Abstract
With the globalization of travel and economic trade, disease can spread rapidly across the globe, sometimes causing panic, population flight and other forms of social disorder. These responses often herald a significant change in the epidemiological pattern or etiology of an infectious disease event. It is therefore increasingly important not only to detect outbreaks of infectious disease early, but also to anticipate and describe the social response to the disease. We use social network analysis to model situations in which a society exhibits social strain in connection with a disease. We model negative social response (NSR) by coupling disease spread and opinion diffusion and verify the results against real-world scenarios. This model captures the complex interaction between disease and culturally determined social responses, providing insights that may help operational analysts and policy makers better respond to sudden disease outbreaks.
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Evans, J., Fast, S., Markuzon, N. (2013). Modeling the Social Response to a Disease Outbreak. In: Greenberg, A.M., Kennedy, W.G., Bos, N.D. (eds) Social Computing, Behavioral-Cultural Modeling and Prediction. SBP 2013. Lecture Notes in Computer Science, vol 7812. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37210-0_17
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DOI: https://doi.org/10.1007/978-3-642-37210-0_17
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-37209-4
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