{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T19:06:46Z","timestamp":1782846406939,"version":"3.54.5"},"reference-count":28,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMIR Public Health Surveill"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec sec-type=\"background\">\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>In response to the early spread of COVID-19 in Lebanon, the University of Balamand developed the HAYATI app, a community-focused, geographic information system (GIS)\u2013based digital health platform aimed at enhancing public health surveillance. At the time, while the Lebanese Ministry of Public Health utilized centralized dashboards to report confirmed cases and monitor national trends, no interactive tool existed to engage the public directly in real-time risk assessment and surveillance, especially in underserved regions.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"objective\">\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>The aim of this study was to design, implement, and evaluate the effectiveness of the HAYATI app as a GIS-integrated digital surveillance tool to identify high-risk individuals and support targeted testing and contact tracing during the early stages of the COVID-19 pandemic in Lebanon.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"methods\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>The HAYATI app was launched in March 2020 using ArcGIS Survey123 and real-time dashboards, incorporating a risk scoring algorithm based on 21 clinical and behavioral criteria. Between April 2020 and March 2021, self-reported data were collected from 10,235 individuals across Lebanon. Participants identified as high or major risk through the automated scoring algorithm were referred for free polymerase chain reaction testing at the University of Balamand. Test results were securely communicated to local municipalities and the Ministry of Public Health. Data were analyzed for associations between symptoms and positivity rates, as well as geographic and demographic trends using spatial analysis tools.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"results\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Of the 10,235 individuals who submitted data, 1782 were classified as high or major risk and referred for polymerase chain reaction testing. Among them, 394 (22.1%) tested positive for SARS-CoV-2. Loss of smell and taste was strongly associated with positive test results (\n                      <jats:italic>P<\/jats:italic>\n                      &lt;.001). The highest positivity rates were observed among individuals aged 18\u201029 years and in the North Governorate. GIS mapping enabled real-time visualization of case clusters, which informed localized containment responses.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"conclusions\">\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The HAYATI app effectively filled a critical surveillance gap during the early pandemic phase in Lebanon. By integrating GIS technology, automated risk stratification, and community-level engagement, it provided a scalable model for public health surveillance in resource-limited settings. This approach has potential for broader applications in managing future outbreaks and endemic diseases through decentralized, real-time digital health strategies.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.2196\/80331","type":"journal-article","created":{"date-parts":[[2025,11,20]],"date-time":"2025-11-20T21:41:11Z","timestamp":1763674871000},"page":"e80331-e80331","source":"Crossref","is-referenced-by-count":0,"title":["Digital Survey\u2013Based Tracing of COVID-19 Over the Early Pandemic: Comprehensive Geospatial and Symptomatic Analysis in Lebanon"],"prefix":"10.2196","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-1149-4809","authenticated-orcid":false,"given":"Youssef","family":"Bassim","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-3358-3788","authenticated-orcid":false,"given":"Abir","family":"Abdelrahman","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0628-2964","authenticated-orcid":false,"given":"Amal","family":"Iaaly","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5164-6707","authenticated-orcid":false,"given":"Gavin M","family":"Douglas","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-6513-9844","authenticated-orcid":false,"given":"Patrick","family":"Daou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-2372-569X","authenticated-orcid":false,"given":"Mayda","family":"Finianos","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-5081-4681","authenticated-orcid":false,"given":"Rim","family":"Hassan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-3295-9490","authenticated-orcid":false,"given":"Ibrahim","family":"Nassif","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-4698-5610","authenticated-orcid":false,"given":"Layal","family":"Greige","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-7468-1449","authenticated-orcid":false,"given":"Liza","family":"Dib","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-1300-7989","authenticated-orcid":false,"given":"Jean Marc","family":"Mardirossian","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8889-4234","authenticated-orcid":false,"given":"Mira","family":"El Chaar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1010","published-online":{"date-parts":[[2025,11,20]]},"reference":[{"key":"R1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijid.2020.01.009","article-title":"The continuing 2019-nCoV epidemic threat of novel coronaviruses to global health\u2014the latest 2019 novel coronavirus outbreak in Wuhan, China","volume":"91","author":"Hui","journal-title":"Int J Infect Dis"},{"issue":"4","key":"R2","doi-asserted-by":"publisher","first-page":"441","DOI":"10.1002\/jmv.25689","article-title":"Updated understanding of the outbreak of 2019 novel coronavirus (2019-nCoV) in Wuhan, China","volume":"92","author":"Wang","journal-title":"J Med Virol"},{"issue":"1","key":"R3","doi-asserted-by":"publisher","DOI":"10.1186\/s41256-020-00135-6","article-title":"The novel coronavirus outbreak in Wuhan, China","volume":"5","author":"Zhu","journal-title":"Glob Health Res Policy"},{"key":"R4","unstructured":"Epidemiological surveillance program of COVID-19. 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