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Early warning system models and components in emergency and disaster: a systematic literature review protocol
BACKGROUND: Emergency and disaster are on the rise in the world. One of the most important components of disaster risk management is the early warning system. Studies have shown divergent models of warning systems with different structures. However, since no systematic review of early warning system...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6896508/ https://www.ncbi.nlm.nih.gov/pubmed/31810477 http://dx.doi.org/10.1186/s13643-019-1211-5 |
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author | Khankeh, Hamid Reza Hosseini, Seyed Hossein Farrokhi, Mehrdad Hosseini, Mohammad Ali Amanat, Nasir |
author_facet | Khankeh, Hamid Reza Hosseini, Seyed Hossein Farrokhi, Mehrdad Hosseini, Mohammad Ali Amanat, Nasir |
author_sort | Khankeh, Hamid Reza |
collection | PubMed |
description | BACKGROUND: Emergency and disaster are on the rise in the world. One of the most important components of disaster risk management is the early warning system. Studies have shown divergent models of warning systems with different structures. However, since no systematic review of early warning systems in disasters has been conducted so far, a systematic review of the models, components, and structures of these systems is essential. This protocol is a systematic review study, which aims to evaluate the existing warning systems and their structure. METHODOLOGY: This study attempts to comprehensively search the previous studies with terms and expressions including disaster, emergency model, early warning system, and their synonyms at MESH. To this end, English articles, which have been published from 1980 to 2019, will be assessed. Google Scholar, PubMed, Web of Science, and Scopus databases as well as relevant specialized websites will be searched. Studies will be evaluated by two individuals independently. DISCUSSION: To the best of our knowledge, no systematic review of models, structures, and components of the early warning system has been conducted so far. This study is the first attempt to comprehensively evaluate the models and components of early warning systems. Accordingly, this study will provide evidence of models, structures and elements of the early warning systems. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42018116111 |
format | Online Article Text |
id | pubmed-6896508 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-68965082019-12-11 Early warning system models and components in emergency and disaster: a systematic literature review protocol Khankeh, Hamid Reza Hosseini, Seyed Hossein Farrokhi, Mehrdad Hosseini, Mohammad Ali Amanat, Nasir Syst Rev Protocol BACKGROUND: Emergency and disaster are on the rise in the world. One of the most important components of disaster risk management is the early warning system. Studies have shown divergent models of warning systems with different structures. However, since no systematic review of early warning systems in disasters has been conducted so far, a systematic review of the models, components, and structures of these systems is essential. This protocol is a systematic review study, which aims to evaluate the existing warning systems and their structure. METHODOLOGY: This study attempts to comprehensively search the previous studies with terms and expressions including disaster, emergency model, early warning system, and their synonyms at MESH. To this end, English articles, which have been published from 1980 to 2019, will be assessed. Google Scholar, PubMed, Web of Science, and Scopus databases as well as relevant specialized websites will be searched. Studies will be evaluated by two individuals independently. DISCUSSION: To the best of our knowledge, no systematic review of models, structures, and components of the early warning system has been conducted so far. This study is the first attempt to comprehensively evaluate the models and components of early warning systems. Accordingly, this study will provide evidence of models, structures and elements of the early warning systems. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42018116111 BioMed Central 2019-12-06 /pmc/articles/PMC6896508/ /pubmed/31810477 http://dx.doi.org/10.1186/s13643-019-1211-5 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Protocol Khankeh, Hamid Reza Hosseini, Seyed Hossein Farrokhi, Mehrdad Hosseini, Mohammad Ali Amanat, Nasir Early warning system models and components in emergency and disaster: a systematic literature review protocol |
title | Early warning system models and components in emergency and disaster: a systematic literature review protocol |
title_full | Early warning system models and components in emergency and disaster: a systematic literature review protocol |
title_fullStr | Early warning system models and components in emergency and disaster: a systematic literature review protocol |
title_full_unstemmed | Early warning system models and components in emergency and disaster: a systematic literature review protocol |
title_short | Early warning system models and components in emergency and disaster: a systematic literature review protocol |
title_sort | early warning system models and components in emergency and disaster: a systematic literature review protocol |
topic | Protocol |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6896508/ https://www.ncbi.nlm.nih.gov/pubmed/31810477 http://dx.doi.org/10.1186/s13643-019-1211-5 |
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