Science· 2013Q1
The Hidden Geometry of Complex, Network-Driven Contagion Phenomena
- 1,310citations
- Q1SCImago
- 2013year
Short summary
Complex contagion phenomena like epidemics and rumors can be simplified by replacing geographic distance with a novel 'effective distance' metric, revealing homogeneous wave propagation patterns.
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Key points
- Complex contagion processes (epidemics, rumors, innovations) are simplified by using an 'effective distance' instead of geographic distance.
- This 'effective distance' reveals homogeneous wave propagation patterns from complex spatiotemporal network dynamics.
- The method reliably predicts disease arrival times, even with unknown epidemiological parameters.
- The approach was successfully applied to the 2009 H1N1 and 2003 SARS pandemics to identify origins and arrival times.
AI-generated from the title and abstract; the full text is not read.
Abstract
The global spread of epidemics, rumors, opinions, and innovations are complex, network-driven dynamic processes. The combined multiscale nature and intrinsic heterogeneity of the underlying networks make it difficult to develop an intuitive understanding of these processes, to distinguish relevant from peripheral factors, to predict their time course, and to locate their origin. However, we show that complex spatiotemporal patterns can be reduced to surprisingly simple, homogeneous wave propagation patterns, if conventional geographic distance is replaced by a probabilistically motivated effective distance. In the context of global, air-traffic-mediated epidemics, we show that effective distance reliably predicts disease arrival times. Even if epidemiological parameters are unknown, the method can still deliver relative arrival times. The approach can also identify the spatial origin of spreading processes and successfully be applied to data of the worldwide 2009 H1N1 influenza pandemic and 2003 SARS epidemic.
The authors' abstract, as published at the source. Science, 2013 · DOI ↗
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Field: Modeling and Simulation
Modeling and SimulationMathematics