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<?covid-19-tdm?>
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  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher-id">JMU</journal-id>
      <journal-id journal-id-type="nlm-ta">JMIR Mhealth Uhealth</journal-id>
      <journal-title>JMIR mHealth and uHealth</journal-title>
      <issn pub-type="epub">2291-5222</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">v10i6e36065</article-id>
      <article-id pub-id-type="pmid">35609313</article-id>
      <article-id pub-id-type="doi">10.2196/36065</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>Monitoring Symptoms of COVID-19: Review of Mobile Apps</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="editor">
          <name>
            <surname>Buis</surname>
            <given-names>Lorraine</given-names>
          </name>
        </contrib>
      </contrib-group>
      <contrib-group>
        <contrib contrib-type="reviewer">
          <name>
            <surname>Katehakis</surname>
            <given-names>Dimitrios</given-names>
          </name>
        </contrib>
        <contrib contrib-type="reviewer">
          <name>
            <surname>Amritphale</surname>
            <given-names>Sudhir Sitaram</given-names>
          </name>
        </contrib>
        <contrib contrib-type="reviewer">
          <name>
            <surname>Wu</surname>
            <given-names>Xia</given-names>
          </name>
        </contrib>
        <contrib contrib-type="reviewer">
          <name>
            <surname>Pit</surname>
            <given-names>Sabrina</given-names>
          </name>
        </contrib>
        <contrib contrib-type="reviewer">
          <name>
            <surname>Joseph</surname>
            <given-names>Amanda</given-names>
          </name>
        </contrib>
      </contrib-group>
      <contrib-group>
        <contrib id="contrib1" contrib-type="author">
          <name name-style="western">
            <surname>Schmeelk</surname>
            <given-names>Suzanna</given-names>
          </name>
          <degrees>EdD, MBA, MS, DPS</degrees>
          <xref rid="aff1" ref-type="aff">1</xref>
          <xref rid="aff2" ref-type="aff">2</xref>
          <ext-link ext-link-type="orcid">https://orcid.org/0000-0003-1886-3798</ext-link>
        </contrib>
        <contrib id="contrib2" contrib-type="author">
          <name name-style="western">
            <surname>Davis</surname>
            <given-names>Alison</given-names>
          </name>
          <degrees>MS</degrees>
          <xref rid="aff1" ref-type="aff">1</xref>
          <xref rid="aff3" ref-type="aff">3</xref>
          <ext-link ext-link-type="orcid">https://orcid.org/0000-0001-7577-5845</ext-link>
        </contrib>
        <contrib id="contrib3" contrib-type="author">
          <name name-style="western">
            <surname>Li</surname>
            <given-names>Qiaozheng</given-names>
          </name>
          <degrees>MS</degrees>
          <xref rid="aff1" ref-type="aff">1</xref>
          <xref rid="aff4" ref-type="aff">4</xref>
          <ext-link ext-link-type="orcid">https://orcid.org/0000-0002-9265-6212</ext-link>
        </contrib>
        <contrib id="contrib4" contrib-type="author">
          <name name-style="western">
            <surname>Shippey</surname>
            <given-names>Caroline</given-names>
          </name>
          <degrees>MS</degrees>
          <xref rid="aff1" ref-type="aff">1</xref>
          <ext-link ext-link-type="orcid">https://orcid.org/0000-0003-1944-3410</ext-link>
        </contrib>
        <contrib id="contrib5" contrib-type="author">
          <name name-style="western">
            <surname>Utah</surname>
            <given-names>Michelle</given-names>
          </name>
          <degrees>MS</degrees>
          <xref rid="aff1" ref-type="aff">1</xref>
          <ext-link ext-link-type="orcid">https://orcid.org/0000-0001-7722-2275</ext-link>
        </contrib>
        <contrib id="contrib6" contrib-type="author">
          <name name-style="western">
            <surname>Myers</surname>
            <given-names>Annie</given-names>
          </name>
          <degrees>MA</degrees>
          <xref rid="aff1" ref-type="aff">1</xref>
          <ext-link ext-link-type="orcid">https://orcid.org/0000-0003-2309-3070</ext-link>
        </contrib>
        <contrib id="contrib7" contrib-type="author">
          <name name-style="western">
            <surname>Reading Turchioe</surname>
            <given-names>Meghan</given-names>
          </name>
          <degrees>RN, MPH, PhD</degrees>
          <xref rid="aff1" ref-type="aff">1</xref>
          <ext-link ext-link-type="orcid">https://orcid.org/0000-0002-6264-6320</ext-link>
        </contrib>
        <contrib id="contrib8" contrib-type="author" corresp="yes">
          <name name-style="western">
            <surname>Masterson Creber</surname>
            <given-names>Ruth</given-names>
          </name>
          <degrees>MSc, RN, PhD</degrees>
          <xref rid="aff1" ref-type="aff">1</xref>
          <address>
            <institution>Weill Cornell Medicine</institution>
            <addr-line>425 E 61st Street</addr-line>
            <addr-line>New York, NY, 10065</addr-line>
            <country>United States</country>
            <phone>1 9144340731</phone>
            <email>rmc2009@med.cornell.edu</email>
          </address>
          <ext-link ext-link-type="orcid">https://orcid.org/0000-0002-4238-9902</ext-link>
        </contrib>
      </contrib-group>
      <aff id="aff1">
        <label>1</label>
        <institution>Weill Cornell Medicine</institution>
        <addr-line>New York, NY</addr-line>
        <country>United States</country>
      </aff>
      <aff id="aff2">
        <label>2</label>
        <institution>St John's University</institution>
        <addr-line>Queens, NY</addr-line>
        <country>United States</country>
      </aff>
      <aff id="aff3">
        <label>3</label>
        <institution>Montefiore Medical Center</institution>
        <addr-line>Bronx, NY</addr-line>
        <country>United States</country>
      </aff>
      <aff id="aff4">
        <label>4</label>
        <institution>Memorial Sloan Kettering Cancer Center</institution>
        <addr-line>New York, NY</addr-line>
        <country>United States</country>
      </aff>
      <author-notes>
        <corresp>Corresponding Author: Ruth Masterson Creber <email>rmc2009@med.cornell.edu</email></corresp>
      </author-notes>
      <pub-date pub-type="collection">
        <month>6</month>
        <year>2022</year>
      </pub-date>
      <pub-date pub-type="epub">
        <day>1</day>
        <month>6</month>
        <year>2022</year>
      </pub-date>
      <volume>10</volume>
      <issue>6</issue>
      <elocation-id>e36065</elocation-id>
      <history>
        <date date-type="received">
          <day>12</day>
          <month>1</month>
          <year>2022</year>
        </date>
        <date date-type="rev-request">
          <day>8</day>
          <month>2</month>
          <year>2022</year>
        </date>
        <date date-type="rev-recd">
          <day>1</day>
          <month>3</month>
          <year>2022</year>
        </date>
        <date date-type="accepted">
          <day>3</day>
          <month>5</month>
          <year>2022</year>
        </date>
      </history>
      <copyright-statement>©Suzanna Schmeelk, Alison Davis, Qiaozheng Li, Caroline Shippey, Michelle Utah, Annie Myers, Meghan Reading Turchioe, Ruth Masterson Creber. Originally published in JMIR mHealth and uHealth (https://mhealth.jmir.org), 01.06.2022.</copyright-statement>
      <copyright-year>2022</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 JMIR mHealth and uHealth, is properly cited. The complete bibliographic information, a link to the original publication on https://mhealth.jmir.org/, as well as this copyright and license information must be included.</p>
      </license>
      <self-uri xlink:href="https://mhealth.jmir.org/2022/6/e36065" xlink:type="simple"/>
      <abstract>
        <sec sec-type="background">
          <title>Background</title>
          <p>Mobile health (mHealth) apps have facilitated symptom monitoring of COVID-19 symptoms globally and have been used to share data with health care professionals and support disease prediction, prevention, management, diagnostics, and improvements in treatments and patient education.</p>
        </sec>
        <sec sec-type="objective">
          <title>Objective</title>
          <p>The aim of this review is to evaluate the quality and functionality of COVID-19 mHealth apps that support tracking acute and long-term symptoms of COVID-19.</p>
        </sec>
        <sec sec-type="methods">
          <title>Methods</title>
          <p>We systematically reviewed commercially available mHealth apps for COVID-19 symptom monitoring by searching Google Play and Apple iTunes using search terms such as “COVID-19,” “Coronavirus,” and “COVID-19 and symptoms.” All apps underwent three rounds of screening. The final apps were independently assessed using the Mobile Application Rating Scale (MARS), an informatics functionality scoring system, and the Center for Disease Control and World Health Organization symptom guidelines. The MARS is a 19-item standardized tool to evaluate the quality of mHealth apps on engagement, functionality, aesthetics, and information quality. Functionality was quantified across the following criteria: inform, instruct, record (collect, share, evaluate, and intervene), display, guide, remind or alert, and communicate. Interrater reliability between the reviewers was calculated.</p>
        </sec>
        <sec sec-type="results">
          <title>Results</title>
          <p>A total of 1017 mobile apps were reviewed, and 20 (2%) met the inclusion criteria. The majority of the 20 included apps (n=18, 90%) were designed to track acute COVID-19 symptoms, and only 2 (10%) addressed long-term symptoms. Overall, the apps scored high on quality, with an overall MARS rating of 3.89 out of 5, and the highest domain score for functionality (4.2). The most common functionality among all apps was the instruct function (n=19, 95%). The most common symptoms included in the apps for tracking were fever and dry cough (n=18, 90%), aches and pains (n=17, 85%), difficulty breathing (n=17, 85%), tiredness, sore throat, headache, loss of taste or smell (n=16, 80%), and diarrhea (n=15, 75%). Only 2 (10%) apps specifically tracked long-term symptoms of COVID-19. The top 4 rated apps overall were state-specific apps developed and deployed for public use.</p>
        </sec>
        <sec sec-type="conclusions">
          <title>Conclusions</title>
          <p>Overall, mHealth apps designed to monitor symptoms of COVID-19 were of high quality, but the majority of apps focused almost exclusively on acute symptoms. Future apps should also incorporate monitoring long-term symptoms of COVID-19 and evidence-based educational materials; they should also include a feature that would allow patients to communicate their symptoms to specific caregivers or their own health care team. App developers should also follow updated technical and clinical guidelines from the Center for Disease Control and the World Health Organization.</p>
        </sec>
      </abstract>
      <kwd-group>
        <kwd>COVID-19</kwd>
        <kwd>mobile apps</kwd>
        <kwd>mobile health</kwd>
        <kwd>mHealth</kwd>
        <kwd>symptom assessment</kwd>
        <kwd>symptom tracking</kwd>
        <kwd>public health</kwd>
        <kwd>mobile health application</kwd>
        <kwd>surveillance</kwd>
        <kwd>digital surveillance</kwd>
        <kwd>monitoring system</kwd>
        <kwd>digital health</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec sec-type="introduction">
      <title>Introduction</title>
      <p>Monitoring and tracking acute short-term symptoms are important to help identify the combination of symptoms that occur in individuals with COVID-19 for personal and public health purposes [<xref ref-type="bibr" rid="ref1">1</xref>]. Information gathered from public symptom tracking can also help guide recommendations for self-isolation and testing and help prevent further spread of the virus [<xref ref-type="bibr" rid="ref2">2</xref>]. The Center for Disease Control (CDC) recommends daily monitoring for symptoms of COVID-19 illness to reduce transmission risk [<xref ref-type="bibr" rid="ref1">1</xref>], and to holistically understand its full impact.</p>
      <p>In addition to short-term symptoms, there is a growing awareness of the long-term symptoms of COVID-19 including fatigue or loss of taste and smell, as well as multiorgan effects on the heart, lungs, renal function, and cognitive functions [<xref ref-type="bibr" rid="ref3">3</xref>]. The population prevalence of long COVID is unknown but is estimated to affect between 1 in 5 people (symptoms beyond 5 weeks) and 1 in 10 people (symptoms 12+ weeks) [<xref ref-type="bibr" rid="ref4">4</xref>] who have been infected with COVID-19. Improved understanding of long-COVID symptoms can help health care professionals recognize the most common long-term impacts and add urgency to the public health messaging focused on the importance of COVID-19 vaccination efforts [<xref ref-type="bibr" rid="ref5">5</xref>].</p>
      <p>Since the start of the pandemic, mobile health (mHealth) [<xref ref-type="bibr" rid="ref6">6</xref>] apps have been leveraged in several ways to control the spread of COVID-19 [<xref ref-type="bibr" rid="ref7">7</xref>]. These mHealth apps can be used to monitor symptoms, share data with providers, and support disease prediction, prevention, management, diagnostics, and improvements in treatments and patient education, ultimately giving patients more control [<xref ref-type="bibr" rid="ref8">8</xref>]. The majority of adults in the United States have access to a smartphone (&#62;85%) [<xref ref-type="bibr" rid="ref9">9</xref>]; thus, mHealth apps are poised to provide scalable and cost-effective delivery of health care at the point of need for patients with COVID-19. The incorporation of pertinent epidemiological and geographic data on the presence of transmittable diseases in a region allows the tracing of cases, which can be used as a successful tool to control the spread of the infection [<xref ref-type="bibr" rid="ref10">10</xref>]. The mHealth apps can also help solve several COVID-19–related challenges by increasing the reach of reliable information to both patients and health care professionals. Additionally, mobile apps can assist in tracking physical and mental health symptoms, support home monitoring, and reduce the burden of hospitals [<xref ref-type="bibr" rid="ref7">7</xref>].</p>
      <p>The aim of this review was to evaluate the quality and functionality of mHealth apps that support tracking acute and long-term symptoms of COVID-19. Our research focuses on the CDC [<xref ref-type="bibr" rid="ref1">1</xref>,<xref ref-type="bibr" rid="ref3">3</xref>,<xref ref-type="bibr" rid="ref11">11</xref>] and World Health Organization (WHO) [<xref ref-type="bibr" rid="ref12">12</xref>] symptom guidelines tracked by the apps as medical understandings continue to develop over time. Our analysis can support health care professionals by identifying appropriate mHealth apps for patients regarding COVID-19 acute and long-term symptoms. This review also identified key areas in the quality, functionality, and content of existing COVID-19 apps that can be improved in current and future related app development.</p>
    </sec>
    <sec sec-type="methods">
      <title>Methods</title>
      <sec>
        <title>Systematic Search Criteria and Selection</title>
        <p>In June 2021, we systematically searched 2 major app stores: the Apple App Store and Android Google Play Store. In the 2 app stores, search terms included “COVID-19,” “Coronavirus,” “COVID-19 and Symptoms,” “Coronavirus and Symptoms,” “COVID-19 and Symptom Monitoring,” and “Coronavirus and Symptom Monitoring” to identify relevant apps. Following subsequent searches of “COVID-19” and “Coronavirus,” the authors found that the results were the same. The terms “COVID-19,” “Coronavirus,” “COVID-19 and Symptoms,” and “COVID-19 and Symptom Monitoring” were then collapsed to streamline the search.</p>
        <p>All apps underwent three rounds of screening. During the first round, the title and screenshots of the apps were used to exclude those that were exclusively for contact tracing (without symptom tracking functionality), were not available in English, required an institution-specific login, were clinical guidelines for clinicians, were games, or provided general or other COVID-19–related information. During the second round of review, screenshots and descriptions of the apps were reviewed to exclude apps that were too general, only had a singular function (eg, only track and trace), or were not relevant to tracking COVID-19 symptoms. During the third round of review, the final apps were downloaded, and apps requiring institutional credentialing were excluded.</p>
      </sec>
      <sec>
        <title>Evaluation Measures or Rating Tools</title>
        <p>All apps were evaluated using the Mobile Application Rating Scale (MARS) [<xref ref-type="bibr" rid="ref13">13</xref>,<xref ref-type="bibr" rid="ref14">14</xref>], IQVIA for Healthcare Informatics [<xref ref-type="bibr" rid="ref15">15</xref>] functionality scoring system, and specific COVID-19 symptoms according to the CDC [<xref ref-type="bibr" rid="ref1">1</xref>,<xref ref-type="bibr" rid="ref3">3</xref>,<xref ref-type="bibr" rid="ref11">11</xref>] and WHO COVID-19 health topic guidelines [<xref ref-type="bibr" rid="ref12">12</xref>]. Both the MARS and IQVIA functionality scores were used for this review. The MARS functionality score focuses on performance, ease of use, navigation, and gestural design of the app [<xref ref-type="bibr" rid="ref13">13</xref>]. The 7 IQVIA functionality scores focus on the scope of functions, including informing, instructing, recording, displaying, guiding, reminding, and communicating information [<xref ref-type="bibr" rid="ref14">14</xref>].</p>
        <p>The MARS [<xref ref-type="bibr" rid="ref13">13</xref>] is a widely used, multidimensional tool to evaluate the quality of mobile health apps and was developed based on semantic analysis and a combination of relevant literature. The MARS was used to rate app quality and includes four sections: classification, quality, satisfaction, and a modifiable app-specific section. The classification section provides descriptive information about the apps. The objective app quality section includes 19 items divided into four scales: engagement, functionality, aesthetics, and information quality. MARS items are scored using a 5-point Likert scale (1=inadequate, 2=poor, 3=acceptable, 4=good, and 5=excellent) [<xref ref-type="bibr" rid="ref13">13</xref>]. The final MARS scores include a total mean score for the engagement, functionality, aesthetics, and information subscales. In addition, the MARS also includes a subjective quality score and an app-specific subscale that assesses perceived effect on the user’s knowledge, attitudes, and intentions to change, as well as the likelihood of changing the identified targeted behaviors. The functionality domain measures whether an app is easy to learn, encourages seamless navigation, supports a logical flow, and examines the overall app gestural design. The engagement score includes evaluation of whether the app is fun, interesting, customizable, and interactive (eg, sends alerts, messages, reminders, and feedback, and enables sharing), and is well targeted to the intended audience.</p>
        <p>The IQVIA functionality score (formerly termed the IMS functionally score) is based on 7 functionality criteria and 4 functional subcategories as described in detail in the IQVIA Institute for Healthcare Informatics report [<xref ref-type="bibr" rid="ref14">14</xref>]. IQVIA is not an acronym; the name represents a merger between two companies, IMS Health and Quintiles. The apps were evaluated on the 7 functionality criteria of inform, instruct, record, display, guide, remind or alert, and communicate. The record functionality criteria were further scored on 4 subcategories: collect (ability to enter or store data on individual phone), share (ability to transmit data), evaluate (ability to evaluate health data by caregiver or health care entity), and intervene (ability to alert in response to collected data or propose behavioral intervention).</p>
        <p>The specific symptoms tracked in each app were evaluated against acute and long-term symptoms of COVID-19 as reported by the CDC [<xref ref-type="bibr" rid="ref1">1</xref>] and the WHO [<xref ref-type="bibr" rid="ref12">12</xref>] as of June 2021. Acute COVID-19 symptoms included fever, dry cough, tiredness, aches and pains, sore throat, diarrhea, conjunctivitis, headache, loss of taste or smell, skin rash or discoloration of fingers or toes, difficulty breathing or shortness of breath, chest pain or pressure, and loss of speech or movement. Long-COVID-19 symptoms, defined as more than 4 weeks from the initial infection [<xref ref-type="bibr" rid="ref3">3</xref>], included tiredness or fatigue, difficulty thinking or concentrating (“brain fog”), headache, loss of smell or taste, dizziness while standing, heart palpitations, chest pain, difficulty breathing or shortness of breath, cough, joint or muscle pain, depression or anxiety, fever, and symptoms that worsen after physical or mental activities. Symptoms that are consistent with both short-term and long-term COVID-19 (eg, cough), were evaluated based on how data entry was described in the app and the current version of the app.</p>
      </sec>
      <sec>
        <title>Data Extraction and Data Analysis</title>
        <p>We created a Google data extraction form consisting of questions from (1) the MARS questionnaire [<xref ref-type="bibr" rid="ref13">13</xref>], (2) IQVIA functionality guidelines [<xref ref-type="bibr" rid="ref14">14</xref>], and (3) the CDC [<xref ref-type="bibr" rid="ref1">1</xref>] and WHO [<xref ref-type="bibr" rid="ref12">12</xref>] COVID-19 symptoms. A total of 5 reviewers independently evaluated the 4 randomly selected apps using the data extraction form to assess interrater reliability, which was acceptable (0.75-0.83). Domains with low agreement between reviewers (&#60;0.7) were discussed until consensus was reached, apps were rereviewed, and interrater reliability was recalculated. The remaining apps were independently evaluated by 2 reviewers. Mean MARS scores for each domain, MARS total scores, and IQVIA functionality scores are reported.</p>
      </sec>
    </sec>
    <sec sec-type="results">
      <title>Results</title>
      <p>The Android Google Play and Apple App Store searches identified 1017 potentially relevant apps, of which 20 (2%) met our final inclusion criteria. The search strategy (<xref rid="figure1" ref-type="fig">Figure 1</xref>) shows the number of apps included and excluded in each round of review. In total, 50% (n=509) of the apps had a government affiliation, 10% (n=102), were affiliated with a university and the rest (n=406, 40%) were developed by private companies (<xref ref-type="table" rid="table1">Table 1</xref>).</p>
      <fig id="figure1" position="float">
        <label>Figure 1</label>
        <caption>
          <p>PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flowchart of the screening process. MARS: Mobile Application Rating Scale.</p>
        </caption>
        <graphic xlink:href="mhealth_v10i6e36065_fig1.png" alt-version="no" mimetype="image" position="float" xlink:type="simple"/>
      </fig>
      <table-wrap position="float" id="table1">
        <label>Table 1</label>
        <caption>
          <p>Descriptive characteristics of the apps included.</p>
        </caption>
        <table width="1000" cellpadding="5" cellspacing="0" border="1" rules="groups" frame="hsides">
          <col width="250"/>
          <col width="100"/>
          <col width="90"/>
          <col width="120"/>
          <col width="100"/>
          <col width="130"/>
          <col width="130"/>
          <col width="80"/>
          <thead>
            <tr valign="top">
              <td>App name</td>
              <td>Star rating</td>
              <td>N ratings</td>
              <td>Current version</td>
              <td>Last update</td>
              <td>Affiliation</td>
              <td>Geographic location–dependent?</td>
              <td>Privacy policy</td>
            </tr>
          </thead>
          <tbody>
            <tr valign="top">
              <td>Apollo</td>
              <td>4.8</td>
              <td>16</td>
              <td>1.2.8</td>
              <td>2020</td>
              <td>Commercial<sup>a</sup></td>
              <td>No</td>
              <td>Yes</td>
            </tr>
            <tr valign="top">
              <td>Beebe Covid-19 Screening Tool</td>
              <td>3</td>
              <td>2</td>
              <td>N/A<sup>b</sup></td>
              <td>N/A</td>
              <td>Commercial<sup>a</sup></td>
              <td>No</td>
              <td>Yes</td>
            </tr>
            <tr valign="top">
              <td>Geohealthapp Covid19 Tracker</td>
              <td>3.6</td>
              <td>8</td>
              <td>1.2</td>
              <td>2020</td>
              <td>Commercial<sup>a</sup></td>
              <td>No</td>
              <td>Yes</td>
            </tr>
            <tr valign="top">
              <td>Healthy Together - Covid-19</td>
              <td>4.9</td>
              <td>71,219</td>
              <td>1.5.8</td>
              <td>2021</td>
              <td>Commercial<sup>a</sup></td>
              <td>No</td>
              <td>Yes</td>
            </tr>
            <tr valign="top">
              <td>HowWefeel</td>
              <td>4.8</td>
              <td>54,879</td>
              <td>1.13.3</td>
              <td>2020</td>
              <td>Commercial<sup>a</sup></td>
              <td>No</td>
              <td>Yes</td>
            </tr>
            <tr valign="top">
              <td>Patientsphere Cv</td>
              <td>2.8</td>
              <td>9</td>
              <td>1.1</td>
              <td>2020</td>
              <td>Commercial<sup>a</sup></td>
              <td>No</td>
              <td>Yes</td>
            </tr>
            <tr valign="top">
              <td>Apple Covid-19</td>
              <td>4.2</td>
              <td>2782</td>
              <td>5</td>
              <td>2020</td>
              <td>Commercial<sup>a</sup></td>
              <td>No</td>
              <td>Yes</td>
            </tr>
            <tr valign="top">
              <td>Bc Covid-19 Support</td>
              <td>3.4</td>
              <td>7</td>
              <td>1.41</td>
              <td>2021</td>
              <td>Government</td>
              <td>Yes</td>
              <td>Yes</td>
            </tr>
            <tr valign="top">
              <td>Care 19 Diary</td>
              <td>3.8</td>
              <td>591</td>
              <td>3.6</td>
              <td>2020</td>
              <td>Government</td>
              <td>Yes</td>
              <td>Yes</td>
            </tr>
            <tr valign="top">
              <td>Covid Alert DE</td>
              <td>4.2</td>
              <td>30</td>
              <td>1.2.2</td>
              <td>2020</td>
              <td>Government</td>
              <td>Yes</td>
              <td>Yes</td>
            </tr>
            <tr valign="top">
              <td>Covid Alert NJ</td>
              <td>3.7</td>
              <td>301</td>
              <td>1.1.4</td>
              <td>2021</td>
              <td>Government</td>
              <td>Yes</td>
              <td>Yes</td>
            </tr>
            <tr valign="top">
              <td>Covid Alert NY</td>
              <td>4.6</td>
              <td>544</td>
              <td>1.1.7</td>
              <td>2021</td>
              <td>Government</td>
              <td>Yes</td>
              <td>Yes</td>
            </tr>
            <tr valign="top">
              <td>Covid Alert Pennsylvania</td>
              <td>4.1</td>
              <td>301</td>
              <td>2.0.0</td>
              <td>2021</td>
              <td>Government</td>
              <td>Yes</td>
              <td>Yes</td>
            </tr>
            <tr valign="top">
              <td>Covid Coach</td>
              <td>4.8</td>
              <td>722</td>
              <td>1.6</td>
              <td>2021</td>
              <td>Government</td>
              <td>No</td>
              <td>Yes</td>
            </tr>
            <tr valign="top">
              <td>Covid Trace Nevada</td>
              <td>2.8</td>
              <td>172</td>
              <td>1.2.16</td>
              <td>2021</td>
              <td>Government</td>
              <td>Yes</td>
              <td>Yes</td>
            </tr>
            <tr valign="top">
              <td>Crush Covid RI</td>
              <td>3.6</td>
              <td>195</td>
              <td>3</td>
              <td>2020</td>
              <td>Government</td>
              <td>Yes</td>
              <td>Yes</td>
            </tr>
            <tr valign="top">
              <td>Soco Covid-19 Check</td>
              <td>2.3</td>
              <td>50</td>
              <td>1.1.2</td>
              <td>2020</td>
              <td>Government</td>
              <td>Yes</td>
              <td>Yes</td>
            </tr>
            <tr valign="top">
              <td>Check Covid</td>
              <td>4.5</td>
              <td>74</td>
              <td>3</td>
              <td>2021</td>
              <td>University</td>
              <td>No</td>
              <td>Yes</td>
            </tr>
            <tr valign="top">
              <td>My Covid-19 Tracker</td>
              <td>3.8</td>
              <td>5</td>
              <td>1.2.2</td>
              <td>2021</td>
              <td>University</td>
              <td>No</td>
              <td>No</td>
            </tr>
            <tr valign="top">
              <td>Canada Covid-19</td>
              <td>4.4</td>
              <td>16</td>
              <td>5.17</td>
              <td>2021</td>
              <td>Commercial<sup>a</sup></td>
              <td>Yes</td>
              <td>Yes</td>
            </tr>
          </tbody>
        </table>
        <table-wrap-foot>
          <fn id="table1fn1">
            <p><sup>a</sup>For-profit.</p>
          </fn>
          <fn id="table1fn2">
            <p><sup>b</sup>N/A: not applicable.</p>
          </fn>
        </table-wrap-foot>
      </table-wrap>
      <sec>
        <title>Mobile Application Rating Scale</title>
        <p>The average overall MARS rating for the 20 apps was 3.89 with the functionality domain having the highest score (4.20) and the engagement score having the lowest average score (3.52)<italic>.</italic> The top 4 rated apps overall were state-specific apps developed and deployed for public use in New York, Pennsylvania, Rhode Island, and New Jersey (<xref ref-type="table" rid="table2">Table 2</xref>), between July and October 2020<italic>.</italic></p>
        <table-wrap position="float" id="table2">
          <label>Table 2</label>
          <caption>
            <p>Mobile Application Rating Scale (MARS) quality scores.</p>
          </caption>
          <table width="1000" cellpadding="5" cellspacing="0" border="1" rules="groups" frame="hsides">
            <col width="260"/>
            <col width="150"/>
            <col width="150"/>
            <col width="140"/>
            <col width="150"/>
            <col width="150"/>
            <thead>
              <tr valign="top">
                <td>App name</td>
                <td>Engagement</td>
                <td>Functionality</td>
                <td>Aesthetics</td>
                <td>Information</td>
                <td>Overall score</td>
              </tr>
            </thead>
            <tbody>
              <tr valign="top">
                <td>Covid Alert NY</td>
                <td>4.30</td>
                <td>4.50</td>
                <td>4.83</td>
                <td>4.00</td>
                <td>4.41</td>
              </tr>
              <tr valign="top">
                <td>Covid Alert Pennsylvania</td>
                <td>4.00</td>
                <td>4.13</td>
                <td>4.83</td>
                <td>4.00</td>
                <td>4.24</td>
              </tr>
              <tr valign="top">
                <td>Crush Covid RI</td>
                <td>4.05</td>
                <td>4.44</td>
                <td>4.42</td>
                <td>4.04</td>
                <td>4.23</td>
              </tr>
              <tr valign="top">
                <td>Covid Alert NJ</td>
                <td>4.00</td>
                <td>4.50</td>
                <td>4.50</td>
                <td>3.86</td>
                <td>4.21</td>
              </tr>
              <tr valign="top">
                <td>HowWeFeel</td>
                <td>3.90</td>
                <td>4.55</td>
                <td>4.47</td>
                <td>3.80</td>
                <td>4.18</td>
              </tr>
              <tr valign="top">
                <td>Covid Coach</td>
                <td>3.90</td>
                <td>4.63</td>
                <td>4.67</td>
                <td>3.43</td>
                <td>4.16</td>
              </tr>
              <tr valign="top">
                <td>Healthy Together: Covid-19</td>
                <td>3.92</td>
                <td>4.40</td>
                <td>4.47</td>
                <td>3.74</td>
                <td>4.13</td>
              </tr>
              <tr valign="top">
                <td>Check Covid</td>
                <td>4.00</td>
                <td>4.63</td>
                <td>4.33</td>
                <td>3.29</td>
                <td>4.06</td>
              </tr>
              <tr valign="top">
                <td>Canada Covid-19</td>
                <td>3.60</td>
                <td>4.50</td>
                <td>4.33</td>
                <td>3.71</td>
                <td>4.04</td>
              </tr>
              <tr valign="top">
                <td>Covid Alert DE</td>
                <td>3.60</td>
                <td>4.63</td>
                <td>4.17</td>
                <td>3.64</td>
                <td>4.01</td>
              </tr>
              <tr valign="top">
                <td>Apple Covid-19</td>
                <td>3.60</td>
                <td>4.33</td>
                <td>4.22</td>
                <td>3.74</td>
                <td>3.97</td>
              </tr>
              <tr valign="top">
                <td>SoCo Covid-19 Check</td>
                <td>3.60</td>
                <td>4.25</td>
                <td>4.00</td>
                <td>3.79</td>
                <td>3.91</td>
              </tr>
              <tr valign="top">
                <td>My Covid-19 Tracker</td>
                <td>3.30</td>
                <td>3.88</td>
                <td>4.00</td>
                <td>3.64</td>
                <td>3.70</td>
              </tr>
              <tr valign="top">
                <td>Apollo Covid-19</td>
                <td>2.95</td>
                <td>4.00</td>
                <td>4.17</td>
                <td>3.64</td>
                <td>3.69</td>
              </tr>
              <tr valign="top">
                <td>Beebe Covid-19 Screening</td>
                <td>3.10</td>
                <td>4.00</td>
                <td>3.67</td>
                <td>3.64</td>
                <td>3.60</td>
              </tr>
              <tr valign="top">
                <td>Care19 Diary</td>
                <td>2.90</td>
                <td>3.50</td>
                <td>4.00</td>
                <td>3.71</td>
                <td>3.53</td>
              </tr>
              <tr valign="top">
                <td>Patientsphere CV</td>
                <td>3.10</td>
                <td>4.00</td>
                <td>3.50</td>
                <td>3.43</td>
                <td>3.51</td>
              </tr>
              <tr valign="top">
                <td>BC Covid-19 Support</td>
                <td>3.12</td>
                <td>3.85</td>
                <td>3.53</td>
                <td>3.43</td>
                <td>3.48</td>
              </tr>
              <tr valign="top">
                <td>Covid Trace Nevada</td>
                <td>3.00</td>
                <td>3.58</td>
                <td>3.67</td>
                <td>3.57</td>
                <td>3.46</td>
              </tr>
              <tr valign="top">
                <td>Geohealthapp Covid19 Tracker</td>
                <td>2.40</td>
                <td>3.75</td>
                <td>3.83</td>
                <td>2.79</td>
                <td>3.19</td>
              </tr>
              <tr valign="top">
                <td>Average score</td>
                <td>3.52</td>
                <td>4.20</td>
                <td>4.18</td>
                <td>3.64</td>
                <td>3.89</td>
              </tr>
            </tbody>
          </table>
        </table-wrap>
      </sec>
      <sec>
        <title>IQVIA Functionality</title>
        <p>Overall, the “instruct” function was the most common among all apps (n=19, 95%) (<xref rid="figure2" ref-type="fig">Figure 2</xref>). In many of the apps, the instruct function aided in directing users on next steps based on the symptoms that were recorded. The “Beebe COVID-19” screening app was the only app that had the ability to communicate between patients and health care providers. There were no apps that had all 11 functionalities. Another domain that the majority of the apps had was the collect function (n=18, 90%). These apps collected patients’ daily COVID-19 symptoms and collected some demographic information (n=18, 90%) including: age, name, date of birth, ethnicity, and geographical location.</p>
        <fig id="figure2" position="float">
          <label>Figure 2</label>
          <caption>
            <p>Functionality scores based on IQVIA for Healthcare Informatics.</p>
          </caption>
          <graphic xlink:href="mhealth_v10i6e36065_fig2.png" alt-version="no" mimetype="image" position="float" xlink:type="simple"/>
        </fig>
      </sec>
      <sec>
        <title>COVID-19 WHO and CDC Guidelines</title>
        <p>The acute COVID-19 symptoms tracked in each app (<xref ref-type="table" rid="table3">Table 3</xref>), and long-term symptoms (<xref ref-type="table" rid="table4">Table 4</xref>) were evaluated against the recommendations provided by the CDC [<xref ref-type="bibr" rid="ref1">1</xref>] and the WHO [<xref ref-type="bibr" rid="ref12">12</xref>]. The majority of apps focused on acute COVID-19 symptoms (n=18) with the most common acute symptoms including fever and dry cough (n=18, 90%), aches and pains (n=17, 85%), difficulty breathing (n=17, 85%), tiredness, sore throat, headache, loss of taste or smell (n=16, 80%), and diarrhea (n=15, 75%).</p>
        <table-wrap position="float" id="table3">
          <label>Table 3</label>
          <caption>
            <p>COVID-19 acute symptoms.</p>
          </caption>
          <table width="1000" cellpadding="5" cellspacing="0" border="1" rules="groups" frame="hsides">
            <col width="210"/>
            <col width="50"/>
            <col width="60"/>
            <col width="50"/>
            <col width="60"/>
            <col width="50"/>
            <col width="50"/>
            <col width="70"/>
            <col width="80"/>
            <col width="80"/>
            <col width="60"/>
            <col width="100"/>
            <col width="80"/>
            <thead>
              <tr valign="top">
                <td>App name</td>
                <td>Fever</td>
                <td>Dry cough</td>
                <td>Tiredness</td>
                <td>Aches and pains</td>
                <td>Sore throat</td>
                <td>Diarrhea</td>
                <td>Conjunctivitis</td>
                <td>Headache</td>
                <td>Loss of taste or smell</td>
                <td>Skin rash</td>
                <td>Difficulty breathing or shortness of breath</td>
                <td>Chest pain or pressure</td>
              </tr>
            </thead>
            <tbody>
              <tr valign="top">
                <td>Apollo</td>
                <td>✓<sup>a</sup></td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>—<sup>b</sup></td>
                <td>✓</td>
                <td>✓</td>
                <td>—</td>
                <td>✓</td>
                <td>—</td>
              </tr>
              <tr valign="top">
                <td>Apple Covid-19</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>—</td>
                <td>✓</td>
                <td>✓</td>
                <td>—</td>
                <td>✓</td>
                <td>✓</td>
              </tr>
              <tr valign="top">
                <td>BC COVID-19 Support</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>—</td>
                <td>—</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
              </tr>
              <tr valign="top">
                <td>Beebe COVID-19 Screening Tool</td>
                <td>✓</td>
                <td>✓</td>
                <td>—</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>—</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>—</td>
              </tr>
              <tr valign="top">
                <td>Canada COVID-19</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>—</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>—</td>
              </tr>
              <tr valign="top">
                <td>Care19 Diary</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>—</td>
                <td>—</td>
                <td>—</td>
                <td>—</td>
                <td>—</td>
                <td>—</td>
                <td>—</td>
                <td>✓</td>
                <td>—</td>
              </tr>
              <tr valign="top">
                <td>Check Covid</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>—</td>
                <td>✓</td>
                <td>✓</td>
                <td>—</td>
                <td>✓</td>
                <td>✓</td>
              </tr>
              <tr valign="top">
                <td>COVID Alert DE</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>—</td>
                <td>✓</td>
                <td>✓</td>
                <td>—</td>
                <td>✓</td>
                <td>—</td>
              </tr>
              <tr valign="top">
                <td>COVID Alert NJ</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>—</td>
                <td>✓</td>
                <td>✓</td>
                <td>—</td>
                <td>✓</td>
                <td>✓</td>
              </tr>
              <tr valign="top">
                <td>COVID Alert NY</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>—</td>
                <td>✓</td>
                <td>✓</td>
                <td>—</td>
                <td>✓</td>
                <td>—</td>
              </tr>
              <tr valign="top">
                <td>COVID Alert Pennsylvania</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>—</td>
                <td>✓</td>
                <td>✓</td>
                <td>—</td>
                <td>✓</td>
                <td>—</td>
              </tr>
              <tr valign="top">
                <td>COVID Trace Nevada</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>—</td>
                <td>✓</td>
                <td>✓</td>
                <td>—</td>
                <td>✓</td>
                <td>—</td>
              </tr>
              <tr valign="top">
                <td>Crush Covid RI</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>—</td>
                <td>✓</td>
                <td>✓</td>
                <td>—</td>
                <td>✓</td>
                <td>—</td>
              </tr>
              <tr valign="top">
                <td>Healthy Together</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>—</td>
                <td>✓</td>
                <td>✓</td>
                <td>—</td>
                <td>✓</td>
                <td>—</td>
              </tr>
              <tr valign="top">
                <td>HowWeFeel</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>—</td>
                <td>✓</td>
                <td>✓</td>
                <td>—</td>
                <td>✓</td>
                <td>✓</td>
              </tr>
              <tr valign="top">
                <td>My COVID-19 Tracker</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
              </tr>
              <tr valign="top">
                <td>PatientSphere</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>—</td>
                <td>—</td>
                <td>—</td>
                <td>—</td>
                <td>—</td>
                <td>—</td>
                <td>—</td>
              </tr>
              <tr valign="top">
                <td>SoCo COVID-19 Check</td>
                <td>✓</td>
                <td>✓</td>
                <td>—</td>
                <td>✓</td>
                <td>—</td>
                <td>✓</td>
                <td>—</td>
                <td>✓</td>
                <td>✓</td>
                <td>—</td>
                <td>✓</td>
                <td>—</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn id="table3fn1">
              <p><sup>a</sup>✓ implies that the symptom is measured in the app.</p>
            </fn>
            <fn id="table3fn2">
              <p><sup>b</sup>— implies that the symptoms are not measured in the app.</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
        <table-wrap position="float" id="table4">
          <label>Table 4</label>
          <caption>
            <p>COVID-19 long-term symptoms.</p>
          </caption>
          <table width="1000" cellpadding="5" cellspacing="0" border="1" rules="groups" frame="hsides">
            <col width="180"/>
            <col width="60"/>
            <col width="70"/>
            <col width="90"/>
            <col width="70"/>
            <col width="180"/>
            <col width="150"/>
            <col width="90"/>
            <col width="110"/>
            <thead>
              <tr valign="top">
                <td>App name</td>
                <td>Dry cough</td>
                <td>Tiredness</td>
                <td>Headache</td>
                <td>Loss of taste or smell</td>
                <td>Symptoms that worsen after physical or mental activities</td>
                <td>Difficulty breathing or shortness of breath</td>
                <td>Chest pain or pressure</td>
                <td>Depression or anxiety</td>
              </tr>
            </thead>
            <tbody>
              <tr valign="top">
                <td>BC COVID-19 Support</td>
                <td>✓<sup>a</sup></td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>✓</td>
                <td>—<sup>b</sup></td>
              </tr>
              <tr valign="top">
                <td>HowWeFeel</td>
                <td>—</td>
                <td>—</td>
                <td>—</td>
                <td>—</td>
                <td>—</td>
                <td>—</td>
                <td>—</td>
                <td>✓</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn id="table4fn1">
              <p><sup>a</sup>✓ implies that the symptoms are measured in the app.</p>
            </fn>
            <fn id="table4fn2">
              <p><sup>b</sup>— implies that the symptoms are not measured in the app.</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
      </sec>
    </sec>
    <sec sec-type="discussion">
      <title>Discussion</title>
      <sec>
        <title>Principal Findings</title>
        <p>The aim of this review was to evaluate COVID-19 mHealth apps that support tracking acute and long-term symptoms of COVID-19. The majority of the apps reviewed focused on acute symptoms, including fever and dry cough, aches and pains, difficulty breathing, tiredness, sore throat, headache, loss of taste or smell, and diarrhea. Few apps measured long-term symptoms of COVID-19. Overall, the apps scored high on quality, and the most common functionality was providing the user with instructions on what to do in response to symptoms.</p>
        <p>Previous reviews of mHealth apps for COVID-19 were published by Alanzi [<xref ref-type="bibr" rid="ref16">16</xref>] and Davalbhakta [<xref ref-type="bibr" rid="ref17">17</xref>]. The review published by Alanzi [<xref ref-type="bibr" rid="ref16">16</xref>] reviewed apps from 7 countries (Saudi Arabia, India, Singapore, Australia, Italy, United Kingdom, and the United States). These apps were reviewed on functionality (eg, purpose, services offered, and networking technologies) and effectiveness (eg, learnability, communication strategies, and design). There were no overlapping apps between the review published by Alanzi [<xref ref-type="bibr" rid="ref16">16</xref>] and this review. The review by Davalbhakta and colleagues [<xref ref-type="bibr" rid="ref17">17</xref>] was consistent methodologically by using the MARS to review the apps, in addition to adding more functionalities specific to COVID-19 (eg, individual tracking, contact tracing, and health care worker training). The review by Davalbhakta [<xref ref-type="bibr" rid="ref17">17</xref>] and this review shared 6 common apps (Apollo, PatientSphere, Apple COVID-19, Bc COVID-19 Support, Check COVID, and Canada COVID-19). Other reviews did not evaluate short- and long-term symptom monitoring according to the CDC [<xref ref-type="bibr" rid="ref1">1</xref>] or WHO COVID-19 health topic guidelines [<xref ref-type="bibr" rid="ref12">12</xref>].</p>
        <p>The highest quality apps were developed by individual states within the United States to support acute COVID-19 symptom tracking. Overall, the state-specific apps had the most up-to-date and accurate information, which could be attributed to collaborative efforts between local, county, or state departments of health [<xref ref-type="bibr" rid="ref18">18</xref>-<xref ref-type="bibr" rid="ref23">23</xref>]. The state-specific apps all listed most of the common symptoms and provided information about local COVID-19 case counts and developments in research. Strengths of the state-specific apps included long-term storage of the symptom evaluations, high-quality aesthetics, comprehensive symptom lists, and evidence-based information that was aligned with CDC guidelines [<xref ref-type="bibr" rid="ref1">1</xref>]. While the contact tracing functions were likely most useful to in-state residents, the symptom tracking functionalities were available for anyone regardless of their home state.</p>
        <p>At the time of app development and deployment, less was known about long-term symptoms of COVID-19 [<xref ref-type="bibr" rid="ref24">24</xref>]. Only 2 (10%) apps specifically tracked long-term symptoms of COVID-19 (<xref ref-type="table" rid="table4">Table 4</xref>), though the symptoms of long COVID-19 are increasingly concerning [<xref ref-type="bibr" rid="ref25">25</xref>-<xref ref-type="bibr" rid="ref27">27</xref>]. As such, mHealth apps that track long COVID-19 symptoms could play a significant role in helping to manage them more efficiently and gather additional data about how this disease is affecting patients over a long period of time [<xref ref-type="bibr" rid="ref25">25</xref>-<xref ref-type="bibr" rid="ref27">27</xref>]. The authors suggest that app developers should follow updated technical and clinical guidelines from the CDC and the WHO to ensure consistency and efficacy of long-term symptom monitoring. Future research should focus on expanding these apps to support patients with long-term symptoms [<xref ref-type="bibr" rid="ref3">3</xref>] and providing educational materials about the disease.</p>
        <p>The largest gap in app functionality was in the communication feature, which could be further developed to allow patients to communicate their symptoms to chosen family members for supportive care or their own health care professionals. These algorithms are useful for providing basic information about what to do in response to the symptoms and quarantine guidance. However, many patients, especially those with complex care needs, require additional support and communication with their health team to manage long-term symptoms of COVID-19. There are specific legal and regulatory issues around data sharing that are likely the reasons why many apps do not actively support more data-sharing features. Additional areas of future development include expansion into pediatric populations and long-term symptom tracking integrated into mHealth apps. Lastly, these apps should be evaluated for usability and inclusivity characteristics, including non-English languages.</p>
      </sec>
      <sec>
        <title>Limitations</title>
        <p>A limitation of this review is that it provides a snapshot of the app landscape at a specific point in time when the app stores have continued to rapidly evolve. Many of the apps are also going on and off the market based on the introduction of novel variants. To mitigate the limitation of subjectivity of reviewing apps, we applied a rigorous multistep methodology including using the MARS [<xref ref-type="bibr" rid="ref13">13</xref>,<xref ref-type="bibr" rid="ref28">28</xref>,<xref ref-type="bibr" rid="ref29">29</xref>] and IQVIA for Healthcare Informatics [<xref ref-type="bibr" rid="ref15">15</xref>] functionality scoring system and mapping all the apps to the CDC and WHO COVID-19 health topic guidelines for symptom monitoring.</p>
      </sec>
      <sec>
        <title>Conclusion</title>
        <p>In general, mHealth apps for tracking COVID-19 symptoms offer a potential solution to help people identify and track virus symptoms. Overall, the mHealth apps had high quality, considering the expedited needs during the COVID-19 pandemic. Future apps should also incorporate monitoring long-term symptoms of COVID-19 and include a communication feature that could allow patients to communicate their symptoms to specific caregivers or their own health care team.</p>
      </sec>
    </sec>
  </body>
  <back>
    <app-group/>
    <glossary>
      <title>Abbreviations</title>
      <def-list>
        <def-item>
          <term id="abb1">CDC</term>
          <def>
            <p>Center for Disease Control</p>
          </def>
        </def-item>
        <def-item>
          <term id="abb2">MARS</term>
          <def>
            <p>Mobile Application Rating Scale</p>
          </def>
        </def-item>
        <def-item>
          <term id="abb3">mHealth</term>
          <def>
            <p>mobile health</p>
          </def>
        </def-item>
        <def-item>
          <term id="abb4">WHO</term>
          <def>
            <p>World Health Organization</p>
          </def>
        </def-item>
      </def-list>
    </glossary>
    <ack>
      <p>This work was funded by R00NR016275 and R00NR016275-05S1 (PI: Masterson Creber).</p>
    </ack>
    <fn-group>
      <fn fn-type="conflict">
        <p>None declared.</p>
      </fn>
    </fn-group>
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