Abstract
Early warning systems for the identification and tracking of infections disease outbreaks have become an important tool in the field of epidemiology. While government lead initiatives to increase the sharing of surveillance data have improved early detection and control, along with advanced web monitoring and analytics services, the recent swine flu outbreak of 2009 demonstrated the important role social media has and the wealth of data it exposes. In this paper, we present an investigation into Twitter, using around 3 Million tweets gathered between May and December 2009, as a possible source of surveillance data and its feasibility to serve as an early warning system. By performing simple filtering and normalization, we demonstrate that Twitter can serve as a self-reporting tool, and hence, provide indications of increased infection spreading. Our initial findings indicate that Twitter can detect such events up to one week before conventional GP reported surveillance data.
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© 2011 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering
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Szomszor, M., Kostkova, P., de Quincey, E. (2011). #Swineflu: Twitter Predicts Swine Flu Outbreak in 2009. In: Szomszor, M., Kostkova, P. (eds) Electronic Healthcare. eHealth 2010. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 69. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23635-8_3
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DOI: https://doi.org/10.1007/978-3-642-23635-8_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23634-1
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