Surveillance Sans Frontières: Internet-Based Emerging Infectious Disease Intelligence and the HealthMap Project

By John S. Brownstein, Clark C. Freifeld, Ben Y. Reis, Kenneth D. Mandl. PLoS Medicine, 2008

396 citations recorded by the source corpus.

John Brownstein and colleagues discuss HealthMap, an automated real-time system that monitors and disseminates online information about emerging infectious diseases.

Subfields: Epidemiology, Modeling and Simulation, Public Health, Environmental and Occupational Health

View Paper: https://www.semanticscholar.org/paper/cc1ee9aead1a77f7092145cb77dc06759e8bf5d7

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Citations in the corpus

Digital Epidemiology (2012, background): “These online sources provide a picture of global health that is often different [9] from the picture created by traditional surveillance systems.”
Social big data: Recent achievements and new challenges (2015, methodology): “HealthMap [117] Global disease alert map Mapping techniques”
Refining the Global Spatial Limits of Dengue Virus Transmission by Evidence-Based Consensus (2012, background): “We would also like to thank Susan Aman and Sumiko Mekaru at HealthMap for database support.”
PATRIC: the Comprehensive Bacterial Bioinformatics Resource with a Focus on Human Pathogenic Species (2011, background): “The “Disease Map” page provides a real-time global view of recent reports and outbreaks of bacterial diseases, with geolocation superimposed on an interactive global health map (11).”
Harvesting ambient geospatial information from social media feeds (2011, background): “For example, there has been a number of studies using data mining techniques to trawl through traditional media such as news articles (Brownstein et al. 2008) or Internet search engines (e.g. Polgreen et al. 2008), and blogs (Corley et al. 2010) to explore disease outbreaks.”
Using electronic health records to drive discovery in disease genomics (2011, background): “There are also highly acute changes such as those caused by infectious diseas”
Towards detecting influenza epidemics by analyzing Twitter messages (2010, background): “There has been growing interest in monitoring disease outbreaks using the Internet, typically either by mining newspaper articles mentioning flu illnesses [9, 18, 1, 23, 3, 15], mining the frequency of visits to health-related websites [12] or mining search engine logs for flu-related queries [6, 22”