
Systemic Risk Management stewards decision analysis under uncertainty for the Consortium and reviews how it is applied across platforms.
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