Social vulnerability and spatial inequality in access to healthcare facilities

The case of the Santiago Metropolitan Region (RMS), Chile

Journal Article (2023)
Author(s)

Diana Contreras (Cardiff University, Pontificia Universidad Católica de Chile)

S.K. Bhamidipati (TU Delft - Energy and Industry)

Sean Wilkinson (Newcastle University)

Research Group
Energy and Industry
Copyright
© 2023 Diana Contreras, S.K. Bhamidipati, Sean Wilkinson
DOI related publication
https://doi.org/10.1016/j.seps.2023.101735
More Info
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Publication Year
2023
Language
English
Copyright
© 2023 Diana Contreras, S.K. Bhamidipati, Sean Wilkinson
Research Group
Energy and Industry
Volume number
90
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Abstract

In Chile, the Metropolitan Region of Santiago (RMS) is exposed to several natural and anthropogenic hazards. This means that not only is there a constant need for healthcare, but also a significant increase whenever its inhabitants are affected by disasters. The RMS problem is not the lack of healthcare infrastructure; rather, the inequality in its spatial distribution, which does not consider the location of the most vulnerable population, who may have greater healthcare needs. In this paper, we have performed Pearson's correlation and multicollinearity analysis to select variables to include in the multiple regression analysis to identify the predictors of the number of healthcare facilities per commune in the RMS. Our research found that public healthcare facilities, average monthly income per person per commune, and population density predicts in a 74.1% the number of the total healthcare facilities per commune in the RMS. Network analysis allowed us to integrate distance-based and area-based approaches to spatially visualise the service area of the healthcare facilities in all the districts in the communes of the RMS according to three walking distances. Total coverage of service areas is observed only in 4% of the districts, while high and medium coverage is identified in 30%, low coverage is observed in 28% and 7% of districts are not covered at all. Those districts with low or non-coverage are mainly low-income and/or rural districts in the RMS communes.