Classifying disaster risk reduction strategies: conceptualizing and testing a novel integrated approach

Area of Science:

• Environmental Science
• Public Health
• Urban Planning

Background:

• Disaster risk reduction (DRR) is cost-effective but lacks systematic categorization, hindering coherent planning and implementation.
• Existing DRR classification systems need integration to address underlying causes of disasters effectively.

Purpose of the Study:

• To conceptualize and test a novel integrated DRR framework.
• To highlight the intersection between two existing DRR classification systems.

Main Methods:

• Grounded theory was used to develop the integrated DRR framework.
• Deductive conceptual content analysis categorized interventions from the 2019 Cities100 Report.
• Descriptive statistics analyzed the distribution and application of DRR interventions.

Main Results:

• The framework comprises nine categories: hazard, exposure, and vulnerability, each with prospective, corrective, and compensatory dimensions.
• Under-utilized strategies (exposure-prospective, exposure-compensatory, vulnerability-compensatory) accounted for only 3% of interventions.
• Income-level and geographic disparities in DRR strategy adoption were observed, with European cities showing the highest engagement.

Conclusions:

• The proposed DRR framework can systematically evaluate interventions for completeness.
• This framework aids in designing more equitable and comprehensive disaster risk reduction strategies.