Post-disaster Housing Recovery Research Articles

Post-disaster housing recovery estimation: Data and lessons learned from the 2017 Tubbs and 2018 Camp Fires

Post-wildfire housing recovery is a complex process for which systematically collected data remains scarce. Consequently, our ability to anticipate obstacles and plan for housing recovery from future events is limited. This study leverages housing permit datasets collected in Santa Rosa and Unincorporated Sonoma County, impacted by the 2017 Tubbs Fire, and Paradise, impacted by the 2018 Camp Fire. Permit and tax assessor data are combined to gain insights into the recovery processes for these communities. Although the percentage of rebuilt destroyed homes varies significantly between regions, the peak construction demand occurs around 1.5 years after each wildfire, with a substantial decline in the reconstruction rate after 2.5 years. Moreover, the pace of transition from permit application to reconstruction completion is similar across all three regions. Using this finding, we propose a methodology to forecast the number of parcels rebuilt per unit of time based on observations from prior events. A proof-of-concept application of the proposed methodology indicates that it estimates long-term housing recovery patterns based on permit application data collected within one year of the event. These findings indicate that a longitudinal housing recovery data database would help forecast housing recovery from future disasters by providing a source for early empirical validation of predictive models.

Sustainable development study of the post-disaster housing resettlement case in Yogyakarta Province, Indonesia case study: Nglepen Village and Pagerjurang Village

According to Government Regulation No. 21 of 2008, chapter 67, article 3, the Government of Indonesia promotes community involvement in the post-disaster housing recovery act. The resettlement case in Nglepen Village and Pagerjurang Village is categorized as a rapid and massive recovery based on a contractor-based strategy due to limited land availability, budgetary constraints, post-disaster emergency conditions, and the government’s responsibility to provide large numbers of sufficient housing units. In specific circumstances, the condition of the relocation houses will typically not be able to meet the needs of most residents. This study emphasized the sustainable development of the two case studies and highlighted different private residential housing types: 1) a dome-shaped reinforced structure house in Nglepen and 2) a conventional reinforced concrete structural frame house in Pagerjurang. The two different structural housing system types will affect the sustainable development of the housing condition. Field surveys and interviews were conducted in 2022–2023 to collect the primary data, and study of literacy was used to support the findings and analyzed through a descriptive qualitative method. The sustainable development in the case study relocation area is mainly influenced by aspects such as the economic sector, development priorities related to the residents’ activities and needs, and the adaptive design strategy between old and new buildings. According to the disaster management law and derivative regulations, the Government of Indonesia has sought ideal conditions for disaster-affected residents in the relocation and reconstruction processes. The study’s conclusions suggested that the government, beneficiaries, and all stakeholders must collaborate to improve post-disaster housing and settlement relocation planning and reconstruction in the future by involving the residents in the process of deciding on the location, managing the development, and creating comprehensively sustainable development guidelines for the people’s houses and its living environment.

Modeling post-disaster recovery: Accounting for rental and multi-family housing

Post-disaster housing recovery models increase our understanding of recovery dynamics, vulnerable populations, and how people are affected by the direct losses that disasters create. Past recovery models have focused on single-family owner-occupied housing, while empirical evidence shows that rental units and multi-family housing are disadvantaged in post-disaster recovery. To fill this gap, this article presents an agent-based housing recovery model that includes the four common type–tenure combinations of single- and multi-family owner- and renter-occupied housing. The proposed model accounts for the different recovery processes, emphasizing funding sources available to each type–tenure. The outputs of our model include the timing of financing and recovery at building resolution across a community. We demonstrate the model with a case study of Alameda, California, recovering from a simulated M7.0 earthquake on the Hayward fault. The processes in the model replicate higher non-recovery of multi-family housing than single-family housing, as observed in past disasters, and a heavy reliance of single-family renter-occupied units on Small Business Administration funding, which is expected due to low earthquake insurance penetration. The simulation results indicate that multi-family housing would have the highest portion of unmet need remaining; however, some buildings with unmet needs are anticipated to be able to obtain a large portion of their funding. The remaining portion may be filled using personal financing or may be overcome with downsizing or downgrades. Multi-family housing would also benefit the most from Community Development Block Grants for Disaster Recovery (CDBG-DR). This benefit is a result of modeling the financing sources, that CDBG-DR is available, and that many multi-family buildings do not qualify for other sources. Communities’ allocation of public funding is important for housing recovery. Our model can help inform and compare potential financing policies to allocate public funds.

A Model of Build Back Better Utilization: Long-Term Recovery Groups and Post-Disaster Housing Recovery

Housing recovery, especially for vulnerable populations, can be a challenging process. Questions regarding whether to rebuild damaged housing and whether to restore it to its previous state or to build back better must be answered. In the United States, Long-Term Recovery Groups (LTRGs) play a crucial role in channeling assistance to vulnerable community members as they embark on housing recovery. However, the experiences of LTRGs have been understudied. To address this gap, the study utilizes interviews with a diverse range of LTRG members and develops an agent-based model following the Overview, Design concepts, and Details (ODD) protocol. The results highlight the consequences of adopting or not adopting a Build Back Better (BBB) approach in post-disaster recovery. Communities do not uniformly adhere to the same reconstruction approach, as evidenced by insights from LTRG interviews. BBB implementation is uneven in US LTRGs. BBB has higher initial costs but lower long-term costs because it increases community resilience and sustainability.

Dynamic economic resilience scenarios for measuring long-term community housing recovery

ABSTRACT The research measures post-disaster long-term housing recovery to assess community resilient recovery using the case of Broadmoor, a community located in New Orleans. Dynamic economic resilience scenarios calculate post-disaster housing recovery and differences of rebuilding using three housing recovery scenarios (baseline, reference recovery and dynamic economic resilience). The baseline scenario projects changes in housing market values without a disaster. The reference recovery scenario calculates post-disaster housing reconstruction values (e.g. repair rates and housing rebuilding permits), and a hypothetical housing recovery profile using damage assessments and building permits for rebuilding based on available investments (insurance and buy-outs). The dynamic economic resilience scenario models all potential and accelerated investments (uninsured versus insured, or buyouts for homeowners). A future dynamic economic resilience recovery scenario takes into account the benefits of housing reconstruction improvements, (e.g. levee and pump investments). The results identify an ideal sustainable long-term recovery threshold of three years after the disaster event. The results reveal the conceptualised dynamic economic resilience scenarios leads to shorter time-paths for recovery, and that the sustainable long-term recovery threshold is approximately three years after the disaster event.

A system disconnected: perspectives on post-disaster housing recovery policy and programs

This study provides insights from individuals working to reestablish permanent housing in Sea Bright, NJ, following Hurricane Sandy. To collect these perspectives, we gathered data in two ways: a self-administered questionnaire and semi-structured interviews. We mailed questionnaires to every household in Sea Bright that included a number of fixed response items and open-ended questions that focused on the interface of government and citizens to discuss their housing recovery process and problems or pitfalls they have encountered while recovering. To complement our questionnaire data, we conducted interviews with full-time residents, part-time residents, homeowners, renters, and representatives of the local, state, and federal government. We utilized conventional content analysis methods to discover sociological themes, focusing on the underlying behaviors, actions, and emotions the text portrayed. Several powerful themes emerged from our analysis of the open-ended questions and interviews. Most notably, we found a fundamental disconnect between how policymakers and homeowners viewed the housing recovery process. In particular, survivors highlighted the amount of and complexity-laden paperwork associated with the aid process, unfavorable interactions with government employees and a system that seemed to have goals that were inherently different from their own, and the sense that the rules associated with aid were constantly changing. We conclude with a discussion of additional research needs and some preliminary policy recommendations based on these insights.

Structural Adjustment and Community Resilience: The Case of Postdisaster Housing Recovery After the Canterbury Earthquakes of 2010 and 2011.

This project is a case study of postdisaster housing recovery in Christchurch, New Zealand, after the Canterbury earthquakes of 2010 and 2011. In this qualitative study, we analyzed the statutory framework governing the process of postdisaster housing recovery and its impact on local democracy. We also explored the role of communities and the third sector in housing and urban renewal. This aim was to contribute to the development of a critical theoretical understanding of community resilience as an inherently political concept. Community resilience is influenced by causal factors or generative mechanisms that affect the relations between people in a particular social context. We completed a narrative synthesis of textual data from the thematic analysis of in-depth interviews with key informants, related policies, media, and fieldwork. A centralization of government authority over housing recovery resulted in an erosion of democracy and representative government at a local level. This centralization had major impacts on communities and their voice in the process of postdisaster housing recovery. Communities, however, never relented and worked tirelessly among themselves and with other social sectors to make a positive impact on postdisaster housing and urban recovery against difficult odds and stretched resources. This immense social capital and inspiring sense of community must be fostered and given the opportunity to democratically participate in the development of recovery policy as a key element of community resilience.

Role of Spatial Effect in Postdisaster Housing Recovery: Case Study of Hurricane Katrina

This study examines the influence of spatial effect and demographic characteristics on postdisaster households’ relocations at the block group level. Data for 479 block groups were collected in the city of New Orleans following Hurricane Katrina. The explanatory variables were transformed into five uncorrelated principal components using principal component analysis and spatial autocorrelation of the relocation decision of households tested using Moran’s I index. The results indicate households’ decisions exhibit significant spatial clustering. A better statistical fit was found for spatial lag regression than standard linear regression and other spatial models. Four statistically significant components influencing the block group level percentage of relocated households were identified. Specifically, places characterized by a greater proportion of the population with higher income population and out-of-county employment are more likely to experience high rates of relocation. In addition, family ties and place attachment had significant negative effects on the rate of block group-level relocation.

Postdisaster Housing Stages: A Markov Chain Approach to Model Sequences and Duration Based on Social Vulnerability.

Housing recovery is an unequal and complex process presumed to occur in four stages: emergency shelter, temporary shelter, temporary housing, and permanent housing. This work questions the four-stage typology and examines how different types of shelter align with multiple housing recovery stages given different levels of social vulnerability. This article also presents a Markov chain model of the postdisaster housing recovery process that focuses on the experience of the household. The model predicts the sequence and timing of a household going through housing recovery, capturing households that end in either permanent housing or a fifth possible stage of failure. The probability of a household transitioning through the stages is computed using a transition probability matrix (TPM). The TPM is assembled using proposed transition probability models that vary with the social vulnerability of the household. Monte Carlo techniques are applied to demonstrate the range of sequences and timing that households experience going through the housing recovery process. A set of computational rules are established for sending a household to the fifth stage, representing a household languishing in unstable housing. This predictive model is exemplified on a virtual community, Centerville, where following a severe earthquake scenario, differences in housing recovery times exceed four years. The Centerville analysis results in nearly 5% of households languishing in unstable housing, thereby failing to reach housing recovery. These findings highlight the disparate trajectories experienced by households with different levels of social vulnerability. Recommendations are provided at the end for more equitable postdisaster recovery policies.

A spatially explicit model of postdisaster housing recovery

AbstractAlthough postdisaster housing recovery is an important player in community recovery, its modeling is still in its infancy. This research aims to provide a spatial regression model for predicting households’ recovery decisions based on publicly available data. For this purpose, a hierarchical Bayesian geostatistical model with random spatial effects was developed. To calibrate the model, households’ data that were collected from Staten Island, New York, in the aftermath of Hurricane Sandy were used. The model revealed that on the scale of census tract, residents with higher income or larger household size were significantly less likely to reconstruct. In contrast, odds of reconstruction rose with increase of long‐term residents. The model outputs were also employed to develop a reconstruction propensity score for each census tract. The score predicts probability of reconstruction/repair in each tract versus others. The model was validated through comparison of the propensity scores with the distribution of Community Development Block Grant Disaster Recovery assistance and its resultant reconstruction. The validation indicated capability of the model to predict the potential hotspots of reconstruction. Accordingly, the propensity score can serve as a decision‐support tool to tailor recovery policies.

Anchors of Social Network Awareness Index: A Key to Modeling Postdisaster Housing Recovery

AbstractReestablishment of housing is a crucial component of the recovery process and has a domino effect on the overall timing of recovery. Anchors of social networks, such as schools and churches...

Theorizing distributive justice and the practice of post-disaster housing recovery

ABSTRACTThis paper examines the implications of contemporary conceptions of distributive justice for post-disaster recovery programmes. The question asked in this paper is essentially theoretical: what does a concern with distributive justice entail when developing and evaluating post-disaster recovery programmes? Housing recovery programmes are employed to provide a contextual grounding for the discussion. We present a review of the disaster recovery literature and recent programmes of post-disaster housing recovery to map the ways in which distributive justice have been theorized, interpreted, debated and put into practice. We reflect on what different principles of distributive justice imply for post-disaster recovery programmes in terms of their impact on opportunities for individuals and communities to recover from disasters, and also on their realizing possibilities of advancing justice in the post-disaster society. The paper concludes by outlining a number of dimensions of a pluralist account of distributive justice. Using these dimensions and taking into account tensions within and between them, we attempt to offer a framework for reflecting on and assessing distributive arrangements of disaster recovery programmes.

The Role of Residential Buyouts in Post-Disaster Housing Recovery Support: A Comparison of Recent Cases from Japan and the United States

After recent disasters in Japan and the United States, government acquisition of residential land has played a larger and increasing role within and in relation to housing recovery support programs. With different historical, legal, and governance contexts, residential buyouts are shaped by the respective policies of each country. Framed by earlier precedents, this paper explains the development and implementation of residential buyout programs used after recent disasters: the 2011 Great East Japan Earthquake and tsunami in Japan and 2012 Superstorm Sandy in New York City and New York State in the United States. Through a comparison of roles of buyout in relationship to other aspects of postdisaster housing reconstruction and recovery support, some similarities are identified in the challenges of implementation, as well as uniquely different issues faced by the affected communities and households in each case.

Perceived neighborhood boundaries: A missing link in modeling post-disaster housing recovery

Literature in the domain of disasters has highlighted the importance of reestablishment of housing to restore a community due to its ripple effect on the overall timing of recovery. In fact, previous research studies have revealed the significance of members of social support networks, such as neighbors, church members, and others who share local communal spaces, on the making of recovery decisions. The objective of this research is to explore the determinants that drive households’ perceived neighborhood boundaries, which will in turn facilitate future research on exploring the importance of community assets which would lead to establishment of these social support networks within perceived neighborhoods. To accomplish this, an online survey was designed and conducted in the states of New York and Louisiana, which bore the brunt of the nation's two costliest hurricanes, Sandy and Katrina. The survey provided an online graphical user interface with which participants could manually draw a polygon around the area they perceived to be their neighborhood. These manually-selected neighborhoods were then compared to fixed units defined by the Census Bureau to check for similarities and differences. In summary, out of various internal attributes, prior disaster-related personal impact resulted in identifying larger areas as perceived neighborhood boundaries. Similarly, location density was shown to have an increasing effect on perceived neighborhood area. Moreover, married participants tended to have larger perceived neighborhoods when compared to their unmarried counterparts. Finally, the results revealed a direct relationship between number of perceived community assets and size of perceived neighborhood.

An interdisciplinary system dynamics model for post-disaster housing recovery

Many previous disasters have demonstrated the need for extensive personal, public, and governmental expenditures for housing recovery highlighting the importance of studying housing recovery. Yet, much research is still needed to fully understand the multi-faceted and complex nature of housing recovery. The goal of this paper is to present a holistic model to further the understanding of the dynamic processes and interdependencies of housing recovery. The impetus for this work is that inequalities in housing recovery could be addressed more effectively if we better understood interconnected factors and dynamic processes that slow down recovery for some. Currently, there is a lack of understanding about such factors and processes. Literature from engineering and social sciences was reviewed to develop an integrated system dynamics model for post-disaster housing recovery. While it is beyond current capabilities to quantify such complexities, the presented model takes a major stride toward articulating the complex phenomenon that is housing recovery.

Post-disaster housing recovery guidelines for development countries based on experiences in the American continent

The main purpose of this article is to propose recommendations to the processes of post-disaster recovery in development countries, focusing on housing recovery, based on the analysis of three relevant experiences in the American continent. The methodology adopted is based on the study of real cases of post-disaster recovery and the data was obtained through bibliographic research, documentary collection and also participant observation using the O-P-R (Observation-Participation-Reflection) model. A discussion on key aspects of housing recovery was performed based on the cases and, as a final result, recommendations are presented considering the psychosocial and the social capital recovery, the restoration of livelihoods, the supply of temporary housing and shelters, the selection of beneficiaries for the habitational recovery programs, the provision of permanent housing and the governance in the disaster recovering process.

Rethinking “Build Back Better” in housing reconstruction: A proposal for “People Centered Housing Recovery”

Since 2004, when “Build Back Better” (BBB) was used to call for post-tsunami recovery in Aceh that reduces risk and improves people’s lives, BBB has become widely-used in disaster risk reduction and recovery, and has been featured in post-disaster recovery plans of several countries and the 2015 Sendai Framework for Disaster Risk Reduction. Improving on pre-disaster conditions is a shared goal for recovery, but in relation to housing reconstruction the term BBB has become both too broad to offer meaningful direction. It is also used to narrowly describe safer construction without holistic consideration of what is “better” for people’s lives. This paper argues that “People Centered Housing Recovery” (PCHR) could provide a more meaningful and comprehensive set of principles to guide post-disaster housing reconstruction: housing design and form that meet people’s needs; genuine participation of empowered residents in decision making and construction; and related policies that are accountable to all residents. This paper applies the framework of PCHR to three cases of post-disaster housing recovery--Mt. Merapi in Indonesia, Typhoon Yolanda in the Philippines, and the Great East Japan Earthquake and tsunami in Japan.

Resilience at the margins: informal housing recovery in Bachhau, India, after the 2001 Gujarat quake

This paper examines informal housing recovery in Bachhau, an urban centre in Kutch district close to the epicentre of the 2001 Gujarat earthquake. Unlike other impacted urban areas, an informal housing recovery programme crafted to meet land tenure and housing needs of squatter households within the town's municipal limits was planned and implemented in Bachhau. The study employs a qualitative case study approach based upon in-depth informant interviews. It examines whether the current urban housing policy paradigm of enabling governance extends to post-disaster housing recovery. The paper argues that a centralised approach to post-disaster governance was put in place after the Gujarat earthquake with State appointed local authorities leading urban reconstruction and inviting select local NGOs to work on housing recovery. In Bachhau, the selected NGO became a de facto informal consultant to the Bachhau Authority, a State appointed local body to implement urban reconstruction in the town, and eventually gatekeepers to the informal housing recovery programme. The paper concludes that although an enabling paradigm might in general dominate housing policy it can be thrown into contestation in the context of an urban disaster.

Disaster Induced Resettlement: Multi-stakeholder Interactions and Decision Making Following Tropical Storm Washi in Cagayan de Oro, Philippines

The Tropical Storm Washi (locally known as Sendong) hit the major cities in the region of Northern Mindanao in Southern Philippines between December 16th and 17th, 2011. The flash floods brought by Washi resulted in a massive and unprecedented destruction of urban areas, causing, only in Cagayan de Oro, the displacement of 228,576 persons that represents almost 40% of the total city population, 5,801 houses were totally destroyed and 12,635 were partially damaged. Approximately 85% of the affected households were informal settlers of highly vulnerable and marginal areas located near the river banks. As a result, the post-disaster housing recovery projects focused on the resettlement of these communities as a priority for permanent housing.In the following month of the disaster, the government announced an ambitious resettlement project to build more than 8,500 houses in safer locations. The project implies a complex process in which each stakeholder has specific roles, responsibilities, and approaches. Therefore, the success of the project depends on a large extent of the relationships among stakeholders, leadership and the decisions taken independently by each stakeholder who in turn is affected by other stakeholders’ decisions.This research examines the coordination mechanisms, criteria for decision making and the complex interactions among the different stakeholders involved in the housing reconstruction in Cagayan de Oro in the aftermath of Washi for a better understanding of the process which is needed for an effective management of the resettlement projects.

LASSO Model of Postdisaster Housing Recovery: Case Study of Hurricane Sandy

AbstractUnderstanding the recovery phase of the disaster cycle is still in its infancy. A thorough grasp of recovery can lead to effective postdisaster planning, which is essential for enabling communities to recover quickly from natural and human-made catastrophes. Recent major disasters such as Hurricanes Sandy and Katrina have revealed the inability of existing policies and planning to promptly restore infrastructure, residential properties, and commercial activities in affected communities. While many studies examined the macroeconomic effects of certain policies on overall recovery, very few, if any, have focused on modeling the housing recovery decisions of households and their contributions to the community’s recovery. The reestablishment of housing is a crucial parameter in understanding recovery processes because it has a ripple effect on the overall timing of recovery. The objective of this study is to create a model capable of predicting postdisaster housing recovery decisions founded on the da...