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Applications of GIS: Disaster Management and Emergency Response01:29

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Impact of Social Context on Individuals01:21

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Watershed Planning within a Quantitative Scenario Analysis Framework
12:44

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Published on: July 24, 2016

Measuring individual disaster recovery: a socioecological framework.

David M Abramson1, Tasha Stehling-Ariza, Yoon Soo Park

  • 1National Center for Disaster Preparedness, Columbia University, New York, NY 10027, USA. dma3@columbia.edu

Disaster Medicine and Public Health Preparedness
|October 30, 2012
PubMed
Summary

Disaster recovery is best measured using a comprehensive Socio-Ecological Model, considering individual and community well-being alongside infrastructure. Psychological strength, income, and social support significantly impact positive recovery outcomes.

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Area of Science:

  • Disaster recovery research
  • Socio-ecological systems
  • Community resilience

Background:

  • Traditional disaster recovery metrics focus narrowly on infrastructure, neglecting individual and community well-being.
  • A comprehensive framework is essential for accurately measuring the multifaceted nature of disaster recovery.
  • The Socio-Ecological Model of Recovery (SEMR) is proposed to address these limitations.

Purpose of the Study:

  • To develop and validate a comprehensive model for measuring disaster recovery.
  • To identify key factors influencing individual and community recovery post-disaster.
  • To examine the direct and indirect effects of various factors on recovery outcomes.

Main Methods:

  • Confirmatory factor analysis and structural equation modeling were employed.
  • A sample of households displaced by Hurricane Katrina provided the data.
  • Recovery was operationalized through measures of housing stability, economic stability, physical health, mental health, and social role adaptation.

Main Results:

  • Mental health and social role adaptation showed the strongest correlations with overall recovery.
  • Individual psychological strength, income over $20,000, and informal social support were key positive predictors of recovery.
  • Extended displacement, disability, and community social disorder were associated with poorer recovery outcomes.

Conclusions:

  • The Socio-Ecological Model of Recovery offers a robust framework for assessing recovery.
  • This model facilitates the identification of factors promoting or hindering disaster recovery.
  • Understanding these factors is crucial for developing effective post-disaster interventions.