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  <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">v7i1e5702</article-id>
      <article-id pub-id-type="doi">10.5210/ojphi.v7i1.5702</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>e5702</elocation-id>
      <abstract>
        <p>We describe challenges and lessons learned using biosurveillance methods for identifying Chikungunya (CHIKV) infections. Surveillance was performed using VA ESSENCE, electronic laboratory data and facility reports. As of Aug. 14, 2014, 21 confirmed/probable cases were identified at 10 hospitals. The principal challenges were lack of a specific ICD-9 code for CHIKV, use of non-specific symptom codes at initial and subsequent encounters, lack of CHIKV testing, long turn-around times for results, poor uniformity in test names, and infection control not being notified of  suspected/confirmed CHIKV cases.  Based on our experience, a combination surveillance strategy using multiple data sources is essential for CHIKV detection.</p>
      </abstract>
    </article-meta>
  </front>
</article>