Modelling the propagation of social response during a disease outbreak |
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Authors: | Shannon M. Fast Marta C. González James M. Wilson Natasha Markuzon |
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Affiliation: | 1.Operations Research Center, Massachusetts Institute of Technology, Cambridge, MA 02139, USA;2.Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA;3.Ascel Bio National Infectious Disease Forecast Center, Ascel Bio LLC, New York City, NY 10018, USA;4.Draper Laboratory, Cambridge, MA 02139, USA |
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Abstract: | Epidemic trajectories and associated social responses vary widely between populations, with severe reactions sometimes observed. When confronted with fatal or novel pathogens, people exhibit a variety of behaviours from anxiety to hoarding of medical supplies, overwhelming medical infrastructure and rioting. We developed a coupled network approach to understanding and predicting social response. We couple the disease spread and panic spread processes and model them through local interactions between agents. The social contagion process depends on the prevalence of the disease, its perceived risk and a global media signal. We verify the model by analysing the spread of disease and social response during the 2009 H1N1 outbreak in Mexico City and 2003 severe acute respiratory syndrome and 2009 H1N1 outbreaks in Hong Kong, accurately predicting population-level behaviour. This kind of empirically validated model is critical to exploring strategies for public health intervention, increasing our ability to anticipate the response to infectious disease outbreaks. |
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Keywords: | coupled networks social response epidemic spreading data-driven models panic spreading |
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