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Measuring Social Vulnerability in an Urban Space Through Multivariate Methods and Models

Author

Listed:
  • Cristina Davino

    (University of Naples Federico II)

  • Marco Gherghi

    (University of Naples Federico II)

  • Silvia Sorana

    (University of Macerata)

  • Domenico Vistocco

    (University of Naples Federico II)

Abstract

This article proposes a quantitative analysis to measure social vulnerability in a urban space, specifically in the area of the Municipality of Rome. Social vulnerability can be defined as a situation in which people are characterized by a condition of multidimensional deprivation that encompasses multiple aspects of life and exposes population to different risks and hazards produced by natural, environmental, socioeconomic and epidemic factors. The analysis that follows presents the use of multivariate methods and models to provide an index for every dimensions of vulnerability (housing quality, social context, education, employment, urban mobility, social relations and economic conditions) and a global index for mapping social vulnerability. The analysis also succeeds in identifying significant vulnerability spatial patterns and to measure how and if vulnerability can be different in case of an observed heterogeneity in urban space.

Suggested Citation

  • Cristina Davino & Marco Gherghi & Silvia Sorana & Domenico Vistocco, 2021. "Measuring Social Vulnerability in an Urban Space Through Multivariate Methods and Models," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 157(3), pages 1179-1201, October.
    • Handle: RePEc:spr:soinre:v:157:y:2021:i:3:d:10.1007_s11205-021-02680-0
    DOI: 10.1007/s11205-021-02680-0
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    Cited by:

    1. Wanying Zhong & Yue Wang, 2022. "A study on the spatial and temporal variation of urban integrated vulnerability in Southwest China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 114(3), pages 2855-2882, December.
    2. Arezou Shafaghat & Salim Ferwati & Ali Keyvanfar, 2022. "COVID-19-Adapted Multi-Functional Corniche Street Design Assessment Model: Applying Global Sensitivity Analysis (GSA) and Adaptability Analysis Methods," Sustainability, MDPI, vol. 14(17), pages 1-27, September.
    3. Matheus Pereira Libório & João Francisco Abreu & Petr Iakovlevitch Ekel & Alexei Manso Correa Machado, 2023. "Effect of sub-indicator weighting schemes on the spatial dependence of multidimensional phenomena," Journal of Geographical Systems, Springer, vol. 25(2), pages 185-211, April.

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