EC52503EC2020: The Hidden Geometry of Global Contagion (Movie s2)

Effective vs. geographic distance. The clip depicts the time course of a simulated pandemic with initial outbreak in Mexico City. The panels on the left and right depict the same simulation, only in different representations. On the left one observes a concentric, expanding wave front in the effective distance representation. The same simulation exhibits more complex spatio-temporal structure in the conventional geographic representation on the right (Movie 2). The Hidden Geometry of Global Contagion New mathematical theory for the global spread of epidemics http://www.hu-berlin.de/press-portal/... References (**) Coming to an Airport Near You Science 13 December 2013: Vol. 342 no. 6164 pp. 1330-1331 DOI: 10.1126/science.1247830 http://www.sciencemag.org/content/342... Perspective: Epidemiology Faced with the complexity of the global spread of new infections, a common approach has been to create enormous computer simulations (1, 2). Most of these studies have yielded only tenuous insights, and scientific understanding has been slow to accrue. On page 1337 of this issue, Brockmann and Helbing (3) identify a useful metric—the effective distance—that helps to understand the spread of contagion across a travel network. Once this measure is specified, the global spread of infection can be understood as a simple reaction-diffusion process across the defined transportation network. (*) The Hidden Geometry of Complex, Network-Driven Contagion Phenomena Science 13 December 2013: Vol. 342 no. 6164 pp. 1337-1342 DOI: 10.1126/science.1245200 http://www.sciencemag.org/content/342... Editor's Summary Predicting Disease Dissemination In combating the global spread of an emerging infectious disease, answers must be obtained to three crucial questions: Where did the disease emerge? Where will it go next? When will it arrive? Brockmann and Helbing (p. 1337 (*); see the Perspective by McLean (**) ) analyzed disease spread via the "effective distance" rather than geographical distance, wherein two locations that are connected by a strong link are effectively close. The approach was successfully applied to predict disease arrival times or disease source using data from the the 2003 SARS viral epidemic, 2009 H1N1 influenza pandemic, and the 2011 foodborne enterohaemorrhagic Escherichia coli outbreak in Germany. 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. Supplementary Materials http://www.sciencemag.org/content/sup...