MAPPING SOCIAL VULNERABILITY IN CENSUS TRACTS:
guidelines for public policies in Eunápolis, Brazil
DOI:
https://doi.org/10.14393/BGJ-v16n1-a2025-73530Keywords:
Social vulnerability, Social Vulnerability Index (SVI), Census tracts, Public policies, Eunápolis-BAAbstract
This study aimed to construct and analyze the Social Vulnerability Index (SVI) of the municipality of Eunápolis, Bahia, Brazil, based on data from the 2010 Demographic Census. The methodology involved using Principal Component Analysis (PCA) for variable selection and weighting, and the QGIS software for spatialization of the results at the census tract level. Three fundamental dimensions of vulnerability were considered: human capital, urban infrastructure, and income and employment. The results indicated that most of the municipal territory was classified as having high or very high levels of vulnerability, with a particular emphasis on the human capital dimension, which was strongly impacted by high illiteracy rates, and on urban infrastructure, marked by deficiencies in access to basic services. The income and employment dimension revealed significant gender inequalities and the persistence of poverty pockets. The integration of these dimensions showed that more than two-thirds of the municipality experiences adverse socioeconomic conditions, highlighting priority areas for government intervention. It is concluded that the SVI is an effective analytical tool to support territorial planning and guide the formulation of more equitable and targeted public policies. It overcomes the limitations of aggregated indicators such as the Municipal Human Development Index (MHDI) and contributes to the promotion of inclusive and sustainable development in Eunápolis.
References
BARBOSA, Isabelle Ribeiro; GONÇALVES, Ruana Clara Bezerra; SANTANA, Reginaldo Lopes. Mapa da vulnerabilidade social do município de Natal-RN em nível de setor censitário. Journal of Human Growth and Development, v. 29, n. 1, p. 48-56, 2019. Disponível em: http://dx.doi.org/10.7322/jhgd.157749. Acesso em: 11 out. 2023.
FÁVERO, L. P.; BELFIORE, P.; SILVA, F. L.; CHAN, B. L. Análise de dados: modelagem multivariada para tomada de decisão. Rio de Janeiro: Elsevier, 2009, 646 p.
FIELD, Andy. Descobrindo a estatística usando SPSS. Tradução de Lorí Viali. 2. ed. Porto Alegre: Artmed, 2009. 688 p.
FIGUEIREDO FILHO, Dalson Brito; SILVA JÚNIOR, José Alexandre. Visão além do alcance: uma introdução à análise fatorial. Opinião pública. Campinas, vol. 16, n. 1, junho, 2010, p. 160-185. DOI: https://doi.org/10.1590/S0104-62762010000100007. Acesso em: 14 jun. 2025.
HAIR, Joseph F; BLACK, William C; BABIN, Bary J. Multivariate data analysis. 7th. ed. Upper Saddle River, New Jersey: Pearson Educational International, 2010.
INSTITUTO DE PESQUISA ECONOMICA E APLICADA – IPEA. Atlas da Vulnerabilidade Social nos municípios brasileiros. Brasília, IPEA, 2015. Disponível em: http://ivs.ipea.gov.br/images/publicacoes/Ivs/publicacao_atlas_ivs.pdf. Acesso em: 04 dez. 2020.
MATOS, Daniel Abud Seara; RODRIGUES, Erica Castilho. Análise fatorial. Brasília, DF: Enap, 2019.
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Jeorge Luis Martins de Oliveira, Roberto Muhájir Rahnemay Rabbani, Emilia Rahnemay Kohlman Rabbani, Sandra Adriana Neves Nunes

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
All copyrights are reserved to authors. Reproductions of any part of this journal, including the non-commercial use of figures, maps and other illustrations, are allowed provided that the original source of publication be assigned.
