Household displacement after disasters

For a review on household displacement and return after disasters, please refer to my open access paper

Overview

Over 265 million people were displaced due to disasters between 2008 and 20181. In the forthcoming years, the annual number displaced is expected to increase, driven by poorly-managed urban growth in hazard-prone areas2 and potentially exacerbated by climate change3. Despite this scale of human impact, most disaster risk assessments focus on direct economic losses, a metric that often highlights the wealthiest as the most at-risk. However, the reality of disasters is that the poor are disproportionately affected4, and mitigations informed primarily by economic loss may deepen existing inequalities. This research proposes to quantify disaster-induced displacement; a more equitable risk metric to depict the human toll of disasters.

Key definitions and the scope. The highlighted labels indicate the areas considered in this review. Labels below the highlighted labels are subsets of that category.
Key definitions and the scope. The highlighted labels indicate the areas considered in this review. Labels below the highlighted labels are subsets of that category.

Research themes

The importance of duration

Most statistics regarding population displacement following a disaster event provide single snapshot values, often representing a peak estimate during the emergency phase. However, the duration of displacement is essential for understanding the human impact. For example, large- scale displacement in the form of evacuations before a storm can save lives and be followed by mass return shortly afterward. In contrast, a devastating event such as an earthquake could damage or destroy a significant proportion of the residential building stock, causing occupants to seek alternative accommodations for months to years. Not only does this type of protracted displacement pose a significant disruption to the livelihoods of affected households (e.g., lost income, interrupted education), but the consequences can ripple out into the larger community (e.g., outmigration and urban blight, lost economic production). Therefore, a key objective of this research is to refine our understanding of household displacement duration in disasters.

Timeline representing displacement duration alongside key phases of disaster management and recovery.
Timeline representing displacement duration alongside key phases of disaster management and recovery.

Determinants of household return

Disasters are life events that can subject households to key decision points, such as: whether to evacuate, where to seek shelter, whether to return/wait/relocate, and whether to stay or resettle. From a literature review of household return after disasters, the following categories of determinants have been identified.

CategoryDeterminants of return
Physical damage to the built environment
  • Habitability of housing (damage, weather, utilities)
  • Housing type
  • Community damage
  • Reconstruction progress
Psychological & social phenomena
  • Acceleration of ongoing trends
  • Attachment to place
  • Social capital (networks, family and friends)
  • Perceived risk
Household demographics
  • Socioeconomic status (e.g., income level)
  • Housing and land tenure
  • Race/ethnicity/caste
  • Age
Pre- and post-disaster policies
  • Pre-existing housing conditions (e.g., vacancies)
  • Housing reconstruction approach
  • Other disaster assistance policies

The role of housing damage

For more on the role of housing damage in population displacement predictions, please refer to my open access paper

Disaster literature offers a clear consensus that housing damage is a primary driver of household displacement of disasters, both for initial displacement and longer-term displacement. However, additional factors (e.g., place attachment and housing tenure) have more recently been proposed as highly influential for household return in the recovery phase. Despite the range of factors beyond damage that have been proposed to influence household return, standard practice in disaster risk analysis is to solely consider housing damage. That is, the number of destroyed homes is multiplied by the average household size to yield an estimate of the displaced population.

In an initial study, I benchmarked predictions of household displacement based solely on housing damage to understand the extent to which such simplified models can explain the phenomenon. The results of the benchmarking study are available in a journal paper and a conference paper.

Benchmarking results for displacement estimates using a scenario risk analysis that only considers housing damage (green) versus official reports and mobile location data-based estimates.
Benchmarking results for displacement estimates using a scenario risk analysis that only considers housing damage (green) versus official reports and mobile location data-based estimates.

Predicting displacement durations

More on this topic coming soon!

Acknowledgments

This research is partly funded by the University College London Overseas Research Scholarship (ORS) and the Willis Towers Watson Research Network.

  1. IDMC. 2019. “Disaster Displacement - A Global Review, 2008-2018.” https://www.internal-displacement.org/publications/disaster-displacement-a-global-review. ↩︎

  2. IDMC. 2017. “Global Disaster Displacement Risk - A Baseline for Future Work.” https://www.internal-displacement.org/publications/global-disaster-displacement-risk-a-baseline-for-future-work. ↩︎

  3. IPCC, ed. 2012. “Summary for Policymakers.” In Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation, 1st ed. Cambridge University Press. https://doi.org/10.1017/CBO9781139177245. ↩︎

  4. Hallegatte, Stéphane, Adrien Vogt-Schilb, Julie Rozenberg, Mook Bangalore, and Chloé Beaudet. 2020. “From Poverty to Disaster and Back: A Review of the Literature.” Economics of Disasters and Climate Change 4 (1): 223–47. https://doi.org/10.1007/s41885-020-00060-5. ↩︎

household displacement
Nicole Paul
Nicole Paul
PhD Candidate

Researching population displacement in disasters

Publications

Population displacement after earthquakes: benchmarking predictions based on housing damage
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. While this metric can provide rapid situational awareness regarding potential long-term housing needs, more recent research highlights the importance of additional factors beyond housing damage within the scope of household displacement and return (e.g., utility disruption, tenure, place attachment). This study benchmarks population displacement estimates using this simplified conventional approach that considers only housing destruction through three scenario models for recent earthquakes in Haiti, Japan, and Nepal. These model predictions are compared with officially reported values and data-driven estimates using mobile location data. The results highlight the promise of scenario models to realistically estimate population displacement and potential long-term housing needs after earthquakes, but also highlight a large range of uncertainty in the predicted values. Furthermore, purely basing displacement estimates on housing damage offers no view on how the displaced population counts vary with time as compared to more comprehensive models that include other factors influencing population return or alternative approaches, such as using mobile location data.
Nicole Paul, Carmine Galasso, Vitor Silva, Jack Baker
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Household Displacement and Return in Disasters: A Review
Household displacement following disasters has become endemic in many areas worldwide, affecting at least 265 million people between 2008 and 2018. Although this figure includes short-term and potentially life-saving evacuations, there is ample evidence that not all households return after the emergency phase. Protracted displacement is associated with particularly negative consequences for the affected households and community. Yet, existing data on displacement duration are limited, and only a few disaster recovery models incorporate the multitude of factors beyond housing damage that are known to influence household return. This review 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.
Nicole Paul, Carmine Galasso, Jack Baker
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Benchmarking housing damage as a driver of population displacement following earthquakes
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.
Nicole Paul, Carmine Galasso, Vitor Silva, Jack Baker
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