From ‘fake news’ to innovative technologies, many contagions spread as complex contagions via a process of social reinforcement, where multiple exposures are distinct from prolonged exposure to a single source1. Contrarily, biological agents such as Ebola or measles are typically thought to spread as simple contagions2. Here, we demonstrate that these different spreading mechanisms can have indistinguishable population-level dynamics once multiple contagions interact. In the social context, our results highlight the challenge of identifying and quantifying spreading mechanisms, such as social reinforcement3, in a world where an innumerable number of ideas, memes and behaviours interact. In the biological context, this parallel allows the use of complex contagions to effectively quantify the non-trivial interactions of infectious diseases.
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The data represented in Figs. 1–4 are available as Source Data. Raw data and processing scripts are available online (https://github.com/jg-you/complex-coinfection-inference/; https://github.com/Emergent-Epidemics/Puerto_Rico_Arbovirus_Data).
The inference software is available online (https://github.com/jg-you/complex-coinfection-inference/).
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L.H.-D. acknowledges support from the National Science Foundation grant DMS-1829826 and the National Institutes of Health 1P20 GM125498-01 Centers of Biomedical Research Excellence Award. S.V.S. acknowledges support from start-up funds provided by Northeastern University. J.-G.Y. is supported by a James S. McDonnell Postdoctoral Fellowship. We also thank A. Allard, B. M. Althouse, M. Newman, G. Cantwell and A. Kirkley for insightful discussions as well as J. Burkardt for sharing his Bernstein polynomial implementation.
The authors declare no competing interests.
Peer review information Nature Physics thanks Nicholas Christakis and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
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Hébert-Dufresne, L., Scarpino, S.V. & Young, J. Macroscopic patterns of interacting contagions are indistinguishable from social reinforcement. Nat. Phys. (2020). https://doi.org/10.1038/s41567-020-0791-2