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Infrastructural Inequality and Household COVID-19 Vulnerability in a South African Urban Settlement

COVID-19 has highlighted the importance of household infrastructure in containing the spread of SARS-CoV-2, with Global South urban settlements particularly vulnerable. Targeted interventions have used area or dwelling type as proxies for infrastructural vulnerability, potentially missing vulnerable...

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Detalles Bibliográficos
Autores principales: Marcus, Simon M., Marcus, Tessa S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9020544/
https://www.ncbi.nlm.nih.gov/pubmed/35445280
http://dx.doi.org/10.1007/s11524-022-00625-7
Descripción
Sumario:COVID-19 has highlighted the importance of household infrastructure in containing the spread of SARS-CoV-2, with Global South urban settlements particularly vulnerable. Targeted interventions have used area or dwelling type as proxies for infrastructural vulnerability, potentially missing vulnerable households. We use infrastructural determinants of COVID-19 (crowding, water source, toilet facilities, and indoor pollution) to create an Infrastructural Vulnerability Index using cross-sectional household data (2018–2019) from Mamelodi, a low-income urban settlement in South Africa. Households were stratified into vulnerability groups by index results; sociodemographic variables were assessed as predictors of index scores; and inequality analysis and decomposition were conducted. Thirty-three percent of households fell in the lowest risk group, 32% in the second, 21% in the third, and 14% in the highest. Dwelling type and geographical ward were associated with changes in index scores, with a shack (adjusted β (aβ) = 3.45, CI = 3.39–3.51) associated with highest increase compared to a house. Wards in more developed areas were not consistently associated with lower index scores in the final regression model. The infrastructural vulnerability of the top 10% of households was greater than the bottom 40%, and inequality was predominantly within (80%) rather than between (20%) wards, and more between (60%) than within (40%) dwelling types. Our results show a minority of households account for the majority of infrastructural vulnerability, with its distribution only partially explained by area and dwelling type. Efforts to contain COVID-19 can be improved by using local-level data, and a vulnerability index, to target infrastructural support to households in greatest need. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11524-022-00625-7.