Common tenets in the field of emergency management hold that all disasters are different and all disasters hold a great deal of uncertainty. For these and many other reasons, many challenges are present when providing post-disaster assistance to victims. The Federal Emergency Management Agency (FEMA) has identified post-disaster interim housing as one of its greatest challenges. These challenges have been highlighted in recent years in the media as spectacular failures as evidenced during the recovery efforts for Hurricane Katrina. Partly in response, FEMA developed the National Disaster Housing Strategy that establishes the framework and strategic goals of providing housing to disaster victims. This strategy calls for emergency management professionals to both anticipate needs and balance a host of factors to provide quick, economical, and community-based housing solutions that meet the individual, family, and community needs while enabling recovery. The first problem is that emergency management officials need to make decisions early on without actual event data in order to provide timely interim housing options to victims. The second problem is that there is little guidance and no quantitative measures on prioritizing the many factors that these same officials need for providing interim housing. This research addressed both of these problems. To anticipate needs, a series of models were developed utilizing historical data provided by FEMA and regression analysis to produce a series of forecast models. The models developed were for the cost of a housing mission, the number of individuals applying to FEMA for assistance, the number of people eligible for housing assistance and the number of trailers FEMA will provide as interim housing. The variables analyzed and used to make the prediction were; population, wind-speed, homeownership rate, number of households, income, and poverty level. Of the four models developed, the first three demonstrated statistical significance, while the last one did not. The models were limited only to wind related hazards. These models and associated forecasts can assist federal, state, and local government officials with scoping and planning for a housing mission. In addition, the models also provide insight into how the six variables used to make the prediction can influence it. The second part of this research used a structured feedback process (Delphi) and expert opinion to develop a ranked list of the most important factors that emergency management officials should consider when conducting operational planning for a post-disaster housing mission. This portion of the research took guidance from the "National Disaster Housing Strategy" and attempted to quantify it based on the consensus opinion of a group of experts. The top three factors that were determined by the Delphi were 1) House disaster survivors as soon as possible 2) The availability of existing housing and 3) Status of infrastructure.
|Advisor:||Shaw, Greg L.|
|Commitee:||Deason, Jonathan, Jack, Harrald, Santos, Joost, Steve, Diaz|
|School:||The George Washington University|
|Department:||Engineering Mgt and Systems Engineering|
|School Location:||United States -- District of Columbia|
|Source:||DAI-A 75/11(E), Dissertation Abstracts International|
|Subjects:||Systems science, Urban planning|
|Keywords:||Disaster, Forecasting, Housing, Interim, Planning, Post-disaster|
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