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A Pre-Generation of Emergency Reference Plan Model of Public Health Emergencies with Case-Based Reasoning

BACKGROUND AND PURPOSE: In the early 21st century, the coronavirus alone has ravaged the world three times. Public health emergencies have caused a tremendous negative impact on public health, daily life, and global economic development, for having the characteristics of complexity and great harm. T...

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Autores principales: Ru, Danyang, Wen, Haoyu, Zhang, Yuntao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9762414/
https://www.ncbi.nlm.nih.gov/pubmed/36544507
http://dx.doi.org/10.2147/RMHP.S385967
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author Ru, Danyang
Wen, Haoyu
Zhang, Yuntao
author_facet Ru, Danyang
Wen, Haoyu
Zhang, Yuntao
author_sort Ru, Danyang
collection PubMed
description BACKGROUND AND PURPOSE: In the early 21st century, the coronavirus alone has ravaged the world three times. Public health emergencies have caused a tremendous negative impact on public health, daily life, and global economic development, for having the characteristics of complexity and great harm. To tackle these problems, a pre-generation of emergency reference plan model of public health emergencies is proposed to better deal with the outbreak and spread of public health events. METHODS: The method is divided into three stages. First, the modified SEIR model is used to predict the attribute values of the target case. Then, the similar case sets are extracted and filtered by calculating the similarity through the cross-efficiency evaluation method with the parallel system. Finally, the multi-stage emergency effect evaluation model is conducted so that the emergency plan with the best response effect at this stage can be made for reference. RESULTS: We collected 25 typical events of COVID-19 that occurred in 11 cities in China as historical case bases and target cases, respectively. The result of the experiment verified the feasibility and effectiveness of the proposed method. CONCLUSION: This paper presents a new perspective on making a public health emergency plan, which could improve the decision-making accuracy and efficiency, maximize the emergency effect and save precious time for emergency response. This model can provide rapid decision supports for decision-making for public services such as government departments, centers for disease control, medical emergency centers and transport authorities, etc.
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spelling pubmed-97624142022-12-20 A Pre-Generation of Emergency Reference Plan Model of Public Health Emergencies with Case-Based Reasoning Ru, Danyang Wen, Haoyu Zhang, Yuntao Risk Manag Healthc Policy Original Research BACKGROUND AND PURPOSE: In the early 21st century, the coronavirus alone has ravaged the world three times. Public health emergencies have caused a tremendous negative impact on public health, daily life, and global economic development, for having the characteristics of complexity and great harm. To tackle these problems, a pre-generation of emergency reference plan model of public health emergencies is proposed to better deal with the outbreak and spread of public health events. METHODS: The method is divided into three stages. First, the modified SEIR model is used to predict the attribute values of the target case. Then, the similar case sets are extracted and filtered by calculating the similarity through the cross-efficiency evaluation method with the parallel system. Finally, the multi-stage emergency effect evaluation model is conducted so that the emergency plan with the best response effect at this stage can be made for reference. RESULTS: We collected 25 typical events of COVID-19 that occurred in 11 cities in China as historical case bases and target cases, respectively. The result of the experiment verified the feasibility and effectiveness of the proposed method. CONCLUSION: This paper presents a new perspective on making a public health emergency plan, which could improve the decision-making accuracy and efficiency, maximize the emergency effect and save precious time for emergency response. This model can provide rapid decision supports for decision-making for public services such as government departments, centers for disease control, medical emergency centers and transport authorities, etc. Dove 2022-12-15 /pmc/articles/PMC9762414/ /pubmed/36544507 http://dx.doi.org/10.2147/RMHP.S385967 Text en © 2022 Ru et al. https://creativecommons.org/licenses/by-nc/3.0/This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/ (https://creativecommons.org/licenses/by-nc/3.0/) ). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
spellingShingle Original Research
Ru, Danyang
Wen, Haoyu
Zhang, Yuntao
A Pre-Generation of Emergency Reference Plan Model of Public Health Emergencies with Case-Based Reasoning
title A Pre-Generation of Emergency Reference Plan Model of Public Health Emergencies with Case-Based Reasoning
title_full A Pre-Generation of Emergency Reference Plan Model of Public Health Emergencies with Case-Based Reasoning
title_fullStr A Pre-Generation of Emergency Reference Plan Model of Public Health Emergencies with Case-Based Reasoning
title_full_unstemmed A Pre-Generation of Emergency Reference Plan Model of Public Health Emergencies with Case-Based Reasoning
title_short A Pre-Generation of Emergency Reference Plan Model of Public Health Emergencies with Case-Based Reasoning
title_sort pre-generation of emergency reference plan model of public health emergencies with case-based reasoning
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9762414/
https://www.ncbi.nlm.nih.gov/pubmed/36544507
http://dx.doi.org/10.2147/RMHP.S385967
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