Vulnerability index related to populations at-risk for landslides in the Brazilian Early Warning System (BEWS)

• Published in: International journal of disaster risk reduction 2020-10, Vol.49, p.101742, Article 101742
• Main Authors: Assis Dias, Mariane Carvalho de, Saito, Silvia Midori, Alvalá, Regina Célia dos Santos, Seluchi, Marcelo Enrique, Bernardes, Tiago, Camarinha, Pedro Ivo Mioni, Stenner, Cláudio, Nobre, Carlos Afonso
• Format: Article
• Language: English
• Subjects: at-risk population; CEMADEN; Operational Index for Vulnerability Analysis (InOV); social vulnerability; socioeconomic indicators
• ISSN: 2212-4209; 2212-4209
• DOI: 10.1016/j.ijdrr.2020.101742

Vulnerability indices are valuable tools for supporting disaster risk management and are primarily used to reduce human losses. Despite relevant advances in developing tools and metrics towards identifying vulnerable populations, one current challenge is the incorporation of socioeconomic information into an early warning system for disasters. This paper aims to propose and evaluate a vulnerability population index to support monitoring and issuing early warnings for disaster risk in Brazil. Using indicators that characterize the population's physical exposure and capacity for response, the Operational Index for Vulnerability Analysis (InOV) was developed for 443 Brazilian municipalities. This study advances the current understanding of this topic through its use of data on an intra-urban scale, which allows a relational analysis of at-risk areas within each municipality. Based on a total of 6,227,740 vulnerable people in landslide risk areas, almost 42% were classified with very high, 35% with high and 23% with medium vulnerability. Data regarding the victims and populations affected by landslides were used to validate the index. The correlation between the incidences of human losses in the areas classified as very high vulnerability class was verified. The development and validation of the InOV demonstrated the potential for incorporating socioeconomic information into the context of the Brazilian Early Warning System (BEWS). This index can support the identification of priority areas providing additional information about vulnerable populations to be included in early warnings of disaster risk.