Vulnerability and COVID-19 infection rates: A changing relationship during the first year of the pandemic

Bárcena‐Martín, Elena; Molina, Julián; Muñoz-Fernandez, Ana M.; Pérez‐Moreno, Salvador

doi:10.1016/j.ehb.2022.101177

Cited by 5 publications

(3 citation statements)

References 47 publications

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“…It also addressed residential distribution indicators (population distribution) as one of the indicators for measuring social vulnerability because the spread of settlements and population makes it difficult to access services, especially in rural areas. Moreover, like other related research projects, this study reflected social inequalities and deprivations that existed before the COVID-19 crisis [ 69 ].…”

Section: Discussionmentioning

confidence: 79%

“…It has been also well-recognized that vulnerable people have fewer opportunities to work remotely [ 119 ] and their jobs mostly require physical presence. According to Das et al [ 60 ]; residents in slums and informal settlements worldwide are the most vulnerable to COVID-19.…”

Section: Discussionmentioning

confidence: 99%

“…. Moreover, people who live in inappropriate housing, are exposed to unfavorable environmental conditions, and are at climatic risk are more socially vulnerable [ 69 ].…”

Section: Theoretical Frameworkmentioning

confidence: 99%

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A county-level analysis of association between social vulnerability and COVID-19 cases in Khuzestan Province, Iran

Arvin

Bazrafkan

Beiki

et al. 2023

International Journal of Disaster Risk Reduction

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Section: Discussionmentioning

confidence: 79%

Section: Discussionmentioning

confidence: 99%

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A county-level analysis of association between social vulnerability and COVID-19 cases in Khuzestan Province, Iran

Arvin

Bazrafkan

Beiki

et al. 2023

International Journal of Disaster Risk Reduction

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Assessing Territorial Units’ Contribution to Convergence Beyond Aggregate Measures: The Role of Neighbourhood

Bárcena-Martín,

García-Pardo,

Muñoz-Fernández

et al. 2024

Soc Indic Res

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This paper provides an analytical framework for the study of spatial income dynamics using the classical measures of $$\sigma$$ σ -convergence (reduction in dispersion) and $$\beta$$ β -convergence (poor areas grow more quickly than rich ones) linked by a re-ranking metric and reinterpreted based on the ‘leave no one behind’ principle. Our approach allows identifying the contribution of each territorial unit to each of the three facets of distributional change ($$\sigma$$ σ -convergence, $$\beta$$ β -convergence, and re-ranking), as well as gauging the part of each component of distributional change that corresponds to geographically neighbouring and non-neighbouring units. We illustrate our proposal by examining convergence across the census tracts of Malaga – the sixth most populated city of Spain – before and after the COVID-19 pandemic. We find that while income convergence across Malaga’s census tracts tended to improve over the period 2015–2019, this process was interrupted during the first year of the pandemic, affecting some specific census tracts. We examine our outcomes by grouping the results into deciles and districts made up of specific census tracts. Finally, we analyse the impact of neighbours on regional convergence and each of its components. This spatial decomposition highlights the crucial role of the spatial component in the convergence process.

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The complex link between socioeconomic deprivation and COVID-19. Evidence from small areas of Catalonia

López-Bazo

2024

Spatial and Spatio-temporal Epidemiology

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Vulnerability and COVID-19 infection rates: A changing relationship during the first year of the pandemic

Cited by 5 publications

References 47 publications

A county-level analysis of association between social vulnerability and COVID-19 cases in Khuzestan Province, Iran

A county-level analysis of association between social vulnerability and COVID-19 cases in Khuzestan Province, Iran

Assessing Territorial Units’ Contribution to Convergence Beyond Aggregate Measures: The Role of Neighbourhood

The complex link between socioeconomic deprivation and COVID-19. Evidence from small areas of Catalonia

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