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<article xmlns:xlink="http://www.w3.org/1999/xlink" article-type="review-article" dtd-version="2.0">
  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher-id">JMIR</journal-id>
      <journal-id journal-id-type="nlm-ta">Online J Public Health Inform</journal-id>
      <journal-title>Online Journal of Public Health Informatics</journal-title>
      <issn pub-type="epub">1947-2579</issn>
      <publisher>
        <publisher-name>JMIR Publications</publisher-name>
        <publisher-loc>Toronto, Canada</publisher-loc>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="publisher-id">v7i1e5700</article-id>
      <article-id pub-id-type="doi">10.5210/ojphi.v7i1.5700</article-id>
      <title-group>
        <article-title>Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review</article-title>
      </title-group>
      <pub-date pub-type="epub">
        <year>2015</year>
      </pub-date>
      <volume>7</volume>
      <issue>1</issue>
      <elocation-id>e5700</elocation-id>
      <abstract>
        <p>This presentation compares surveillance algorithms used in the National Poison Data System to identify incidents of public health significance with recently expanded filtering capabilities and with methods beyond the NPDS generalized historical limits model. Collected data series from 55 poison centers over 7 years include hourly counts of general call volumes and of substance-specific (e.g. CO exposure) calls. By applying current, modified, and novel methods to known and simulated clusters among these data, the authors will present the most efficient algorithms for identifying incidents of public health significance.</p>
      </abstract>
    </article-meta>
  </front>
</article>