title: Conceptual framework and quantification of population vulnerability for effective emergency response planning.
abstract: OBJECTIVE
  The study focused on the methodological advancement and analytical approach of using multilevel data to define population vulnerability and risk in bioemergency disaster planning.
  
  
  METHODS
  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.
  
  
  RESULTS
  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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Assistant Professor, Department of Epidemiology, University of North Texas Health Science Center at Fort Worth, Fort Worth, Texas.
authors.forename: Suhasini
authors.initials: S
authors.lastname: Ramisetty-Mikler
authors.affiliation: Professor, Department of Computer Science and Engineering, Center for Computational Epidemiology and Response Analysis (CeCERA), University of North Texas, Denton, Texas.
authors.forename: Armin R
authors.initials: AR
authors.lastname: Mikler
authors.affiliation: Research Analyst, Center for Computational Epidemiology and Response Analysis (CeCERA), Institute of Applied Science, University of North Texas, Denton, Texas.
authors.forename: Martin
authors.initials: M
authors.lastname: O'Neill
authors.affiliation: Research Specialist, Center for Health Statistics - Data Management Group, Texas Department of State Health Services, Austin, Texas.
authors.forename: Jared
authors.initials: J
authors.lastname: Komatz
mesh_terms: D003625:Data Collection; D004189:Disaster Planning / Q000458:organization & administration*; D060731:Emergency Responders; D006297:Health Services Accessibility; D006301:Health Services Needs and Demand; D006801:Humans; D035862:Vulnerable Populations / Q000706:statistics & numerical data*