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Abstract Building an interdisciplinary team is critical to disaster response research as it often deals with acute onset events, short decision horizons, constrained resources, and uncertainties related to rapidly unfolding response environments. This article examines three teaming mechanisms for interdisciplinary disaster response research, includingad hocand/or grant proposal driven teams, research center or institute based teams, and teams oriented by matching expertise toward long‐term collaborations. Using hurricanes as the response context, it further examines several types of critical data that require interdisciplinary collaboration on collection, integration, and analysis. Last, suggesting a data‐driven approach to engaging multiple disciplines, the article advocates building interdisciplinary teams for disaster response research with a long‐term goal and an integrated research protocol.
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The Frontiers of Uncertainty Estimation in Interdisciplinary Disaster Research and Practice
Abstract Conceptualizing, assessing, and managing disaster risks involve collecting and synthesizing pluralistic information—from natural, built, and human systems—to characterize disaster impacts and guide policy on effective resilience investments. Disaster research and practice, therefore, are highly complex and inherently interdisciplinary endeavors. Characterizing the uncertainties involved in interdisciplinary disaster research is imperative, since misrepresenting uncertainty can lead to myopic decisions and suboptimal societal outcomes. Efficacious disaster mitigation should, therefore, explicitly address the uncertainties associated with all stages of hazard modeling, preparation, and response. However, uncertainty assessment and communication in the context of interdisciplinary disaster research remain understudied. In this “Perspective” article, we argue that in harnessing interdisciplinary methods and diverse data types in disaster research, careful deliberations on assessingType IIIandType IVerrors are imperative. Additionally, we discuss the pathologies in frequentist approaches, calling for an increasing role for Bayesian methods in uncertainty estimations. Moreover, we discuss the potential tradeoffs associated with information and uncertainty, calling for deliberate consideration of the role of diversity of information prior to setting the scope in interdisciplinary modeling. Future research guided by further reflections on the ideas raised in this article could help push the frontiers of uncertainty estimation in interdisciplinary hazard research and practice.
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- PAR ID:
- 10247332
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Risk Analysis
- Volume:
- 41
- Issue:
- 7
- ISSN:
- 0272-4332
- Page Range / eLocation ID:
- p. 1129-1135
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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