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During extreme event crises, such as floods, it is crucial to have accurate information about the most vulnerable populations. This study proposes a cost-effective methodology for estimating flood vulnerability by integrating microdata from household-level social records with macrodata derived from demographic and socioeconomic indicators. This approach allows for constructing a regional vulnerability index, which enables identifying high-risk areas even without complete microdata coverage. The method overcomes the challenge of limited data availability by leveraging existing public data sources and a regression model. The results of a case study in Curitiba, Brazil, show the potential to support the prioritization of regions for emergency response and to guide the development of public policies and mitigation strategies based on social and demographic criteria. This replicable methodology can be adapted to other cities facing budget constraints as a practical tool for mapping vulnerabilities and enhancing risk management.

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1	Eduardo Reolon(eduardo_reolon@hotmail.com)
2	Luiz Celso Gomes-Jr(lcjunior@utfpr.edu.br)
3	Ricardo Lüders(luders@utfpr.edu.br)

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