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A Factor Analysis Approach Toward Reconciling Community Vulnerability and Resilience Indices for Natural Hazards.
Paul M Johnson1, Corey E Brady2, Craig Philip1
1Department of Civil and Environmental Engineering, Vanderbilt University, Nashville, TN, United States.
Summary
Understanding community vulnerability and resilience is key to addressing disaster impacts. This study develops a data-driven method to reconcile existing frameworks, identifying five key dimensions for measuring these concepts.
Area of Science:
- Environmental Science
- Sociology
- Disaster Management
Background:
- Natural hazards impact communities differently due to varying vulnerability and resilience.
- Existing frameworks for measuring these concepts lack consistent comparison methods.
Purpose of the Study:
- To develop a data-driven approach for reconciling vulnerability and resilience indices.
- To establish an objective schema for relating constituent elements of these indices.
Main Methods:
- Exploratory factor analysis was conducted on 130 variables from established community vulnerability and resilience indices.
- Analysis focused on U.S. county-level data.
Main Results:
- Fifty of the 130 variables loaded effectively onto five dimensions: wealth, poverty, agencies per capita, elderly populations, and non-English-speaking populations.
- The factor model provides a schema for relating index elements.
Conclusions:
- The developed factor model offers a flexible and robust baseline for validating and expanding current approaches to measuring community vulnerability and resilience.
- This data-driven approach facilitates objective comparison and understanding of disparate community impacts from natural hazards.
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