Evidence map›Paper›PMID 41931590›Full record

ArticlePloS one2026

Associations between area-level socioeconomic disadvantage and COVID-19 disease consequences in Sydney, Australia: A retrospective cohort analysis.

Christopher Standen, Esther Tordjmann, James Wood, Fiona Haigh

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Christopher StandenInternational Centre for Future Health Systems, University of New South Wales, Sydney New South Wales, Australia.ORCID https://orcid.org/0000-0002-8027-6773
Esther TordjmannSchool of Population Health, University of New South Wales, New South Wales, Australia.ORCID https://orcid.org/0000-0001-5598-6880
James WoodSchool of Population Health, University of New South Wales, New South Wales, Australia.
Fiona HaighInternational Centre for Future Health Systems, University of New South Wales, Sydney New South Wales, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSocioeconomic disparities have shaped COVID-19 outcomes worldwide. Focusing on disease consequences once infected (severity among cases), we examined whether area-level socioeconomic disadvantage was associated with hospitalisation and death among COVID-19 cases in Greater Sydney, Australia.

methodsWe conducted a retrospective cohort study of confirmed and probable COVID-19 cases recorded in the New South Wales Notifiable Conditions Information Management System from 2 March 2020-21 February 2022. Area-level disadvantage was measured using the Index of Relative Socio Economic Disadvantage (IRSD). We modelled the odds of (a) hospitalisation and (b) death conditional on infection using logistic regression, adjusting for age, gender and pandemic phase.

resultsAmong 782,883 included cases, 3.5% were hospitalised and 0.2% died due to COVID-19. After adjustment, a 100-point increase in IRSD score (indicating less socioeconomic disadvantage) was significantly associated with lower odds of hospitalisation (adjusted odds ratio [AOR] 0.80, 95% CI 0.79-0.81) and death (AOR 0.78, 95% CI 0.74-0.83). There was no evidence that these associations differed across pandemic phases.

conclusionsArea‑level socioeconomic disadvantage was associated with higher risks of hospitalisation and death among COVID‑19 cases in Greater Sydney - a setting with public hospital care - with some postal areas having more than twice the odds of hospitalisation and death as others. Given the absence of linked comorbidity and vaccination data, the most plausible explanation is disparities in comorbidity and risk‑factor burden, although contributions from differences in access to testing and quality of care cannot be ruled out. Public health responses should prioritise chronic disease prevention and management in disadvantaged communities to mitigate inequitable outcomes in future pandemics.

Indexed as

COVID-19AdultAgedFemaleHospitalizationHumansLow Socioeconomic StatusMaleMiddle AgedNew South WalesPandemicsRetrospective StudiesSARS-CoV-2Socioeconomic Disparities in HealthSocioeconomic Factors

Identifiers

PMID41931590
PMCPMC13048482

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.