Modeling and Optimizing the Public-Health Infrastructure for Emergency Response
Modeling and Optimizing the Public-Health Infrastructure for Emergency Response
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DOI：
10.1287/inte.1090.0463
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发表时间：
2009-09-01
期刊：
影响因子：
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通讯作者：
Benecke, Bernard
中科院分区：
文献类型：
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作者：
Lee, Eva K.;Chen, Chien-Hung;Benecke, Bernard
公共卫生紧急情况，如生物恐怖袭击或流行病，需要快速，高效，大规模的关键医疗对策分配。通过将数学建模、大规模仿真和强大的优化引擎相结合，并将它们与自动绘图工具和用户友好的界面相耦合，设计并实现了一个快速实用的应急响应决策支持工具RealOpt（c）。RealOpt允许公共卫生紧急协调员（1）确定分发点（POD）设施设置的位置;（2）通过自动绘图工具为POD设计定制和高效的平面图;（3）确定所需的劳动力资源，并在POD内的各个站点提供工作人员的有效安置;（4）进行疾病传播分析，了解和监测POD内疾病困境，并帮助制定动态响应策略以减轻伤亡;（5）评估资源并确定最低需求，以便为在紧急情况下治疗其区域人口做好准备;（6）开展大规模虚拟演习和绩效分析，并研究替代战略;以及（7）设计包括紧急事件演习的各种分配方案以训练人员。这些先进而强大的计算策略使紧急协调员能够快速分析设计决策，根据可用的最佳估计和分析生成可行的区域分配计划，并在事件展开时重新配置POD。分析规划策略、比较各种选项并确定最具成本效益的分配策略组合的能力对于任何大规模分配工作的最终成功至关重要。
Public-health emergencies, such as bioterrorist attacks or pandemics, demand fast, efficient, large-scale dispensing of critical medical countermeasures. By combining mathematical modeling, large-scale simulation, and powerful optimization engines, and coupling them with automatic graph-drawing tools and a user-friendly interface, we designed and implemented RealOpt (c), a fast and practical emergency-response decision-support tool. RealOpt allows public-health emergency coordinators to (1) determine locations for point-of-dispensing (POD) facility setup; (2) design customized and efficient floor plans for PODs via an automatic graph-drawing tool; (3) determine required labor resources and provide efficient placement of staff at individual stations within a POD; (4) perform disease-propagation analysis, understand and monitor the intra-POD disease dilemma, and help to derive dynamic response strategies to mitigate casualties; (5) assess resources and determine minimum needs to prepare for treating their regional populations in emergency situations; (6) carry out large-scale virtual drills and performance analyses, and investigate alternative strategies; and (7) design a variety of dispensing scenarios that include emergency-event exercises to train personnel. These advanced and powerful computational strategies allow emergency coordinators to quickly analyze design decisions, generate feasible regional dispensing plans based on best estimates and analyses available, and reconfigure PODs as an event unfolds. The ability to analyze planning strategies, compare the various options, and determine the most cost-effective combination of dispensing strategies is critical to the ultimate success of any mass dispensing effort.