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The efficacy of various types of intervention measures intended to facilitate post-earthquake housing recovery can be evaluated ahead of time by using simulation models to quantify their benefits and tradeoffs. Towards this end, this paper presents a conceptual framework comprised of three components for modeling post-earthquake housing recovery. The modeling framework starts with a probabilistic assessment of building-level damage using recovery-based limit states that characterize post-earthquake functionality, inhabitability, and repairability. These limit states are the basis for the second component, which includes two different utility-based models for representing post-earthquake household decision making. Stochastic models to probabilistically quantify building-level recovery trajectories comprise the third and final component of the framework. Collectively, these alternative models can integrate the effect of building states, available resources, household decisions, and endogenous factors such as lifeline restoration. The modeling framework can be scaled to model spatiotemporal scenarios of housing recovery to inform jurisdictional-level policies, plans, and interventions to increase residential community resilience.

The goal of this study was to first develop a systematic data collection strategy to create and maintain a database of policies in the United States that promote seismic mitigation. With this database, indices were developed to facilitate understanding of the relationship between policy activity, policy coverage, and seismic risk, as well as to perform cross-state comparison. The most basic index is a count of the number of policies each state has adopted. An index was developed that directly accounts for the seismic risk of each state. A Guttman scale was developed to characterize states’ policy coverage, as well as the level of intensity represented by states’ policy activity. The relationship between policy coverage and seismic risk was also explored. For the most part, this study found a moderate relationship between seismic risk and policy activity, as well as a moderately strong relationship between risk and policy coverage.

The 12 January 2010 Haiti earthquake resulted in some of the most significant social impacts from an earthquake in recent decades. In early March, an Earthquake Engineering Research Institute (EERI) social impacts reconnaissance team documented broad impacts on shelter, livelihood opportunities, and service provision through direct observation, photo documentation, interviews, and a review of other sources. The earthquake left over half of the residential housing in Port-au-Prince heavily damaged; widespread fear that even undamaged structures were unsafe swelled the number of homeless to 1.3 million. The infrastructure damage and significant loss of life within the Haitian government and international aid agencies slowed the early response and reduced the already low levels of basic service provision. Continued research is needed on media portrayal, outcomes of injuries, sheltering decisions, social networks, and learning trajectories for Haiti's youth, among other areas.

This paper sets out the foundations for developing robust models of community recovery from earthquake disasters. Models that anticipate post-disaster trajectories are complementary to loss estimation models that predict damage and loss. Such models can serve as important decision support tools for increasing community resilience and reducing disaster vulnerability. The paper first presents a comprehensive conceptual model of recovery. The conceptual model enumerates important relationships between a community's households, businesses, lifeline networks, and neighborhoods. The conceptual model can be operationalized to create a numerical model of recovery. To demonstrate this, we present a prototype computer simulation model and graphical user interface. As the model is intended for decision support, it is important to involve potential users in model development. We conducted a focus group involving Puget Sound, Washington, area disaster management practitioners to elicit local insight about community recovery and model development needs, using the prototype as stimulus. Important focus group issues included potential model inputs, useful recovery indicators, potential uses of recovery models, and suitable types of software systems.