Integrated deployment of local urban relief teams in the first hours after mass casualty incidents
Atefe Baghaian (),
M. M. Lotfi () and
Shabnam Rezapour ()
Additional contact information
Atefe Baghaian: Yazd University
M. M. Lotfi: Yazd University
Shabnam Rezapour: Florida International University
Operational Research, 2022, vol. 22, issue 4, No 40, 4517-4555
Abstract:
Abstract This paper develops scenario-based stochastic optimization model to choose optimal policies for the integrated deployment of local urban relief teams in the early aftermath of sudden-onset mass casualty incidents. The deployment of local relief teams in an urban area with several affected sites, allocation of casualties to casualty treatment centres, and assignment of medical teams to casualty treatment centres and triage groups are simultaneously determined. Seven strategies under “streaming” and “pooling” groups of treatment strategies are linked to the activity of relief teams. Based on realistic data, our model is analysed for 1750 random samples of the disaster field and 35 instances of a hypothetical earthquake. The results show the integration of SAR and on-field treatment operations can increase the number of survivors. The robust model results in a less number of survivors because it tries to maintain the optimal solution under given scenarios close to its expected value.
Keywords: Mass casualty incident; Casualty management; Search and rescue; Treatment strategy; Streaming; Pooling (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://link.springer.com/10.1007/s12351-022-00689-y Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:operea:v:22:y:2022:i:4:d:10.1007_s12351-022-00689-y
Ordering information: This journal article can be ordered from
https://www.springer ... search/journal/12351
DOI: 10.1007/s12351-022-00689-y
Access Statistics for this article
Operational Research is currently edited by Nikolaos F. Matsatsinis, John Psarras and Constantin Zopounidis
More articles in Operational Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().