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  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher-id">IJPDS</journal-id>
      <journal-title-group>
        <journal-title>International Journal of Population Data Science</journal-title>
        <abbrev-journal-title>IJPDS</abbrev-journal-title>
      </journal-title-group>
      <issn pub-type="epub">2399-4908</issn>
      <publisher>
        <publisher-name>Swansea University</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.23889/ijpds.v10i3.3103</article-id>
      <article-id pub-id-type="publisher-id">10:3:86</article-id>
      <title-group>
        <article-title>Unsupervised evaluation of a large-scale historical population linkage</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Adebisi</surname>
            <given-names initials="Y">Yusuff Adebayo</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Pattaro</surname>
            <given-names initials="S">Serena</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Henderson</surname>
            <given-names initials="A">Angela</given-names>
          </name>
          <xref ref-type="aff" rid="affil-2">2</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Bailey</surname>
            <given-names initials="N">Nick</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
      </contrib-group>
      <aff id="affil-1"><label>1</label><institution>College of Social Sciences, University of
        Glasgow, Glasgow, United Kingdom</institution></aff>
      <aff id="affil-2"><label>2</label><institution>School of Health and Wellbeing, University of
        Glasgow, Glasgow, United Kingdom</institution></aff>
      <pub-date date-type="pub" publication-format="electronic">
        <day>01</day>
        <month>06</month>
        <year>2025</year>
      </pub-date>
      <pub-date date-type="collection" publication-format="electronic">
        <year>2025</year>
      </pub-date>
      <volume>8</volume>
      <issue>4</issue>
      <elocation-id>3103</elocation-id>
      <permissions>
        <license license-type="open-access"
          xlink:href="https://creativecommons.org/licences/by/4.0/">
          <license-p>This work is licenced under a Creative Commons Attribution 4.0 International
            License.</license-p>
        </license>
      </permissions>
      <self-uri xlink:href="https://ijpds.org/article/view/3103">This article is available from the
        IJPDS website at: https://ijpds.org/article/view/3103</self-uri>
    </article-meta>
  </front>
  <body>
    <sec>
      <title>Objectives</title>
      <p>This study examines the associations between household living arrangements and COVID-19
        outcomes (infection and severity) among people with intellectual and physical disabilities
        in Scotland. Understanding these associations will help identify disparities, inform
        pandemic preparedness, and contribute to evidence-based policies aimed at protecting
        vulnerable populations from infectious diseases.</p>
    </sec>
    <sec>
      <title>Methods</title>
      <p>A retrospective, population-based study is being conducted using linked administrative data
        covering approximately 90% of the Scottish population from March 1, 2020, to December 30,
        2022. Cox Proportional Hazards Models will assess the associations between household living
        arrangements and COVID-19 outcomes. Data sources include the 2011 Census (disability status,
        demographics, socio-economic details), Community Health Index Register and Ordnance Survey
        data (household composition), and Public Health Scotland’s COVID-19 Research Database
        (infection status, hospitalizations, mortality, and pre-existing conditions).</p>
    </sec>
    <sec>
      <title>Results</title>
      <p>Data processing and preliminary analysis are underway. The study will evaluate differences
        in COVID-19 infection and severity (hospitalization and mortality) across various household
        living arrangements, comparing disabled and non-disabled populations. Expected findings
        include potential disparities based on household composition, such as differences in
        infection risk for those living alone, in shared residences, or institutional settings. Full
        results, including hazard ratios and statistical significance, will be presented at the
        conference.</p>
    </sec>
    <sec>
      <title>Conclusion</title>
      <p>This study will enhance understanding of how household living arrangements impact COVID-19
        infection, hospitalization and mortality among disabled individuals compared to non-disabled
        individuals. By integrating novel measures of household composition with administrative
        health data, the findings will inform public health strategies aimed at reducing health
        inequalities and improving pandemic response planning for vulnerable populations.</p>
    </sec>
  </body>
</article>