Measles Tracker: a near-real-time data hub for measles surveillance
As a centralized, scalable tool, Measles Tracker advances measles surveillance by leveraging digital epidemiology principles. Future iterations will incorporate additional data streams (eg, climate variables, genomic surveillance) and advanced analytics (eg, machine learning for risk prediction, network models for transmission dynamics) to further optimize outbreak preparedness and resource allocation. This framework underscores the transformative potential of integrated data systems in global measles elimination efforts.
Authors
- Fabio Scarpa (ORCID: https://orcid.org/0000-0002-3501-714X)
- Francesco Branda (ORCID: https://orcid.org/0000-0002-9485-3877)
- Massimo Ciccozzi (ORCID: https://orcid.org/0000-0003-3866-9239)
- Maria Tomasso (ORCID: https://orcid.org/0000-0002-4969-2007)
- Mohamed Mustaf Ahmed (ORCID: https://orcid.org/0009-0006-5991-4052)
Institutions
- Texas State University (US)
- Università Campus Bio-Medico (IT)
- University of Sassari (IT)
- SIMAD University (SO)
Publication Details
- Journal
- JAMIA Open
- Published
- 2025-05-02
- DOI
- https://doi.org/10.1093/jamiaopen/ooaf062
- Citations
- 1
- Primary Topic
- Data-Driven Disease Surveillance
- Type
- article
- Field-Weighted Citation Impact
- 1.35