Technologies Enabling Situational Awareness During Disaster Response: A Systematic Review.

disaster response emergency responders multi-agency coordination situational awareness technology

Journal

Disaster medicine and public health preparedness
ISSN: 1938-744X
Titre abrégé: Disaster Med Public Health Prep
Pays: United States
ID NLM: 101297401

Informations de publication

Date de publication:
02 2022
Historique:
pubmed: 25 8 2020
medline: 26 5 2022
entrez: 25 8 2020
Statut: ppublish

Résumé

Situational awareness (SA) is critical to mobilizing a rapid, efficient, and effective response to disasters. Limited by time and resources, response agencies must make decisions about rapidly evolving situations, which requires the collection, analysis, and sharing of actionable information across a complex landscape. Emerging technologies, if appropriately applied, can enhance SA and enable responders to make quicker, more accurate decisions. The aim of this systematic review is to identify technologies that can improve SA and assist decision-making across the United States Government and the domestic and international agencies they support during disaster response operations. A total of 1459 articles and 36 after-action reports were identified during literature searches. Following the removal of duplicates and application of inclusion/exclusion criteria, 302 articles and after-action reports were included in the review. Our findings suggest SA is constrained primarily due to unreliable and significantly delayed communications, time-intensive data analysis and visualization, and a lack of interoperable sensor networks and other capabilities providing data to shared platforms. Many of these challenges could be addressed by existing technologies. Bridging the divide between research and development efforts and the operational needs of response agencies should be prioritized.

Identifiants

pubmed: 32829725
pii: S1935789320001962
doi: 10.1017/dmp.2020.196
doi:

Types de publication

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

Langues

eng

Sous-ensembles de citation

IM

Pagination

341-359

Auteurs

Tara Kedia (T)

Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland.

Jeremy Ratcliff (J)

Nuffield Department of Medicine, Peter Medawar Building for Pathogen Research, University of Oxford, Oxford, United Kingdom.

Megan O'Connor (M)

Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland.

Sophia Oluic (S)

Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland.

Michelle Rose (M)

Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland.

Jeff Freeman (J)

Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland.

Kaitlin Rainwater-Lovett (K)

Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland.

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Classifications MeSH