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Systems modeling in support of evidence-based disaster planning for rural areas

The objective of this communication is to introduce a conceptual framework for a study that applies a rigorous systems approach to rural disaster preparedness and planning. System Dynamics is a well-established computer-based simulation modeling methodology for analyzing complex social systems that...

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Autores principales: Hoard, Marna, Homer, Jack, Manley, William, Furbee, Paul, Haque, Arshadul, Helmkamp, James
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Published by Elsevier GmbH 2005
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7185526/
https://www.ncbi.nlm.nih.gov/pubmed/15881985
http://dx.doi.org/10.1016/j.ijheh.2005.01.011
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author Hoard, Marna
Homer, Jack
Manley, William
Furbee, Paul
Haque, Arshadul
Helmkamp, James
author_facet Hoard, Marna
Homer, Jack
Manley, William
Furbee, Paul
Haque, Arshadul
Helmkamp, James
author_sort Hoard, Marna
collection PubMed
description The objective of this communication is to introduce a conceptual framework for a study that applies a rigorous systems approach to rural disaster preparedness and planning. System Dynamics is a well-established computer-based simulation modeling methodology for analyzing complex social systems that are difficult to change and predict. This approach has been applied for decades to a wide variety of issues of healthcare and other types of service capacity and delivery, and more recently, to some issues of disaster planning and mitigation. The study will use the System Dynamics approach to create computer simulation models as “what-if” tools for disaster preparedness planners. We have recently applied the approach to the issue of hospital surge capacity, and have reached some preliminary conclusions – for example, on the question of where in the hospital to place supplementary nursing staff during a severe infectious disease outbreak—some of which we had not expected. Other hospital disaster preparedness issues well suited to System Dynamics analysis include sustaining employee competence and reducing turnover, coordination of medical care and public health resources, and hospital coordination with the wider community to address mass casualties. The approach may also be applied to preparedness issues for agencies other than hospitals, and could help to improve the interactions among all agencies represented in a community's local emergency planning committee. The simulation models will support an evidence-based approach to rural disaster planning, helping to tie empirical data to decision-making. Disaster planners will be able to simulate a wide variety of scenarios, learn responses to each and develop principles or best practices that apply to a broad spectrum of disaster scenarios. These skills and insights would improve public health practice and be of particular use in the promotion of injury and disease prevention programs and practices.
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spelling pubmed-71855262020-04-28 Systems modeling in support of evidence-based disaster planning for rural areas Hoard, Marna Homer, Jack Manley, William Furbee, Paul Haque, Arshadul Helmkamp, James Int J Hyg Environ Health Article The objective of this communication is to introduce a conceptual framework for a study that applies a rigorous systems approach to rural disaster preparedness and planning. System Dynamics is a well-established computer-based simulation modeling methodology for analyzing complex social systems that are difficult to change and predict. This approach has been applied for decades to a wide variety of issues of healthcare and other types of service capacity and delivery, and more recently, to some issues of disaster planning and mitigation. The study will use the System Dynamics approach to create computer simulation models as “what-if” tools for disaster preparedness planners. We have recently applied the approach to the issue of hospital surge capacity, and have reached some preliminary conclusions – for example, on the question of where in the hospital to place supplementary nursing staff during a severe infectious disease outbreak—some of which we had not expected. Other hospital disaster preparedness issues well suited to System Dynamics analysis include sustaining employee competence and reducing turnover, coordination of medical care and public health resources, and hospital coordination with the wider community to address mass casualties. The approach may also be applied to preparedness issues for agencies other than hospitals, and could help to improve the interactions among all agencies represented in a community's local emergency planning committee. The simulation models will support an evidence-based approach to rural disaster planning, helping to tie empirical data to decision-making. Disaster planners will be able to simulate a wide variety of scenarios, learn responses to each and develop principles or best practices that apply to a broad spectrum of disaster scenarios. These skills and insights would improve public health practice and be of particular use in the promotion of injury and disease prevention programs and practices. Published by Elsevier GmbH 2005-04-08 2005-03-14 /pmc/articles/PMC7185526/ /pubmed/15881985 http://dx.doi.org/10.1016/j.ijheh.2005.01.011 Text en Copyright © 2005 Published by Elsevier GmbH. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Hoard, Marna
Homer, Jack
Manley, William
Furbee, Paul
Haque, Arshadul
Helmkamp, James
Systems modeling in support of evidence-based disaster planning for rural areas
title Systems modeling in support of evidence-based disaster planning for rural areas
title_full Systems modeling in support of evidence-based disaster planning for rural areas
title_fullStr Systems modeling in support of evidence-based disaster planning for rural areas
title_full_unstemmed Systems modeling in support of evidence-based disaster planning for rural areas
title_short Systems modeling in support of evidence-based disaster planning for rural areas
title_sort systems modeling in support of evidence-based disaster planning for rural areas
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7185526/
https://www.ncbi.nlm.nih.gov/pubmed/15881985
http://dx.doi.org/10.1016/j.ijheh.2005.01.011
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