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  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher-id">JMIR</journal-id>
      <journal-id journal-id-type="nlm-ta">J Med Internet Res</journal-id>
      <journal-title>Journal of Medical Internet Research</journal-title>
      <issn pub-type="epub">1438-8871</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">v23i8e21656</article-id>
      <article-id pub-id-type="pmid">34402801</article-id>
      <article-id pub-id-type="doi">10.2196/21656</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Original Paper</subject>
        </subj-group>
        <subj-group subj-group-type="article-type">
          <subject>Original Paper</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Using Infodemiology Metrics to Assess Public Interest in Liver Transplantation: Google Trends Analysis</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="editor">
          <name>
            <surname>Kukafka</surname>
            <given-names>Rita</given-names>
          </name>
        </contrib>
      </contrib-group>
      <contrib-group>
        <contrib contrib-type="reviewer">
          <name>
            <surname>Mavragani</surname>
            <given-names>Amaryllis</given-names>
          </name>
        </contrib>
        <contrib contrib-type="reviewer">
          <name>
            <surname>Cruvinel</surname>
            <given-names>Thiago</given-names>
          </name>
        </contrib>
      </contrib-group>
      <contrib-group>
        <contrib id="contrib1" contrib-type="author" equal-contrib="yes">
          <name name-style="western">
            <surname>Effenberger</surname>
            <given-names>Maria</given-names>
          </name>
          <degrees>MD</degrees>
          <xref rid="aff1" ref-type="aff">1</xref>
          <ext-link ext-link-type="orcid">https://orcid.org/0000-0002-0499-9953</ext-link>
        </contrib>
        <contrib id="contrib2" contrib-type="author">
          <name name-style="western">
            <surname>Kronbichler</surname>
            <given-names>Andreas</given-names>
          </name>
          <degrees>PhD</degrees>
          <xref rid="aff2" ref-type="aff">2</xref>
          <ext-link ext-link-type="orcid">https://orcid.org/0000-0002-2945-2946</ext-link>
        </contrib>
        <contrib id="contrib3" contrib-type="author">
          <name name-style="western">
            <surname>Bettac</surname>
            <given-names>Erica</given-names>
          </name>
          <degrees>BSc</degrees>
          <xref rid="aff3" ref-type="aff">3</xref>
          <ext-link ext-link-type="orcid">https://orcid.org/0000-0001-8515-505X</ext-link>
        </contrib>
        <contrib id="contrib4" contrib-type="author">
          <name name-style="western">
            <surname>Grabherr</surname>
            <given-names>Felix</given-names>
          </name>
          <degrees>MD</degrees>
          <xref rid="aff1" ref-type="aff">1</xref>
          <ext-link ext-link-type="orcid">https://orcid.org/0000-0001-5731-8253</ext-link>
        </contrib>
        <contrib id="contrib5" contrib-type="author">
          <name name-style="western">
            <surname>Grander</surname>
            <given-names>Christoph</given-names>
          </name>
          <degrees>MD</degrees>
          <xref rid="aff1" ref-type="aff">1</xref>
          <ext-link ext-link-type="orcid">https://orcid.org/0000-0003-2971-6224</ext-link>
        </contrib>
        <contrib id="contrib6" contrib-type="author">
          <name name-style="western">
            <surname>Adolph</surname>
            <given-names>Timon Erik</given-names>
          </name>
          <degrees>PhD</degrees>
          <xref rid="aff1" ref-type="aff">1</xref>
          <ext-link ext-link-type="orcid">https://orcid.org/0000-0002-4736-830X</ext-link>
        </contrib>
        <contrib id="contrib7" contrib-type="author">
          <name name-style="western">
            <surname>Mayer</surname>
            <given-names>Gert</given-names>
          </name>
          <degrees>MD</degrees>
          <xref rid="aff2" ref-type="aff">2</xref>
          <ext-link ext-link-type="orcid">https://orcid.org/0000-0003-4605-1789</ext-link>
        </contrib>
        <contrib id="contrib8" contrib-type="author">
          <name name-style="western">
            <surname>Zoller</surname>
            <given-names>Heinz</given-names>
          </name>
          <degrees>MD</degrees>
          <xref rid="aff1" ref-type="aff">1</xref>
          <ext-link ext-link-type="orcid">https://orcid.org/0000-0003-1794-422X</ext-link>
        </contrib>
        <contrib id="contrib9" contrib-type="author">
          <name name-style="western">
            <surname>Perco</surname>
            <given-names>Paul</given-names>
          </name>
          <degrees>PhD</degrees>
          <xref rid="aff2" ref-type="aff">2</xref>
          <ext-link ext-link-type="orcid">https://orcid.org/0000-0003-2087-5691</ext-link>
        </contrib>
        <contrib id="contrib10" contrib-type="author" corresp="yes">
          <name name-style="western">
            <surname>Tilg</surname>
            <given-names>Herbert</given-names>
          </name>
          <degrees>MD</degrees>
          <xref rid="aff1" ref-type="aff">1</xref>
          <address>
            <institution>Department of Internal Medicine I, Gastroenterology, Hepatology, Endocrinology and Metabolism</institution>
            <institution>Medical University of Innsbruck</institution>
            <addr-line>Anichstrasse 35</addr-line>
            <addr-line>Innsbruck, 6020</addr-line>
            <country>Austria</country>
            <fax>43 512 504 23538</fax>
            <phone>43 512 504 23539</phone>
            <email>herbert.tilg@i-med.ac.at</email>
          </address>
          <ext-link ext-link-type="orcid">https://orcid.org/0000-0002-4235-2579</ext-link>
        </contrib>
      </contrib-group>
      <aff id="aff1">
        <label>1</label>
        <institution>Department of Internal Medicine I, Gastroenterology, Hepatology, Endocrinology and Metabolism</institution>
        <institution>Medical University of Innsbruck</institution>
        <addr-line>Innsbruck</addr-line>
        <country>Austria</country>
      </aff>
      <aff id="aff2">
        <label>2</label>
        <institution>Department of Internal Medicine IV, Nephrology and Hypertensiology</institution>
        <institution>Medical University of Innsbruck</institution>
        <addr-line>Innsbruck</addr-line>
        <country>Austria</country>
      </aff>
      <aff id="aff3">
        <label>3</label>
        <institution>Department of Psychology</institution>
        <institution>Washington State University Vancouver</institution>
        <addr-line>Vancouver, WA</addr-line>
        <country>United States</country>
      </aff>
      <author-notes>
        <corresp>Corresponding Author: Herbert Tilg <email>herbert.tilg@i-med.ac.at</email></corresp>
      </author-notes>
      <pub-date pub-type="collection">
        <month>8</month>
        <year>2021</year>
      </pub-date>
      <pub-date pub-type="epub">
        <day>17</day>
        <month>8</month>
        <year>2021</year>
      </pub-date>
      <volume>23</volume>
      <issue>8</issue>
      <elocation-id>e21656</elocation-id>
      <history>
        <date date-type="received">
          <day>20</day>
          <month>6</month>
          <year>2020</year>
        </date>
        <date date-type="rev-request">
          <day>29</day>
          <month>8</month>
          <year>2020</year>
        </date>
        <date date-type="rev-recd">
          <day>23</day>
          <month>10</month>
          <year>2020</year>
        </date>
        <date date-type="accepted">
          <day>21</day>
          <month>6</month>
          <year>2021</year>
        </date>
      </history>
      <copyright-statement>©Maria Effenberger, Andreas Kronbichler, Erica Bettac, Felix Grabherr, Christoph Grander, Timon Erik Adolph, Gert Mayer, Heinz Zoller, Paul Perco, Herbert Tilg. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 17.08.2021.</copyright-statement>
      <copyright-year>2021</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 the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.</p>
      </license>
      <self-uri xlink:href="https://www.jmir.org/2021/8/e21656" xlink:type="simple"/>
      <abstract>
        <sec sec-type="background">
          <title>Background</title>
          <p>Liver transplantation (LT) is the only curative treatment for end-stage liver disease. Less than 10% of global transplantation needs are met worldwide, and the need for LT is still increasing. The death rates on the waiting list remain too high.</p>
        </sec>
        <sec sec-type="objective">
          <title>Objective</title>
          <p>It is, therefore, critical to raise awareness among the public and health care providers and in turn increasingly acquire donors.</p>
        </sec>
        <sec sec-type="methods">
          <title>Methods</title>
          <p>We performed a Google Trends search using the search terms <italic>liver transplantation</italic> and <italic>liver transplant</italic> on October 15, 2020. On the basis of the resulting monthly data, the annual average Google Trends indices were calculated for the years 2004 to 2018. We not only investigated the trend worldwide but also used data from the United Network for Organ Sharing (UNOS), Spain, and Eurotransplant. Using pairwise Spearman correlations, Google Trends indices were examined over time and compared with the total number of liver transplants retrieved from the respective official websites of UNOS, the Organización Nacional de Trasplantes, and Eurotransplant.</p>
        </sec>
        <sec sec-type="results">
          <title>Results</title>
          <p>From 2004 to 2018, there was a significant decrease in the worldwide Google Trends index from 78.2 in 2004 to 20.5 in 2018 (–71.2%). This trend was more evident in UNOS than in the Eurotransplant group. In the same period, the number of transplanted livers increased worldwide. The waiting list mortality rate was 31% for Eurotransplant and 29% for UNOS. However, in Spain, where there are excellent awareness programs, the Google Trends index remained stable over the years with comparable, increasing LT numbers but a significantly lower waiting list mortality (15%).</p>
        </sec>
        <sec sec-type="conclusions">
          <title>Conclusions</title>
          <p>Public awareness in LT has decreased significantly over the past two decades. Therefore, novel awareness programs should be initialized.</p>
        </sec>
      </abstract>
      <kwd-group>
        <kwd>digital medicine</kwd>
        <kwd>search trends</kwd>
        <kwd>public awareness</kwd>
        <kwd>infodemiology</kwd>
        <kwd>eHealth</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec sec-type="introduction">
      <title>Introduction</title>
      <sec>
        <title>Background</title>
        <p>Liver transplantation (LT) remains to be the only curative therapy for patients affected by end-stage liver disease, cirrhosis with hepatocellular carcinoma, acute fulminant hepatic failure, hepatocellular carcinoma, hilar cholangiocarcinoma, and several metabolic disorders [<xref ref-type="bibr" rid="ref1">1</xref>,<xref ref-type="bibr" rid="ref2">2</xref>].</p>
        <p>Each year, approximately 12,000 LTs are performed in Europe and the United States, with numbers significantly increasing over time [<xref ref-type="bibr" rid="ref3">3</xref>]. At present, more than 70% of liver transplant recipients survive for at least 5 years, compared with 20% in the 1980s. Such statistics are especially encouraging, considering that transplanted patients tend to have more severe diseases [<xref ref-type="bibr" rid="ref4">4</xref>]. Several factors increase the survival of patients with LT, including better control of disease before LT, improved surgical techniques and surgeons specialized in these techniques, improved organ preservation, and advanced immunosuppressive therapy regimens [<xref ref-type="bibr" rid="ref5">5</xref>]. However, the improved success rate of LT has resulted in substantial organ shortages [<xref ref-type="bibr" rid="ref4">4</xref>]. Such shortages have led to a prolonged time for patients on the waiting list and increased waiting list mortality [<xref ref-type="bibr" rid="ref6">6</xref>-<xref ref-type="bibr" rid="ref8">8</xref>].</p>
        <p>In 2017, the median pretransplant waiting time among active waitlisted adults was 10 months in the Eurotransplant region and approximately 9 months in the United States [<xref ref-type="bibr" rid="ref9">9</xref>]. Mortality on the list was 18.7% in the Eurotransplant region, which is comparable with the United States’ 19.8% of listed patient deaths before transplantation. It is important to note that limited donor organs are available from deceased donors after brain death [<xref ref-type="bibr" rid="ref6">6</xref>].</p>
        <p>The discrepancy between available liver allografts and transplant candidates continues to increase globally. Significant efforts have been made to raise the donor pool in Europe and the United States, such as using extended criteria donor organs [<xref ref-type="bibr" rid="ref10">10</xref>], inventing extracorporeal normothermic or hypothermic organ perfusion systems [<xref ref-type="bibr" rid="ref11">11</xref>], and accepting liver allografts as donation after circulatory determination of death (DCDD) [<xref ref-type="bibr" rid="ref12">12</xref>]. Despite these efforts, there remains no significant decrease in waiting list mortality. To close the gap between available organs and the number of patients in need of LT, a higher awareness and acceptance of the transplant and donor program in the general population, as well as among health care providers, is a potentially effective strategy.</p>
        <p>Infodemiology is an emerging area of research among health informatics, health care professionals, and patients. Introduced in 2002 [<xref ref-type="bibr" rid="ref13">13</xref>], the term infodemiology is defined as a new area of scientific research that holds great promise for improving public health by focusing on specific internet searches for user-contributed health-related content [<xref ref-type="bibr" rid="ref13">13</xref>-<xref ref-type="bibr" rid="ref15">15</xref>]. These searches track public opinion, behavior, attention, knowledge, and attitudes [<xref ref-type="bibr" rid="ref16">16</xref>].</p>
      </sec>
      <sec>
        <title>Objectives</title>
        <p>The first study indicated a correlation between searches on the internet and incidence in the field of <italic>infectious diseases</italic> [<xref ref-type="bibr" rid="ref17">17</xref>]. The number of infodemiological studies has increased over the past decade, and these studies have used Twitter and Google [<xref ref-type="bibr" rid="ref18">18</xref>]. Many researchers have used the infodemiological approach to study various health-related topics, for example, infectious diseases such as influenza or HIV/AIDS, chronic diseases such as multiple sclerosis, or patterns of smoking and tobacco use [<xref ref-type="bibr" rid="ref19">19</xref>-<xref ref-type="bibr" rid="ref27">27</xref>]. A particular interest in infodemiology has risen because of the ongoing COVID-19 pandemic [<xref ref-type="bibr" rid="ref28">28</xref>], as research informs about the speed of misinformation [<xref ref-type="bibr" rid="ref29">29</xref>], correlation between search behavior and COVID-19 related mortality [<xref ref-type="bibr" rid="ref30">30</xref>], mental health issues [<xref ref-type="bibr" rid="ref31">31</xref>], and pressing health care topics such as telehealth capacity of hospitals [<xref ref-type="bibr" rid="ref32">32</xref>]. In addition, these data are becoming valuable tools for exploring human behavior. The advantage of infodemiology is that metrics are available in real time, which can provide quantitative and qualitative data while being automatically and inexpensively collected.</p>
        <p>The analysis of internet search queries offers information on the extent of public attention, thereby reflecting the level of public awareness [<xref ref-type="bibr" rid="ref33">33</xref>-<xref ref-type="bibr" rid="ref36">36</xref>]. Google Trends is one of the most widely used tools for this purpose. It is not only used to study public interest in health care topics but also to predict disease occurrence and outbreaks [<xref ref-type="bibr" rid="ref17">17</xref>,<xref ref-type="bibr" rid="ref37">37</xref>,<xref ref-type="bibr" rid="ref38">38</xref>].</p>
        <p>In this study, we evaluated public interest in LT over time using Google Trends data and compared them with the number of transplanted livers reported from the United Network for Organ Sharing (UNOS), the Organización Nacional de Trasplantes (ONT), and the Eurotransplant regions.</p>
      </sec>
    </sec>
    <sec sec-type="methods">
      <title>Methods</title>
      <sec>
        <title>Retrieving Transplantation Numbers for UNOS, ONT, and Eurotransplant</title>
        <p>Data were retrieved by accessing the respective websites of the transplant organizations UNOS, ONT, and Eurotransplant [<xref ref-type="bibr" rid="ref39">39</xref>-<xref ref-type="bibr" rid="ref41">41</xref>]. We extracted information on living and deceased donors over a period of 15 years (2004-2018) for the following countries: the United States (UNOS), Spain (ONT), Austria, Belgium, Croatia, Germany, Hungary, Luxembourg, and the Netherlands (belonging to the Eurotransplant countries). No organs from executed prisoners were used in these transplant organizations.</p>
      </sec>
      <sec>
        <title>Retrieving Google Trends Data on LT</title>
        <p>The Google Trends tool was used on October 15, 2020, to retrieve data on internet user search activities in the context of LT [<xref ref-type="bibr" rid="ref42">42</xref>]. Worldwide Google Trends indices were retrieved from January 2004 onward using the search terms, <italic>liver transplantation</italic> and <italic>liver transplant</italic>. We retrieved Google Trends indices for the United States, Spain, and European countries, in part included in the Eurotransplant network, namely Austria, Belgium, Croatia, Germany, Hungary, and the Netherlands. No Google Trends indices could be retrieved for Luxembourg and Slovenia. Whereas the worldwide search was performed in English, individual searches across non–English-speaking countries were performed in their respective official languages. We used individual search terms and combined the search terms yielding Google Trends results in larger queries, as listed in <xref ref-type="table" rid="table1">Table 1</xref>. On the basis of monthly data, annual average Google Trends indices were calculated for the years 2004 to 2018 and used to generate the line plots with the ggplot2 package of the statistical software R (version 3.4.1; R Foundation for Statistical Computing). It is important to note that none of the queries in the Google database for this study can be associated with a particular individual. The database does not retain information about the identity, IP address, or specific physical location of any user. The Spearman correlation coefficient was used to determine pairwise correlations between total liver transplant numbers per country and Google Trends indices.</p>
        <table-wrap position="float" id="table1">
          <label>Table 1</label>
          <caption>
            <p>Google Trends search query listing (2004-present).</p>
          </caption>
          <table width="1000" cellpadding="5" cellspacing="0" border="1" rules="groups" frame="hsides">
            <col width="300"/>
            <col width="200"/>
            <col width="500"/>
            <thead>
              <tr valign="top">
                <td>Region</td>
                <td>Language</td>
                <td>Google Trends search query</td>
              </tr>
            </thead>
            <tbody>
              <tr valign="top">
                <td>Worldwide</td>
                <td>English</td>
                <td><italic>liver transplantation</italic> and <italic>liver transplant</italic></td>
              </tr>
              <tr valign="top">
                <td>United States</td>
                <td>English</td>
                <td><italic>liver transplantation</italic> and <italic>liver transplant</italic></td>
              </tr>
              <tr valign="top">
                <td>Spain</td>
                <td>Spanish</td>
                <td><italic>trasplante de hígado</italic>, <italic>trasplante higado</italic>, and <italic>trasplante de higado</italic></td>
              </tr>
              <tr valign="top">
                <td>Belgium</td>
                <td>French</td>
                <td><italic>transplantation hépatique</italic> and <italic>levertransplantatie</italic></td>
              </tr>
              <tr valign="top">
                <td>The Netherlands</td>
                <td>Dutch</td>
                <td>
                  <italic>Levertransplantatie</italic>
                </td>
              </tr>
              <tr valign="top">
                <td>Germany</td>
                <td>German</td>
                <td>
                  <italic>Lebertransplantation</italic>
                </td>
              </tr>
              <tr valign="top">
                <td>Austria</td>
                <td>German</td>
                <td>
                  <italic>Lebertransplantation</italic>
                </td>
              </tr>
              <tr valign="top">
                <td>Hungary</td>
                <td>Hungarian</td>
                <td><italic>májátültetés</italic> and <italic>májtranszplantáció</italic></td>
              </tr>
              <tr valign="top">
                <td>Croatia</td>
                <td>Croatian</td>
                <td>
                  <italic>transplantacija jetre</italic>
                </td>
              </tr>
            </tbody>
          </table>
        </table-wrap>
      </sec>
    </sec>
    <sec sec-type="results">
      <title>Results</title>
      <sec>
        <title>Google Trends and Trends for LT Worldwide</title>
        <p>The global Google Trends index for LT decreased from 73.8 to 36.6 (–50.4%) between 2004 and 2014. In 2018, there was a slight upward trend in the LT index to 46.3 (+27.5%; <xref rid="figure1" ref-type="fig">Figure 1</xref>).</p>
        <p>A similar trend was observed for the UNOS, with the Google Trends index dropping from 59.2 to 38.8 (–34.5%) in 2014 and an upward trend since then to 50.3 (+46.2%) until 2018. Similarly, Google Trends indices in the Eurotransplant region exhibited a decline in numbers in all Eurotransplant countries across the same period (<xref rid="figure2" ref-type="fig">Figure 2</xref>; <xref ref-type="table" rid="table2">Tables 2</xref> and <xref ref-type="table" rid="table3">3</xref>).</p>
        <fig id="figure1" position="float">
          <label>Figure 1</label>
          <caption>
            <p>Worldwide interest in liver transplantation using Google Trends.</p>
          </caption>
          <graphic xlink:href="jmir_v23i8e21656_fig1.png" alt-version="no" mimetype="image" position="float" xlink:type="simple"/>
        </fig>
        <fig id="figure2" position="float">
          <label>Figure 2</label>
          <caption>
            <p>Google Trends and number of liver transplants in Eurotransplant, United Network for Organ Sharing, and Organización Nacional de Trasplantes over time.</p>
          </caption>
          <graphic xlink:href="jmir_v23i8e21656_fig2.png" alt-version="no" mimetype="image" position="float" xlink:type="simple"/>
        </fig>
        <table-wrap position="float" id="table2">
          <label>Table 2</label>
          <caption>
            <p>The respective year, number of search queries using Google Trends, and the total number of liver transplantations performed in different countries are provided (deceased donor and living donor).</p>
          </caption>
          <table width="1000" cellpadding="5" cellspacing="0" border="1" rules="groups" frame="hsides">
            <col width="80"/>
            <col width="80"/>
            <col width="90"/>
            <col width="100"/>
            <col width="110"/>
            <col width="80"/>
            <col width="100"/>
            <col width="80"/>
            <col width="80"/>
            <col width="110"/>
            <col width="90"/>
            <thead>
              <tr valign="top">
                <td>Year</td>
                <td>World Google Trends index</td>
                <td>United States Google Trends</td>
                <td>United States TX<sup>a</sup> total</td>
                <td>Spain Google Trends index</td>
                <td>Spain TX total</td>
                <td>Belgium Google Trends index</td>
                <td>Belgium TX total</td>
                <td>Luxembourg TX total</td>
                <td>The Netherlands Google Trends index</td>
                <td>The Netherlands TX total</td>
              </tr>
            </thead>
            <tbody>
              <tr valign="top">
                <td>2004</td>
                <td>73.8</td>
                <td>59.1667</td>
                <td>6642</td>
                <td>8.3</td>
                <td>1040</td>
                <td>22.8</td>
                <td>210</td>
                <td>1</td>
                <td>19.7</td>
                <td>175</td>
              </tr>
              <tr valign="top">
                <td>2005</td>
                <td>68.3</td>
                <td>60.5833</td>
                <td>7015</td>
                <td>24.1</td>
                <td>1070</td>
                <td>11.9</td>
                <td>234</td>
                <td>2</td>
                <td>5.3</td>
                <td>140</td>
              </tr>
              <tr valign="top">
                <td>2006</td>
                <td>55.7</td>
                <td>49.3333</td>
                <td>7302</td>
                <td>12.2</td>
                <td>1051</td>
                <td>16.3</td>
                <td>253</td>
                <td>5</td>
                <td>6.4</td>
                <td>121</td>
              </tr>
              <tr valign="top">
                <td>2007</td>
                <td>45.7</td>
                <td>45.9167</td>
                <td>7202</td>
                <td>6.0</td>
                <td>1112</td>
                <td>8.6</td>
                <td>288</td>
                <td>1</td>
                <td>5.7</td>
                <td>175</td>
              </tr>
              <tr valign="top">
                <td>2008</td>
                <td>46.5</td>
                <td>45.25</td>
                <td>7000</td>
                <td>10.3</td>
                <td>1108</td>
                <td>13.4</td>
                <td>232</td>
                <td>0</td>
                <td>5.5</td>
                <td>141</td>
              </tr>
              <tr valign="top">
                <td>2009</td>
                <td>47.5</td>
                <td>52.0833</td>
                <td>6958</td>
                <td>6.3</td>
                <td>1119</td>
                <td>16.6</td>
                <td>296</td>
                <td>0</td>
                <td>10.8</td>
                <td>174</td>
              </tr>
              <tr valign="top">
                <td>2010</td>
                <td>43.3</td>
                <td>43.3333</td>
                <td>6893</td>
                <td>8.9</td>
                <td>989</td>
                <td>10.4</td>
                <td>275</td>
                <td>3</td>
                <td>8.0</td>
                <td>159</td>
              </tr>
              <tr valign="top">
                <td>2011</td>
                <td>41.3</td>
                <td>41.8333</td>
                <td>6931</td>
                <td>7.6</td>
                <td>1145</td>
                <td>12.5</td>
                <td>351</td>
                <td>9</td>
                <td>8.6</td>
                <td>189</td>
              </tr>
              <tr valign="top">
                <td>2012</td>
                <td>40.3</td>
                <td>40.0833</td>
                <td>6876</td>
                <td>13.4</td>
                <td>1101</td>
                <td>10.1</td>
                <td>339</td>
                <td>4</td>
                <td>11.5</td>
                <td>193</td>
              </tr>
              <tr valign="top">
                <td>2013</td>
                <td>37.9</td>
                <td>38.1667</td>
                <td>7026</td>
                <td>13.8</td>
                <td>1122</td>
                <td>12.3</td>
                <td>357</td>
                <td>6</td>
                <td>8.1</td>
                <td>187</td>
              </tr>
              <tr valign="top">
                <td>2014</td>
                <td>36.6</td>
                <td>38.0833</td>
                <td>7344</td>
                <td>13.3</td>
                <td>1100</td>
                <td>10.3</td>
                <td>321</td>
                <td>3</td>
                <td>9.7</td>
                <td>223</td>
              </tr>
              <tr valign="top">
                <td>2015</td>
                <td>39.4</td>
                <td>39.9167</td>
                <td>7775</td>
                <td>17.7</td>
                <td>1229</td>
                <td>11.3</td>
                <td>375</td>
                <td>3</td>
                <td>9.3</td>
                <td>210</td>
              </tr>
              <tr valign="top">
                <td>2016</td>
                <td>39.9</td>
                <td>39.75</td>
                <td>8497</td>
                <td>15.3</td>
                <td>1292</td>
                <td>11.4</td>
                <td>384</td>
                <td>3</td>
                <td>9.3</td>
                <td>207</td>
              </tr>
              <tr valign="top">
                <td>2017</td>
                <td>42.7</td>
                <td>43.9167</td>
                <td>8740</td>
                <td>14.3</td>
                <td>1413</td>
                <td>9.8</td>
                <td>380</td>
                <td>9</td>
                <td>8.1</td>
                <td>234</td>
              </tr>
              <tr valign="top">
                <td>2018</td>
                <td>46.3</td>
                <td>50.25</td>
                <td>8875</td>
                <td>17.3</td>
                <td>1426</td>
                <td>11.8</td>
                <td>387</td>
                <td>7</td>
                <td>9.0</td>
                <td>261</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn id="table2fn1">
              <p><sup>a</sup>TX: number of transplantations.</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
        <table-wrap position="float" id="table3">
          <label>Table 3</label>
          <caption>
            <p>The respective year, number of search queries using Google Trends, and the total number of liver transplantations performed are provided (deceased donor and living donor).</p>
          </caption>
          <table width="1000" cellpadding="5" cellspacing="0" border="1" rules="groups" frame="hsides">
            <col width="90"/>
            <col width="90"/>
            <col width="100"/>
            <col width="120"/>
            <col width="90"/>
            <col width="90"/>
            <col width="120"/>
            <col width="90"/>
            <col width="110"/>
            <col width="100"/>
            <thead>
              <tr valign="top">
                <td>Year</td>
                <td>Germany Google Trends index</td>
                <td>Germany TX<sup>a</sup> total</td>
                <td>Austria Google Trends index</td>
                <td>Austria TX total</td>
                <td>Slovenia TX total</td>
                <td>Hungary Google Trends index</td>
                <td>Hungary TX total</td>
                <td>Croatia Google Trends index</td>
                <td>Croatia TX total</td>
              </tr>
            </thead>
            <tbody>
              <tr valign="top">
                <td>2004</td>
                <td>61.6</td>
                <td>795</td>
                <td>15.5</td>
                <td>135</td>
                <td>24</td>
                <td>0.0</td>
                <td>0</td>
                <td>8.3</td>
                <td>0</td>
              </tr>
              <tr valign="top">
                <td>2005</td>
                <td>52.0</td>
                <td>901</td>
                <td>14.6</td>
                <td>142</td>
                <td>15</td>
                <td>0.0</td>
                <td>0</td>
                <td>8.3</td>
                <td>0</td>
              </tr>
              <tr valign="top">
                <td>2006</td>
                <td>35.3</td>
                <td>979</td>
                <td>6.9</td>
                <td>141</td>
                <td>21</td>
                <td>8.3</td>
                <td>0</td>
                <td>0.0</td>
                <td>0</td>
              </tr>
              <tr valign="top">
                <td>2007</td>
                <td>32.6</td>
                <td>1074</td>
                <td>16.2</td>
                <td>121</td>
                <td>15</td>
                <td>1.4</td>
                <td>0</td>
                <td>0.8</td>
                <td>22</td>
              </tr>
              <tr valign="top">
                <td>2008</td>
                <td>35.8</td>
                <td>1122</td>
                <td>11.7</td>
                <td>119</td>
                <td>22</td>
                <td>1.0</td>
                <td>0</td>
                <td>1.5</td>
                <td>65</td>
              </tr>
              <tr valign="top">
                <td>2009</td>
                <td>35.3</td>
                <td>1065</td>
                <td>9.4</td>
                <td>165</td>
                <td>22</td>
                <td>2.2</td>
                <td>0</td>
                <td>2.0</td>
                <td>65</td>
              </tr>
              <tr valign="top">
                <td>2010</td>
                <td>29.2</td>
                <td>1173</td>
                <td>8.8</td>
                <td>135</td>
                <td>34</td>
                <td>0.6</td>
                <td>0</td>
                <td>1.7</td>
                <td>113</td>
              </tr>
              <tr valign="top">
                <td>2011</td>
                <td>33.6</td>
                <td>1097</td>
                <td>11.8</td>
                <td>129</td>
                <td>24</td>
                <td>2.2</td>
                <td>0</td>
                <td>1.3</td>
                <td>128</td>
              </tr>
              <tr valign="top">
                <td>2012</td>
                <td>36.3</td>
                <td>980</td>
                <td>12.9</td>
                <td>129</td>
                <td>38</td>
                <td>1.8</td>
                <td>8</td>
                <td>1.2</td>
                <td>142</td>
              </tr>
              <tr valign="top">
                <td>2013</td>
                <td>31.8</td>
                <td>836</td>
                <td>9.8</td>
                <td>142</td>
                <td>35</td>
                <td>1.3</td>
                <td>51</td>
                <td>1.9</td>
                <td>120</td>
              </tr>
              <tr valign="top">
                <td>2014</td>
                <td>30.1</td>
                <td>793</td>
                <td>9.3</td>
                <td>162</td>
                <td>34</td>
                <td>1.2</td>
                <td>122</td>
                <td>1.0</td>
                <td>131</td>
              </tr>
              <tr valign="top">
                <td>2015</td>
                <td>27.9</td>
                <td>765</td>
                <td>5.6</td>
                <td>150</td>
                <td>43</td>
                <td>1.3</td>
                <td>122</td>
                <td>2.3</td>
                <td>145</td>
              </tr>
              <tr valign="top">
                <td>2016</td>
                <td>27.3</td>
                <td>771</td>
                <td>7.3</td>
                <td>157</td>
                <td>37</td>
                <td>0.8</td>
                <td>100</td>
                <td>1.3</td>
                <td>133</td>
              </tr>
              <tr valign="top">
                <td>2017</td>
                <td>30.3</td>
                <td>716</td>
                <td>11.2</td>
                <td>164</td>
                <td>34</td>
                <td>1.3</td>
                <td>91</td>
                <td>1.8</td>
                <td>122</td>
              </tr>
              <tr valign="top">
                <td>2018</td>
                <td>27.3</td>
                <td>807</td>
                <td>6.5</td>
                <td>166</td>
                <td>29</td>
                <td>1.9</td>
                <td>93</td>
                <td>2.3</td>
                <td>138</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn id="table3fn1">
              <p><sup>a</sup>TX: number of transplantations.</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
        <p>In the same period (2004-2018), UNOS reported the most significant increase in deceased donor liver transplants from 6642 to 8875 (+34.0%). Conversely, the number of living donor donations remained stable during the same period. The number of LTs increased by 24.0% and 18.2% in the Eurotransplant and ONT, respectively (<xref rid="figure3" ref-type="fig">Figure 3</xref>; <xref ref-type="supplementary-material" rid="app1">Multimedia Appendix 1</xref>), and the number of (both deceased and live donor) LTs increased by 24.0% and 18.2% in the Eurotransplant and ONT, respectively (<xref rid="figure3" ref-type="fig">Figure 3</xref>; <xref ref-type="supplementary-material" rid="app1">Multimedia Appendix 1</xref>).</p>
        <fig id="figure3" position="float">
          <label>Figure 3</label>
          <caption>
            <p>Number of liver transplants in Eurotransplant, United Network for Organ Sharing, and Organización Nacional de Trasplantes. AUT: Austria; B: Belgium; CRO: Croatia; ESP: Spain; GER: Germany; GT: Google Trends; H: Hungary; NL: the Netherlands; TX: nuber of transplantations; US: United States.</p>
          </caption>
          <graphic xlink:href="jmir_v23i8e21656_fig3.png" alt-version="no" mimetype="image" position="float" xlink:type="simple"/>
        </fig>
        <p>Belgium and the Netherlands were the only 2 countries in the Eurotransplant region with a mild increase in living donor LT; however, in these countries, a significant decrease in the Google Trends index was observed (Belgium: –48.3%; the Netherlands: –53.3%; <xref ref-type="supplementary-material" rid="app2">Multimedia Appendix 2</xref>). Similar downward trends were observed in all Eurotransplant countries. A correlogram of the total transplant numbers and Google Trends indices of the investigated countries are depicted in <xref rid="figure4" ref-type="fig">Figure 4</xref><bold>.</bold> Most notably, even in Croatia, a country with 42 transplantations per million and a dissent solution, the Google Trends index significantly decreased from 7.8 to 2.5 (–75.7%). Google Trends changes and the number of transplants (deceased donor and living donor transplantations) in the respective countries over time are displayed in <xref rid="figure2" ref-type="fig">Figure 2</xref>. The number of DCDD donors in the Eurotransplant region and the UNOS area showed a mild increase. In 2018, only 8.08% (145/1795) and 5.71% (537/9412) of deceased donors were DCDD donors for LT in the Eurotransplant and UNOS regions, respectively (<xref ref-type="supplementary-material" rid="app3">Multimedia Appendix 3</xref>).</p>
        <fig id="figure4" position="float">
          <label>Figure 4</label>
          <caption>
            <p>Correlogram of total transplant numbers and Google Trends indices of investigated countries. Correlations are based on the Spearman correlation coefficient. Pairwise correlations between total transplant numbers per country and Google Trends indices were calculated. Significant correlations with <italic>P</italic> values &#60;.05 and &#60;.001 are highlighted by a colorful background in the upper and lower half of the matrix, respectively. AUT: Austria; B: Belgium; CRO: Croatia; ESP: Spain; GER: Germany; GT: Google Trends; H: Hungary; NL: the Netherlands; TX: nuber of transplantations; US: United States.</p>
          </caption>
          <graphic xlink:href="jmir_v23i8e21656_fig4.png" alt-version="no" mimetype="image" position="float" xlink:type="simple"/>
        </fig>
      </sec>
      <sec>
        <title>Google Trends and Waiting List Mortality</title>
        <p>The waiting list mortality did not change significantly in UNOS (–5.2%) and Eurotransplant (–6.2%; <xref ref-type="supplementary-material" rid="app4">Multimedia Appendix 4</xref>) regions. Even in Germany, the Eurotransplant country with the highest waiting list mortality (451/1379, 32.7%), the Google Trends index decreased from 40.4 to 21.1 (–48.5%). Furthermore, we analyzed the data of UNOS based on ethnicity. With no significant change over time, Hispanic individuals (2.4%), and American Indians and Alaska Natives (each 4.8%), had a significantly higher mortality on the waiting list than that of all ethnicities (<xref ref-type="supplementary-material" rid="app5">Multimedia Appendix 5</xref>). An overview of changes in Google Trends over time, number of transplants (deceased donor, DCDD, and living donor transplantation) in the respective countries is depicted in <xref rid="figure3" ref-type="fig">Figure 3</xref>.</p>
      </sec>
      <sec>
        <title>Google Trends and LT Program in Spain</title>
        <p>Spain exhibited a distinct Google Trends index pattern compared to other countries. The index slightly decreased until 2011 (the year of implementation of the DCDD program in Spain). A campaign for DCDD donors in the public, as well as in hospitals where potential donors are hospitalized, resulted in an increase in the Google Trends index. In the period of 15 years, we could not find a significant decrease in the Google Trends index (–1.8%). In fact, the number of transplanted livers increased because of DCDD by 18.1%. Moreover, there was a decrease in waiting list mortality between 2011 and 2012 (–4.7%). The overall waiting list mortality, too sick to transplant, and the dropout rate for other reasons were also significantly lower in Spain (15%) than in UNOS (31%) or Eurotransplant (29%; <xref ref-type="supplementary-material" rid="app5">Multimedia Appendix 5</xref>).</p>
      </sec>
    </sec>
    <sec sec-type="discussion">
      <title>Discussion</title>
      <sec>
        <title>Principal Findings</title>
        <p>In this study, we found a significant decrease in Google Trends search queries for LT in the UNOS and Eurotransplant regions. As such, public and health care providers’ levels of awareness regarding LT are decreasing alarmingly. In Spain, the leading country for transplantation, these findings were not as pronounced. Furthermore, the dropout rate in Spain was significantly lower than that in UNOS and Eurotransplant. Although the need for LT, as the only curative option for chronic liver disease, is increasing, the number of donor organs is also increasing. However, the gap between possible recipients and donors is also increasing. To close this gap, transplant and donor programs, which in part bring awareness to both the public and health care domains, may provide some improvement.</p>
        <p>As indicated by the compelling findings presented here, the application of internet data in health care research presents a promising new field. It may further complement and extend the current data sources and foundations [<xref ref-type="bibr" rid="ref43">43</xref>]. Approximately 90% of US citizens use the internet regularly. According to a data analysis of Pew Research Center (Washington, DC), following an ongoing rapid growth of <italic>going online</italic> and use of social media in the United States over the last decade, it stayed stable over the past 3 years. Comparable data are available in Europe.</p>
        <p><italic>Health</italic> and <italic>health care</italic> were the number 2 priorities to the US public in 2019. Internet users tend to search for health-related topics accordingly. In fact, more than 80% of all internet users look for health information on the web. Among them, 66% searched for information concerning a specific disease or medical problem (perennially the most popular purpose), and 56% were interested in a certain medical treatment or procedure. After checking emails and using search engines, looking for health topics was the third most frequent activity on the internet. Interestingly, the typical search for health information is on behalf of someone else [<xref ref-type="bibr" rid="ref44">44</xref>]. The most popular science Facebook group boasts up to 44 million followers [<xref ref-type="bibr" rid="ref45">45</xref>]. Limited access to internet use, especially internet search for health-related topics, has been found in minorities such as Hispanic, American Indian, and Alaska Native (PEW Research Center). This finding might in part explain the higher mortality and morbidity rates in these ethnicities compared with other ethnicities. Although health care topics on the internet are constantly rising, interest in LT has been decreasing since 2014 all over the world. This trend indicates that the topic LT is underrepresented in the web, despite a small increase seen from 2014 onward. However, the internet (eg, search engines and social media) is the largest platform for awareness programs in the field of liver disease and LT.</p>
        <p>To date, very little is published regarding the awareness of LT. This disparity between the low search volumes of the terms relating to LT and the actual increasing number of transplantations may originate in the established low awareness campaigns of LT. Such campaigns are highly useful, as past awareness movements have proved extremely effective. For example, the <italic>Ice Bucket Challenge</italic> promoted awareness of amyotrophic lateral sclerosis. This activity, demonstrated by the dumping of a bucket of ice water over a person’s head, went viral in the summer of 2014 and resulted in a nearly 1000-fold increase in the Google Trends index. Subsequently, over US $220 million in funding has been raised worldwide for this rare disease. Several awareness campaigns related to other health issues in recent years have also proved immensely successful. One of the best known includes the <italic>Red Ribbon</italic> movement to fight HIV infection. Even a <italic>World AIDS Day</italic> was initiated on December 1, 1988 [<xref ref-type="bibr" rid="ref46">46</xref>]. Other programs, such as those promoting the fight against breast cancer, were followed with significant successes in both awareness and funding. An additional notable example is the <italic>Jade Ribbon Campaign,</italic> which was a great success in hepatitis B virus awareness, screening, and physician follow-ups in Chinese Americans. Conversely, the term <italic>liver disease</italic> is strongly underrepresented in the public awareness and, in turn, the World Health Organization’s goal to eradicate hepatitis C by 2030 will most likely not be achieved. Even in well-developed countries, there is too little awareness of this disease among health care providers and the broad public [<xref ref-type="bibr" rid="ref47">47</xref>]. The LT field was even more underrepresented. The reasons for this dearth of awareness are two-fold. The knowledge of primary care providers regarding the possibilities of LT remains insufficient. However, patients complain about a lack of information related to the nature of their disease and the potential to undergo LT.</p>
        <p>As shown from past promotion campaigns of various other diseases, public awareness should be the key goal to increase organ donation rates. Spain’s case offers evidence of such contention. The overwhelming number of 43.4 donors per million population in the country (2016) reflects the increased level of information provided to the public regarding organ donation. Close attention to the mass media is a key point of the Spanish system and serves a preeminent way to inform the public and raise awareness. As a result of Spain’s communication policy, journalists have become extremely important in promoting organ donation. This topic is massive and continuously presented in the media. In 2016, a total of 155 Spanish media reports or news on the topic transplantation were on TV, radio, and printed press releases on the European organ donation day in October. The internet and social media were not included in the survey. The estimated audience comprised 24 million people [<xref ref-type="bibr" rid="ref48">48</xref>]. Thus, the interest in LT in Spain has remained high over the past 16 years.</p>
        <p>In addition, it is important to note that the number of DCDD LTs has increased significantly over the last few years in Spain. This increase in LTs, including DCDD, might reflect the success of awareness campaigns by the ONT. The ONT has established awareness programs across the country, subject to the national Spanish health ministry. Hepatologists and anesthesiologists with special training in the field of LT are representatives of transplantation programs [<xref ref-type="bibr" rid="ref49">49</xref>]. The fruits of this work were visible in our Google Trends analysis. Specifically, there were increased search rates of the topic, <italic>liver transplantation</italic>, in Spain, alongside increased number of donors, transplantations, and a lower mortality rate on the waiting list. Thus, we conclude that a stable Google Trends index, compared with the global trend, reflects the success story in Spain. This underlines our hypothesis that sensitizing people for the topic could close the gap between supply and demand in LT. Furthermore, the worldwide increase of the search terms <italic>liver transplantation</italic> and <italic>liver transplant</italic> since 2014 may be because of more awareness programs, as well as an increasing number of DCDD and living donor transplants worldwide. Indeed, steps to increase awareness are underway. For example, the first National Patient Advisory Committee of America’s Liver Foundation was founded. At present, more than 50 diverse members are trained to raise awareness of the field of LT across the United States. In 2015, legislators were educated about LT and liver disease. Such discussions resulted in an annual Advocacy Day, which allowed for more awareness and an increase in search terms in the United States and worldwide.</p>
        <p>The impact of web-based research has grown continuously in the past decade [<xref ref-type="bibr" rid="ref50">50</xref>]. To date, Google Trends is the only unbiased approach that includes millions of users and has been widely used in economics and health issues. In economics, Google Trends data can help to improve forecasts of the current level of activity for a number of different economic time series such as automobile sales, retail sales, or unemployment [<xref ref-type="bibr" rid="ref51">51</xref>,<xref ref-type="bibr" rid="ref52">52</xref>]. Economists have already been at work using Google Trends to make quantitative forecasts [<xref ref-type="bibr" rid="ref51">51</xref>,<xref ref-type="bibr" rid="ref53">53</xref>]. Several recent research publications demonstrate that data on web searches from Google Trends can improve the accuracy of forecasts over conventional models. The use of Google data has rapidly spread in the literature to predict other economic indicators, such as analyzing their impact on stock markets and studying bond markets or their impact on commodities [<xref ref-type="bibr" rid="ref54">54</xref>,<xref ref-type="bibr" rid="ref55">55</xref>]. Goggle Trends and the field of infodemiology are being widely used in the field of health-related issues as well. Public attention in different fields of health care has been published recently (eg, osteoarthritis, breast cancer, or chronic inflammatory lung disease) [<xref ref-type="bibr" rid="ref34">34</xref>,<xref ref-type="bibr" rid="ref56">56</xref>,<xref ref-type="bibr" rid="ref57">57</xref>]. Furthermore, infodemiology and Google Trends are used to generate awareness profiles and are suitable substitutes for classical data collection, such as surveys [<xref ref-type="bibr" rid="ref50">50</xref>]. Thus far, Google Trends has been primarily used to monitor disease control and awareness in cancer, HIV, or stroke and also in rare diseases such as antiphospholipid syndrome or systemic lupus erythematosus [<xref ref-type="bibr" rid="ref35">35</xref>,<xref ref-type="bibr" rid="ref58">58</xref>-<xref ref-type="bibr" rid="ref60">60</xref>]. Google Trends offers a wide range of capabilities, with one being the detection of success rates of awareness programs [<xref ref-type="bibr" rid="ref61">61</xref>,<xref ref-type="bibr" rid="ref62">62</xref>].</p>
      </sec>
      <sec>
        <title>Limitations</title>
        <p>Our data indicate multiple novel aspects in the field of LT, such as those concerning donor and recipient awareness. Nonetheless, as with any study, there are some potential limitations. Data should be interpreted with caution in the context of public health and disease awareness. Rationale is 2-fold. First, there was no information about individual searches for the analyzed topics. A bias related to a high number of search queries by health care professionals, industry, or marketing agencies cannot be excluded. Second, it is to some extent elusive which search queries are summarized in the topics defined by Google Trends algorithms, as detailed information on how Google generates these data is not provided. The selection of spelling or terms might affect the results and conclusions; therefore, we chose to use more accurate spelling by native speakers and provide a detailed description of our data-gathering approach to facilitate reproducibility. Misspellings, slang words, or different accent use were considered; foreign languages (eg, English and official languages of neighboring countries) were not taken into consideration. Furthermore, some countries (eg, Hungary and Luxembourg) have a lower number of inhabitants, thus resulting in a small sample size for these countries. This may result in huge variations in Google Trends analyses over time. Another limitation may concern rural areas, as they tend to have limited internet access. Moreover, the internet use of the term <italic>liver transplantation</italic> is low in some countries and their official languages. The importance of accuracy in defining search queries is exemplified by searching Google Trends for the topic <italic>immunosuppressants</italic>. Although not specifically representing LT, immunosuppressants are associated with LT. Hence, using the query <italic>immunosuppressant</italic> may be useful to analyze symptom-related interest but does not sufficiently represent LT awareness. Finally, the number of studies based on Google Trends has been increasing, but so far, there is no standardized procedure for data collection. More guidance by Google is warranted to assist researchers in establishing an optimal search strategy [<xref ref-type="bibr" rid="ref63">63</xref>].</p>
      </sec>
      <sec>
        <title>Conclusions</title>
        <p>Google Trends provides a powerful tool for evaluating public interest related to LT and associated liver diseases. According to our study, interest in LT has decreased over the last decade in all investigated countries except Spain. The success story in Spain is encouraging, as it confirms that more awareness campaigns in the field of LT are needed to close the gap between increasing demand and a small supply of potential donor organs. Therefore, international awareness programs are required. In the future, the effects of awareness programs could be evaluated using Google Trends. In line with the goal of higher awareness for solid organ transplantation, Google Trends helps to collect, analyze, report, and disseminate LT-related health data. Google Trends may, therefore, not only drive change and track progress but may also help to improve programs to counteract the current lack of public LT awareness.</p>
      </sec>
    </sec>
  </body>
  <back>
    <app-group>
      <supplementary-material id="app1">
        <label>Multimedia Appendix 1</label>
        <p>Liver transplant numbers per country and year.</p>
        <media xlink:href="jmir_v23i8e21656_app1.pdf" xlink:title="PDF File  (Adobe PDF File), 134 KB"/>
      </supplementary-material>
      <supplementary-material id="app2">
        <label>Multimedia Appendix 2</label>
        <p>Living, deceased, and donation after circulatory determination of death donors in Eurotransplant by country.</p>
        <media xlink:href="jmir_v23i8e21656_app2.pdf" xlink:title="PDF File  (Adobe PDF File), 147 KB"/>
      </supplementary-material>
      <supplementary-material id="app3">
        <label>Multimedia Appendix 3</label>
        <p>Living, deceased, and donation after circulatory determination of death donors in Eurotransplant, United Network for Organ Sharing, and Organización Nacional de Trasplantes.</p>
        <media xlink:href="jmir_v23i8e21656_app3.pdf" xlink:title="PDF File  (Adobe PDF File), 128 KB"/>
      </supplementary-material>
      <supplementary-material id="app4">
        <label>Multimedia Appendix 4</label>
        <p>Liver waiting list removal due to death, too sick to transplant, died during transplant, and others.</p>
        <media xlink:href="jmir_v23i8e21656_app4.pdf" xlink:title="PDF File  (Adobe PDF File), 161 KB"/>
      </supplementary-material>
      <supplementary-material id="app5">
        <label>Multimedia Appendix 5</label>
        <p>United Network for Organ Sharing data on death removal by ethnicity by year in percentages (%).</p>
        <media xlink:href="jmir_v23i8e21656_app5.pdf" xlink:title="PDF File  (Adobe PDF File), 147 KB"/>
      </supplementary-material>
    </app-group>
    <glossary>
      <title>Abbreviations</title>
      <def-list>
        <def-item>
          <term id="abb1">DCDD</term>
          <def>
            <p>donation after circulatory determination of death</p>
          </def>
        </def-item>
        <def-item>
          <term id="abb2">LT</term>
          <def>
            <p>liver transplantation</p>
          </def>
        </def-item>
        <def-item>
          <term id="abb3">ONT</term>
          <def>
            <p>Organización Nacional de Trasplantes</p>
          </def>
        </def-item>
        <def-item>
          <term id="abb4">UNOS</term>
          <def>
            <p>United Network for Organ Sharing</p>
          </def>
        </def-item>
      </def-list>
    </glossary>
    <ack>
      <p>This work was supported by the Excellence Initiative VASCage (Centre for Promoting Vascular Health in the Ageing Community), a research and development K-Centre (COMET [Competence Centers for Excellent Technologies] program) funded by the Austrian Ministry for Transport, Innovation and Technology, the Austrian Ministry for Digital and Economic Affairs, and the federal states Tyrol, Salzburg, and Vienna.</p>
    </ack>
    <fn-group>
      <fn fn-type="conflict">
        <p>None declared.</p>
      </fn>
    </fn-group>
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