Evidence map›Paper›PMID 40433428›Full record

ArticleInternational journal of population data science2025

Individual, household structure, and socioeconomic predictors of COVID-19 testing and vaccination outcomes: a whole population linked data analysis.

Nicole Satherley, Andrew Sporle

Abstract read
In one paragraph

Article in International journal of population data science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Family typology among Mexican families after the COVID-19 pandemic.Journal of family medicine and primary care · 2026
    Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Nicole SatherleyiNZight Analytics Ltd.
Andrew SporleiNZight Analytics Ltd.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The COVID-19 pandemic produced social inequities in health outcomes between and within nations. Reported inequitable COVID-19 outcomes for ethnic minorities and indigenous peoples are likely to be associated in part because of poorer socioeconomic circumstances experienced by these populations. Understanding these associations within national populations is vital for future pandemic management. Objective: This study explores the social inequity of COVID-19 outcomes within New Zealand over the first 3 years of the pandemic. We aimed to identify policy amenable socioeconomic factors associated with COVID-19 outcomes while adjusting for relevant individual factors and household structure. We also aimed to examine whether ethnic group differences are smaller when accounting for these socioeconomic factors and household structure. Methods: Administrative individual-level data for the New Zealand population was analysed to assess COVID-19 health outcomes during 2020 - 2023. The association between individual (e.g. age, ethnicity, disability status), household structure (e.g. household composition) and socioeconomic (e.g. crowding, housing quality, deprivation) factors and four COVID-19 health outcomes - infection, hospitalisation, mortality, and vaccination status was assessed. Results: Indigenous peoples and ethnic minorities experienced worse outcomes across most COVID-19 outcomes. Adjusting for household structure and socioeconomic factors reduced but did not eliminate these inequities between ethnic groups. Housing issues including high housing mobility, poor quality housing, and household crowding were associated with worse outcomes, as were disability status, no primary health care enrolment, lower household income and older age. The size of these effects also differed for different health outcomes. Conclusions: Ethnic inequity was persistent and likely partly explained by policy-modifiable social factors, despite the relatively minor population health impacts of COVID-19 in New Zealand. We also demonstrate how a range of socioeconomic determinants predict COVID-19 outcomes in different ways.

Indexed as

COVID-19COVID-19 TestingCOVID-19 VaccinesFamily CharacteristicsHealth Status DisparitiesVaccinationAdolescentAdultAgedChildChild, PreschoolEthnicityFemaleHumansMaleMiddle AgedCOVID-19 Vaccinesadministrative dataCOVID-19New Zealandsocial determinantssocial inequity

Identifiers

PMID40433428
PMCPMC12108692

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LicenceCC BY-NC-ND
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Registered trials

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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.