Analysis of Effects of Socioeconomic Status on Hurricane Disaster Relief Plans

Abstract

Understanding the impacts of transportation policies on different socio-economic groups is a crucial part of ensuring equity in the overall transportation planning process. However, despite substantial research on the socioeconomic impacts of transportation in various contexts, there has been relatively little discussion of their potential influence on the provision of disaster relief. After the recent catastrophic natural disasters and terrorist acts around the world, transportation for disaster relief has become an increasingly important area of research. This paper focuses on the provision of disaster relief after a hurricane. By using a spatial model developed to site facilities for the distribution of relief goods, the study described in this paper considered the various decisions related to where these facilities should be located and investigated the differential impacts of the decisions on socioeconomically disadvantaged groups. The model is formulated and solved by using spatial data for a midsized city in the southeastern United States. The results of the analysis point out the differential accessibility to relief goods that population groups may experience and suggest that consideration of socioeconomic status in future disaster relief decision making is warranted.

The effects of transportation network failure on people’s accessibility to hurricane disaster relief goods: a modeling approach and application to a Florida case study

“…One related set of issues would be incorporating uncertainty about relief demand and/or the types of goods/services available at sited centers. The question about relief demand could be augmented with additional data on social vulnerability (Zahran et al 2008;Cutter et al 2003) to get an even better handle on who might be most likely in need of service, along the lines of Horner and Downs (2008) who incorporated data on personal incomes to proxy vulnerability. Also, given the challenging nature of solving large capacitated median problems in this particular instance (594 nodes), future work should consider alternative solution approaches other than those available in commercial optimization software, which might speed computation time.…”

“…Among these, uncertainty with respect to demand (i.e., how many people will actually stay behind and need relief service) and its spatial distribution are considerations (Horner and Downs 2008;Sheu 2010). From a transportation perspective, however, network uncertainties must also be considered.…”

“…Later work refined this strategy to more carefully weight the linkages between neighborhoods and distribution points, so as to maximize people's overall accessibility to these facilities (Horner and Downs 2010). Still, other approaches to the relief facility problem focused solely on minimizing the transportation costs between sited centers and population demand, thereby ignoring the centers' locations with respect to larger warehouses that might be used to re-stock them with supplies (Horner and Downs 2008). Given the focus of this paper, we adopt the latter view and employ a model that optimizes the locations of relief distribution centers relative to populations in need.…”

“…Scanning the literature on hurricane disaster relief provision, there are no studies that expressly consider the potential damage that may be caused to a transportation network by such storms. In fact, studies have treated the network as if it would be fully available for supporting post-event relief efforts (Horner and Downs 2008). While it is possible to make the argument that networks in many places are ''robust'' and people would ''find a way'' to access goods, it would be instructive for planning and policy efforts to learn more about the effects of potential network failures on the provision of disaster relief.…”

A hierarchical approach to modeling hurricane disaster relief goods distribution

“…Horner et al initially described major considerations for planning hurricane disaster relief networks (Horner and Downs, 2007), moved to design policy-oriented spatial optimization models for distributing goods after a hurricane (Horner and Downs, 2010) and looked at the possible impacts of various distribution point location strategies on disadvantaged populations (Horner and Downs, 2008;Horner and Widener, 2010).…”