Communicating Geographical Risks in Crisis Management: The Need for Research.


Journal

Risk analysis : an official publication of the Society for Risk Analysis
ISSN: 1539-6924
Titre abrégé: Risk Anal
Pays: United States
ID NLM: 8109978

Informations de publication

Date de publication:
01 2019
Historique:
received: 29 09 2016
revised: 04 08 2017
accepted: 09 08 2017
pubmed: 24 10 2017
medline: 6 8 2019
entrez: 24 10 2017
Statut: ppublish

Résumé

In any crisis, there is a great deal of uncertainty, often geographical uncertainty or, more precisely, spatiotemporal uncertainty. Examples include the spread of contamination from an industrial accident, drifting volcanic ash, and the path of a hurricane. Estimating spatiotemporal probabilities is usually a difficult task, but that is not our primary concern. Rather, we ask how analysts can communicate spatiotemporal uncertainty to those handling the crisis. We comment on the somewhat limited literature on the representation of spatial uncertainty on maps. We note that many cognitive issues arise and that the potential for confusion is high. We note that in the early stages of handling a crisis, the uncertainties involved may be deep, i.e., difficult or impossible to quantify in the time available. In such circumstance, we suggest the idea of presenting multiple scenarios.

Identifiants

pubmed: 29059698
doi: 10.1111/risa.12904
doi:

Substances chimiques

Air Pollutants 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Pagination

9-16

Informations de copyright

© 2017 Society for Risk Analysis.

Auteurs

Simon French (S)

Department of Statistics, University of Warwick, Coventry, UK.

Nikolaos Argyris (N)

School of Business and Economics, Loughborough University, Loughborough, UK.

Stephanie M Haywood (SM)

Centre for Radiation, Chemical and Environmental Hazards, Public Health England, Chilton, Oxfordshire, UK.

Matthew C Hort (MC)

The Met Office, Exeter, Devon, UK.

Jim Q Smith (JQ)

Alan Turing Institute, and, Department of Statistics, University of Warwick, British Library, London, UK.

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Classifications MeSH