Digital Survey–Based Tracing of COVID-19 Over the Early Pandemic: Comprehensive Geospatial and Symptomatic Analysis in Lebanon
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.
Authors
- Gavin M. Douglas (ORCID: https://orcid.org/0000-0001-5164-6707)
- Amal Iaaly (ORCID: https://orcid.org/0000-0002-0628-2964)
- Mira El Chaar (ORCID: https://orcid.org/0000-0002-8889-4234)
- Ibrahim Nassif (ORCID: https://orcid.org/0009-0008-3295-9490)
- Abir Abdel Rahman (ORCID: https://orcid.org/0009-0005-3358-3788)
- Mayda Finianos (ORCID: https://orcid.org/0009-0009-2372-569X)
- Youssef Bassim (ORCID: https://orcid.org/0009-0000-1149-4809)
- Jean Marc Mardirossian (ORCID: https://orcid.org/0009-0004-1300-7989)
- Patrick Daou (ORCID: https://orcid.org/0009-0004-6513-9844)
- Layal Greige (ORCID: https://orcid.org/0009-0002-4698-5610)
- Liza Dib (ORCID: https://orcid.org/0009-0001-7468-1449)
- Rim Hassan (ORCID: https://orcid.org/0009-0001-5081-4681)
Institutions
- University of New Brunswick (CA)
- University of Balamand (LB)
- Jacksonville College (US)
Publication Details
- Journal
- JMIR Public Health and Surveillance
- Published
- 2025-11-20
- DOI
- https://doi.org/10.2196/80331
- Primary Topic
- Data-Driven Disease Surveillance
- Type
- article
- Field-Weighted Citation Impact
- 0.00