Ramisetty-Mikler Suhasini, Mikler Armin R, O'Neill Martin, Komatz Jared
Assistant Professor, Department of Epidemiology, University of North Texas Health Science Center at Fort Worth, Fort Worth, Texas.
Professor, Department of Computer Science and Engineering, Center for Computational Epidemiology and Response Analysis (CeCERA), University of North Texas, Denton, Texas.
J Emerg Manag. 2015 May-Jun;13(3):227-38. doi: 10.5055/jem.2015.0236.
The study focused on the methodological advancement and analytical approach of using multilevel data to define population vulnerability and risk in bioemergency disaster planning.
The authors considered two types of vulnerabilities, transportation vulnerability that stems from lack of access to transportation (public or private) and communication vulnerability that stems from unavailability of needed language-specific communication resources. The authors used Transit Authority general transit feed data and the American Community Survey 5-year estimate data (2006-2010 summary files) to quantify these vulnerabilities. These data were integrated with Topologically Integrated Geographic Encoding and Referencing (TIGER) data for spatial analysis. A response plan was generated for Tarrant County, TX, and deemed feasible before consideration of vulnerable populations.
The results point to the importance of integrating geographical and population demographic features that represent potential barriers to the optimum distribution and utilization of resources into the analysis of response plans. An examination of transportation vulnerabilities indicate that, of those vulnerable in Tarrant County, nearly 23,000 individuals will be at-risk of not being able to reach the Point Of Dispensing (POD) to obtain services as they are beyond walking distance to the POD and lack access to transportation resources. The analysis of language vulnerability depicts an uneven distribution resulting in nonuniform demand at PODs for translation resources. There are more than 11,000 at-risk households in the South East region of Tarrant County alone that are truly in need of translation services.
The authors demonstrated that multiple vulnerabilities at each POD can be quantified by aggregating the vulnerability at the available granularity (ie, all blocks or block groups) in a given service area. The quantification of vulnerability at each service area facilitates a POD-based at-risk analysis for the response plan. Disparities stemming from social, behavioral, cultural, economic, and health characteristics of diverse subpopulations could induce the need for additional targeted resources to support emergency response efforts.
本研究聚焦于在生物应急灾难规划中，运用多层次数据定义人群脆弱性和风险的方法改进及分析方法。
作者考虑了两种类型的脆弱性，一种是因缺乏交通方式（公共或私人交通）导致的交通脆弱性，另一种是因缺乏所需的特定语言通信资源导致的通信脆弱性。作者使用了交通管理局的一般公交出行数据和美国社区调查5年估计数据（2006 - 2010年汇总文件）来量化这些脆弱性。这些数据与拓扑集成地理编码与参考（TIGER）数据整合用于空间分析。为德克萨斯州塔兰特县生成了一个应对计划，在考虑脆弱人群之前被认为是可行的。
结果表明，将代表资源最优分配和利用潜在障碍的地理和人口统计特征纳入应对计划分析具有重要意义。对交通脆弱性的研究表明，在塔兰特县的脆弱人群中，近23000人因距离药品分发点（POD）步行距离之外且缺乏交通资源，面临无法到达POD获取服务的风险。对语言脆弱性的分析显示分布不均，导致POD对翻译资源的需求不一致。仅在塔兰特县东南部地区就有超过11000个真正需要翻译服务的风险家庭。
作者证明，通过汇总给定服务区域内可用粒度（即所有街区或街区组）的脆弱性，可以量化每个POD的多种脆弱性。每个服务区域脆弱性的量化有助于为应对计划进行基于POD的风险分析。不同亚人群的社会、行为、文化、经济和健康特征导致的差异可能促使需要额外的针对性资源来支持应急响应工作。
