household displacement

This study uses data from the United States Household Pulse Survey to fit predictive models for displacement duration and return after disasters. Three predictive models are proposed, which range in complexity and predictive power. The leading contributors to different duration and return outcomes are also explored. These models can be integrated within disaster risk analyses, as illustrated through a hurricane scenario analysis for Atlantic City, NJ.

In the aftermath of an earthquake, the number of residents whose housing was destroyed is often used to approximate the number of people displaced (i.e., rendered homeless) after the event. This study benchmarks this conventional approach against officially reported impacts and data-driven estimates using mobile location data for three recent earthquakes in Haiti, Japan, and Nepal.

This review paper synthesizes the current literature on disaster-induced displacement, including key terminology and context, the determinants of household return decisions, existing model-based approaches, and opportunities for future research.

In the aftermath of an earthquake, the number of occupants within destroyed housing is often used to approximate the number of people rendered homeless after the event. While this metric can provide rapid situational awareness, more recent research highlights the importance of additional factors beyond housing damage within the scope of household displacement (e.g., utility disruption, housing tenure, place attachment). This study models three recent earthquakes from different geographies (Haiti, Japan, and Nepal) to benchmark housing damage as a driver of population displacement against reported values and mobile location data-based estimates.