An Analytics Framework to Support Surge Capacity Planning for Emerging Epidemics

Martina Curran, E. Howley, J. Duggan
{"title":"An Analytics Framework to Support Surge Capacity Planning for Emerging Epidemics","authors":"Martina Curran, E. Howley, J. Duggan","doi":"10.1145/2896338.2896354","DOIUrl":null,"url":null,"abstract":"Epidemics are a serious public health challenge, with epidemiologists and health analysts constantly trying to find more succinct ways to predict, and then prevent or minimize their impact. An important problem facing health systems is ensuring they are prepared for severe epidemics. Being able to predict an epidemic is only one part of the problem: resources need to be monitored in order to ensure their availability in the event of severe epidemics. Using System Dynamic modelling, health analysts can predict epidemics to a certain extent using previous infection dynamics, however mitigation strategies would be improved dramatically if the prediction was in real-time, utilizing the full potential of information from a range of sources: participatory surveillance systems, sentinel data from General Practitioners (GPs) etc. Using these techniques alongside Surge Capacity modelling allows the monitoring of resources for all areas of the health system, equipment levels, staff levels, and bed availability etc., ensuring better preparedness. This paper introduces a way to bring these concepts together, and highlights future work which will expand on these ideas allowing for the possible reallocation of resources in the event of shortage in some areas, and spare capacity in others.","PeriodicalId":146447,"journal":{"name":"Proceedings of the 6th International Conference on Digital Health Conference","volume":"111 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 6th International Conference on Digital Health Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2896338.2896354","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

Abstract

Epidemics are a serious public health challenge, with epidemiologists and health analysts constantly trying to find more succinct ways to predict, and then prevent or minimize their impact. An important problem facing health systems is ensuring they are prepared for severe epidemics. Being able to predict an epidemic is only one part of the problem: resources need to be monitored in order to ensure their availability in the event of severe epidemics. Using System Dynamic modelling, health analysts can predict epidemics to a certain extent using previous infection dynamics, however mitigation strategies would be improved dramatically if the prediction was in real-time, utilizing the full potential of information from a range of sources: participatory surveillance systems, sentinel data from General Practitioners (GPs) etc. Using these techniques alongside Surge Capacity modelling allows the monitoring of resources for all areas of the health system, equipment levels, staff levels, and bed availability etc., ensuring better preparedness. This paper introduces a way to bring these concepts together, and highlights future work which will expand on these ideas allowing for the possible reallocation of resources in the event of shortage in some areas, and spare capacity in others.
支持新出现流行病的激增能力规划的分析框架
流行病是一项严重的公共卫生挑战,流行病学家和卫生分析师不断试图找到更简洁的方法来预测,然后预防或尽量减少其影响。卫生系统面临的一个重要问题是确保它们为严重流行病做好准备。能够预测流行病只是问题的一部分:需要监测资源,以确保在发生严重流行病时能够获得资源。使用系统动态建模,卫生分析人员可以在一定程度上利用以前的感染动态预测流行病,但是,如果预测是实时的,利用来自一系列来源的信息的全部潜力,如参与式监测系统、全科医生的哨点数据等,缓解策略将得到极大改善。将这些技术与激增能力模型一起使用,可以监测卫生系统所有领域的资源、设备水平、工作人员水平和床位供应情况等,确保更好地做好准备。本文介绍了一种将这些概念结合在一起的方法,并强调了未来的工作,将扩展这些想法,允许在某些地区短缺和其他地区闲置产能的情况下可能的资源重新分配。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信