Accepted for/Published in: JMIR Public Health and Surveillance
Date Submitted: Jul 9, 2025
Date Accepted: Sep 26, 2025
Digital Survey-based Tracing of COVID-19 Over the Early Pandemic: A Comprehensive Geospatial and Symptomatic Analysis in Lebanon
ABSTRACT
Background:
In response to the early spread of COVID-19 in Lebanon, the University of Balamand developed the Hayati application, a community-focused, GIS-based 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.
Objective:
The aim of this study was to design, implement, and evaluate the effectiveness of the Hayati application 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.
Methods:
The Hayati application was launched in March 2020 using ArcGIS Survey123 and real-time dashboards, incorporating a risk scoring algorithm based on 23 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 PCR 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
Results:
Of the 10,235 individuals who submitted data, 1,782 were classified as high or major risk and referred for PCR testing. Among them, 394 (22.1%) tested positive for SARS-CoV-2. Loss of smell and taste were strongly associated with positive test results (P < .001). The highest positivity rates were observed among individuals aged 18–29 and in the North Governorate. GIS mapping enabled real-time visualization of case clusters, which informed localized containment responses
Conclusions:
The Hayati application 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
Citation
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.