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  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher-id">IPROC</journal-id>
      <journal-id journal-id-type="nlm-ta">iproc</journal-id>
      <journal-title>Iproceedings</journal-title>
      <issn pub-type="epub">2369-6893</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">v4i1e10549</article-id>
    <article-id pub-id-type="pmid"/>
    <article-id pub-id-type="doi">10.2196/10549</article-id>
    <article-categories>
      <subj-group subj-group-type="heading">
        <subject>Abstract</subject>
      </subj-group>
      <subj-group subj-group-type="article-type">
        <subject>Abstract</subject>
      </subj-group>
    </article-categories>
    <title-group>
      <article-title>How Did Data Visualization Identify and Improve Response to an Enteric Fever Outbreak in Syria?</article-title>
    </title-group>
    <contrib-group>
      <contrib contrib-type="editor">
        <name>
          <surname>Khader</surname>
          <given-names>Yousef</given-names>
        </name>
      </contrib>
    </contrib-group>
    <contrib-group>
      <contrib contrib-type="author" id="contrib1" corresp="yes">
        <name name-style="western">
          <surname>Ahmed</surname>
          <given-names>Ranya</given-names>
        </name>
      </contrib>
    </contrib-group>
    <author-notes>
      <corresp>Corresponding Author: Ranya Ahmed 
      <email>rahmed@sams-usa.net</email></corresp>
    </author-notes>
    <pub-date pub-type="collection"><season>Jan-Dec</season><year>2018</year></pub-date>
    <pub-date pub-type="epub">
      <day>29</day>
      <month>03</month>
      <year>2018</year>
    </pub-date>
    <volume>4</volume>
    <issue>1</issue>
    <elocation-id>e10549</elocation-id>
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    <history>
      <date date-type="received">
        <day>29</day>
        <month>3</month>
        <year>2018</year>
      </date>
      <date date-type="accepted">
        <day>29</day>
        <month>3</month>
        <year>2018</year>
      </date>
    </history>
    <!--(c) the authors - correct author names and publication date here if necessary. Date in form ', dd.mm.yyyy' after jmir.org-->
    <copyright-statement>©Ranya Ahmed. Originally published in Iproceedings (http://www.iproc.org), 29.03.2018.</copyright-statement>
    <copyright-year>2018</copyright-year>
    <license license-type="open-access" xlink:href="https://creativecommons.org/licenses/by/4.0/">
      <p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in Iproceedings, is properly cited. The complete bibliographic information, a link to the original publication on http://www.iproc.org/, as well as this copyright and license information must be included.</p>
    </license>  
    <self-uri xlink:href="http://www.iproc.org/2018/1/e10549/" xlink:type="simple"/>
    <abstract>
      <sec sec-type="background">
        <title>Background</title>
        <p>Population displacement and damage to infrastructure in Syria has contributed to an increase in water borne infectious diseases including enteric fever. The collection, presentation and analysis of data collected in real time is therefore vital for early identification of outbreaks. EWARN and EWARS are used in Syria for the reporting of communicable diseases however this is not always available to facilities in real time. As such, the prompt availability of diagnostics and treatment may be lacking. This is vital for enteric fever where morbidity and mortality without appropriate treatment is high.</p>
      </sec>
      <sec sec-type="objective">
        <title>Objective</title>
        <p>In this study, we examine the utility of a data visualization tool to track cases of enteric fever in three facilities supported by the Syrian American Medical Society (SAMS).</p>
      </sec>
      <sec sec-type="methods">
        <title>Methods</title>
        <p>All cases of enteric fever between March 2017 and July 2017 were tracked in near real time and presented using data visualization software, namely Tableau. Tableau is a visualization software generally used within the business sector, but its ability to visually express data has far reaching potential in the realm of public health. Sites in Daraa, Quneitra and Rural Damascus were included. Close communication with data personnel in SAMS country offices and health workers working in the facilities was maintained.</p>
      </sec>
      <sec sec-type="results">
        <title>Results</title>
        <p>In March 2017, there were 21 cases of enteric fever across the three governorates and in July 2017, this had increased to 784 cases. Close liaison with the teams on the ground identified that facilities were seeing a significant increase in cases and that there was a shortage of appropriate antibiotics to treat patients. It was also apparent that there was a shortage of microbiology facilities which could isolate the causative organisms (Salmonella typhi or paratyphi) and therefore limited ability to identify the susceptibility of the organisms resulting in empiric therapy where available. Using data visualization in real time can allow for preparedness and responsiveness to outbreaks of communicable diseases during the conflict.</p>
      </sec>
      <sec sec-type="conclusions">
        <title>Conclusions</title>
        <p>Visualization should be integrated into online and offline data collection tools in order to create an early warning system on each device used in the field.</p>
      </sec>
    </abstract></article-meta>
  </front>
</article>
