Revealing the Social Vulnerability of Communities to Disasters using a Composite Index based on Village-Level Poverty Data

Journal of Biodiversity and Environmental Sciences (JBES) 13(6), 109-116, December 2018

11 Pages Posted: 19 May 2020

See all articles by Michael Arieh Medina

Michael Arieh Medina

Central Mindanao University

Joseph Paquit

Central Mindanao University

Date Written: 2018

Abstract

This study was done to develop a barangay social vulnerability index (BSVI) for the purpose of prioritizing disaster resilience programs in local communities. Six (6) of the Community Based Monitoring System 13+1 Core Local Poverty Indicators were used in computing for the BSVI. Factor Analysis using Principal Component Analysis was able to identify 4 components of the index namely: Water Sanitation and Hygiene Inaccessibility (WASHI), Health and Nutrition Inadequacy (HNI), Financial Vulnerability (FV), and Vulnerability of Housing (VH). The factor loadings were used in the weighting process while normalization was done using Min-Max method. BSVI is computed using the linear additive aggregation. The BSVI was able to identify 5 moderately vulnerable barangays in Valencia City, Bukidnon, Philippines out of the 31 barangays in the city. Furthermore, index evaluation using a series of correlation analyses confirms the soundness of the mathematical architecture of the index.

Keywords: Social Vulnerability, Disasters, Composite Indicators

JEL Classification: I32

Suggested Citation

Medina, Michael Arieh and Paquit, Joseph, Revealing the Social Vulnerability of Communities to Disasters using a Composite Index based on Village-Level Poverty Data (2018). Journal of Biodiversity and Environmental Sciences (JBES) 13(6), 109-116, December 2018, Available at SSRN: https://ssrn.com/abstract=3582199

Michael Arieh Medina (Contact Author)

Central Mindanao University ( email )

Philippines

Joseph Paquit

Central Mindanao University

Philippines

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
6
Abstract Views
59
PlumX Metrics