This research seeks to improve the current state of knowledge about housing recovery following a major natural disaster through examining single family housing recovery following Hurricane Andrew, a category 5 hurricane, which impacted southern sections of Miami-Dade County in 1992. This inquiry focused on two questions: (1) what is the recovery process for single family housing in a disaster impact area, and (2) how does the housing recovery process vary across households and neighborhoods? To answer these questions, the 1992-96 tax appraisal values for Miami-Dade County were used to measure housing damage and recovery after the storm. Hierarchical Linear Modeling (HLM) was used to quantitatively model this recovery process and identify the major factors in play. With regard to the first question, our findings suggested that Hurricane Andrew caused extensive housing damage in the impact area, rendering an average loss to households of 50.4% of pre-disaster home value. Two years after the storm (1994), the average home value returned to its pre-disaster level. In the subsequent two years (1995-96), the average home value continued growing, representing a 7.6% and 14.9% gain, respectively, over the pre-disaster average. Regarding the second question, our analysis found that the housing recovery process varied significantly across households and neighborhoods. Owner-occupied homes recovered more rapidly than rental units. Household income had a positive effect on housing recovery. Our analysis also suggested that post-disaster home sales had a significant negative effect on housing recovery. Neighborhood race/ethnicity composition affected the housing recovery process. Homes in minority populated neighborhoods (both Hispanic and non-Hispanic Black) recovered more slowly than homes in majority populated areas (non-Hispanic White). When considering Cuban- Hispanics and non-Cuban Hispanics as two separate groups, neighborhoods with a higher concentration of Cuban-Hispanics, while having no clear advantage at the beginning of the recovery period, recovered more rapidly than other minority populated areas. Previous studies suggested that the long-term impact of natural disasters at the aggregated level is minimal, and yet our results showed that the housing impact of Hurricane Andrew lasted at least more than four years. In fact, housing inequality in the impact area increased markedly during the recovery process due to the unequal nature of housing recovery.

A large number of natural disasters affects hundreds of thousands of people each year in their housing around the world. Therefore, there is a call to find more appropriate strategies for housing reconstruction following a disaster. This study aims to reduce the construction time and cost of housing affected by such disasters. The academic literature on the 3 Dimensional Lightweight Panels construction system (3D-LPs), Building Information Modelling system (BIM) and experiences gained in post-disaster housing reconstruction strengthens the argument that here is an opportunity to contribute to solve the housing reconstruction problem. The study points out that the combination of these systems and community participation presents an option to produce both affordable and sustainable housing in the shortest time on a large scale by the affected people after overcoming the emergence phase of a disaster. A holistic philosophy was used to study the housing reconstruction problem as a whole to understand all parts of the problem and three research questions were set up to explore the possible solution to this problem. The research strategy to address the problem was based on a survey of worldwide experts, interviewing a forum of lightweight concrete panel manufacturers and the modelling of a basic housing prototype in BIM. Research question (1) How can displaced people use their own labour to save money and time? and research question (2) How does the 3D-LPs construction system contribute to housing recovery after natural disasters? Research questions (1) and (2) were answered by 17 open-ended questions conducted with 22 housing experts from 11 countries and 7 semi-structured interviews composed of 14 questions with 7 manufacturers of construction materials respectively which collected rich qualitative data (15,419 words) that were analysed in Nvivo 10 through pattern matching and validated by triangulation techniques to give reliability to the study. The housing prototype modelling was used to answer the research question (3) Can the BIM model show the cost-benefit in building housing with the 3D-LPs construction system and displaced people's own labour?The main findings of this study are that a housing prototype built with 3D-LPs is 36.82% cheaper in comparison to houses built with bricks and reinforcement elements and could be built by unskilled people in 90 days. The study provides novel in-depth knowledge of how unskilled people from communities affected should participate in housing reconstruction and how new construction systems can be implemented after disasters, which contributes to the body of knowledge. In addition, the study provides guidelines to implement a system directed at unskilled people and also Non-Governmental Organizations (NGOs) in a novel way, to help to solve the housing reconstruction problem and engage the displaced people in the housing reconstruction.

Anecdotal evidence in disaster studies suggests that multifamily housing takes longer to recover than single family homes, but almost no studies have provided quantitative evidence to clarify this “multifamily home lag” phenomenon. This research examines the recovery of single family, duplex, and apartment complex housing in south Miami-Dade County, Florida, after 1992 Hurricane Andrew to determine if there is indeed a "multifamily home lag." This research also provides a better understanding of the factors influencing the recovery trajectories of these three housing types. The findings of this research indicate that duplexes and apartment buildings have slower recovery trajectories than single family dwellings. In addition, rental housing, housing that sustained higher levels of damage, and single family dwellings and duplexes located in predominately non-Hispanic Black neighborhoods show significantly slower recovery trajectories. The analyses specific to apartment buildings also finds that apartment buildings with fewer than 10 units have significantly slower recovery trend than apartment buildings with more than 50 units.