Classifying disaster risk reduction strategies

Conceptualizing and testing a novel integrated approach

Bibliographic Data

ID19533835
AuthorsMariya Dimitrova (0000-0003-1834-8307, Evergreen Valley College, corresponding author), Megan Snair
Year2024
Volume20
Issue1
Pages7-7
Publication date2024-01-08
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueGlobalization and Health (JOURNAL)
Journal identifiersISSN: 1744-8603 • E-ISSN: 1744-8603
PublisherSpringer Science and Business Media LLC (PUBLISHER)
DOI10.1186/s12992-023-01006-8
PMID38191369
OpenAlexW4390663413
LanguageEN
Citations received4
References cited23

BACKGROUND: Although disaster risk reduction (DRR) addresses underlying causes and has been shown to be more cost-effective than other emergency management efforts, there is lack of systematized DRR categorization, leading to insufficient coherence in the terminology, planning, and implementation of DRR. The aim of this study was to conceptualize and test a novel integrated DRR framework that highlights the intersection between two existing classification systems. METHODS: Grounded theory was used to conceptualize a novel DRR framework. Next, deductive conceptual content analysis was used to categorize interventions from the 2019 Cities100 Report into the proposed DRR framework. The term "connection" indicates that an intervention can be categorized into a particular section of the novel integrated approach. A "connection" was determined to be present when the intervention description stated an explicit connection to health and to the concept within one of the categories from the novel approach. Further descriptive statistics were used to give insight into the distribution of DRR interventions across categories and into the application of the proposed framework. RESULTS: The resulting framework contains nine intersecting categories: "hazard, prospective", "hazard, corrective", "hazard, compensatory", "exposure, prospective", "exposure, corrective", "exposure, compensatory", "vulnerability, prospective", "vulnerability, corrective", and "vulnerability, compensatory". The thematic analysis elucidated trends and gaps in the types of interventions used within the 2019 Cities100 Report. For instance, exposure-prospective, exposure-compensatory, and vulnerability-compensatory were the most under-utilized strategies, accounting for only 3% of the total interventions. Further descriptive statistics showed that upper middle-income countries favored "hazard, corrective" strategies over other DRR categories while lower middle-income countries favored "exposure, corrective" over other DRR strategies. Finally, European cities had the highest percentage of DRR connections (51.39%) compared to the maximum possible DRR connections, while African cities had the lowest percentage of DRR connections (22.22%). CONCLUSIONS: The study suggests that the proposed DRR framework could potentially be used to systematically evaluate DRR interventions for missing elements, aiding in the design of more equitable and comprehensive DRR strategies

Computer security · Disaster risk reduction · Economics · Environmental resource management · Hazard · Psychological intervention · Computer Science · Disaster Management and Resilience · Disaster Response and Management · Flood Risk Assessment and Management · Medicine · Psychology